CN114500296B - Communication, storage and computing resource unified characterization method based on function expansion diagram - Google Patents

Communication, storage and computing resource unified characterization method based on function expansion diagram Download PDF

Info

Publication number
CN114500296B
CN114500296B CN202210087697.5A CN202210087697A CN114500296B CN 114500296 B CN114500296 B CN 114500296B CN 202210087697 A CN202210087697 A CN 202210087697A CN 114500296 B CN114500296 B CN 114500296B
Authority
CN
China
Prior art keywords
node
virtual
data
nodes
functional
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210087697.5A
Other languages
Chinese (zh)
Other versions
CN114500296A (en
Inventor
刘伟
杨惠婷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xidian University
Original Assignee
Xidian University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xidian University filed Critical Xidian University
Priority to CN202210087697.5A priority Critical patent/CN114500296B/en
Publication of CN114500296A publication Critical patent/CN114500296A/en
Application granted granted Critical
Publication of CN114500296B publication Critical patent/CN114500296B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/12—Discovery or management of network topologies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/142—Network analysis or design using statistical or mathematical methods

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Mathematical Physics (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Algebra (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Probability & Statistics with Applications (AREA)
  • Computational Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

The invention discloses a unified characterization method of communication, storage and computing resources based on a function expansion diagram, which mainly solves the problem that the traditional time expansion diagram can not characterize the computing resources, and the realization scheme is as follows: initializing a characterization network parameter, dividing network nodes, and decomposing the network nodes according to the functions of the network nodes; dividing a planning period into T unequal time intervals; initializing a blank T-layer directed graph, and adding non-functional nodes, virtual sub-nodes and virtual computing nodes; adding a transmission link, a storage link and a virtual transmission link in the directed graph to form a function expansion graph; and setting communication capacity constraint, storage capacity constraint, calculation capacity constraint and flow conservation constraint, and converting the joint management problem of communication, storage and calculation resources into a data flow problem in a function expansion diagram. The invention can use the function expansion diagram to represent the time-varying property and the relativity of the resources in the network, and can be used for the unified analysis and management of communication, storage and computing resources in the time-varying network.

Description

Communication, storage and computing resource unified characterization method based on function expansion diagram
Technical Field
The invention belongs to the technical field of information, and particularly relates to a communication, storage and computing resource unified characterization method based on a function expansion diagram, which can be used for communication, storage and computing resource analysis and management of time-varying networks such as public transport, communication and supply chains.
Background
In order to model the influence of network topology on data transmission, fulkerson et al propose a time expansion diagram, and connect discrete time snapshots by introducing a storage link, thereby implementing joint characterization of communication resources and storage resources of network nodes. Time expansion maps are widely used to characterize dynamic networks that change over time, such as multi-commodity problems, evacuation planning problems, spatial information networks, and communication networks. However, the network node has other computing processing functions in addition to the communication function and the storage function. For example, for a communication network, a network node may have an image processing function, and an original image flowing into the node may be compressed into a compressed image and then flows out from the node; for data flow problems, a network node may have processing functionality that converts incoming raw material into product after processing, such as processing apples into apple juice, and flows out of the node. However, such time-expansion diagrams do not characterize the computational processing functions of the nodes in the dynamic network.
For example, in a "Maximum flow routing protocol for space information network with service function constraints" article by husting Yang, a time-varying spatial information network is represented by using a time expansion diagram, and discrete time snapshots are connected by introducing a storage link, so that joint representation of communication resources and storage resources of network nodes is realized. However, nodes in the spatial information network, such as satellites, have other computing processing functions, such as image compression, in addition to communication and storage functions. The time expansion graph cannot take the corresponding computing resources of the spatial information network nodes into account, and therefore cannot be used for joint planning of communication, storage and computation in the spatial information network.
Disclosure of Invention
The invention aims to provide a unified characterization method of communication, storage and computing resources based on a function expansion diagram aiming at the defect that the prior art cannot jointly characterize the communication, storage and computing resources, so as to form a unified function diagram model, describe the connection and transformation relation among different resources and realize the analysis and management of the communication, storage and computing resources in a time-varying network.
In order to achieve the purpose, the technical scheme of the invention comprises the following steps:
(1) Initializing a set of network nodes to
Figure BDA0003487692200000011
The number of the network nodes is N;
(2) Dividing network nodes, namely dividing nodes which can not provide a task computing function and only play a role in communication and storage in a network into non-functional nodes, and dividing nodes which can not only provide the communication and storage functions but also provide the computing function in the network into functional nodes; aggregating network nodes according to the partitioning
Figure BDA0003487692200000021
Expressed as:
Figure BDA0003487692200000022
wherein
Figure BDA0003487692200000023
Is a collection of non-functional nodes that,
Figure BDA0003487692200000024
in the form of a collection of functional nodes,
Figure BDA0003487692200000025
denotes the jth non-functional node, N 1 The number of non-functional nodes is,
Figure BDA0003487692200000026
denotes the ith functional node, N 2 Number of functional nodes, N = N 1 +N 2 ；
(3) Decomposing the network nodes according to the functions of the network nodes:
if function node
Figure BDA0003487692200000027
Can provide M i A computing function, then decomposing the node into a virtual child node v i And M i A virtual computing node
Figure BDA0003487692200000028
And two virtual transmission links
Figure BDA0003487692200000029
And
Figure BDA00034876922000000210
wherein M is i As a functional node
Figure BDA00034876922000000211
The total number of computing functions can be provided,
Figure BDA00034876922000000212
functional node of a representation
Figure BDA00034876922000000213
The mth virtual compute node of the decomposition,
Figure BDA00034876922000000214
representing a slave virtual child node v i To virtual computing node
Figure BDA00034876922000000215
The directional line segment of (a) is,
Figure BDA00034876922000000216
representing slave virtual computing nodes
Figure BDA00034876922000000217
To virtual child node v i Is directed line segment of (1), m is E [1,M i ]；
(4) Planning the network period according to the connectivity of the network node
Figure BDA00034876922000000218
Divided into T time intervals
Figure BDA00034876922000000219
Wherein
Figure BDA00034876922000000220
And at a time interval tau q The internal network topology remains unchanged, q ∈ [1,T ∈ [ ]]；
(5) Constructing a function expansion diagram:
(5a) Initializing a blank T-layer directed graph, wherein the time interval of the q-th layer directed graph is tau q ；
(5b) At each time interval τ of the directed graph q Adding all non-functional nodes, virtual sub-nodes decomposed by all functional nodes, and virtual computing nodes decomposed by all functional nodes in network to form functional node graphAnd obtaining three types of node sets of the functional node graph:
Figure BDA00034876922000000221
Figure BDA00034876922000000222
Figure BDA00034876922000000223
wherein,
Figure BDA00034876922000000224
is a set of non-functional nodes of a functional node map,
Figure BDA00034876922000000225
is a set of virtual child nodes of the functional node map,
Figure BDA00034876922000000226
is a virtual compute node set of a functional node map,
Figure BDA00034876922000000227
is expressed in time interval tau q Non-functional node of internal network
Figure BDA00034876922000000228
A copy of (a) is made of,
Figure BDA00034876922000000229
for a virtual sub-node v i A copy of (a) is made of,
Figure BDA00034876922000000230
is expressed in time interval tau q Intra-network virtual compute node
Figure BDA00034876922000000231
Copies of (2)；
(5c) Adding links in the functional node graph:
(5c1) Adding a transmission link according to the connectivity of the node:
if at time interval τ q The jth non-functional node in the internal and external network
Figure BDA0003487692200000031
Can give the kth non-functional node
Figure BDA0003487692200000032
Transmitting data, and then transmitting the data in the jth non-functional node in the functional node diagram
Figure BDA0003487692200000033
And the kth non-functional node
Figure BDA0003487692200000034
Adding a directed line segment between
Figure BDA0003487692200000035
If at time interval τ q Inner, j th non-functional node
Figure BDA0003487692200000036
Can give the ith functional node
Figure BDA0003487692200000037
Transmitting data, and then transmitting the data in the jth non-functional node in the functional node diagram
Figure BDA0003487692200000038
And the ith virtual child node
Figure BDA0003487692200000039
Adding a directed line segment between
Figure BDA00034876922000000310
If at time interval τ q In the interior of said container body,ith function node
Figure BDA00034876922000000311
Can give the kth function node
Figure BDA00034876922000000312
When data is transmitted, the ith virtual child node in the functional node graph
Figure BDA00034876922000000313
And the kth virtual child node
Figure BDA00034876922000000314
Adding a directed line segment between
Figure BDA00034876922000000315
If at time interval τ q Inner, i-th function node
Figure BDA00034876922000000316
Can give the jth non-functional node
Figure BDA00034876922000000317
When data is transmitted, the ith virtual child node in the functional node diagram
Figure BDA00034876922000000318
And the jth non-functional node
Figure BDA00034876922000000319
Adding a directed line segment between
Figure BDA00034876922000000320
(5c2) Adding a storage link:
adding a slave node between adjacent time intervals of each non-functional node of the functional node map
Figure BDA00034876922000000321
To the node
Figure BDA00034876922000000322
Directed line segment of
Figure BDA00034876922000000323
Adding a slave node between adjacent time intervals of each virtual child node of the functional node graph
Figure BDA00034876922000000324
To the node
Figure BDA00034876922000000325
Directed line segment of
Figure BDA00034876922000000326
(5c3) Adding a virtual transmission link: at each virtual child node of the functional node map
Figure BDA00034876922000000327
Virtual sub-computing node corresponding thereto
Figure BDA00034876922000000328
Adding two directed line segments in between
Figure BDA00034876922000000329
And
Figure BDA00034876922000000330
obtaining a function expansion diagram;
(6) Setting communication capacity constraint, storage capacity constraint, calculation capacity constraint and flow conservation constraint:
the communication capacity constraint is to limit the sum of the data amount transmitted by all the data streams on the transmission link or the virtual transmission link not to exceed the communication capacity of the transmission link or the virtual transmission link;
the storage capacity constraint is to limit the sum of the data amount stored on the storage link of all the data streams to be not more than the storage capacity of the storage link;
the computing capacity constraint is to define a data flow
Figure BDA00034876922000000331
Streaming virtual compute nodes
Figure BDA00034876922000000332
The consumed computing capacity cannot exceed the virtual computing node
Figure BDA0003487692200000041
Provided computing power, wherein
Figure BDA0003487692200000042
To calculate the function for the upcoming reception
Figure BDA0003487692200000043
The data stream of (a) is transmitted,
Figure BDA0003487692200000044
m∈[1,M i ]，
Figure BDA0003487692200000045
showing the flow through the transport and storage links into virtual child nodes in a functional expansion graph
Figure BDA0003487692200000046
The number of types of different data streams;
the flow conservation constraint includes: defining the amount of data flowing into the non-functional node of each data stream to be equal to the amount of data flowing out of the non-functional node; defining the amount of data flowing into the virtual child node for each data stream to be equal to the amount of data flowing out of the virtual child node; qualifying instant data streams
Figure BDA0003487692200000047
Streaming virtual compute nodes
Figure BDA0003487692200000048
Is multiplied by the amount of data of
Figure BDA0003487692200000049
Equaling data streams
Figure BDA00034876922000000410
Egress virtual compute node
Figure BDA00034876922000000411
The amount of data of (a), wherein,
Figure BDA00034876922000000412
computing functions for received
Figure BDA00034876922000000413
The data stream of (2);
(7) Under the four set constraints, the problem of joint management of communication, storage and computing resources is converted into a data flow problem in a function expansion diagram, namely the function expansion diagram is used for uniformly representing dynamic network communication, storage and computing resources changing along with time.
Compared with the prior art, the invention has the following advantages:
1) The invention uniformly represents communication, storage and computing capabilities through the function expansion diagram framework, thereby solving the problem that a plurality of computing functions in one node cannot be represented in the traditional time expansion diagram. Specifically, each node with a computing function is virtually decomposed into three virtual components based on a conventional time expansion graph: the system comprises a sub-virtual node, a virtual computing node and a virtual transmission link, wherein the sub-virtual node maintains the communication and storage capacity of the original node, the virtual computing node provides the computing capacity of the original node, and the virtual transmission link connects the sub-virtual node and the virtual computing node. Meanwhile, the function expansion diagram of the invention can represent a plurality of parallel or a plurality of continuous computing functions in one node.
2) In the invention, the problem that the data processing process of the computing function unit of the node cannot be represented in the traditional time expansion diagram is solved by introducing the virtual transmission link in the construction of the function expansion diagram. The invention uses the transmission link, the storage link and the virtual transmission link in the function expansion diagram to represent communication, storage and calculation resources in the time-varying network, provides a uniform representation for the joint communication, storage and calculation resources, and the position relationship among different links in the function expansion diagram represents the connection and transformation relationship among different resources.
3) The invention sets communication capacity constraint, storage capacity constraint, calculation capacity constraint and flow conservation constraint on data flow in the function expansion diagram, overcomes the problem that the flow conservation constraint is difficult to quantify caused by the possible change of the type of the data flow and the proportion of the input data flow and the output data flow for a node with a plurality of parallel calculation functions or a plurality of continuous functions, and can uniformly represent dynamic network communication, storage and calculation resources changing along with time through the function expansion diagram.
Drawings
FIG. 1 is a schematic view of a scenario in which the present invention is used;
FIG. 2 is a general flow chart of an implementation of the present invention;
FIG. 3 is a schematic diagram illustrating the connection relationship between nodes in a network during a planning period according to the present invention;
FIG. 4 is a schematic diagram of different nodes and virtual transmission links obtained by decomposing functional nodes in the present invention;
FIG. 5 is a blank directed graph initialized in the present invention;
FIG. 6 is a functional node diagram constructed in the present invention.
Fig. 7 is a function expansion diagram constructed in the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings and examples, which are only for the purpose of illustrating the invention and do not constitute any limitation to the invention.
Referring to fig. 1, the network scenario of the present example consists of 6 network nodes
Figure BDA0003487692200000051
Composition of network nodes
Figure BDA0003487692200000052
And
Figure BDA0003487692200000053
the three nodes can not provide task computing function and only play roles of communication and storage, but
Figure BDA0003487692200000054
And
Figure BDA0003487692200000055
the three network nodes can not only provide communication and storage functions, but also can respectively provide M 1 ,M 2 And M 3 A computing function. The planning period of the network is
Figure BDA0003487692200000056
Connectivity between nodes in a planning period is shown in fig. 3, and each abscissa and ordinate in fig. 3 corresponds to a connection relationship between a pair of nodes, where the abscissa represents time, the ordinate represents connectivity, state 1 represents connection, and state 0 represents disconnection.
Referring to fig. 2, the specific implementation steps of this example under the above scenario conditions are as follows:
step 1, initializing network parameters and dividing network nodes.
The number of the initialized network nodes is N, N =6, and the initialized network nodes are aggregated into
Figure BDA0003487692200000057
I.e. the set is composed of
Figure BDA0003487692200000058
Six network nodes, wherein the network nodes
Figure BDA0003487692200000059
And
Figure BDA00034876922000000510
these three nodes cannotProviding task computing functions only serves communication and storage functions, and
Figure BDA00034876922000000511
and
Figure BDA00034876922000000512
the three network nodes can not only provide communication and storage functions, but also can respectively provide M 1 ,M 2 And M 3 A computing function.
Dividing nodes which can not provide task computing function and only play communication and storage roles in the network into non-functional nodes, and dividing nodes which can not only provide communication and storage functions but also provide computing function in the network into functional nodes;
aggregating network nodes according to the partitioning
Figure BDA00034876922000000513
Expressed as:
Figure BDA00034876922000000514
wherein
Figure BDA00034876922000000515
Is a collection of non-functional nodes that,
Figure BDA0003487692200000061
in the form of a collection of functional nodes,
Figure BDA0003487692200000062
represents the jth nonfunctional node, j is in the field of 1,N 1 ]，N 1 =3 is the number of nonfunctional nodes,
Figure BDA0003487692200000063
represents the ith function node, i ∈ [1,N 2 ]，N 2 =3 number of functional nodes, N = N 1 +N 2 。
And 2, decomposing the network nodes according to the functions of the network nodes.
If function node
Figure BDA00034876922000000640
Can provide M i A computing function, then decomposing the node into a virtual child node v i And M i A virtual computing node
Figure BDA0003487692200000064
And two virtual transmission links
Figure BDA0003487692200000065
And
Figure BDA0003487692200000066
as shown in FIG. 4, wherein M i As a functional node
Figure BDA0003487692200000067
The total number of computing functions can be provided,
Figure BDA0003487692200000068
functional node of a representation
Figure BDA0003487692200000069
The m-th virtual computing node of the decomposition,
Figure BDA00034876922000000610
representing a slave virtual child node v i To virtual computing node
Figure BDA00034876922000000611
The directional line segment of (a) is,
Figure BDA00034876922000000612
representing slave virtual computing nodes
Figure BDA00034876922000000613
To virtual child node v i Is directed line segment of (1), m is E [1,M i ]Virtual child node v i Virtual computing node implementing communication and storage functions
Figure BDA00034876922000000614
Implementing a computing function
Figure BDA00034876922000000615
And data flow
Figure BDA00034876922000000616
Streaming virtual compute nodes
Figure BDA00034876922000000617
Will be processed and converted into a new type of data stream
Figure BDA00034876922000000618
From the virtual computing node
Figure BDA00034876922000000619
And the water flows out, wherein,
Figure BDA00034876922000000620
to calculate the function for the upcoming reception
Figure BDA00034876922000000621
The data stream of (a) is transmitted,
Figure BDA00034876922000000622
computing functions for received
Figure BDA00034876922000000623
The data stream of (2).
And 3, dividing a network planning period into T continuous unequal time intervals according to the connectivity of the network nodes.
As shown in fig. 3, it comprises three time intervals, i.e. a first time interval τ 1 Second time interval τ 2 Third time interval τ 3 Wherein:
first time interval τ 1 Inner, 1 st non-functional node
Figure BDA00034876922000000624
Can give the 1 st functional node
Figure BDA00034876922000000625
Transmitting data, 1 st functional node
Figure BDA00034876922000000626
Can give the 2 nd functional node
Figure BDA00034876922000000627
Transmitting data, 2 nd non-functional node
Figure BDA00034876922000000628
Can give the 3 rd non-functional node
Figure BDA00034876922000000629
Transmitting data;
second time interval tau 2 Inner, 1 st non-functional node
Figure BDA00034876922000000630
Can give the 1 st functional node
Figure BDA00034876922000000631
Transmitting data, 2 nd functional node
Figure BDA00034876922000000632
Can give the 3 rd function node
Figure BDA00034876922000000633
Transmitting data, 3 rd function node
Figure BDA00034876922000000634
Can give the 2 nd non-functional node
Figure BDA00034876922000000635
Transmitting data;
third time interval τ 3 Inner, 1 st function node
Figure BDA00034876922000000641
Can give the 2 nd functional node
Figure BDA00034876922000000636
Transmitting data, 2 nd functional node
Figure BDA00034876922000000637
Can give the 3 rd function node
Figure BDA00034876922000000638
Transmitting data, 3 rd function node
Figure BDA00034876922000000642
Can give the 2 nd non-functional node
Figure BDA00034876922000000639
Transmitting data, 2 nd non-functional node
Figure BDA0003487692200000071
Can give the 3 rd non-functional node
Figure BDA0003487692200000072
And transmitting the data.
Planning the network period according to the connectivity of the 6 network nodes
Figure BDA0003487692200000073
Divided into 3 time intervals { tau 1 ,τ 2 ,τ 3 Where T =3, τ q ＝[t q-1 ,t q ) And at a time interval tau q The internal network topology remains unchanged, q ∈ [1,T ∈ [ ]]。
And 4, constructing a function expansion diagram.
4.1 A blank T =3 level directed graph is initialized, wherein the time interval of the q-th level directed graph is tau q Q is more than or equal to 1 and less than or equal to 3, as shown in FIG. 5;
4.2 At each time interval τ of the directed graph q Inner is respectivelyAdding all non-functional nodes, all virtual child nodes decomposed by functional nodes, and all virtual computing nodes decomposed by functional nodes in the network to form a functional node map, as shown in fig. 6, wherein:
set of non-functional nodes of a functional node map as
Figure BDA0003487692200000074
I.e. the set is composed of
Figure BDA0003487692200000075
Nine non-functional nodes, as shown by the pentagonal nodes of fig. 6, wherein,
Figure BDA0003487692200000076
indicating the jth network non-functional node
Figure BDA0003487692200000077
At the qth time interval τ q Inner copy, j is more than or equal to 1 and less than or equal to N 1 ，1≤q≤T，N 1 ＝3，T＝3；
Set of virtual child nodes of functional node graph as
Figure BDA0003487692200000078
I.e. the set is composed of
Figure BDA0003487692200000079
Nine virtual child nodes, as shown by the circle node in fig. 6, wherein,
Figure BDA00034876922000000710
representing the ith network virtual child node v i At the qth time interval τ q Inner copy, i is more than or equal to 1 and less than or equal to N 2 ，1≤q≤T，N 2 ＝3，T＝3；
The virtual computing node set of the functional node graph is
Figure BDA00034876922000000711
The set consists of virtual compute nodes in three time intervals, as shown by the rectangle of nodes in fig. 6, i.e.,
at a first time interval tau 1 Therein is provided with
Figure BDA00034876922000000712
Figure BDA00034876922000000713
In total of M 1 +M 2 +M 3 A virtual compute node;
at a second time interval tau 2 Therein is provided with
Figure BDA00034876922000000714
Figure BDA00034876922000000715
In total of M 1 +M 2 +M 3 A plurality of virtual compute nodes;
at a third time interval tau 3 Therein is provided with
Figure BDA00034876922000000716
Figure BDA0003487692200000081
In total of M 1 +M 2 +M 3 A plurality of virtual compute nodes; wherein,
Figure BDA0003487692200000082
representing the ith network virtual compute node
Figure BDA0003487692200000083
At the qth time interval τ q Inner copy, i is more than or equal to 1 and less than or equal to N 2 ，1≤m≤M i ，1≤q≤T，N 2 ＝3，T＝3；
4.3 Add links in the functional node map as shown in fig. 7:
4.3.1 Transmission links are added according to the connectivity of the node, as shown by the solid line in fig. 7:
if at time interval τ q The jth non-functional node in the internal and external network
Figure BDA0003487692200000084
Can give the kth non-functional node
Figure BDA0003487692200000085
Transmitting data, and then transmitting the data in the jth non-functional node in the functional node diagram
Figure BDA0003487692200000086
And the kth non-functional node
Figure BDA0003487692200000087
Adding a directed line segment between
Figure BDA0003487692200000088
If at time interval tau q Inner, j th non-functional node
Figure BDA0003487692200000089
Can give the ith functional node
Figure BDA00034876922000000810
Transmitting data, and then transmitting the data in the jth non-functional node in the functional node diagram
Figure BDA00034876922000000811
And the ith virtual child node
Figure BDA00034876922000000833
Adding a directed line segment between
Figure BDA00034876922000000812
If at time interval τ q Inner, i-th function node
Figure BDA00034876922000000813
Can give the kth function node
Figure BDA00034876922000000814
When data is transmitted, the ith virtual child node in the functional node diagram
Figure BDA00034876922000000815
And the kth virtual child node
Figure BDA00034876922000000816
Adding a directed line segment between
Figure BDA00034876922000000817
If at time interval τ q Inner, i-th function node
Figure BDA00034876922000000818
Can give the jth non-functional node
Figure BDA00034876922000000819
When data is transmitted, the ith virtual child node in the functional node diagram
Figure BDA00034876922000000820
And the jth non-functional node
Figure BDA00034876922000000821
Adding a directed line segment between
Figure BDA00034876922000000822
4.3.2 Add storage links as shown by the dashed lines in fig. 7:
adding a node from the q-th time interval between adjacent time intervals of each non-functional node of the functional node map
Figure BDA00034876922000000823
Node to the (q + 1) th time interval
Figure BDA00034876922000000824
Directed line segment of
Figure BDA00034876922000000825
Adding a node from the q-th time interval between adjacent time intervals of each virtual child node of the functional node graph
Figure BDA00034876922000000826
Node to qth time interval
Figure BDA00034876922000000827
Directed line segment of
Figure BDA00034876922000000828
4.3.3 Add virtual transmission link: at each virtual child node of the functional node map
Figure BDA00034876922000000829
Virtual sub-computing node corresponding thereto
Figure BDA00034876922000000830
Two directed line segments are added in between
Figure BDA00034876922000000831
And
Figure BDA00034876922000000832
as shown by the dotted line of fig. 7, the function expansion diagram shown in fig. 7 is obtained up to this point.
And 5, setting a communication capacity constraint, a storage capacity constraint, a calculation capacity constraint and a flow conservation constraint.
5.1 Set a communication capacity constraint, i.e. define that the sum of the data amounts transmitted by all data streams on a transmission link or virtual transmission link cannot exceed the communication capacity of its transmission link or virtual transmission link:
5.1.1 For a transmission link, the sum of the data amounts transmitted on the transmission link for all data streams defined by its traffic capacity constraint cannot exceed the traffic capacity of its transmission link, and the formula is as follows:
Figure BDA0003487692200000091
Figure BDA0003487692200000092
Figure BDA0003487692200000093
Figure BDA0003487692200000094
wherein,
Figure BDA0003487692200000095
representing a node from the jth non-function
Figure BDA0003487692200000096
To the kth non-functional node
Figure BDA0003487692200000097
Is transmitted over a network
Figure BDA0003487692200000098
The number of types of data streams on the network,
Figure BDA0003487692200000099
representing a node from the jth non-function
Figure BDA00034876922000000910
To the ith virtual child node
Figure BDA00034876922000000911
Is transmitted to
Figure BDA00034876922000000912
The number of types of data streams on the network,
Figure BDA00034876922000000913
representing the from the ith virtual child node
Figure BDA00034876922000000914
To the k-th virtual child node
Figure BDA00034876922000000915
Is transmitted over a network
Figure BDA00034876922000000916
The number of types of data streams on the network,
Figure BDA00034876922000000917
representing the from the ith virtual child node
Figure BDA00034876922000000918
To the jth non-functional node
Figure BDA00034876922000000919
Is transmitted over a network
Figure BDA00034876922000000920
The number of types of data streams on the network,
Figure BDA00034876922000000921
Figure BDA00034876922000000922
and
Figure BDA00034876922000000923
respectively representing data streams xi n In a transmission link
Figure BDA00034876922000000924
Figure BDA00034876922000000925
And
Figure BDA00034876922000000926
the amount of data to be transmitted over the network,
Figure BDA00034876922000000927
and
Figure BDA00034876922000000928
are respectively transmission links
Figure BDA00034876922000000929
And
Figure BDA00034876922000000930
the capacity of the communication of (a) to (b),
Figure BDA00034876922000000931
a set of transmission links in the function expansion diagram;
5.1.2 For a virtual transmission link, the sum of the data amounts transmitted by the data streams on the virtual transmission link, which are defined in the constraint of communication capacity, cannot exceed the communication capacity of the virtual transmission link, and the formula is as follows:
Figure BDA00034876922000000932
Figure BDA00034876922000000933
wherein,
Figure BDA00034876922000000934
as a stream xi n In virtual transmission links
Figure BDA00034876922000000935
Amount of data transmitted;
Figure BDA00034876922000000936
converted for received computing functionsNew type of data stream xi n ' in a virtual transmission link
Figure BDA0003487692200000101
The amount of data transmitted;
Figure BDA0003487692200000102
as a stream xi n In virtual transmission links
Figure BDA0003487692200000103
A transmission capacity of (a), which represents the maximum amount of data that can be transmitted;
Figure BDA0003487692200000104
data stream xi of new type converted for received computing function n ' in a virtual transmission link
Figure BDA0003487692200000105
The transmission capacity of (a);
Figure BDA0003487692200000106
a set of virtual transmission links from the virtual child nodes to the virtual compute nodes in the function expansion graph;
Figure BDA0003487692200000107
is a set of virtual transmission links from a virtual child compute node to a virtual child node in a functional expansion graph.
5.2 Set the storage capacity constraint, i.e. define that the sum of the data amount stored on the storage link for all data streams cannot exceed the storage capacity of its storage link, the formula is as follows:
Figure BDA0003487692200000108
Figure BDA0003487692200000109
wherein,
Figure BDA00034876922000001010
and
Figure BDA00034876922000001011
respectively representing data streams xi n In a memory link
Figure BDA00034876922000001012
And
Figure BDA00034876922000001013
the amount of data stored on the memory device,
Figure BDA00034876922000001014
and
Figure BDA00034876922000001015
respectively representing memory links
Figure BDA00034876922000001016
And
Figure BDA00034876922000001017
the storage capacity of (a) of (b),
Figure BDA00034876922000001018
representing a flow through a transmission link and a storage link into a jth non-functional node in a functional expansion graph
Figure BDA00034876922000001019
The number of types of different data streams of (2),
Figure BDA00034876922000001020
representing the flow through the transport link, storage link and virtual transport link into the ith virtual child node in the function expansion graph
Figure BDA00034876922000001021
The number of types of different data streams of (2),
Figure BDA00034876922000001022
the set of links is stored for the function expansion map.
5.3 Set a computation capacity constraint, i.e., a defined upcoming computation function
Figure BDA00034876922000001023
Of a data stream
Figure BDA00034876922000001024
Streaming virtual compute nodes
Figure BDA00034876922000001025
The consumed computing capacity cannot exceed the virtual computing node
Figure BDA00034876922000001026
The computational power provided, formulated as follows:
Figure BDA0003487692200000111
wherein,
Figure BDA0003487692200000112
computing functions for imminent reception
Figure BDA0003487692200000113
The data stream of (a) is transmitted,
Figure BDA0003487692200000114
computing functions for received
Figure BDA0003487692200000115
The stream of data of (a) is,
Figure BDA0003487692200000116
is a number ofData stream
Figure BDA0003487692200000117
In a virtual transmission link
Figure BDA0003487692200000118
The amount of data to be transmitted over the network,
Figure BDA0003487692200000119
for calculating the factor, what is indicated is that the data stream per unit is processed
Figure BDA00034876922000001110
And converted into a data stream
Figure BDA00034876922000001111
The amount of computing power that needs to be consumed,
Figure BDA00034876922000001112
representing virtual computing nodes
Figure BDA00034876922000001113
The computing power of the device.
5.4 Set flow conservation constraints:
the constraint comprises three aspects of non-functional nodes, virtual child nodes and virtual computing nodes, and is specifically realized as follows:
5.4.1 For non-functional nodes, define data stream ξ n The amount of data flowing into a non-functional node is equal to the amount of data it flows out of the non-functional node, and the formula is as follows:
Figure BDA00034876922000001114
wherein,
Figure BDA00034876922000001115
and
Figure BDA00034876922000001116
respectively representing data streams xi n In a transmission link
Figure BDA00034876922000001117
And
Figure BDA00034876922000001118
the amount of data to be transmitted over the network,
Figure BDA00034876922000001119
and
Figure BDA00034876922000001120
respectively representing data streams xi n In a memory link
Figure BDA00034876922000001121
And
Figure BDA00034876922000001122
the amount of data stored on the memory device,
Figure BDA00034876922000001123
for streaming to non-functional nodes via transmission and storage links
Figure BDA00034876922000001124
Of the different data streams of (a) to (b),
Figure BDA00034876922000001125
is a collection of transmission links in the function expansion diagram.
5.4.2 For a virtual child node, define a data stream ξ n The amount of data flowing into a virtual child is equal to the amount of data it flows out of the virtual child, and the formula is as follows:
Figure BDA00034876922000001126
wherein,
Figure BDA0003487692200000121
and
Figure BDA0003487692200000122
respectively representing data streams xi n In a transmission link
Figure BDA0003487692200000123
And
Figure BDA0003487692200000124
the amount of data to be transmitted over the network,
Figure BDA0003487692200000125
and
Figure BDA0003487692200000126
respectively representing data streams xi n In a virtual transmission link
Figure BDA0003487692200000127
And
Figure BDA0003487692200000128
the amount of data to be transmitted over the network,
Figure BDA0003487692200000129
and
Figure BDA00034876922000001210
respectively representing data streams xi n In a memory link
Figure BDA00034876922000001211
And
Figure BDA00034876922000001212
the amount of data stored on the memory device,
Figure BDA00034876922000001213
for streaming into the ith virtual sub-node over a transport link, a storage link and a virtual transport link
Figure BDA00034876922000001214
Of the different data streams of (a) to (b),
Figure BDA00034876922000001215
a set of transmission links in the function expansion diagram;
Figure BDA00034876922000001216
a set of virtual transmission links from the virtual child nodes to the virtual compute nodes in the function expansion graph;
Figure BDA00034876922000001217
is a set of virtual transmission links from a virtual child compute node to a virtual child node in a functional expansion graph.
5.4.3 For virtual compute nodes, define data flows
Figure BDA00034876922000001218
Streaming virtual compute nodes
Figure BDA00034876922000001219
Is multiplied by the amount of data of
Figure BDA00034876922000001220
Equal to another type of data stream
Figure BDA00034876922000001221
Egress virtual compute node
Figure BDA00034876922000001222
The formula is as follows:
Figure BDA00034876922000001223
wherein,
Figure BDA00034876922000001224
to calculate the function for the upcoming reception
Figure BDA00034876922000001225
The data stream of (a) is transmitted,
Figure BDA00034876922000001226
computing functions for received
Figure BDA00034876922000001227
The data stream of (2);
Figure BDA00034876922000001228
to calculate the function for the upcoming reception
Figure BDA00034876922000001229
Of a data stream
Figure BDA00034876922000001230
In virtual transmission links
Figure BDA00034876922000001231
The amount of data transmitted;
Figure BDA00034876922000001232
for a received computing function
Figure BDA00034876922000001233
Of a data stream
Figure BDA00034876922000001234
In a virtual transmission link
Figure BDA00034876922000001235
The amount of data transmitted;
Figure BDA00034876922000001236
indicating that a computing function is about to be received
Figure BDA00034876922000001237
Of a data stream
Figure BDA00034876922000001238
And received computing function
Figure BDA00034876922000001239
Of a data stream
Figure BDA00034876922000001240
A scaling factor in between.
And 6, uniformly representing communication, storage and computing resources by using the function expansion diagram.
Because the transmission link, the storage link and the virtual transmission link in the function expansion diagram respectively represent communication, storage and calculation resources in the time-varying network, and the position relationship between different links in the function expansion diagram represents the bearing conversion relationship between different resources, and simultaneously, under the four constraints set in the step 5, the data stream in the function expansion diagram can meet the communication resource constraint, the storage resource constraint, the calculation constraint and the conversion relationship between various data streams in the network, so that the problem of joint management of the communication, storage and calculation resources can be converted into the problem of the data stream in the function expansion diagram, namely the problem of unified representation of dynamic network communication, storage and calculation resources changing along with time by using the function expansion diagram. The communication, storage and computation resources of the time-varying network can be analyzed and managed uniformly by using the function expansion diagram.
The foregoing description is only an example of the present invention, and it will be apparent to those skilled in the art that various modifications and variations in form and detail can be made without departing from the principle and structure of the invention, but these modifications and variations are within the scope of the invention as defined in the appended claims.

Claims (8)

1. A unified characterization method for communication, storage and computing resources based on a function expansion diagram is characterized by comprising the following steps:
(1) Initializing a set of network nodes to
Figure FDA0003997834590000011
The number of the network nodes is N;
(2) Dividing network nodes, namely dividing nodes which can not provide task computing function and only play communication and storage roles in a network into non-functional nodes, and dividing nodes which can not only provide communication and storage functions but also can provide computing function in the network into functional nodes; aggregating network nodes according to the partitioning
Figure FDA0003997834590000012
Expressed as:
Figure FDA0003997834590000013
wherein
Figure FDA0003997834590000014
Is a collection of non-functional nodes that,
Figure FDA0003997834590000015
in the form of a collection of functional nodes,
Figure FDA0003997834590000016
denotes the jth non-functional node, N 1 The number of non-functional nodes is,
Figure FDA0003997834590000017
denotes the ith functional node, N 2 For the number of functional nodes, N = N 1 +N 2 ；
(3) Decomposing the network nodes according to the functions of the network nodes:
if function node
Figure FDA0003997834590000018
Can provide M i A computing function, then decomposing the node into a virtual child node v i And M i A virtual computing node
Figure FDA0003997834590000019
And two virtual transmission links
Figure FDA00039978345900000110
And
Figure FDA00039978345900000111
wherein M is i As a functional node
Figure FDA00039978345900000112
The total number of calculation functions can be provided,
Figure FDA00039978345900000113
functional node of a representation
Figure FDA00039978345900000114
The mth virtual compute node of the decomposition,
Figure FDA00039978345900000115
representing a slave virtual child node v i To virtual computing node
Figure FDA00039978345900000116
The directional line segment of (a) is,
Figure FDA00039978345900000117
representing slave virtual computing nodes
Figure FDA00039978345900000118
To virtual child node v i Is directed line segment of (1), m is E [1,M i ]；
(4) Planning the network period according to the connectivity of the network node
Figure FDA00039978345900000119
Divided into T time intervals
Figure FDA00039978345900000120
Wherein tau is q ＝[t q-1 ,t q ) And at a time interval tau q The internal network topology remains unchanged, q ∈ [1,T ∈ [ ]]；
(5) Constructing a function expansion diagram:
(5a) Initializing a blank T-layer directed graph, wherein the time interval of the q-th layer directed graph is tau q ；
(5b) At each time interval τ of the directed graph q Adding all non-functional nodes, virtual sub-nodes decomposed by all functional nodes and virtual computing nodes decomposed by all functional nodes in the network respectively to form a functional node graph and obtain three types of node sets of the functional node graph:
Figure FDA00039978345900000121
Figure FDA00039978345900000122
Figure FDA0003997834590000021
wherein,
Figure FDA0003997834590000022
is a set of non-functional nodes of a functional node map,
Figure FDA0003997834590000023
is a set of virtual child nodes of the functional node map,
Figure FDA0003997834590000024
virtual meter for a functional node graphA set of the compute nodes is then selected,
Figure FDA0003997834590000025
is expressed in time interval tau q Non-functional node of internal network
Figure FDA0003997834590000026
A copy of (a) is made of,
Figure FDA0003997834590000027
for a virtual sub-node v i A copy of (a) is made of,
Figure FDA0003997834590000028
is expressed in time interval tau q Intra-network virtual compute node
Figure FDA0003997834590000029
A copy of (1);
(5c) Adding links in the functional node graph:
(5c1) Adding a transmission link according to the connectivity of the node:
if at time interval τ q The jth non-functional node in the internal and external network
Figure FDA00039978345900000210
Can give the kth non-functional node
Figure FDA00039978345900000211
Transmitting data, and then transmitting the data in the jth non-functional node in the functional node diagram
Figure FDA00039978345900000212
And the kth non-functional node
Figure FDA00039978345900000213
Adding a directed line segment between
Figure FDA00039978345900000214
If at time interval τ q Inner, j th non-functional node
Figure FDA00039978345900000215
Can give the ith functional node
Figure FDA00039978345900000216
Transmitting data, and then transmitting the data in the jth non-functional node in the functional node diagram
Figure FDA00039978345900000217
And the ith virtual child node
Figure FDA00039978345900000218
Adding a directed line segment between
Figure FDA00039978345900000219
If at time interval τ q Inner, i-th function node
Figure FDA00039978345900000220
Can give the kth function node
Figure FDA00039978345900000221
When data is transmitted, the ith virtual child node in the functional node diagram
Figure FDA00039978345900000222
And the kth virtual child node
Figure FDA00039978345900000223
Adding a directed line segment between
Figure FDA00039978345900000224
If at time interval τ q Inner, i-th function node
Figure FDA00039978345900000225
Can give the jth non-functional node
Figure FDA00039978345900000226
When data is transmitted, the ith virtual child node in the functional node diagram
Figure FDA00039978345900000227
And the jth non-functional node
Figure FDA00039978345900000228
Adding a directed line segment between
Figure FDA00039978345900000229
(5c2) Adding a storage link:
adding a slave node between adjacent time intervals of each non-functional node of the functional node map
Figure FDA00039978345900000230
To the node
Figure FDA00039978345900000231
Directed line segment of
Figure FDA00039978345900000232
Adding a slave node between adjacent time intervals of each virtual child node of the functional node graph
Figure FDA00039978345900000233
To node
Figure FDA00039978345900000234
Directed line segment of
Figure FDA00039978345900000235
(5c3) Adding a virtual transmission link: at each virtual child node of the functional node map
Figure FDA00039978345900000236
Virtual sub-computing node corresponding thereto
Figure FDA00039978345900000237
Adding two directed line segments in between
Figure FDA00039978345900000238
And
Figure FDA00039978345900000239
obtaining a function expansion diagram;
(6) Setting communication capacity constraint, storage capacity constraint, calculation capacity constraint and flow conservation constraint:
the communication capacity constraint is to limit the sum of the data quantity transmitted by all the data streams on the transmission link or the virtual transmission link not to exceed the communication capacity of the transmission link or the virtual transmission link;
the storage capacity constraint is to limit the sum of the data amount stored on the storage link of all the data streams to be not more than the storage capacity of the storage link;
the computing capacity constraint is to restrict the data flow
Figure FDA0003997834590000031
Streaming virtual compute nodes
Figure FDA0003997834590000032
The consumed computing capacity cannot exceed the virtual computing node
Figure FDA0003997834590000033
Provided computing power, wherein
Figure FDA0003997834590000034
To calculate the function for the upcoming reception
Figure FDA0003997834590000035
The data stream of (a) is transmitted,
Figure FDA0003997834590000036
Figure FDA0003997834590000037
Figure FDA0003997834590000038
showing the flow of the transport links and storage links into virtual child nodes in a function expansion graph
Figure FDA00039978345900000335
The number of types of different data streams;
the flow conservation constraint includes: defining the amount of data flowing into the non-functional node of each data stream to be equal to the amount of data flowing out of the non-functional node; defining the amount of data flowing into the virtual child node for each data stream to be equal to the amount of data flowing out of the virtual child node; qualifying instant data streams
Figure FDA0003997834590000039
Streaming virtual compute nodes
Figure FDA00039978345900000310
Is multiplied by the amount of data of
Figure FDA00039978345900000311
Equaling data streams
Figure FDA00039978345900000312
Egress virtual compute node
Figure FDA00039978345900000313
The amount of data of (a), wherein,
Figure FDA00039978345900000314
computing functions for received
Figure FDA00039978345900000315
The data stream of (2);
said defined data stream
Figure FDA00039978345900000316
Streaming virtual compute nodes
Figure FDA00039978345900000317
Is multiplied by the amount of data of
Figure FDA00039978345900000318
Equal to another type of data stream
Figure FDA00039978345900000319
Egress virtual compute node
Figure FDA00039978345900000320
The formula is as follows:
Figure FDA00039978345900000321
wherein,
Figure FDA00039978345900000322
to calculate the function for the upcoming reception
Figure FDA00039978345900000323
Of a data stream
Figure FDA00039978345900000324
In virtual transmission links
Figure FDA00039978345900000325
The amount of data transmitted;
Figure FDA00039978345900000326
computing functions for received
Figure FDA00039978345900000327
Of a data stream
Figure FDA00039978345900000328
In virtual transmission links
Figure FDA00039978345900000329
The amount of data transmitted;
Figure FDA00039978345900000330
indicating that a computing function is about to be received
Figure FDA00039978345900000331
Of a data stream
Figure FDA00039978345900000332
And received computing function
Figure FDA00039978345900000333
Of a data stream
Figure FDA00039978345900000334
A scaling factor in between;
(7) Under the four set constraints, the problem of joint management of communication, storage and computing resources is converted into a data flow problem in a function expansion diagram, namely the function expansion diagram is used for uniformly representing dynamic network communication, storage and computing resources changing along with time.
2. The method of claim 1, wherein the virtual child nodes and virtual compute nodes in (3), each implement different functions, namely:
virtual child node v i Communication and storage functions are realized;
virtual computing node
Figure FDA0003997834590000041
Implementing a computing function
Figure FDA0003997834590000042
And data flow
Figure FDA0003997834590000043
Streaming virtual compute nodes
Figure FDA0003997834590000044
Will be processed and converted into a new type of data stream
Figure FDA0003997834590000045
From the virtual computing node
Figure FDA0003997834590000046
And the water flows out, wherein,
Figure FDA0003997834590000047
to calculate the function for the upcoming reception
Figure FDA0003997834590000048
The data stream of (a) is transmitted,
Figure FDA0003997834590000049
for a received computing function
Figure FDA00039978345900000410
The data stream of (2).
3. The method of claim 1, wherein the sum of the data amounts transmitted on the transmission link for all the data streams defined by the communication capacity constraint in (6) cannot exceed the communication capacity of the transmission link, and the formula is as follows:
Figure FDA00039978345900000411
Figure FDA00039978345900000412
Figure FDA00039978345900000413
Figure FDA00039978345900000414
wherein,
Figure FDA00039978345900000415
representing slave non-functional nodes
Figure FDA00039978345900000416
To non-functional nodes
Figure FDA00039978345900000417
Is transmitted over a network
Figure FDA00039978345900000418
The number of types of data streams on the network,
Figure FDA00039978345900000419
representing slave non-functional nodes
Figure FDA00039978345900000420
To the virtual child node
Figure FDA00039978345900000421
Is transmitted over a network
Figure FDA00039978345900000422
The number of types of data streams on the network,
Figure FDA00039978345900000423
representing slave virtual child nodes
Figure FDA00039978345900000424
To the virtual child node
Figure FDA00039978345900000425
Is transmitted to
Figure FDA00039978345900000426
The number of types of data streams on the network,
Figure FDA00039978345900000427
representing slave virtual child nodes
Figure FDA00039978345900000428
To non-functional nodes
Figure FDA00039978345900000429
Is transmitted over a network
Figure FDA00039978345900000430
The number of types of data streams on the network,
Figure FDA00039978345900000431
and
Figure FDA00039978345900000432
are respectively provided withRepresenting a data stream xi n In a transmission link
Figure FDA00039978345900000433
Figure FDA00039978345900000434
And
Figure FDA00039978345900000435
the amount of data to be transmitted over the network,
Figure FDA00039978345900000436
and
Figure FDA00039978345900000437
are respectively transmission links
Figure FDA00039978345900000438
And
Figure FDA00039978345900000439
the communication capacity of the mobile communication terminal (c),
Figure FDA00039978345900000440
is a collection of transmission links in the function expansion diagram.
4. The method according to claim 1, wherein the sum of the data amount transmitted on the virtual transmission link for the data streams defined in the communication capacity constraint in (6) cannot exceed the communication capacity of the virtual transmission link, and the formula is as follows:
Figure FDA00039978345900000441
Figure FDA0003997834590000051
wherein,
Figure FDA0003997834590000052
as a stream xi n In virtual transmission links
Figure FDA0003997834590000053
The amount of data to be transmitted over the network,
Figure FDA0003997834590000054
data stream xi of new type converted for received computing function n ' in a virtual transmission link
Figure FDA0003997834590000055
The amount of data to be transmitted over the network,
Figure FDA0003997834590000056
as a stream xi n In virtual transmission links
Figure FDA0003997834590000057
A transmission capacity of (a), which represents the maximum amount of data that can be transmitted;
Figure FDA0003997834590000058
data stream xi of new type converted for received computing function n ' in a virtual transmission link
Figure FDA0003997834590000059
The transmission capacity of (a);
Figure FDA00039978345900000510
a set of virtual transmission links from the virtual child nodes to the virtual compute nodes in the function expansion graph;
Figure FDA00039978345900000511
is a set of virtual transmission links from a virtual child compute node to a virtual child node in a functional expansion graph.
5. The method of claim 1, wherein the sum of the amounts of data stored on the storage links for all data streams defined in (6) under the storage capacity constraint cannot exceed the storage capacity of its storage link, and the formula is expressed as follows:
Figure FDA00039978345900000512
Figure FDA00039978345900000513
wherein,
Figure FDA00039978345900000514
and
Figure FDA00039978345900000515
respectively representing data streams xi n In a memory link
Figure FDA00039978345900000516
And
Figure FDA00039978345900000517
the amount of data stored on the memory device,
Figure FDA00039978345900000518
and
Figure FDA00039978345900000519
respectively representing memory links
Figure FDA00039978345900000520
And
Figure FDA00039978345900000521
the storage capacity of (a) of (b),
Figure FDA00039978345900000522
representing non-functional nodes flowing into a functional expansion graph over transport links and storage links
Figure FDA00039978345900000523
The number of types of different data streams of (2),
Figure FDA00039978345900000524
representing flow into a virtual child node in a function extension graph through transport links, storage links, and virtual transport links
Figure FDA00039978345900000525
The number of types of different data streams of (2),
Figure FDA0003997834590000061
the set of links is stored for the function expansion diagram.
6. The method of claim 1 wherein the receive-soon-to-compute function defined in (6) in the constraint on computing capacity
Figure FDA0003997834590000062
Data stream of
Figure FDA0003997834590000063
Streaming virtual compute nodes
Figure FDA0003997834590000064
The consumed computing capacity cannot exceed the virtual computing node
Figure FDA0003997834590000065
The computational power provided, the formula is as follows:
Figure FDA0003997834590000066
wherein,
Figure FDA0003997834590000067
to calculate the function for the upcoming reception
Figure FDA0003997834590000068
The data stream of (a) is transmitted,
Figure FDA0003997834590000069
computing functions for received
Figure FDA00039978345900000610
The data stream of (a) is transmitted,
Figure FDA00039978345900000611
as a stream of data
Figure FDA00039978345900000612
In virtual transmission links
Figure FDA00039978345900000613
The amount of data to be transmitted over the network,
Figure FDA00039978345900000614
for calculating the factor, what is indicated is that the data stream per unit is processed
Figure FDA00039978345900000615
And converted into a data stream
Figure FDA00039978345900000616
The amount of computing power that needs to be consumed,
Figure FDA00039978345900000617
representing virtual computing nodes
Figure FDA00039978345900000618
The computing power of the device.
7. The method of claim 1, wherein the data stream ξ as defined in the conservation of flow constraint in (6) n The amount of data flowing into a non-functional node is equal to the amount of data it flows out of the non-functional node, and the formula is as follows:
Figure FDA00039978345900000619
wherein,
Figure FDA00039978345900000620
and
Figure FDA00039978345900000621
respectively representing data streams xi n In a transmission link
Figure FDA00039978345900000622
And
Figure FDA00039978345900000623
the amount of data to be transmitted over the network,
Figure FDA00039978345900000624
and
Figure FDA00039978345900000625
respectively representing data streams xi n In a memory link
Figure FDA00039978345900000626
And
Figure FDA00039978345900000627
the amount of data stored on the memory device,
Figure FDA00039978345900000628
for streaming to non-functional nodes via transmission and storage links
Figure FDA00039978345900000629
Of the different data streams of (a) to (b),
Figure FDA00039978345900000630
the set of transmission links in the diagram is extended for functionality.
8. The method of claim 1, wherein the data stream ξ as defined in the conservation of flow constraint in (6) n The amount of data flowing into a virtual child is equal to the amount of data it flows out of the virtual child, and the formula is as follows:
Figure FDA0003997834590000071
wherein,
Figure FDA0003997834590000072
and
Figure FDA0003997834590000073
respectively representing data streams xi n In a transmission link
Figure FDA0003997834590000074
And
Figure FDA0003997834590000075
the amount of data to be transmitted over the network,
Figure FDA0003997834590000076
and
Figure FDA0003997834590000077
respectively representing data streams xi n In a virtual transmission link
Figure FDA0003997834590000078
And
Figure FDA0003997834590000079
the amount of data to be transmitted over the network,
Figure FDA00039978345900000710
and
Figure FDA00039978345900000711
respectively representing data streams xi n In a memory link
Figure FDA00039978345900000712
And
Figure FDA00039978345900000713
the amount of data stored on the memory device,
Figure FDA00039978345900000714
for streaming to virtual sub-nodes via transport links, storage links and virtual transport links
Figure FDA00039978345900000715
Of the different data streams of (a) to (b),
Figure FDA00039978345900000716
a set of transmission links in the function expansion diagram;
Figure FDA00039978345900000717
a set of virtual transmission links from the virtual child nodes to the virtual compute nodes in the function expansion graph;
Figure FDA00039978345900000718
is a set of virtual transmission links from a virtual child compute node to a virtual child node in a functional expansion graph.
CN202210087697.5A 2022-01-25 2022-01-25 Communication, storage and computing resource unified characterization method based on function expansion diagram Active CN114500296B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210087697.5A CN114500296B (en) 2022-01-25 2022-01-25 Communication, storage and computing resource unified characterization method based on function expansion diagram

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210087697.5A CN114500296B (en) 2022-01-25 2022-01-25 Communication, storage and computing resource unified characterization method based on function expansion diagram

Publications (2)

Publication Number Publication Date
CN114500296A CN114500296A (en) 2022-05-13
CN114500296B true CN114500296B (en) 2023-02-07

Family

ID=81475438

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210087697.5A Active CN114500296B (en) 2022-01-25 2022-01-25 Communication, storage and computing resource unified characterization method based on function expansion diagram

Country Status (1)

Country Link
CN (1) CN114500296B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114641029B (en) * 2022-05-17 2022-08-02 亚太卫星宽带通信（深圳）有限公司 Transmitting method and system based on satellite communication signal device
CN115833899B (en) * 2022-09-30 2024-08-16 西安电子科技大学 Virtual network function deployment and route joint optimization method in spatial information network

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106877921A (en) * 2017-03-14 2017-06-20 西安电子科技大学 Information Network multi dimensional resource integration characterizing method
CN110636002A (en) * 2019-10-15 2019-12-31 西安电子科技大学 Time division based maximum flow routing method for limited space information network of transceiver
CN113365355A (en) * 2021-04-29 2021-09-07 西安交通大学 Multidimensional resource management method and system under air-space-ground integrated network
CN113438156A (en) * 2021-06-29 2021-09-24 西安电子科技大学 Time deterministic multi-path routing method based on time expansion diagram

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR3007605A1 (en) * 2013-06-25 2014-12-26 France Telecom ARCHITECTURE COOPERATIVE NETWORK
CN108718251B (en) * 2018-05-10 2021-01-29 西安电子科技大学 Spatial information network connectivity analysis method based on resource time-varying graph
US11418526B2 (en) * 2019-12-20 2022-08-16 Microsoft Technology Licensing, Llc Detecting anomalous network activity
US12106154B2 (en) * 2021-06-12 2024-10-01 Intel Corporation Serverless computing architecture for artificial intelligence workloads on edge for dynamic reconfiguration of workloads and enhanced resource utilization

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106877921A (en) * 2017-03-14 2017-06-20 西安电子科技大学 Information Network multi dimensional resource integration characterizing method
CN110636002A (en) * 2019-10-15 2019-12-31 西安电子科技大学 Time division based maximum flow routing method for limited space information network of transceiver
CN113365355A (en) * 2021-04-29 2021-09-07 西安交通大学 Multidimensional resource management method and system under air-space-ground integrated network
CN113438156A (en) * 2021-06-29 2021-09-24 西安电子科技大学 Time deterministic multi-path routing method based on time expansion diagram

Also Published As

Publication number Publication date
CN114500296A (en) 2022-05-13

Similar Documents

Publication Publication Date Title
CN114500296B (en) Communication, storage and computing resource unified characterization method based on function expansion diagram
Zhang et al. A hierarchical game framework for resource management in fog computing
CN112491714B (en) Intelligent QoS route optimization method and system based on deep reinforcement learning in SDN environment
CN106934497B (en) Intelligent community power consumption real-time prediction method and device based on deep learning
CN109359385A (en) A kind of training method and device of service quality assessment model
Nie et al. Network traffic prediction based on deep belief network and spatiotemporal compressive sensing in wireless mesh backbone networks
CN102546220B (en) Key quality indicator (KQI) composition method based on service characteristics
CN103596191B (en) A kind of wireless sensor network intelligent configuration system and method thereof
CN114422349B (en) Cloud-edge-end-collaboration-based deep learning model training and reasoning architecture deployment method
CN101860908B (en) Seamless and efficient communication mechanism between wireless multimedia sensor network nodes
CN110928694B (en) Computer system
CN105976020B (en) A kind of network flow prediction method considering small echo cross-layer relevance
CN115665227B (en) Universal heterogeneous integrated computing network resource intelligent adaptation network architecture and method
CN112650581A (en) Cloud-side cooperative task scheduling method for intelligent building
CN113518007A (en) Multi-internet-of-things equipment heterogeneous model efficient mutual learning method based on federal learning
CN114745383A (en) Mobile edge calculation assisted multilayer federal learning method
CN102711125B (en) Method for improving transmission capability of wireless mesh network
CN107454009B (en) Data center-oriented offline scene low-bandwidth overhead traffic scheduling scheme
CN102946443B (en) Multitask scheduling method for realizing large-scale data transmission
CN116455768A (en) Cloud edge end collaborative CNN reasoning method and system for global time delay optimization
WO2022083549A1 (en) Traffic signal conversion method and apparatus, electronic device, and storage medium
CN112506656B (en) Distribution method based on calculation tasks of power distribution Internet of things
CN113541986B (en) Fault prediction method and device for 5G slice and computing equipment
CN104168603B (en) The building method of the data acquisition tree with high energy efficiency based on compressed sensing technology
CN104065580A (en) M2M network topology control method and system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant