CN115001565A - Computing power perception routing method and device of dynamic satellite network model - Google Patents
Computing power perception routing method and device of dynamic satellite network model Download PDFInfo
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- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
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Abstract
The invention relates to a computing power perception routing method and device of a dynamic satellite network model. The optimal routing path is determined by adopting a computational power perception routing method, and the bandwidth of a transmission link is saved and the risk of network congestion is reduced by transmitting a calculation result instead of original data. Meanwhile, the optimal routing path is found for each subtask, so that parallel transmission and calculation can be performed by using a large number of satellites in the low-earth orbit satellite network, and the total delay of task transmission and processing is reduced.
Description
The application is a divisional application of a parent application, which is filed on 11/08/2021, application number 202111312083.4 and title of the invention, namely, "construction method of dynamic satellite network model and calculation-aware routing method".
Technical Field
The invention relates to the technical field of satellite communication, in particular to a computing power perception routing method and device of a dynamic satellite network model.
Background
The satellite communication system is an important supplement to a ground communication network, and has the advantages of realizing global coverage with low cost, supporting mobile terminal communication with the speed exceeding the Mach level, improving the system throughput by utilizing a high frequency band and the like. Low Earth Orbit (LEO Low Earth Orbit) satellite networks are considered to be the most promising satellite mobile communication networks due to advantages in terms of delay, cost, development period, etc. Routing is one of the important functions of a communication network. Although the ground network routing strategy is deeply researched at present, due to the high dynamic property of the low-orbit satellite network, the existing routing algorithm cannot be directly applied to the low-orbit satellite network.
The high dynamics of low-orbit satellite networks make the application of traditional routing strategies challenging. First, the traditional static "snapshot" based network modeling approach is no longer applicable due to the changing network topology caused by the high-speed relative motion between low-earth satellites. Second, the mobility of the satellite and the intermittent connectivity due to the limited communication range present challenges for traditional shortest path algorithms (e.g., Dijkstra's algorithm), where there is no synchronization path between the source node and the destination node. Third, the very limited on-board resources (e.g., energy and storage) impose new constraints on the transmission and forwarding of routes.
At the same time, the massive data and intensive computational requirements of space tasks present new challenges to low earth orbit satellite network routing. Due to advances in remote sensing and data acquisition technologies, the computational demands for image processing, data fusion, and other tasks are rapidly increasing. The increase in data accuracy and the increase in task size put higher demands on the transmission rate. However, because the satellite has a limited bandwidth to the ground spectrum, routing a large amount of raw data to the ground for processing may cause severe network congestion, and cannot meet the requirements of delay-sensitive tasks.
In summary, it can be seen that the conventional low-orbit satellite network is also adversely affected by the above obstacles in communication applications.
Disclosure of Invention
Based on this, it is necessary to provide a method and an apparatus for computationally aware routing of a dynamic satellite network model for the adverse effect of the conventional low-earth orbit satellite network on communication applications.
A construction method of a dynamic satellite network model comprises the following steps:
configuring a virtual node for the static area; dividing the earth into a plurality of static disjoint areas according to the longitude and latitude to obtain static areas;
according to the calculation task reaching the virtual node and the satellite available resources of the associated satellite, carrying out weight definition on the virtual node and the edge formed by the virtual node pair to obtain an edge weight and a node weight;
and establishing a dynamic satellite network model according to the virtual nodes, the edges, the edge weight values and the node weight values.
According to the method for constructing the dynamic satellite network model, after the virtual nodes are configured for the static area, the virtual nodes and the edges formed by the virtual nodes are defined according to the calculation tasks reaching the virtual nodes and the satellite available resources of the associated satellite, the edge weight and the node weight are obtained, and the dynamic satellite network model is established according to the virtual nodes, the edges, the edge weight and the node weight. Dynamic edge weights and node weights are used for representing the dynamic property of a satellite network, the problem of network topology change caused by high-speed relative motion of a satellite is solved with good expansibility, and adverse effects caused by a network modeling method based on snapshots are avoided. Meanwhile, the routing strategy fusion calculation and transmission of the dynamic satellite network model are facilitated.
In one embodiment, the process of defining the weight of the virtual node and obtaining the node weight includes the following steps:
and taking the processing time delay of the subtask in the calculation task as the node weight of the virtual node.
In one embodiment, the process of calculating the processing delay of the subtask in the task as the node weight of the virtual node is as follows:
wherein a virtual node VN is reached u Is Γ u,k Computing task gamma u,k Is a set of subtasks
For computing tasks t u,k The ith subtask of (1), n u,k Is gamma u,k The total number of neutron tasks;
for a virtual node VN i Completing the subtask at time t
The required processing delay;
to complete subtasks
The amount of calculation that is required is,
to complete subtasks
The amount of memory required;
for a virtual node VN i The computing power that can be provided at the time t,
for a virtual node VN i The memory resources that can be provided at time t,
for a virtual node VN i The battery energy that can be provided at time t; f (-) is a mapping function between the amount of computation and the energy consumption.
In one embodiment, the process of defining the weight of the edge formed by the virtual node pair to obtain the edge weight includes the following steps:
and taking the sum of the transmission delay and the propagation delay of the subtask in the calculation task as the edge weight.
In one embodiment, the sum of the propagation delay and the propagation delay of the subtask in the task is calculated as an edge weight, which is as follows:
wherein the content of the first and second substances,
for a subtask of time t
The propagation delay on the edge e-i, j,
for a subtask of time t
Propagation delay on edge e ═ i, j);
as a subtask
The amount of data of (a) is,
for the edge e ═ transmission rate at time t, D i,j (t) virtual node VN at time t i And virtual node VN j The distance between them, c represents the speed of light,
for the virtual node VN at time t i And virtual node VN j A communicable time period therebetween.
In one embodiment, the process of building the dynamic satellite network model according to the virtual nodes, edges, edge weights and node weights is as follows:
G VSMN (t)＝{V,E,W E (t),W V (t)}
wherein G is VSMN (t) denotes a dynamic satellite network model, V denotes a set of virtual nodes, E denotes a set of edges, W V (t) represents a set of node weights, W E (t) represents a set of edge weights.
An apparatus for constructing a dynamic satellite network model, comprising:
the node configuration module is used for configuring virtual nodes for the static area; dividing the earth into a plurality of static disjoint areas according to the longitude and the latitude to obtain a static area;
the weight defining module is used for defining the virtual nodes and edges formed by the virtual nodes according to the calculation tasks reaching the virtual nodes and the satellite available resources of the associated satellites to obtain edge weights and node weights;
and the network establishing module is used for establishing a dynamic satellite network model according to the virtual nodes, the edges, the edge weight and the node weight.
After the virtual nodes are configured for the static area, the device for constructing the dynamic satellite network model defines the virtual nodes and the edges formed by the virtual nodes according to the calculation tasks reaching the virtual nodes and the satellite available resources of the associated satellites to obtain edge weights and node weights, and establishes the dynamic satellite network model according to the virtual nodes, the edges, the edge weights and the node weights. Dynamic edge weights and node weights are used for representing the dynamic property of the satellite network, the problem of network topology change caused by high-speed relative motion of the satellite is solved with good expansibility, and adverse effects caused by a network modeling method based on snapshot are avoided. Meanwhile, the routing strategy fusion calculation and transmission of the dynamic satellite network model are facilitated.
A computing power perception routing method of a dynamic satellite network model comprises the following steps:
calculating the total time delay of each alternative routing path in the dynamic satellite network model of each subtask in the task; the alternative routing path consists of virtual nodes and edges formed by the virtual nodes; one virtual node on the alternative routing path is used as a computing node to complete the computing requirement of the subtask; wherein, the total time delay comprises processing time delay and transmission time delay;
and obtaining the optimal routing path of the subtask according to the alternative routing path corresponding to the minimum value in the total time delay of the subtask on each alternative routing path.
According to the computing power perception routing method of the dynamic satellite network model, after the total time delay of each subtask on each alternative routing path in the computing task is calculated, the optimal routing path for processing the subtask is obtained according to the path corresponding to the minimum value in the total time delay of each alternative routing path. The optimal routing path is determined by adopting a computational power perception routing method of a dynamic satellite network model, and the bandwidth of a transmission link is saved and the risk of network congestion is reduced by transmitting a calculation result instead of original data. Meanwhile, the optimal routing path is found for each subtask, so that parallel transmission and calculation can be performed by using a large number of satellites in the low-earth orbit satellite network, and the total delay of task transmission and processing is reduced.
In one embodiment, the process of obtaining the optimal routing path of the subtask according to the candidate routing path corresponding to the minimum value of the total time delays of the subtasks on the candidate routing paths is as follows:
wherein pi is an alternative routing path and is a transmission path pi u,v,t And a computing node u thereon q Composition is carried out;
is the path length; u is a subtask
V is a subtask
Ψ (-) is a mapping between the alternative routing path Π and the start time t and path length (i.e., total delay).
In one embodiment, the process of obtaining an alternative routing path includes the steps of:
calculating the shortest path from the source node to each calculation node as a first sub-path;
calculating the shortest path from each calculation node to the target node as a second sub-path;
an alternative routing path is determined from the first sub-path, the compute node, and the second sub-path.
In one embodiment, the process of calculating the shortest path from a source node to each of the computing nodes as a first sub-path includes the steps of:
converting the process of transmitting the subtasks from the source node to the computing node into a first DSSSP problem, and determining a first sub-path according to the solution of the first DSSSP problem;
the process of calculating the shortest path from each calculation node to the target node as the second sub-path includes the steps:
and converting the process of transmitting the subtasks from the computing node to the target node into a second DSSSP problem, and determining a second sub-path according to the solution of the second DSSSP problem.
A computing-aware routing device for a dynamic satellite network model, comprising:
the time delay calculation module is used for calculating the total time delay of each alternative routing path of each subtask in the tasks in the dynamic satellite network model; the alternative routing path consists of virtual nodes and edges formed by the virtual nodes; one virtual node on the alternative routing path is used as a computing node to complete the computing requirement of the subtask; wherein, the total time delay comprises processing time delay and transmission time delay;
and the route sensing module is used for obtaining the optimal routing path of the subtask according to the alternative routing path corresponding to the minimum value in the total time delay of the subtask on each alternative routing path.
According to the computing power perception routing device of the dynamic satellite network model, after the total time delay of each subtask in the computing task on each alternative routing path, the optimal routing path for processing the subtask is obtained according to the path corresponding to the minimum value in the total time delay of each alternative routing path. The optimal routing path is determined by adopting a computational power perception routing method of a dynamic satellite network model, and the bandwidth of a transmission link is saved and the risk of network congestion is reduced by transmitting a calculation result instead of original data. Meanwhile, the optimal routing path is found for each subtask, so that parallel transmission and calculation can be performed by using a large number of satellites in the low-earth orbit satellite network, and the total delay of task transmission and processing is reduced.
A computer storage medium having stored thereon computer instructions, which when executed by a processor, implement the method for constructing a dynamic satellite network model or the method for computing-aware routing of a dynamic satellite network model according to any of the above embodiments.
A computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for constructing a dynamic satellite network model or the method for computing-aware routing of a dynamic satellite network model according to any of the above embodiments when executing the program.
Drawings
FIG. 1 is a flow chart of a method for constructing a dynamic satellite network model according to an embodiment;
FIG. 2 is a flow chart of a method for constructing a dynamic satellite network model according to another embodiment;
FIG. 3 is a schematic diagram of a dynamic satellite network model according to an embodiment;
FIG. 4 is a flow diagram of a computational-aware routing method for a dynamic satellite network model according to one embodiment;
FIG. 5 is a schematic diagram of the effect of the data size and computational requirements of the subtasks on the computation of the ratio of the perceived routing delay to the delay of the reference routing algorithm;
FIG. 6 is a block diagram of an apparatus for constructing a dynamic satellite network model according to an embodiment;
FIG. 7 is a block diagram of a computational power aware routing device module of the dynamic satellite network model according to an embodiment;
FIG. 8 is a schematic diagram of an internal structure of a computer according to an embodiment.
Detailed Description
For better understanding of the objects, technical solutions and effects of the present invention, the present invention will be further explained with reference to the accompanying drawings and examples. Meanwhile, the following described examples are only for explaining the present invention, and are not intended to limit the present invention.
The embodiment of the invention provides a method for constructing a dynamic satellite network model.
Fig. 1 is a flowchart of a method for constructing a dynamic satellite network model according to an embodiment, and as shown in fig. 1, the method for constructing a dynamic satellite network model according to an embodiment includes steps S100 to S102:
s100, configuring virtual nodes for the static area; dividing the earth into a plurality of static disjoint areas according to the longitude and latitude to obtain static areas;
s101, according to a calculation task reaching a virtual node and satellite available resources of an associated satellite, defining the virtual node and an edge formed by the virtual node pair to obtain an edge weight and a node weight;
and S102, establishing a dynamic satellite network model according to the virtual nodes, the edges, the edge weight values and the node weight values.
Before the dynamic satellite network model is established, the earth is divided into a plurality of static disjoint areas according to longitude and latitude, namely, longitude and latitude area division of the earth surface is obtained, for example, a middle area determined by two warps and two wefts is used as a static area. A static area corresponding to a virtual node VN i In one embodiment, the sub-satellite points of the satellites associated with a virtual node are located in a static region corresponding to the virtual node. The satellites associated with a particular virtual node are dynamically changed based on the operation of the LEO constellation. Wherein the edges between each pair of virtual nodes represent communication links between the associated satellites. If the number of satellites associated with two virtual nodes is n1 and n2, there are n1 × n2 edges between the two virtual nodes.
As a preferred embodiment, the links established between the virtual nodes and the peripheral virtual nodes include 2 same-track links and 2 different-track links.
Due to the high dynamics of the LEO constellation, the inter-satellite distance of the satellite, the available inter-satellite spectrum resources and the available on-satellite resources all vary in real time. In one embodiment, the computing task needs to select a virtual node as a computing node in a transmission path for computing, and the corresponding processing delay is related to the satellite available resources of the virtual node.
In one embodiment, a computing task includes a plurality of subtasks.
Virtual node VN arrival setting u Is Γ u,k The calculation task T u,k Decomposable into a plurality of independent subtasks, i.e.
Wherein the content of the first and second substances,
for computing tasks t u,k The ith subtask of (1), n u,k Is gamma u,k The total number of neutron tasks. Wherein, the route destination node of the subtask is the same as the task of the subtask.
In one embodiment, the sub-tasks are passed
Required amount of calculation
(in giga floating point operations), subtasks
Amount of data required
(in bits), subtasks
Required memory resources
(in bits), subtasks
Required delay requirement
(in seconds) and subtasks
Destination longitude of
Latitude
And time of subtask creation
The subtask is defined by parameters, which are as follows:
based on the complexity of the subtasks, in one embodiment, the self-parameter definition of the calculation task needs to be considered for the edge weight and the node weight in step S101 to cope with the dynamic satellite network change.
In one embodiment, the on-board available resources in step S101 include on-board computing resources, battery storage resources, and storage resources. And through a calculation task reaching the virtual node and satellite available resources related to the satellite, performing weight definition on the virtual node and an edge formed by the virtual node pair to obtain an edge weight and a node weight, wherein the edge formed by the virtual node pair is subjected to attribute set definition, and the virtual node is subjected to attribute set definition.
The node weight and the edge weight of the virtual node are determined by several factors: the distance between satellites, the transmission rate between satellites, and the resources of satellite-borne calculation, energy and storage. Wherein, the first represents the network topology dynamic, and the second and third represent the network resource dynamic. The distance between the satellites continuously changes due to the high-speed movement of the satellites, so that the dynamic property of network topology is formed; the inter-satellite transmission rate and the on-board resources are constantly being occupied and released as tasks are transmitted and computed beginning and ending.
The above factors are updated according to a certain rule, and the edge weight and the node weight are correspondingly updated, so that the dynamic property of the network can be effectively reflected by the edge weight and the node weight
The definition of the attribute set for the virtual node is as follows: lambda V C, S, E, where the computation power matrix is defined as
The available memory matrix is defined as
The available battery energy storage matrix is defined as
And
respectively representing virtual nodes VN i Available computing power, memory resources and battery storage at time t.
The attribute set definition of the edge formed by the virtual node pair is as follows: lambda E D, B, where the inter-satellite distance matrix is denoted D ═ D i,j (t),i,j∈V,t∈[0,T]}，D i,j (t) is the time t virtual node VN i And virtual node VN j T is the simulation duration. The available spectrum bandwidth matrix of the inter-satellite link is expressed as
Is the virtual node VN at time t i And virtual node VN j The available spectrum bandwidth of the communication link therebetween. Wherein the content of the first and second substances,
transmission rate at time t of edge e ═ i, j, which indicates the configuration of the virtual node pair
And available spectrum bandwidth
Is in direct proportion.
In one embodiment, the inter-satellite distance matrix D is calculated based on satellite orbit parameters, and the available spectrum bandwidth matrix B, the calculation capability matrix C, the available memory matrix S, and the available battery energy storage matrix E are updated when LEO satellite network resources change.
Based on the method, the calculation task of the virtual nodes and the attribute definition of the edges formed by the virtual nodes and the virtual node pairs by the satellite available resources are completed. After the attribute definition is completed, weight definition is carried out according to the calculation task and the available resources on the satellite, and an edge weight and a node weight are calculated. The edge weight is the weight of the edge formed by the virtual node pairs, and the node weight is the weight of each virtual node.
In one embodiment, fig. 2 is a flowchart of a method for constructing a dynamic satellite network model according to another embodiment, and as shown in fig. 2, a process of defining a weight value of a virtual node in step S101 to obtain a node weight value includes step S200:
and S200, taking the processing time delay of the subtask in the calculation task as the node weight of the virtual node.
And the processing time delay is defined as a node weight value, so that the fusion of calculation and transmission in subsequent routing calculation is facilitated.
In one embodiment, in step S200, a process of calculating a processing delay of a sub-task in a task as a node weight of a virtual node is as follows:
wherein a virtual node VN is reached u Is Γ u,k Computing task gamma u,k Is a set of subtasks
For computing tasks t u,k The ith subtask of (1), n u,k Is gamma u,k The total number of neutron tasks;
for a virtual node VN i Completing the subtask at time t
The required processing delay;
to complete subtasks
The amount of computation required (in giga floating point operations),
to complete subtasks
The amount of memory required (in bits);
for a virtual node VN i The computational power available at time t (in giga floating point operations per second (GFLOPS)),
for a virtual node VN i The memory resources (in bits) that can be provided at time t,
for a virtual node VN i The battery energy storage (in watts-hour) that can be provided at time t; f (-) is a mapping function between the amount of computation and the energy consumption.
In one embodiment, when
Or
When the temperature of the water is higher than the set temperature,
is equal to ∞, indicating that virtual node VN at that time i The available memory or energy of cannot complete the subtask
The computational requirements of (1).
In one embodiment, as shown in fig. 2, the process of defining the weight of the edge formed by the virtual node pair in step S101 and obtaining the edge weight includes step S201:
s201, taking the sum of the transmission delay and the propagation delay of the subtask in the calculation task as an edge weight value.
And further converting the task data of the transmission task into the dynamic attribute of the dynamic satellite network model by taking the sum of the transmission delay and the propagation delay of the task as the edge weight.
In one embodiment, the process of calculating the sum of the propagation delay and the propagation delay of the subtask in the task as the edge weight in step S201 is as follows:
wherein the content of the first and second substances,
for a subtask of time t
The propagation delay on the edge e-i, j,
for a subtask at time t
Propagation delay on edge e ═ i, j;
as a subtask
The amount of data (in bit units),
for the edge e ═ transmission rate (in bits per second) at time t, D i,j (t) virtual node VN at time t i And virtual node VN j The distance between (in meters), c represents the speed of light (in meters per second),
for the virtual node VN at time t i And virtual node VN j The communicable time period therebetween (in seconds).
In one embodiment, in
When the temperature of the water is higher than the set temperature,
is equal to ∞, indicating that when the communicable time period is less than the time required for the transmission process, the calculation task
A successful transmission via the edge e ═ i, j cannot take place at time t.
After the attribute definition and the weight definition of the virtual nodes, the edges, the edge weights and the node weights are completed, a dynamic satellite network model is established according to the virtual nodes, the edges, the edge weights and the node weights.
In one embodiment, in step S102, a process of establishing a dynamic satellite network model according to the virtual nodes, the edges, the edge weights and the node weights is as follows:
G VSMN (t)＝{V,E,W E (t),W V (t)}
wherein, G VSMN (t) denotes a dynamic satellite network model, V denotes a set of virtual nodes, E denotes a set of edges, W V (t) represents a set of node weights, W E (t) represents a set of edge weights.
Wherein the set of virtual nodes V ═ { V ═ V 1 ,v 2 ,...,v n }(n＝|V|)。
Set of edges E ═ E 1 ,e 2 ,…,e m And (m ═ E |), side E ═ i, j indicates that i is the head node of E, and j is the tail node of E.
Set of node weights
Set of edge weights
To better explain the technical features of the embodiments of the present invention, a specific application example is explained below. Fig. 3 is a schematic diagram of a dynamic satellite network model according to a specific application example, and as shown in fig. 3, 16 static regions are included in a point (a/B/C/D). Conversion into dynamic satellite network model As shown in FIG. 3, the edge formed by the virtual node pair is represented as e (i, j, t), and the weight of the virtual node is w v The weight of the edge is w e 。
As shown in fig. 3, in the dynamic satellite network model in the embodiment of the present invention, there is no association with the snapshot, so that there is no problem that the generated routing path is invalid due to the fact that the duration of the generated routing path exceeds the effective time of the snapshot in the conventional snapshot-based LEO satellite network modeling method.
In the method for constructing a dynamic satellite network model according to any of the embodiments, after the virtual nodes are configured for the static region, the virtual nodes and the edges formed by the virtual nodes are defined by the weights according to the calculation tasks reaching the virtual nodes and the satellite available resources of the associated satellites, so as to obtain the edge weights and the node weights, and the dynamic satellite network model is established according to the virtual nodes, the edges, the edge weights and the node weights. Dynamic edge weights and node weights are used for representing the dynamic property of a satellite network, the problem of network topology change caused by high-speed relative motion of a satellite is solved with good expansibility, and adverse effects caused by a network modeling method based on snapshots are avoided. Meanwhile, the routing strategy fusion calculation and transmission of the dynamic satellite network model are facilitated.
Based on the dynamic satellite network model in any of the embodiments, an embodiment of the present invention further provides a computational power aware routing method for a dynamic satellite network model, which is used to design a computational power routing policy for a spatial computation task (hereinafter, "task"), of the dynamic satellite network model, where the task corresponds to a computation task in the method for constructing a dynamic satellite network model in any of the embodiments, and includes multiple sub-tasks.
Fig. 4 is a flowchart of a computing power aware routing method of a dynamic satellite network model according to an embodiment, as shown in fig. 4, including step S300 and step S301:
s300, calculating the total time delay of each routing path of each subtask in the task in the dynamic satellite network model; calculating the total time delay of each subtask on a plurality of alternative routing paths; the routing path consists of virtual nodes and edges formed by the virtual nodes; one virtual node on the path is used as a computing node to complete the computing requirement of the subtask; wherein, the total time delay comprises processing time delay and transmission time delay;
wherein, the processing time delay is the calculation time delay of the calculation node.
S301, obtaining the optimal routing path of the subtask according to the alternative routing path corresponding to the minimum value in the total time delay of the subtask on each alternative routing path.
In the dynamic satellite network model, both the node weight and the edge weight are related to time and task. And calculating the total time delay of each subtask in each alternative routing path in the task based on the node weight and the edge weight, so as to conveniently select an optimal routing path for each subtask.
In one embodiment, the optimal path of the subtask is characterized as the alternative routing path with the minimum total delay. The optimization problem (namely, the problem P1) selected for the optimal path of any subtask is defined as follows:
problem P1: g VSMN (t)＝{V,E,W E (t),W V (t) is a directed graph, where V ═ V 1 ,v 2 ,...,v n Is a node set, E ═ E |, V |) 1 ,e 2 ,…,e m And (m ═ E |) is a set of edges.
Wherein G is VSMN (t) denotes a dynamic satellite network model, V denotesSet of virtual nodes, E represents set of edges, W V (t) represents a set of node weights, W E (t) represents a set of edge weights. Hypothesis task
Is the k-th arriving virtual node VN u The task of (a), wherein,
is task gamma u,k U and v are subtasks, respectively
A source node and a destination node. For subtasks
Is a set of edge weight values that are,
is a set of node weights. Hypothesis subtasks
On the path P u,v ＝{(u 1 ,v 1 ),(u 2 ,v 2 ),…,(u q ,v q ),…,(u p ,v p )}(u 1 ＝u,v p ＝v,u p ＝v p-1 ,p,q∈Z + P ≧ q) and is transmitted by path P u,v Computing node u of q Processing (i.e., computing). If path P u,v Has a starting time of t 0 The length of the path P is defined as
Wherein, t q Is a subtask
To compute node u q Time of (u) q Is an edge e q ＝(u q ,v q ) With the starting point of Ψ (-) being the path P u,v And a computing node u q And a starting time t 0 And path length
To be mapped between. { t 1 ,t 2 ,...,t q-1 ,t q ,t′ q ,t q+1 ,...,t p The relationship between } is as follows:
t 1 ＝t 0
…
…
drawing G VSMN The computationally intensive routing problem in (t) (i.e., problem P1) is defined as finding a path π from a source node u to a destination node v at time t u,v,t And a computing node u on this path q So that the corresponding path length
Phi (-) is the mapping relation between the source node, the destination node, the start time and the optimal path).
Based on this, in one embodiment, the optimization of the P1 problem is performed according to the process of the alternative routing path corresponding to the minimum value in the total delay in step S300, as follows:
wherein pi is an alternative routing path and is a transmission path pi u,v,t And a computing node u thereon q Composition is carried out;
is the path length; u is a subtask
V is a subtask
The target node of (2). Ψ (-) is a mapping between alternate route path Π and the start time t and path length (i.e., total time delay).
The optimization problem P1 is an NP-hard problem, which is solved by the GA algorithm in this embodiment.
In one embodiment, the process of obtaining alternative routing paths includes the steps of:
calculating the shortest path from the source node to each calculation node as a first sub-path;
calculating the shortest path from each calculation node to the target node as a second sub-path;
an alternative routing path is determined from the first sub-path, the compute node, and the second sub-path.
Wherein the alternative routing path is determined by the first sub-path, the compute node, and the second sub-path. As a subtask
The process of finding an alternate routing path comprises the steps of:
(1) transmitting the subtask from the source node to the computing node (determining a first subpath), (2) processing the task by the computing node, (3) transmitting the calculation result from the computing node to the target node (determining a second subpath). Wherein, executing the embodiment includes converting the processes (1) and (3) into DSSSP (Dynamic Single Source short Path) problem. The computing power perception routing path of the subtask is computed by splitting the computing power perception routing problem of the subtask into a plurality of DSSSP problems and solving the DSSSP problems.
In one embodiment, the process of calculating the shortest path from a source node to each of the computing nodes as a first sub-path includes the steps of:
converting the process of transmitting the subtasks from the source node to the computing node into a first DSSSP problem, and determining a first subpath according to the solution of the first DSSSP problem;
the process of calculating the shortest path from each calculation node to the target node as the second sub-path includes the steps:
and converting the process of transmitting the subtasks from the computing node to the target node into a second DSSSP problem, and determining a second sub-path according to the solution of the second DSSSP problem.
Based on this, the source node u is calculated to the alternative computing node u q Shortest path to V
And its path length
The shortest path solution from the source node to the compute node is converted to a first DSSSP problem. In one embodiment, the first DSSSP problem may be solved by a genetic algorithm.
Acquiring the processing time delay of each alternative computing node;
as described above, candidate compute node u q E.g. V, a processing delay of
Calculating each alternative calculation node u q The shortest path from the epsilon V to the target node V is used as a second sub-path;
wherein, the node u is calculated q Shortest path from epsilon V to target node V
Having a path length of
And converting the shortest path calculation from the computing node to the target node into a second DSSSP problem. In one embodiment, the second DSSSP problem may be solved by a genetic algorithm.
Wherein, the obtained calculation result only contains a small amount of data (for example, only contains a few bits), so that the transmission delay of the edge is ignored.
Determining a routing path including the first sub-path, the computing node and the second sub-path as an alternative routing path;
the first path is longSum of degree, processing delay and second path length
The set of paths including the selected computing node is:
thereby determining the task
And complete the subtasks
Transmission and calculation of.
In one embodiment, the method for computing power-aware routing of a dynamic satellite network model of an embodiment further includes the steps of:
and updating the dynamic satellite network model.
Wherein updating the dynamic satellite network model comprises updating corresponding attribute values, including transmission subtasks for each edge on path pi
Computing node on the residual intersatellite bandwidth and path pi of the moment of (1)
And updating the residual energy storage of each virtual node. Based on the method, the real-time performance of the dynamic satellite network model is guaranteed.
Based on this, the power-aware routing method of the dynamic satellite network model of any of the above embodiments saves inter-satellite and satellite-ground bandwidth. The method saves the bandwidth of the inter-satellite and inter-satellite transmission links by transmitting the calculation result instead of the original data in the network, and reduces the risk of network congestion.
Meanwhile, the computational effort perception routing strategy provided by the computational effort perception routing method of the dynamic satellite network model in any embodiment transmits a computation result instead of original data after the computation node completes processing of the subtasks. Therefore, the amount of data to be transmitted is greatly reduced, and the energy consumption of transmission is reduced.
Meanwhile, the computational power perception routing method of the dynamic satellite network model of any embodiment realizes task computation in the transmission process, and a large number of satellites in an LEO constellation are used for parallel transmission and computation. Thus, the overall delay of task transmission and processing can be reduced.
Meanwhile, the computational power sensing routing method of the dynamic satellite network model in any of the embodiments considers intermittent communication and limited satellite-borne resources (such as energy and memory). The dynamic satellite network model has higher expansibility due to the fact that the dynamic performance of the low-orbit satellite and the constraint of limited satellite-borne resources are met.
In order to better explain the effect of the embodiment of the present invention, the following explains the technical effect of the embodiment of the present invention with a specific application example. Fig. 5 is a schematic diagram showing the effect of the data amount and the calculation requirement of the subtask on the calculation of the delay ratio of the perceived routing delay to the delay of the reference routing algorithm, and as shown in fig. 5, a ratio of 1.0 indicates that the two methods have the same good performance. The lower the ratio, the better the method of computationally aware routing of embodiments of the present invention.
The benchmark algorithm is to unload the subtasks to the ground for processing. As shown in fig. 5, the ratio of the delay of the computed aware route to the delay of the reference routing algorithm is less than 1 in a large parameter range, which indicates that the performance of the computed aware route in the large parameter range is due to the reference routing algorithm. In addition, the ground station may calculate the upper map in advance to obtain a parameter (i.e., the data amount and the calculation requirement of the subtask) boundary such that the ratio of the calculated perceived routing delay to the delay of the reference routing algorithm is equal to 1, store the corresponding parameter boundary in the low-earth satellite, and determine whether to use the calculated perceived routing or unload the received task to the ground for processing by the low-earth satellite.
The embodiment of the invention also provides a device for constructing the dynamic satellite network model.
Fig. 6 is a block diagram of a device for constructing a dynamic satellite network model according to an embodiment, and as shown in fig. 6, the device for constructing a dynamic satellite network model according to an embodiment includes a node configuration module 100, a weight definition module 101, and a network establishment module 102:
a node configuration module 100, configured to configure a virtual node for a static area; dividing the earth into a plurality of static disjoint areas according to the longitude and the latitude to obtain a static area;
the weight definition module 101 is configured to define a weight of a virtual node and an edge formed by the virtual node according to a calculation task reaching the virtual node and an available satellite resource of an associated satellite, and obtain an edge weight and a node weight;
the network establishing module 102 is configured to establish a dynamic satellite network model according to the virtual nodes, the edges, the edge weights, and the node weights.
After the virtual nodes are configured for the static area, the device for constructing the dynamic satellite network model defines the virtual nodes and the edges formed by the virtual nodes according to the calculation tasks reaching the virtual nodes and the satellite available resources of the associated satellites to obtain edge weights and node weights, and establishes the dynamic satellite network model according to the virtual nodes, the edges, the edge weights and the node weights. Dynamic edge weights and node weights are used for representing the dynamic property of a satellite network, the problem of network topology change caused by high-speed relative motion of a satellite is solved with good expansibility, and adverse effects caused by a network modeling method based on snapshots are avoided. Meanwhile, the routing strategy fusion calculation and transmission of the dynamic satellite network model are facilitated.
The embodiment of the invention also provides a computing power perception routing device of the dynamic satellite network model.
Fig. 7 is a block diagram of a computational power aware routing apparatus of a dynamic satellite network model according to an embodiment, and as shown in fig. 7, the computational power aware routing apparatus of a dynamic satellite network model according to an embodiment includes a delay computation module 200 and a route awareness module 201:
a time delay calculation module 200, configured to calculate a total time delay of each alternative routing path in the dynamic satellite network model for each subtask in the task; the alternative routing path consists of virtual nodes and edges formed by the virtual nodes; one virtual node on the alternative routing path is used as a computing node to complete the computing requirement of the subtask; wherein, the total time delay comprises processing time delay and transmission time delay;
and the route sensing module 201 is configured to obtain an optimal routing path of the subtask according to the alternative routing path corresponding to the minimum value of the total time delays of the subtask on each alternative routing path.
According to the calculation-force-sensing routing method of the dynamic satellite network model, after the total time delay of each subtask in a calculation task on each alternative routing path, the optimal routing path for processing the subtask is obtained according to the path corresponding to the minimum value in the total time delay of each alternative routing path. The optimal routing path is determined by adopting a computational power perception routing method, and the bandwidth of a transmission link is saved and the risk of network congestion is reduced by transmitting a calculation result instead of original data. Meanwhile, the optimal routing path is found for each subtask, so that parallel transmission and calculation can be performed by using a large number of satellites in the low-earth orbit satellite network, and the total delay of task transmission and processing is reduced.
The embodiment of the invention also provides a computer storage medium, on which computer instructions are stored, and when the instructions are executed by a processor, the method for constructing the dynamic satellite network model or the method for computing power-aware routing of the dynamic satellite network model according to any of the above embodiments is implemented.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, the computer program can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a RAM, a ROM, a magnetic or optical disk, or various other media that can store program code.
Corresponding to the computer storage medium, in an embodiment, there is also provided a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any one of the methods for constructing a dynamic satellite network model and the method for computationally aware routing of a dynamic satellite network model in the embodiments.
The computer device may be a terminal, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of building a dynamic satellite network model or a method of computationally aware routing of a dynamic satellite network model. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
After the computer equipment configures the virtual nodes for the static area, the weight of the virtual nodes and the edges formed by the virtual nodes are defined according to the calculation tasks reaching the virtual nodes or the available resources on the satellite of the associated satellite, the edge weight and the node weight are obtained, and a dynamic satellite network model is established according to the virtual nodes, the edges, the edge weight and the node weight. The dynamic property of the satellite network is represented based on the dynamic edge weight and the node weight, so that the problem of network topology change caused by high-speed relative motion of the satellite can be well solved in an expandable manner, and adverse effects caused by a network modeling method based on a snapshot are avoided. Meanwhile, the routing strategy fusion calculation and transmission of the dynamic satellite network model are facilitated.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A computing power perception routing method of a dynamic satellite network model is characterized by comprising the following steps:
calculating the total time delay of each alternative routing path in the dynamic satellite network model of each subtask in the task; the alternative routing path consists of virtual nodes and edges formed by the virtual nodes; one virtual node on the alternative routing path is used as a computing node to complete the computing requirement of the subtask; wherein the total time delay comprises a processing time delay and a transmission time delay;
and obtaining the optimal routing path of the subtask according to the alternative routing path corresponding to the minimum value in the total time delay of the subtask on each alternative routing path.
2. The computing power aware routing method of a dynamic satellite network model according to claim 1, wherein the process of obtaining the optimal routing path of the subtask according to the candidate routing path corresponding to the minimum value of the total delays of the subtasks on the candidate routing paths is as follows:
II is the alternative route path, and pi is the transmission path u,v,t And a computing node u thereon q Forming;
the path length of the alternative routing path; u is a subtask
V is a subtask
Ψ (-) is a mapping between the alternative routing path Π and the start time t and path length.
3. The computational-aware routing method of a dynamic satellite network model according to claim 1 or 2, wherein the process of obtaining the alternative routing path comprises the steps of:
calculating the shortest path from the source node to each calculation node as a first sub-path;
calculating the shortest path from each calculation node to the target node as a second sub-path;
determining the alternative routing path according to the first sub-path, the compute node, and the second sub-path.
4. The computational-aware routing method of a dynamic satellite network model according to claim 3, wherein the process of computing the shortest path from a source node to each computing node as a first sub-path comprises the steps of:
converting the process of transmitting the subtasks from the source node to the computing node into a first DSSSP problem, and determining the first sub-path according to the solution of the first DSSSP problem;
the process of calculating the shortest path from each of the calculation nodes to the target node as a second sub-path includes the steps of:
and converting the process of transmitting the subtask from the computing node to the target node into a second DSSSP problem, and determining the second subpath according to the solution of the second DSSSP problem.
5. The computational-aware routing method for a dynamic satellite network model according to claim 1, wherein the processing delay is a computational delay of a computational node.
6. The computational-aware routing method of a dynamic satellite network model according to claim 4, wherein the first DSSSP problem is solved by a genetic algorithm.
7. The computational-aware routing method for a dynamic satellite network model according to claim 1, further comprising the steps of:
and updating the dynamic satellite network model.
8. A computing power aware routing apparatus for a dynamic satellite network model, comprising:
the time delay calculation module is used for calculating the total time delay of each alternative routing path of each subtask in the tasks in the dynamic satellite network model; the alternative routing path consists of virtual nodes and edges formed by the virtual nodes; one virtual node on the alternative routing path is used as a computing node to complete the computing requirement of the subtask; wherein, the total time delay comprises processing time delay and transmission time delay;
and the route sensing module is used for obtaining the optimal routing path of the subtask according to the alternative routing path corresponding to the minimum value in the total time delay of the subtask on each alternative routing path.
9. A computer storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the computational-aware routing method of the dynamic satellite network model of any of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, implements the computational power aware routing method of a dynamic satellite network model according to any of claims 1 to 7.
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