CN107483355A - The online scene low bandwidth overhead flow scheduling scheme at data-oriented center - Google Patents
The online scene low bandwidth overhead flow scheduling scheme at data-oriented center Download PDFInfo
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- CN107483355A CN107483355A CN201710805436.1A CN201710805436A CN107483355A CN 107483355 A CN107483355 A CN 107483355A CN 201710805436 A CN201710805436 A CN 201710805436A CN 107483355 A CN107483355 A CN 107483355A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
Abstract
The online scene low bandwidth overhead flow scheduling scheme at data-oriented center, is a kind of the Internet transmission control technology.Its purpose is to pass through each bulk transport stream of rational management so that the bandwidth of data center owner rents expense minimum, while also ensures that all bulk transport streams are timely completed.It performs flow as 1) operation controller, obtains the source destination node of all bulk transport streams in a lease period, data volume, arrival and deadline in real time；2) when each bulk transport stream reaches, expense is rented as target to minimize extra bandwidth, on the premise of ensureing that all bulk transport streams can be completed, reaches the minimum of bandwidth cost.The present invention can effectively reduce the expense that data center owner rents bandwidth to Internet Service Provider on the premise of ensuring service quality, and reduce data center's operation cost.
Description
Technical field
The invention belongs to Internet technical field, is related to flow scheduling technology, more particularly to a kind of data-oriented center
Online scene low bandwidth overhead flow scheduling scheme.
Background technology
Many Internet service providers and cloud service provider maintain multiple data centers to support its business, such as Microsoft, paddy
Song.The various distributed application programs of the overall situation are run in these data centers, and they are distributed in different geographic areas,
Which dictates that they have the demand being in communication with each other across geographic area, wide area network is ensureing that these data centers can be in different geographical positions
The effect of key has been played in the intercommunication put.Mass data transport stream result in high bandwidth and open between data center
Pin, data center owner will rent wide area network bandwidth to Internet Service Provider every year, costly up to several hundred million.It is severeer
, irrational flow scheduling result in the low bandwidth availability ratio between data center, the bandwidth profit of most links
It is no more than 60% with rate, it means that the waste of significant proportion in high bandwidth cost be present.How rationally and effectively to carry out
Flow scheduling, bandwidth cost is reduced, while ensures that data flow is timely completed, become one of flow scheduling field between data center
Individual major issue.
Bulk transport stream is defined as between data center that accounting is great in wide area network flow, and data volume is big and when continuing
Between long a kind of stream.Usual bulk transport stream account for 85% to 95% proportion between data center in flow, data volume is several
TB to several PB, duration are up to some hours.Its two exemplaries are：Financial institution is in day of trade remote backup transaction
Record, search engine periodically synchronous index entry etc. between data center.Another kind of stream between data center is interactive small
Stream, their duration is shorter, and delay sensitive is stronger.The requirement to time delay is not high by contrast for bulk transport stream, can
The time delay brought is scheduled using Centralized Controller with tolerance.To sum up, reasonably scheduling is carried out to bulk transport stream has weight
The meaning wanted.In some scenarios, the parameter of all bulk transport streams is all unpredictable in a period of time, and a bulk passes
The arrival time of defeated stream, deadline, data volume is only just it is known that these scenes are referred to as in the field of line after it is produced
Scape.To the rational management of chunk data stream under online scene, the great guarantee of network service quality is not only, can more be saved
Substantial amounts of bandwidth rents the effective way of expense.
Many research work around the expansion of rational management bulk transport stream have been emerged in recent years.A kind of main thought
It is to increase storage device on the data centre, chooses whether to store when data reach or forward, that is, storage forwarding plan
Slightly.The research work deployed under this thinking has two kinds, and the first work proposes to keep in what is reached when link is busy
Data, data are transmitted when link idle, the utilization rate of bandwidth is finally improved on time dimension.Another kind work is logical
The bandwidth availability ratio crossed on each link of storage forwarding strategy balance, it is achieved thereby that load balancing.Since it is desired that temporary pass through
The flow of each data center, the deployed with devices under this thinking need to increase extra storage device in each data center,
Storage overhead is so not only adds additional, also causes flow scheduling to become more complicated.Therefore, it is intended that seek one kind more
Rational scheduling scheme, the optimization of bandwidth cost is carried out, while ensured on the premise of extra storage expense is not increased each big
Block transport stream is timely completed.
The content of the invention
The shortcomings that in order to overcome above-mentioned prior art, it is an object of the invention to provide a kind of the online of data-oriented center
Scene low bandwidth overhead flow scheduling scheme, on the premise of ensureing that all bulk transport streams can be timely completed, pass through conjunction
The scheduling of reason, minimize the extra bandwidth that every bulk transport stream of number is brought and rent expense, so as to minimize total bandwidth cost；
The present invention is that each bulk transport stream reasonably distributes bandwidth in each transmission time slot, sets transmitting path, is ensureing own
On the basis of bulk transport stream is timely completed, minimizes bandwidth and rent expense.
To achieve these goals, the technical solution adopted by the present invention is：
A kind of online scene low bandwidth overhead flow scheduling scheme at data-oriented center, the Wide Area Network between data center
Under realized according to following steps：
Step (1), a lease period is divided into several transmission time slots, i.e., 1 ..., T, with a digraph G=(V,
E the link between data center and data center) is represented, wherein V is the node set of digraph, is represented in all data
The set of the heart, E are the side collection of digraph, represent the set of all links, with five-tuple ri=(si,ti,di,ai,τi) carry out generation
One bulk transport stream of table, wherein si, ti, di, ai, τiSource node, destination node, the number of i-th of bulk transport stream are represented respectively
According to amount, arrival time and deadline；Centralized Controller is run, dynamically obtains source node, the mesh of each bulk transport stream
Node, data volume, arrival time and deadline；
Step (2), OPPG algorithms are run, calculate its scheduling scheme when every bulk transport stream reaches, algorithm is initial
During change, all bandwidth value c are madee=0；
Step (3), when each bulk transport stream reaches, minimum additional bandwidth overhead is calculated by OPPG algorithms, specifically
Step is as follows：
Step (3a), whole feasible paths of the stream are traveled through by Depth Priority Algorithm, finds out and continues in the stream
Time [ai,ti] interior bandwidth value ceThe path not being fully used, there is the number of the path transmission of the remaining bandwidth stream using these
According to；If riIt is transmitted, then algorithm terminates, and goes to step (3e), otherwise, goes to step (3b)；
Step (3b), all V of Schillinge=0, VeIt is worth for link e rental；
Step (3c), whole feasible paths of the stream are traveled through by Depth Priority Algorithm, because sharp in step 2
With all remaining bandwidths, so all feasible paths must have a congestion side, the i.e. moment on congestion side at any time
The bandwidth value used is ce；In ergodic process, the congestion side at all moment on all paths is found out, for certain road at moment
A congestion side e on footpath, calculate the bandwidth value c on the sideeIncrease it is one unit greater after, can additional transmissions on the moment path
Data volume d, order
Wherein, ueRepresent side e unit bandwidth price；
Step (3d), afterwards, select VeMaximum side e, makes ce=ce← 1, new remaining bandwidth is introduced with this, then redirect
To step (3a), remaining flow is transmitted using remaining bandwidth；
Step (3e), algorithm terminate, and obtain the scheduling scheme of the stream；
Step (4), flow scheduling scheme is generated according to arithmetic result, carries out flow scheduling.
Present invention P0Represent under traffic constraints, capacity-constrained and Integer constrained characteristic totally three constraints, make object function：
The optimization problem of minimum；
Wherein, traffic constraints have two, and first traffic constraints is：
And v ≠ si,v≠ti,
t∈[ai,τi] and t ∈ N+
δ+(v) set using node v as all directed edges of starting point, δ are represented-(v) represent using node v as all of terminal
The set of directed edge, xi,e(t) transmitted data amount at t-th moment of i-th of request on connection e, N are represented+Represent positive integer
Set；
Another traffic constraints is：
Wherein, δ+(si) represent with node siFor the set of all directed edges of starting point, δ-(si) represent with node siFor end
The set of all directed edges of point；
The capacity-constrained is：
Wherein, ceThe unit for the bandwidth rented for the bandwidth value rented on the e of side, expression data center owner on the e of side
Number, δcRepresent the size of unit bandwidth, δtRepresent the size of each timeslice；
The Integer constrained characteristic is：
Wherein N represents natural number set.
Compared with prior art, the beneficial effects of the invention are as follows：
1) on the premise of ensureing that all bulk transport streams can be transmitted at the appointed time, bandwidth rent is minimized
Expense.
2) scheme proposed by the present invention considers ISP and charged by certain particle size, and practicality is stronger.
3) scheme proposed in the present invention need not introduce extra storage device, save total scheduling overhead.
Brief description of the drawings
Fig. 1 is the online schematic diagram of a scenario at data-oriented center.
Fig. 2 is the particular flow sheet of the online scene low bandwidth overhead flow scheduling scheme at data-oriented center.Wherein ce
For the bandwidth value rented on the e of side, VeIt is worth for side e rental.
Embodiment
Describe embodiments of the present invention in detail with reference to the accompanying drawings and examples.
As shown in figure 1, the present invention considers the scheduling problem of the bulk transport stream in a lease period, if will be divided into the cycle
Dry transmission time slot, i.e., 1 ..., T.The link between data center and data center is represented with a digraph G=(V, E),
Wherein V is the node set of digraph, represents the set of all data centers, and E is the side collection of digraph, represents all chains
The set on road.With five-tuple ri=(si,ti,di,ai,τi) represent a bulk transport stream, wherein si, ti, di, ai, τiRespectively
Represent the source node of i-th of bulk transport stream, destination node, data volume, arrival time, and deadline.
For a bulk transport stream ri, it transmit data time be limited in time interval [ai,τi] within time
On piece.In addition, the source mesh node s of a requestiAnd tiBetween there may be a plurality of feasible path, per paths by one in E
Individual or multiple side e are in series, and as described above, use xi,e(t) t-th moment of i-th of request on the e of side is represented
Transmitted data amount, traffic constraints can be obtained：
And v ≠ si,v≠ti,
t∈[ai,τi] and t ∈ N+
The constraint is meant that, institute of any one bulk transport stream on the node outside its all source destination nodes
Sometimes engrave and must be fulfilled for flow conservation, i.e., be necessarily equal to flow from the flow sum for belonging to the bulk transport stream of node outflow
Enter the flow sum for belonging to the bulk transport stream of the node.Wherein, δ+(v) all directed edges using node v as starting point are represented
Set, δ-(v) set using node v as all directed edges of terminal is represented.
Another traffic constraints is：
The constraint ensures the flow sum for belonging to the bulk transport stream of the source node outflow of any one bulk transport stream
Subtract the flow sum for belonging to the bulk transport stream for flowing into source node and summation is engraved when all equal to the bulk transport stream
Total data transmission quantity, it is to ensure that all bulk transport streams can be completed at the appointed time that it, which is acted on,.
Total speed that flow is transmitted to ensure any one link in any transmission time slot is no more than the link rented
Amount of bandwidth, xi,e(t) it must is fulfilled for capacity-constrained：
Wherein, wherein ceRepresent the units for the bandwidth that data center owner rents on the e of side, δcRepresent unit bandwidth
Size, δtRepresent the size of each timeslice.
Due to the bandwidth of graduation of whole numbers of units, c must be rented when data center owner rents bandwidtheFor integer variable, therefore ce
Need to meet Integer constrained characteristic：
In order to realize that the present invention minimizes the target that bandwidth rents expense, this programme P0Represent in traffic constraints, capacity
Constraint and Integer constrained characteristic under totally three constraints, make object function：
The optimization problem of minimum.Wherein ueRepresent the unit bandwidth price of e this edges.
Because P0In each bulk transport stream be timesharing produce rather than predict in advance, P0It is not the integer line of standard
Property planning problem, this programme include solve the problem online rental scheme generating algorithm (OPPG).The thought of the algorithm is,
When each bulk transport stream reaches, minimize to dispatch the increased overhead of newly arrived bulk transport stream institute, algorithm
Flow be：
1st, all bandwidth value c are madeeEqual to zero.
2nd, whenever new bulk transport stream riDuring arrival, by Depth Priority Algorithm travel through the stream all can walking along the street
Footpath, find out the duration [a in the streami,ti] interior bandwidth value ceThe path not being fully used, there is remaining bandwidth using these
The path transmission stream data.If riIt is transmitted, then algorithm terminates.
If the 3, the data of the stream also have residue, need additionally to rent new bandwidth according to the value of link.Definition
VeIt is worth for the rental of e this edges, VeCalculation it is as follows：
All V of SchillingeEqual to zero.Afterwards, whole feasible paths of the stream are traveled through by Depth Priority Algorithm, because
All remaining bandwidths have been make use of in step 2, so all feasible paths must have a congestion side at any time, i.e., this when
It is c to be engraved in the bandwidth value used on congestion sidee.In ergodic process, the congestion side at all moment on all paths is found out, for
A congestion side e on certain moment paths, calculate the bandwidth value c on the sideeIncrease it is one unit greater after, energy on the moment path
The data volume d of additional transmissions, order
Afterwards, V is selectedeMaximum side, makes ce←ce+ 1, new remaining bandwidth is introduced with this, then step 2 is jumped to, utilize
Remaining bandwidth transmits remaining flow.
Therefore, reference picture 2, the online scene low bandwidth overhead flow scheduling scheme at data-oriented center of the present invention, in number
Realized according under Wide Area Network between center according to following steps：
Step (1) runs Centralized Controller, dynamically obtains the source node of each bulk transport stream, destination node, data
Amount, arrival time and deadline.OPPG algorithms are run simultaneously, its dispatching party is calculated when every bulk transport stream reaches
Case.
During step (2) algorithm initialization, all c are madee=0.
When each bulk transport stream of step (3) reaches, minimum additional bandwidth overhead, specific step are calculated by OPPG algorithms
It is rapid as follows：
Step (3a) travels through whole feasible paths of the stream by Depth Priority Algorithm, find out the stream it is lasting when
Between [ai,ti] interior bandwidth value ceThe path not being fully used, there are the data of the path transmission of the remaining bandwidth stream using these.
If riIt is transmitted, then algorithm terminates, and goes to step (3e), otherwise, goes to step (3b).
All V of step (3b) Schillinge=0.
Step (3c) travels through whole feasible paths of the stream by Depth Priority Algorithm, because sharp in step 2
With all remaining bandwidths, so all feasible paths must have a congestion side, the i.e. moment on congestion side at any time
The bandwidth value used is ce.In ergodic process, the congestion side at all moment on all paths is found out, for certain road at moment
A congestion side e on footpath, calculate the bandwidth value c on the sideeIncrease it is one unit greater after, can additional transmissions on the moment path
Data volume d, order
After step (3d), V is selectedeMaximum side e, makes ce←ce+ 1, new remaining bandwidth is introduced with this, then jump to
Step (3a), remaining flow is transmitted using remaining bandwidth.
Step (3e) algorithm terminates, and obtains the scheduling scheme of the stream.
Step (4) generates flow scheduling scheme according to arithmetic result, carries out flow scheduling.
In summary, the present invention proposes a kind of online scene low bandwidth overhead flow scheduling side at data-oriented center
Case.The program can ensure that all bulk transport streams are timely completed, while not introduce extra storage overhead.In this premise
Under, the program greatly improves link utilization, minimizes the extra bandwidth that every stream is brought and rents expense, so as to save
The operation cost of data center.
Claims (2)
1. the online scene low bandwidth overhead flow scheduling scheme at a kind of data-oriented center, it is characterised in that in data center
Between realized according to following steps under Wide Area Network：
Step (1), a lease period is divided into several transmission time slots, i.e., 1 ..., T, come with a digraph G=(V, E)
The link between data center and data center is represented, wherein V is the node set of digraph, represents all data centers
Set, E is the side collection of digraph, represents the set of all links, with five-tuple ri=(si,ti,di,ai,τi) represent one
Individual bulk transport stream, wherein si, ti, di, ai, τiRepresent respectively the source node of i-th of bulk transport stream, destination node, data volume,
Arrival time and deadline；Centralized Controller is run, dynamically obtains source node, the purpose section of each bulk transport stream
Point, data volume, arrival time and deadline；
Step (2), OPPG algorithms are run, calculate its scheduling scheme when every bulk transport stream reaches, during algorithm initialization,
Make all bandwidth value ce=0；
Step (3), when each bulk transport stream reaches, minimum additional bandwidth overhead, specific steps are calculated by OPPG algorithms
It is as follows：
Step (3a), whole feasible paths of the stream are traveled through by Depth Priority Algorithm, find out the duration in the stream
[ai,ti] interior bandwidth value ceThe path not being fully used, there are the data of the path transmission of the remaining bandwidth stream using these；Such as
Fruit riIt is transmitted, then algorithm terminates, and goes to step (3e), otherwise, goes to step (3b)；
Step (3b), all V of Schillinge=0, VeIt is worth for side e rental；
Step (3c), whole feasible paths of the stream are traveled through by Depth Priority Algorithm, because make use of in step 2
All remaining bandwidths, so all feasible paths must have a congestion side at any time, i.e. the moment uses on congestion side
Bandwidth value be ce；In ergodic process, the congestion side at all moment on all paths is found out, on certain moment paths
A congestion side e, calculate the bandwidth value c on the sideeIncrease it is one unit greater after, on the moment path can additional transmissions data
Measure d, order
Wherein, ueRepresent link e unit bandwidth price；
Step (3d), afterwards, select VeMaximum side e, makes ce←ce+ 1, new remaining bandwidth is introduced with this, then jump to step
(3a), remaining flow is transmitted using remaining bandwidth；
Step (3e), algorithm terminate, and obtain the scheduling scheme of the stream；
Step (4), flow scheduling scheme is generated according to arithmetic result, carries out flow scheduling.
2. the online scene low bandwidth overhead flow scheduling scheme at data-oriented center, its feature exist according to claim 1
In using P0Represent under traffic constraints, capacity-constrained and Integer constrained characteristic totally three constraints, make object function：
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| CN108833294A (en) * | 2018-08-08 | 2018-11-16 | 清华大学 | The traffic scheduling method of the low bandwidth overhead of data-oriented center wide area network |
| CN109150597A (en) * | 2018-08-08 | 2019-01-04 | 清华大学 | The bandwidth cost of cloud service-oriented provider reduces method |
| CN109617710A (en) * | 2018-11-09 | 2019-04-12 | 西北大学 | The big data transmission bandwidth dispatching method for thering is deadline to constrain between data center |
| CN115442313A (en) * | 2022-07-20 | 2022-12-06 | 中通服咨询设计研究院有限公司 | Wide-area deterministic service flow online scheduling system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108833294A (en) * | 2018-08-08 | 2018-11-16 | 清华大学 | The traffic scheduling method of the low bandwidth overhead of data-oriented center wide area network |
| CN109150597A (en) * | 2018-08-08 | 2019-01-04 | 清华大学 | The bandwidth cost of cloud service-oriented provider reduces method |
| CN108833294B (en) * | 2018-08-08 | 2020-10-30 | 清华大学 | Low-bandwidth-overhead flow scheduling method for data center wide area network |
| CN109617710A (en) * | 2018-11-09 | 2019-04-12 | 西北大学 | The big data transmission bandwidth dispatching method for thering is deadline to constrain between data center |
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