CN115942472A - Concurrent scheduling and resource allocation method in wireless ad hoc network - Google Patents
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Abstract
The invention relates to a concurrent scheduling and resource allocation method in a wireless ad hoc network, which comprises the following steps: initializing a mobile ad hoc network, wherein each transmission link of the mobile ad hoc network has a transmission opportunity in each time period; based on the idea of the maximum independent set, all transmission links in the current time period are dispatched and distributed to different concurrent sets; maximizing the number of concurrent links in each group when scheduling allocation; initializing a group of time slot distribution coefficients, constructing a network benefit function according to different service requirements of links, converting the network benefit function into a nonlinear programming model, solving the nonlinear programming model by using a heuristic search algorithm to obtain an optimal time slot distribution strategy, and distributing transmission time slots for each group of concurrent sets based on the optimal time slot distribution strategy; and the transmission link determines a transmission mode and optimal transmission power according to the allocated time slot resources and the service flow of the transmission link. The invention can ensure the throughput gain while maximizing the energy gain.
Description
Technical Field
The invention relates to the technical field of resource allocation in a wireless ad hoc network, in particular to a concurrent scheduling and resource allocation method in the wireless ad hoc network.
Background
In the traditional TDMA mode, unicast transmission with a certain number of time slots is separately allocated to each data stream in a scheduling stage. Although data collisions and collisions are avoided, the transmission efficiency of the system is reduced. In addition, the traditional scheduling scheme does not consider the heterogeneous traffic demand of different links, and cannot adaptively schedule time slot and power resources of a network according to the dynamic change of the traffic demand of the links, thereby bringing certain resource waste.
Under the condition that the same time slot resource is allocated to a plurality of heterogeneous links to transmit services, the parallel transmission scheduling can enable each link to obtain more transmission time slots than a single-row scheme, and by increasing the time slot of each transmission, the transmission rate required by data transmission is reduced, so that the transmission power of the link is reduced, and the energy consumption is reduced while the data transmission task is completed.
A diagram of concurrent scheduling is shown in fig. 1. When multiple links required by heterogeneous services are transmitted concurrently, each link may generate a certain potential energy gain because the concurrent duration is longer than the duration required by the link service transmission. The potential energy gain is related to the concurrency duration and the traffic flow of the link, and the lower the traffic flow is, the larger the obtained potential energy gain is, but the throughput gain obtained by transmission is reduced. Therefore, there is a trade-off between throughput gain and energy gain at a certain concurrency duration. Therefore, based on the consideration of the overall efficiency of the network, a concurrent scheduling and resource allocation mechanism in the wireless ad hoc network needs to be designed.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a concurrent scheduling and resource allocation method in a wireless ad hoc network, which can ensure throughput gain while maximizing energy gain.
The technical scheme adopted by the invention for solving the technical problem is as follows: a concurrent scheduling and resource allocation method in a wireless ad hoc network is provided, which comprises the following steps:
(1) Initializing a mobile ad hoc network, wherein each transmission link of the mobile ad hoc network has a transmission opportunity in each time period;
(2) Based on the idea of the maximum independent set, all transmission links in the current time period are dispatched and distributed to different concurrent sets; maximizing the number of concurrent links per group during scheduling allocation;
(3) Initializing a group of time slot distribution coefficients, constructing a network benefit function according to different service requirements of links, converting the network benefit function into a nonlinear programming model, solving the nonlinear programming model by using a heuristic search algorithm to obtain an optimal time slot distribution strategy, and distributing transmission time slots for each group of concurrent sets based on the optimal time slot distribution strategy;
(4) And the transmission link determines a transmission mode and optimal transmission power according to the allocated time slot resources and the service flow of the transmission link.
The step (2) is specifically as follows: and simulating the competition relationship among the transmission links by using a competition graph, approaching a maximum independent set by using a minimum greedy algorithm, and iteratively scheduling all links to each group of concurrent sets.
Each vertex in the competition graph represents a transmission link in the mobile ad hoc network, each edge represents the competition relationship among the transmission links, and the connected transmission links do not allow concurrent transmission; if the interference between two transmission links is greater than a predetermined threshold, it represents that the vertices of the two transmission links are connected, and if an edge exists between two vertices, the two vertices are called neighbors.
The simulating the competition relationship among the transmission links by using the competition graph, approximating the maximum independent set by using a least greedy algorithm, and iteratively scheduling all the links to each group of concurrent sets specifically comprises:
(a) Representing the set of all transmission links in the mobile ad hoc network as V, representing the set of adjacent vertexes with any vertex V E V by N (V), and representing the degree of any vertex V E V by d (V);
(b) Constructing a transmission link with the minimum d (V) in the V into an ith group of concurrent set, and constructing a competition graph CG for the ith group of concurrent set i ＝(V i ,E i ) (ii) a Wherein, V i Set of vertices in the ith set of concurrent sets, E i Is the set of edges in the ith group of concurrent sets;
(c) Connecting V with any link V epsilon V i The unconnected links are used as candidate link sets of the ith group of concurrent sets and are expressed as
(d) Selecting
The transmission link with the minimum d (v) in the group I is added into the group I concurrent set, and the competition graph CG is updated i ＝(V i ,E i ) And from V and->
Wherein the transmission link is removed;
(e) Recycling step (d) until
If the link is null, obtaining the ith group of maximum concurrent link sets;
(f) And (c) turning to the step (b) to construct a next group of concurrent sets until V is empty.
The objective function of the nonlinear programming model in the step (3) is as follows:
wherein, { theta } 1 ,θ 2 ,…,θ K Assign coefficients for the time slots of each group of concurrent link sets, satisfy ^ er>
EE is a function of the benefit,
l i indicating the ith transmissionLink, χ k Represents a low load link set, and>
representing a set of high-load links, D i Indicating the traffic demand, T, of the ith transmission link c Indicating the number of slots of a transmission cycle, τ indicating the duration of a slot number, R i Indicates the transmission rate that can be achieved when the ith transmission link is concurrently transmitted with other transmission links in the concurrent link set in which the ith transmission link is located, and/or the transmission rate is greater than or equal to>
Representing the number of transmission links in the highly loaded link set.
The service flow of the transmission link in the low-load link set is less than a set flow threshold, the service flow of the transmission link in the high-load link set is greater than or equal to a set flow threshold, and the set flow threshold ω is i ＝R i θ k T c τ。
The constraint conditions of the nonlinear programming model in the step (3) are as follows:
wherein C1 and C2 respectively represent a low-load link set chi k And high load link set->
The threshold condition of the medium service requirement is met; c3 is to avoid traffic congestion, a high load link set @>
The flow threshold value of the medium transmission link is not less than epsilon times of the service requirement; c4 is the constraint of the concurrent link set on the number of links; c5 is a constraint on the slot allocation coefficient.
The step (4) is specifically as follows: when the transmission link belongs to the low-load link set, the time slot is allocated according to
Determining a transmission power, when the transmission link belongs to the set of low-load links, at a maximum transmission power P in the allocated time slot max W represents a channel bandwidth, V, as a transmission power k And G (i, j) represents the transmission path gain from the sending node of the j transmission link to the receiving node of the ith transmission link, and G (i, i) represents the path gain of the ith transmission link.
Advantageous effects
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects:
the invention increases the available time slot of each transmission of the link through concurrent transmission, so that the transmission rate required by service transmission is reduced, and further, the transmission power is reduced, and higher energy gain is obtained. The strategy firstly adopts a competition graph to simulate the competition relationship among links, then utilizes a least greedy algorithm to approach a maximum independent set, and iteratively schedules all links to be transmitted into each group of concurrent sets.
The invention adaptively allocates reasonable time slot resources and transmission power for the link according to the dynamic change of the traffic demand. Firstly, designing a flow threshold, dividing a link into a low-load link and a high-load link, transmitting data according to different transmission modes, then, taking throughput and energy consumption ratio as benefit indexes, providing a nonlinear programming model with maximized benefit, finally, solving by using a heuristic search algorithm to obtain an optimal time slot allocation strategy, and determining the optimal transmission power of all links.
The invention realizes and manages the concurrent transmission of all links by utilizing a concurrent strategy, reasonably distributes the time slot resources of the network and the transmission power of the links by combining the self-adaptive resource distribution, and ensures the throughput gain while maximizing the energy gain, thereby obtaining higher overall performance benefit of the network.
Drawings
FIG. 1 is a schematic diagram of concurrent scheduling;
fig. 2 is a schematic view of a superframe in the present embodiment;
fig. 3 is a flowchart of a concurrent scheduling and resource allocation method in the wireless ad hoc network according to the present embodiment;
FIG. 4 is a flowchart of the maximum independent set-based concurrent scheduling in this embodiment;
fig. 5 is a schematic diagram showing the relationship between the energy gain and the flow rate threshold value in the present embodiment.
Detailed Description
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
The embodiment of the invention relates to a concurrent scheduling and resource allocation method in a wireless ad hoc network, wherein the time is divided into a series of non-overlapping frames, one frame is a time period, and T is the time period c A plurality of equal-length time slots, as shown in fig. 2. Each frame is divided into two phases, one is a scheduling phase and the other is a transmission phase. In the scheduling stage, the network determines the specific scheduling scheme of all links to be transmitted in the current period through a scheduling strategy and a power control strategy. In the transmission phase, all links operate according to a scheduling scheme. As shown in fig. 3, the method specifically includes the following steps:
s1 network initialization
A mobile ad hoc network is initialized, the network is composed of a plurality of static nodes, each node is provided with an omnidirectional antenna and operates in a half-duplex mode. It is known that, in a certain time period, traffic volumes of all links to be transmitted and traffic flows thereof in a network are different. Each transmission link has a transmission opportunity during each time period.
S2 concurrent scheduling based on maximum independent set
Based on the idea of the maximum independent set, all transmission link schedules in the current time period are distributed to different concurrent sets, the number of links in the concurrent scheduling pairs is maximized as much as possible, and the number of total concurrent sets is reduced. In this step, given that the length of each time period is fixed, under the condition that the same time slot resource is allocated to a plurality of links to transmit services, the parallel transmission scheduling can enable each link to obtain more transmission time slots than the single-row scheme, and by increasing the available time slots of each transmission of the link, the link can reduce the transmission rate required by the service transmission of the link, and further can reduce the transmission power, so that the energy consumption can be reduced while the data transmission task is completed, and a certain energy gain can be obtained.
In this step, the number of concurrent links per group should be maximized as much as possible, so that more slots can be allocated to each group of concurrent sets by allocating all links to fewer concurrent sets. Therefore, a maximum independent set strategy is adopted to divide all the links to be transmitted into different concurrent sets.
The contention relationship between links is first simulated using a contention map. Each vertex in the contention map represents a link in the network. Each edge represents a contention relationship between links, and the connected links do not allow concurrent transmission. If the interference between the two links is greater than a predetermined threshold, it represents that the vertices of the two links are connected. Two vertices are said to be neighbors if there is an edge between them. The set of all links in the network is denoted V, with N (V) representing the set of adjacent vertices for any vertex V ∈ V. The degree of any vertex V ∈ V is represented by d (V). Next, the most independent set is approximated using a least greedy algorithm, iteratively scheduling links in V into each set of concurrent sets. As shown in fig. 4, the specific steps are as follows:
the method comprises the following steps: firstly, the link with the minimum d (V) in V is obtained to construct the ith group of concurrent set, and a competition graph CG is constructed for the group of links i ＝(V i ,E i ). Wherein V i For the set of vertices in the ith set, E i Is the set of edges in the ith pair.
Step two: connecting V with any link V epsilon V i The unconnected links are used as candidate link sets of the ith group of concurrent sets and are expressed as
Step three: selecting
Link join pairing in which d (v) is smallest, i.e. [ phi ]>
Updating the competition graph CG i ＝(V i ,E i ) And from V and->
Wherein the link is removed.
Step four: the third step is circulated until
And if the link is null, obtaining the ith group of the maximum concurrent link set.
Step five: and (5) turning to the step one to construct a next group of concurrent pairs until V is empty.
S3 time slot allocation strategy based on nonlinear programming model
Initializing a group of time slot distribution coefficients, constructing a network benefit function according to different service requirements of links, converting the network benefit function into a nonlinear programming model, solving the model by using a heuristic search algorithm to obtain an optimal time slot distribution strategy, and distributing transmission time slots for each group of concurrent sets respectively.
In this step, it is assumed that the transmission power of all links is P max According to a path loss model, link l i Received power P i Estimated as G (i, i) P max Wherein G (i, i) represents link l i The path gain of (1). When the link l j And l i Concurrent transmission, link l i Receiving a message from a link l j Has an interference power of G (i, j) P max Wherein G (i, j) represents link l j To the link l i Receiving the transmission path gain between nodes.
Suppose that M transmission links in a superframe are divided into K concurrent link groups Φ = { V = 1 ,V 2 ,…,V K For link l i ,l i ∈V k The signal-to-noise ratio SINR can be expressed as
Wherein V k Represents the kth set of concurrent links, σ 2 Representing the power spectral density of gaussian white noise.
Link l i And V k The achievable transmission rate when the other links transmit concurrently can be calculated as
Where W (hz) represents the channel bandwidth.
Defining a set of scaling coefficients Θ = { Θ = 1 ,θ 2 ,…,θ K The time slot distribution coefficient of each group of concurrent link sets is taken as, and the proportionality coefficient satisfies
Then it is assigned to the concurrent link set V k ,/>
Number of time slots delta for transmitting data k Is shown as
Wherein T is c Indicating the number of slots of one transmission cycle.
For link l i ∈V k At the allocated transmission duration delta k The transmission rate required to complete a transmission may be expressed as
Wherein D is i Represents a link l i τ denotes the duration of one slot number.
When other concurrent links l j ∈V k The transmission power of j ≠ i is P max Time, link l i Realization of R i ' required transmission power is
In the concurrent link set, all concurrent links have the same transmission duration, but the duration time required for transmitting data is different due to different sizes of the service demands of the links. As shown in fig. 5, when the service requirement of the link is less than a certain threshold, the data transmission duration required by the link is less than the allocated concurrency duration, and the link has a certain potential energy gain, and conversely, when the service requirement of the link is greater than the certain threshold, the data transmission duration required by the link is greater than the allocated concurrency duration, and a partial energy loss may occur. Therefore, it is necessary to reasonably allocate transmission time slots according to different traffic demands of the links, so as to maximize network efficiency.
The size of the traffic threshold ω is defined in relation to the duration of the link traffic transmission required and the allocated concurrency period. For link l i ∈V k With a flow threshold of
ω i ＝R i θ k T c τ(6)
Wherein the content of the first and second substances,
/>
when the link l i Traffic flow of less than threshold ω i A certain energy gain can be obtained by adjusting the transmission power, and the magnitude of the energy gain is related to the concurrency duration and the traffic demand of the link itself, on the contrary, when the link l is in use i Traffic flow of greater than a flow threshold ω i Adjusting its transmission power to complete the transmission of all services will bringA certain gain loss. Therefore, in order to maximize potential energy gain and improve energy efficiency of transmission, it is necessary to divide links into low-load links and high-load links according to a traffic threshold, and transmit data in different transmission modes:
(1) And (3) low-load link: the traffic flow is less than the flow threshold omega, and the transmission power is adjusted to
And completes transmission of all traffic flow with the power.
(2) High-load link: the traffic flow is larger than the flow threshold omega, and the maximum transmission power P is used in the concurrency duration max And completing transmission of a certain amount of service flow.
In this step, a set of scaling factors Θ = { θ = is initialized randomly 1 ,θ 2 ,…,θ K Define the set of low-load links as χ k ,
The set of heavily loaded links is ≧>
The total throughput of all transmission links in a transmission cycle is
Total energy consumption of all links is
Wherein (a) is derived from equation (5)
As can be seen from fig. 5, the higher the link traffic demand, the smaller the energy gain, but the increased throughput gain. I.e. there are conflicting constraints between throughput and energy gain. To equalize the overall performance gain between throughput and energy consumption, we define the throughput and energy consumption ratio as the benefit index. To equalize the overall performance gain between throughput and energy consumption.
The benefit function of the system is then:
approximated by xIn2 to 2 x -1, whereby the above formula can be simplified to
In order to maximize the performance gain of the system, the objective function P is expressed as
Constraint conditions
C1 and C2 respectively represent a low-load link set chi k And high-load link set
A threshold condition for medium service requirements; c3 is the set of heavily loaded links @, in order to avoid traffic congestion>
The flow threshold value of the medium transmission link is not less than epsilon times of the service requirement; c4 is the number of concurrent link sets to linksConstraining; c5 is a constraint on the slot allocation coefficients.
Finally, solving the optimization model by using a heuristic search algorithm to obtain a group of optimal proportionality coefficients theta 1 ,θ 2 ,…,θ K 。
S4 power control
Then, the link determines its transmission mode and optimal transmission power according to the allocated time slot resources and its own traffic flow. For link l i ∈V k Firstly, judging whether the service flow is lower than a flow threshold value, if so, determining the link is a low-load link and allocating time slot delta k Wherein the transmission power is determined according to equation (5). Otherwise, for the high-load link, in the allocated time slot delta k At the maximum transmission power P max And completing transmission of a certain amount of service flow.
S5 data transmission
And finally, the link transmits data with certain transmission power in the allocated time slot according to the scheduling scheme. Specifically, the network determines the specific scheduling scheme of all links to be transmitted in the current period through concurrent scheduling, time slot allocation and power control in the scheduling stage, and then all links perform operations according to the scheduling scheme in the transmission stage.
The invention realizes and manages the concurrent transmission of all links by utilizing a concurrent strategy, reasonably distributes the time slot resources of the network and the transmission power of the links by combining self-adaptive resource distribution, and ensures the throughput gain while maximizing the energy gain, thereby obtaining higher overall performance benefit of the network.
Claims (8)
1. A concurrent scheduling and resource allocation method in a wireless ad hoc network, comprising the steps of:
(1) Initializing a mobile ad hoc network, wherein each transmission link of the mobile ad hoc network has a transmission opportunity in each time period;
(2) Based on the idea of the maximum independent set, all transmission links in the current time period are dispatched and distributed to different concurrent sets; maximizing the number of concurrent links in each group when scheduling allocation;
(3) Initializing a group of time slot distribution coefficients, constructing a network benefit function according to different service requirements of links, converting the network benefit function into a nonlinear programming model, solving the nonlinear programming model by using a heuristic search algorithm to obtain an optimal time slot distribution strategy, and distributing transmission time slots for each group of concurrent sets based on the optimal time slot distribution strategy;
(4) And the transmission link determines a transmission mode and optimal transmission power according to the allocated time slot resources and the service flow of the transmission link.
2. The method for concurrent scheduling and resource allocation in a wireless ad hoc network according to claim 1, wherein the step (2) is specifically: and simulating the competition relationship among the transmission links by using a competition graph, approximating a maximum independent set by using a least greedy algorithm, and iteratively scheduling all links to each group of concurrent sets.
3. The method according to claim 2, wherein each vertex in the contention map represents a transmission link in the ad hoc network, each edge represents a contention relationship between transmission links, and a connected transmission link does not allow concurrent transmission; if the interference between two transmission links is greater than a predetermined threshold, it represents that the vertices of the two transmission links are connected, and if an edge exists between two vertices, the two vertices are called neighbors.
4. The method according to claim 2, wherein the simulating a contention relationship between transmission links by using a contention map, approximating a maximum independent set by using a least-squares greedy algorithm, and iteratively scheduling all links into each group of the concurrent sets comprises:
(a) Representing the set of all transmission links in the mobile ad hoc network as V, representing the set of adjacent vertexes with any vertex V E V by N (V), and representing the degree of any vertex V E V by d (V);
(b) Constructing the transmission link with the minimum d (V) in V into the ith group of concurrent set, and constructing a competition graph CG for the ith group of concurrent set i ＝(V i ,E i ) (ii) a Wherein, V i Set of vertices in the ith set of concurrent sets, E i Is the set of edges in the ith group of concurrent sets;
(c) Connecting V with any link V epsilon V i The unconnected links are used as candidate link sets of the ith group of concurrent sets and are denoted as V i c ；
(d) Selection of V i c The transmission link with the minimum middle d (v) is added into the ith group of concurrent sets, and the competition graph CG is updated i ＝(V i ,E i ) And from V and V i c Wherein the transmission link is removed;
(e) Recycling step (d) to V i c If the link is null, obtaining the ith group of maximum concurrent link sets;
(f) And (c) turning to the step (b) to construct a next group of concurrent sets until V is empty.
5. The method according to claim 1, wherein the objective function of the non-linear programming model in step (3) is:
wherein, { theta } 1 ,θ 2 ,…,θ K Assign coefficients for the time slots of each group of concurrent link sets, satisfy ^ er>
EE is the function of the benefit,
6. The method according to claim 5, wherein the traffic flow of the transmission links in the low-load link set is smaller than a set traffic threshold, the traffic flow of the transmission links in the high-load link set is greater than or equal to a set traffic threshold, and the set traffic threshold ω is smaller than the set traffic threshold i ＝R i θ k T c τ。
7. The method according to claim 5, wherein the constraints of the non-linear programming model in the step (3) are:
wherein C1 and C2 respectively represent a low-load link set chi k And high load link set->
The threshold condition of the medium service requirement is met; c3 is the set of heavily loaded links @, in order to avoid traffic congestion>
The flow threshold value of the medium transmission link is not less than epsilon times of the service requirement; c4 is the constraint of the concurrent link set on the number of links; c5 is a constraint on the slot allocation coefficients.
8. The method for concurrent scheduling and resource allocation in a wireless ad hoc network according to claim 5, wherein the step (4) is specifically: when the transmission link belongs to a set of low-load links, in accordance with
Determining a transmission power, and when the transmission link belongs to the low-load link set, using the maximum transmission power P in the allocated time slot max W represents a channel bandwidth, V, as a transmission power k And G (i, j) represents the transmission path gain from the sending node of the j transmission link to the receiving node of the ith transmission link, and G (i, i) represents the path gain of the ith transmission link. />
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| CN101247165A (en) * | 2007-02-16 | 2008-08-20 | 中兴通讯股份有限公司 | Networking system of TD-SCDMA system multi-frequency point community |
| CN106412992A (en) * | 2015-07-28 | 2017-02-15 | 上海无线通信研究中心 | Dynamic distributed resource scheduling method under ultra-dense WiFi network scenario |
| CN113840366A (en) * | 2020-06-24 | 2021-12-24 | 大唐移动通信设备有限公司 | Power control method, device, electronic equipment and storage medium |
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| CN101247165A (en) * | 2007-02-16 | 2008-08-20 | 中兴通讯股份有限公司 | Networking system of TD-SCDMA system multi-frequency point community |
| CN106412992A (en) * | 2015-07-28 | 2017-02-15 | 上海无线通信研究中心 | Dynamic distributed resource scheduling method under ultra-dense WiFi network scenario |
| CN113840366A (en) * | 2020-06-24 | 2021-12-24 | 大唐移动通信设备有限公司 | Power control method, device, electronic equipment and storage medium |
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