A distributed multi-channel anti-interference stable dynamic broadcast scheduling method and system

Abstract

The present invention proposes a distributed multi-channel anti-interference stable dynamic broadcast scheduling method and system, which relates to the technical field of wireless network broadcast scheduling, including: obtaining network source nodes and packet flows, building a multi-channel wireless network model according to network time and global accumulated wireless interference; using a random packet injection model to inject the packet flow at the source node into the multi-channel wireless network model; using a distributed multi-channel anti-interference wireless static broadcast scheduling method to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time; wherein the distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations, and the broadcast task of the injected packet is realized through the iterative multi-channel anti-interference wireless static broadcast scheduling method. The present invention can maintain the continuity and stability of key communications even in an interference environment, better utilize spectrum resources, and improve spectrum utilization.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless network broadcast scheduling, and in particular relates to a distributed multi-channel anti-interference stable dynamic broadcast scheduling method and system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Stable dynamic broadcast scheduling in wireless networks based on continuous flow is one of the key technologies for next-generation wireless networks. It faces challenges such as global accumulation of co-channel interference and random and malicious interference from external channels of the target network. At the same time, since packets are continuously randomly injected at all source nodes, it is extremely challenging to achieve distributed stable dynamic broadcast scheduling with high throughput efficiency and no central control under the premise of queue and delay stability.

[0004] The existing related wireless network stable dynamic broadcast scheduling methods have the following problems and shortcomings:

[0005] 1. Existing stable dynamic broadcast scheduling methods are mainly centralized dynamic broadcast scheduling methods based on traditional optimization methods or machine learning technologies. They are highly dependent on central control nodes and are difficult to apply to distributed wireless network systems that only rely on local information exchange between nodes.

[0006] The main reasons include the following two aspects: (1) All scheduling decisions of centralized dynamic broadcast scheduling rely on the central node. When the number of network nodes increases, the computing and communication burden of the central node will increase significantly; (2) The central node is easily attacked by malicious interference nodes. Once the central node is attacked, the scheduling work of the entire network will be unable to proceed, affecting the stability and reliability of the network.

[0007] 2. The existing stable dynamic broadcast scheduling methods are mainly aimed at reliable wireless communication environments. They do not consider the adverse effects of random and unpredictable wireless signal interference generated by malicious interference nodes in real wireless networks on the correctness, throughput and delay performance of dynamic broadcast scheduling methods, and are difficult to resist wireless interference attacks generated by malicious interference nodes in real wireless networks.

[0008] This is mainly because malicious interference can increase the noise level in the network, causing the channel quality to degrade, which directly affects the capacity and transmission rate of the wireless network. Malicious interference can cause the loss or delay of critical information, which is particularly problematic for communication systems that require high reliability.

[0009] 3. Most of the existing stable dynamic broadcast scheduling methods rely on the network backbone structure and the transmission scheduling technology based on the network backbone structure, such as the broadcast scheduling method based on the network spanning tree or the connected dominating set, which is difficult to adapt to large-scale time-varying wireless networks and unreliable wireless communication environments with malicious interference.

[0010] In a large-scale time-varying wireless network environment, when the network topology changes, the network backbone structure needs to be reconstructed, which has a high maintenance cost. In addition, when there is malicious interference in the network, the network backbone nodes are easily targeted by malicious interference attacks. Once the backbone nodes are attacked, broadcast scheduling cannot be executed correctly.

[0011] 4. The existing stable dynamic broadcast scheduling method is mainly based on the single-channel communication mode to develop the scheduling method design, and has not fully explored the throughput and delay performance gains that multi-channel transmission scheduling cooperation may bring to stable dynamic broadcast scheduling. At the same time, in a single-channel system, if the channel is interfered, the entire communication system will be affected, lacking redundancy and flexibility in anti-interference. Summary of the invention

[0012] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a distributed multi-channel anti-interference stable dynamic broadcast scheduling method and system, constructs a distributed stable dynamic broadcast scheduling method with high throughput and strong robustness, which will improve the overall performance of the wireless network.

[0013] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0014] A first aspect of the present invention provides a distributed multi-channel anti-interference stable dynamic broadcast scheduling method.

[0015] A distributed multi-channel anti-interference stable dynamic broadcast scheduling method, comprising:

[0016] Obtain network source nodes and packet flows, and build a multi-channel wireless network model based on network time and global accumulated wireless interference;

[0017] A random packet injection model is used to inject packet flows at source nodes into a multi-channel wireless network model;

[0018] A distributed multi-channel anti-interference wireless static broadcast scheduling method is used to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time.

[0019] Among them, the distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. Through the dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration, the dynamic broadcast scheduling process of injecting packets at all source nodes is divided into multiple iteration cycles of equal length. In each iteration cycle, the global broadcast scheduling problem of all packets injected into all source nodes is regarded as a multi-source node static global broadcast scheduling problem. Through the iterative multi-channel anti-interference wireless static broadcast scheduling method, the broadcast task of the injected packets is realized.

[0020] A second aspect of the present invention provides a distributed multi-channel anti-interference stable dynamic broadcast scheduling system.

[0021] A distributed multi-channel anti-interference stable dynamic broadcast scheduling system, comprising:

[0022] The model building module is configured to obtain network source nodes and packet flows, and build a multi-channel wireless network model according to network time and global accumulated wireless interference;

[0023] The packet injection module is configured to inject the packet flow at the source node into the multi-channel wireless network model using a random packet injection model;

[0024] The broadcast scheduling module is configured to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time using a distributed multi-channel anti-interference wireless static broadcast scheduling method;

[0025] Among them, the distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. Through the dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration, the dynamic broadcast scheduling process of injecting packets at all source nodes is divided into multiple iteration cycles of equal length. In each iteration cycle, the global broadcast scheduling problem of all packets injected into all source nodes is regarded as a multi-source node static global broadcast scheduling problem. Through the iterative multi-channel anti-interference wireless static broadcast scheduling method, the broadcast task of the injected packets is realized.

[0026] The third aspect of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in a method as described in the second aspect of the present invention are implemented.

[0027] A fourth aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in a method as described in the second aspect of the present invention.

[0028] A fifth aspect of the present invention provides a computer program product comprising instructions, which, when running on a computer, enables the computer program to implement the steps in a method as described in the second aspect of the present invention when executed by a processor.

[0029] One or more of the above technical solutions have the following beneficial effects:

[0030] The present invention can realize stable broadcast scheduling with high throughput. Through the construction method, during the execution process, the expected value of the queue length of each network node always has an upper bound, and the expected value of the global broadcast delay of each injected packet always has an upper bound, thereby satisfying the queue and delay stability, and realizing a distributed wireless network system that only relies on local information exchange between nodes.

[0031] The present invention can ensure critical communications. In the fields of public safety and emergency rescue, the reliability of wireless communications is crucial. Compared with the existing dynamic broadcast scheduling method based on reliable communication, the distributed multi-channel anti-interference wireless stable dynamic broadcast scheduling method proposed in the present invention builds malicious interference in the model, taking into account the random unpredictable wireless signal interference generated by malicious interference nodes in real wireless networks on the correctness of the dynamic broadcast scheduling method and the throughput and delay performance, which can ensure the continuity and stability of critical communications even in interference environments.

[0032] The present invention can improve the utilization efficiency of spectrum resources. The spectrum resources of wireless communication systems are limited. Compared with the existing dynamic broadcast scheduling method, the distributed multi-channel anti-interference wireless stable dynamic broadcast scheduling method can better utilize spectrum resources and improve the utilization rate of spectrum.

[0033] The present invention can improve user experience. Users have increasing requirements for communication speed and quality. Compared with the existing dynamic broadcast scheduling method, the distributed multi-channel anti-interference wireless stable dynamic broadcast scheduling method can provide faster data transmission speed and more stable communication quality, thereby improving user experience.

[0034] The present invention supports network coverage and capacity optimization: in high-density user areas or complex wireless environments, an effective anti-interference broadcast scheduling method helps to optimize network coverage and capacity, achieve reasonable allocation and utilization of network resources, and ensure that all users can obtain good services.

[0035] The present invention adapts to network development: With the rapid development of mobile communication technology, the number of users has increased dramatically, and the capacity of communication systems has continued to expand. The distributed multi-channel anti-interference wireless stable dynamic broadcast scheduling method proposed in the present invention can adapt to this development trend and support more users and higher data transmission rates.

[0036] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0038] Figure 1 This is a flowchart of the distributed multi-channel anti-interference wireless static broadcast scheduling method (JMSBS) in the first embodiment of the present invention;

[0039] Figure 2 It is an execution flow chart of each iteration cycle i of the distributed multi-channel anti-interference wireless stable dynamic broadcast scheduling method (JMDBS) in the first embodiment of the present invention;

[0040] Figure 3 A schematic diagram of a multi-hop wireless network topology used in Embodiment 1 of the present invention;

[0041] Figure 4 The figure is a schematic diagram showing the performance comparison and advantages of the distributed multi-channel anti-interference wireless stable dynamic broadcast scheduling method (JMDBS) in the first embodiment of the present invention and the existing broadcast scheduling method in terms of queue length and broadcast delay. DETAILED DESCRIPTION

[0042] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0043] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0044] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0045] The overall idea proposed in this invention includes three aspects: construction of a multi-channel wireless network model, design of a static broadcast scheduling method, and design of a two-stage static broadcast scheduling iteration method. Among them, the first aspect specifies the wireless network scenario to which the broadcast scheduling method proposed in this invention is applicable, the second aspect designs a distributed multi-channel anti-interference wireless static broadcast scheduling method (JMSBS) with high concurrency and low complexity, and the third aspect further proposes an efficient two-stage static broadcast scheduling iteration method based on the designed static broadcast scheduling method, thereby solving the problem of efficient and stable dynamic broadcast scheduling with distributed, multi-channel and anti-interference characteristics in an unreliable wireless communication environment.

[0046] Glossary:

[0047] Benchmark: Benchmark broadcast scheduling algorithm.

[0048] JMDBS method (ie MDBS method) is a dynamic broadcast scheduling method based on two-stage static broadcast scheduling iteration.

[0049] Embodiment 1

[0050] This embodiment discloses a distributed multi-channel anti-interference stable dynamic broadcast scheduling method.

[0051] In one embodiment of the present disclosure, a distributed multi-channel anti-interference stable dynamic broadcast scheduling method is provided, and the specific steps include:

[0052] Step 1: Obtain network source nodes and packet flows, and build a multi-channel wireless network model based on network time and global accumulated wireless interference;

[0053] Step 2: Use a random packet injection model to inject the packet flow at the source node into the multi-channel wireless network model;

[0054] Step 3: Use the distributed multi-channel anti-interference wireless static broadcast scheduling method to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time;

[0055] Among them, the distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. Through the dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration, the dynamic broadcast scheduling process of injecting packets at all source nodes is divided into multiple iteration cycles of equal length. In each iteration cycle, the global broadcast scheduling problem of all packets injected into all source nodes is regarded as a multi-source node static global broadcast scheduling problem. Through the iterative multi-channel anti-interference wireless static broadcast scheduling method, the broadcast task of the injected packets is realized.

[0056] In order to more clearly illustrate this embodiment, a distributed multi-channel anti-interference stable dynamic broadcast scheduling method can be specifically described as follows:

[0057] Step 1: Obtain network source nodes and packet flows, and build a multi-channel wireless network model based on network time and global accumulated wireless interference.

[0058] In this embodiment, a multi-channel wireless network model is constructed. First, multi-channel communication modeling is performed. Secondly, global cumulative wireless interference is considered. A composite wireless interference model combining SINR (signal to interference and noise ratio) and malicious interference is adopted. Then the transmission radius is defined. Finally, the packet flow at the source node is injected into the modeling.

[0059] The specific method of constructing a multi-channel wireless network model is as follows;

[0060] Step 101: Multi-channel communication modeling:

[0061] The network time is divided into continuous time slots of equal length, and the length of each time slot is just enough to allow a node to complete the sending and receiving operations of a packet.

[0062] The network nodes adopt half-duplex communication mode, that is, in each time slot, the nodes either choose to send packets or receive packets, but not both at the same time.

[0063] In each time slot, each network node can receive ( ) channels to participate and is unaware of any events occurring on all non-selected channels.

[0064] In this embodiment, in order to model the adverse effects of a large number of irrelevant wireless network applications, irrelevant electromagnetic devices, and some malicious wireless interference nodes that share the same spectrum on the message transmission behavior between target wireless network nodes, it is assumed that the malicious interference nodes in the network can select from all channels based on the code knowledge of the proposed dynamic broadcast scheduling method and the execution history information (including the history information of node channel selection and packet transmission related operations). ( ) channels, so that all transmission behaviors on all maliciously interfered channels will fail.

[0065] Step 102: Composite wireless interference modeling:

[0066] Considering multi-channel communication, the above malicious wireless interference, and the global cumulative wireless interference caused by concurrent transmission between nodes on the same channel, a composite wireless interference model combining SINR (signal to interference and noise ratio) and malicious interference is adopted. The specific description is as follows: t In the example, a sending node u Packets sent K Can be used by a receiving nodev To successfully receive, the following conditions must be met:

[0067] (1) Node u A packet is sent on the selected channel. ;

[0068] (2) Node v Listening to the selected channel;

[0069] (3) Node u and nodes v The same channel is selected ;

[0070] (4) Channel In time slot There is no interference channel selected by malicious interference nodes;

[0071] (5) Channel On the node u and nodes v The corresponding SINR constraint inequality holds, namely:

[0072] ;

[0073] in, Indicates time slot The set of all sending nodes in , Representation Node u The transmission power, Representation Node u and nodes v The Euclidean distance between Representation Node w and nodes v The Euclidean distance between The path loss exponent representing the wireless signal strength, Indicates the interference node The selected channel, represents the background noise intensity, Indicates grouping Hardware-defined threshold that needs to be met for successful reception.

[0074] It should be noted that in this example, Representation Node The transmission power, Representation Node and nodes The Euclidean distance between .

[0075] Step 103, transmission radius:

[0076] Given a node x Consistent transmission power P ,use Indicates that there are only nodes in the entire network x Under the conditions of sending packets (i.e. ), the maximum distance that the packet can be successfully transmitted, then it satisfies All nodes y can successfully receive the packet. According to the above SINR constraint inequality definition, the inequality Established. Because usually, there are multiple nodes in the network sending packets at the same time.

[0077] To this end, the present invention defines a local broadcast radius and proximity radius , so that Here the local broadcast radius The broadcast scheduling method proposed in the present invention will provide a single-hop transmission distance with a high probability of successful packet transmission, and use D Indicates based on local broadcast radius The network diameter is defined as the maximum number of hops in the shortest path between any two nodes.

[0078] like Figure 3 As shown, the local broadcast radius is given A schematic diagram of the multi-hop wireless network topology defined by the present invention, describing the connectivity relationship between network nodes, so that the Euclidean distance Any two network nodes x and y There is an edge between them. Neighboring radius It is used to indicate the neighboring range where the cumulative interference degree accounts for a large part. The interference nodes within the neighboring range of the receiving node play the main role of co-channel interference, and the co-channel interference effect of the interference nodes outside the neighboring range can be ignored to a certain extent. In addition, using Representation Node x The set of neighbor nodes within the local broadcast radius is used Indicates the total number of network nodes, using Represents the maximum node degree of the network, that is, any node The maximum number of nodes within the radius area.

[0079] Step 2: Use a random packet injection model to inject the packet flow at the source node into the multi-channel wireless network model.

[0080] In this embodiment, a random packet injection model is used to model the data packet flow in all the real wireless multi-hop networks. The model specifies that all The number of injected packets of the data packet flow at each source node in different time slots is random and independent and identically distributed with respect to different time slots and different source nodes.

[0081] Specifically, using Indicates that any source node in time slot The number of packets injected into is a random variable and with respect to different time slots and different source nodes are independent and identically distributed. represents the expected packet injection rate at each source node, that is, the mathematical expectation of the number of packets injected into each source node in each time slot, that is, .

[0082] Step 3: Use the distributed multi-channel anti-interference wireless static broadcast scheduling method to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time.

[0083] In this embodiment, it mainly includes the design of a static broadcast scheduling method and the design of a two-stage static broadcast scheduling iteration method. First, a distributed multi-channel anti-interference wireless static broadcast scheduling method with high concurrency and low complexity is designed. Secondly, based on the designed static broadcast scheduling method, an efficient two-stage static broadcast scheduling iteration method is further proposed.

[0084] That is, the distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. Through the dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration, the dynamic broadcast scheduling process of injecting packets at all source nodes is divided into multiple iteration cycles of equal length. In each iteration cycle, the global broadcast scheduling problem of all packets injected into all source nodes is regarded as a multi-source node static global broadcast scheduling problem. Through the iterative multi-channel anti-interference wireless static broadcast scheduling method, the broadcast task of the injected packets is realized. In this way, the problem of efficient and stable dynamic broadcast scheduling with distributed, multi-channel and anti-interference characteristics in an unreliable wireless communication environment is solved.

[0085] Step 301, distributed multi-channel anti-interference wireless static broadcast scheduling method (JMSBS):

[0086] The goal of the distributed multi-channel anti-interference wireless static broadcast scheduling method JMSBS is to allocate all k ( ) indivual All the initial storage at the source node ( ) packets are propagated to all nodes in the entire network in the shortest possible time.

[0087] In the multi-channel wireless network scenario, the JMSBS method adopts a random channel switching and dynamic adjustment strategy of sending probability. Relying on the randomness of channel switching and packet sending operations, it minimizes the malicious wireless signal interference attacks of malicious interference nodes in the network, thereby realizing static global broadcast scheduling with high concurrency and low complexity.

[0088] The JMSBS method first establishes a dual mapping mechanism, and then implements the random channel switching and grouped probabilistic sending operations of nodes based on the dual mapping mechanism.

[0089] Step 3011, dual mapping mechanism:

[0090] First, the JMSBS method Probability of sending and Channels A one-to-one mapping relationship is established between them, so that for any , satisfying the sending probability Corresponding channel number .

[0091] Through the mapping between the transmission probability and the channel number, each transmitting node can synchronously adjust its packet transmission probability in the current time slot and the channel to be involved. It should be noted that malicious interference nodes can maliciously interfere with the packet transmission behavior of nodes with larger transmission probabilities by attacking channels with larger numbers, thereby reducing the efficiency of random packet transmission scheduling.

[0092] Secondly, in order to reduce the adverse effects of the above malicious interference nodes, the JMSBS method establishes a second remapping, namely pseudo-random channel mapping. Pseudo-random channel mapping establishes a mapping table between physical channel numbers and logical channel numbers. The physical channel numbers of all channels in the channel mapping table (i.e., the actual numbers of all channels) are ) remains unchanged as the index of the channel mapping table. At the same time, the channel mapping table contains Each logical channel number is a sequence of all physical channel numbers and is different from each other. When, in the time slot Physical channel number Possibly related to the logical channel number One-to-one correspondence, and in the time slot Physical channel number Possibly related to the logical channel number Table 1 gives An example of a pseudo-random channel mapping table for channels. The physical channel number is in each time slot, and the JMSBS method will A group of logical channel numbers is randomly selected from the group and corresponds to the physical channel number one by one. After pseudo-random channel mapping is adopted, the node sends the probability Corresponding channel number , refers to the logical channel number The corresponding physical channel number can be based on the logical channel number and the pseudo-random channel mapping table of the current time slot.

[0093] Table 1 Physical channel numbers The corresponding Group logical channel number

[0094]

[0095] Through pseudo-random channel mapping, a set of logical channel numbers is assigned to all available channels in each time slot, and the node's transmission probability is mapped to the channel's logical channel number, so that the channels actually participated in by nodes with the same transmission probability in different time slots will change synchronously. After pseudo-random channel mapping, the logical number of each channel is time-varying. Malicious interference nodes can only see the physical number of the channel and cannot obtain the time-varying logical channel number. Therefore, they cannot determine which physical channel the node corresponding to each current transmission probability is participating in.

[0096] Step 3012: random channel switching and probability transmission operation:

[0097] Based on the above dual mapping mechanism, the JMSBS method stipulates that each network node In each time slot The channel switching and probability transmission operations are as follows. Figure 1 As shown, the specific execution process of the distributed multi-channel anti-interference wireless static broadcast scheduling method (JMSBS) is:

[0098] Initially, all k Source nodes are active, and all non-source nodes are inactive. The sending probability of active nodes is The initial value is .

[0099] (1) Inactive node operation. In each time slot In each inactive node From all Channel number (i.e. ) uniformly and randomly selects a channel number and listens to the physical channel corresponding to the channel number .if Listening on channel A packet is successfully received during ,So Group Add to message queue and jumps to the active state, and sends the probability Set to .

[0100] (2) Active state node operation. Initialize the variables and sending probability of the active node. Each active node Try to queue its messages with high probability Each packet in is sent to all its first hops -Neighbor nodes. Specifically, nodes Send with variable probability Phased transfer Each packet in the packet until the packet has been sent to the All neighbor nodes in time slots, of which , , Active Nodes In each time slot The operations in are as follows:

[0101] A. Determine the physical channel to be involved in the current time slot. Initially, the node Generate the channel mapping corresponding to the current time slot by performing pseudo-random channel mapping , and determine the current sending probability The corresponding logical channel number And the corresponding physical channel to be involved .

[0102] B. Message Queuing The action to be performed when the message queue is empty. When it is an empty set, the node There are no packets to send. At this point, the node Listen to the physical channel If the node A packet was successfully received , and has never successfully received a packet before , then the node Group Add to message queue middle( is no longer an empty set).

[0103] C.Message Queue The operation to be performed when it is not empty. When it is not equal to the empty set, the node In the channel Probability send The first group in On the one hand, if the node After the probability send operation is executed, the packet is actually sent , then the node Will send probability Reset to , and restart a new phase. If the node Already sent The first group in achieve times, then the node Group From the message queue , and start trying to send the message queue with probability The next group in This is not empty), here On the other hand, if the node Select the listening channel after the probabilistic send operation is performed , then when the node Successfully received a packet After that, the sending probability will be reset , and when grouped If it is a packet that has never been received before, the packet Add to message queue In addition, if the node It is detected that the total number of time slots for performing probabilistic sending operations in the current stage has reached And the node During this period, no packets have been sent or received successfully, so the node The probability of sending it Double (i.e. ). It should be noted here that if After doubling, more than ,So will be reset to , and restart a new phase. Finally, when the node Detected its The number of packets sent by all one-hop neighbor nodes with high probability reaches the upper bound When the node Exit the execution of the JMSBS method.

[0104] Step 302: Dynamic broadcast scheduling method JMDBS based on two-stage static broadcast scheduling iteration:

[0105] The JMDBS method will The dynamic broadcast scheduling process of injecting packets at source nodes is divided into iterative cycles of equal length and uses Indicates the total number of time slots contained in each iteration cycle. ( ) is injected into The global broadcast scheduling problem of all groups of source nodes can be regarded as a multi-source node static global broadcast scheduling problem, which can be solved by the iterative JMSBS method.

[0106] At this point, you only need to iterate over the parameters in the JMSBS method Set an appropriate threshold Here the parameters For all involved in step 301 The upper limit value of the packets to be broadcast initially stored by the source node, the threshold Set to ,in is a constant, is the expected value of the packet injection rate at each source node, Represents the number of all source nodes in the entire network, Indicates the number of time slots contained in each iteration cycle of the JMDBS method.

[0107] Since in each iteration cycle The actual number of packets injected into a source node is random and may exceed the preset threshold. , which causes some broadcast tasks of injected packets to fail. To handle this situation, the JMDBS method adopts a two-stage static broadcast scheduling iteration.

[0108] Specifically, the JMDBS method divides each iteration cycle into It is further divided into two phases, namely, the best broadcast phase and the leak-filling broadcast phase. In the broadcast phase, try to complete as many iterations as possible. The packets injected in the trap broadcast phase attempt to process the iteration cycle And all injected groups that have not completed the broadcast task in all previous iteration cycles.

[0109] The JMDBS method performs The specific operations include the following three aspects:

[0110] (1) Message queue allocation and use. Each source node Using message queue Stores all the packets injected in each iteration cycle. Use Represents the source node In the iteration cycle All the groups injected in the iteration cycle In each iteration cycle, Initially, each source node Will All packets are moved to the message queue and clear To store the iteration cycle All packets injected in .

[0111] (2) Broadcasting stage. Broadcasting stage includes Time slot, here and In this phase, each node Threshold-based and message queues Execute the JMSBS method, here the message queue Corresponds to the queue in the JMSBS method definition After this phase is completed, all nodes in the network Message Queues Iteration cycle is stored All the packets injected into the node that have not yet completed the broadcast task. At the end of this phase, each node Will All packets are moved to the message queue and clear So that in the iteration cycle Processing iteration cycle All packets injected.

[0112] (3) Leakage patching broadcast stage. The leak patching broadcast stage includes In this phase, each node x Based on threshold 1 and message queue Execute the JMSBS method, here Corresponds to the queues involved in the JMSBS method After this phase is completed, all nodes x The queue Stores all the iterations i Groups that were previously injected but did not complete the broadcast task.

[0113] Currently, there is no research work in the literature that can solve the problem of anti-interference distributed stable multi-source dynamic broadcast scheduling in an unreliable communication environment. In order to demonstrate the performance advantage of the JMDBS method proposed in this embodiment, the following benchmark broadcast scheduling algorithm (Benchmark) is used as a comparison.

[0114] The benchmark algorithm Benchmark uses the same iterative framework as the JMDBS method. The difference is that the multi-source static broadcast scheduling method iterated by Benchmark always uses As the sending probability of each network node, here Represents the maximum node degree of the network. Figure 4 As shown in the figure, the performance difference between the JMDBS method (ie, the MDBS method) and the benchmark method in terms of the total node queue length and the average broadcast delay of the injected packets is demonstrated.

[0115] from Figure 4 It can be seen that (i) when the packet injection rate When the node queue length and the instantaneous value of the packet broadcast delay of the Benchmark method are convergent when the packet / time slot is less than 0.0013 packets / time slot. When the packet rate is greater than 0.00135 packets / time slot, the instantaneous values ​​of the node queue length and packet broadcast delay of the Benchmark method increase continuously over time.

[0116] (ii) When the packet injection rate When the packet / time slot is less than 0.00145, the JMDBS method satisfies the queue and delay stability. When the packet rate is greater than 0.0015 packets / time slot, the instantaneous values ​​of the node queue length and packet broadcast delay of the JMDBS method increase continuously over time.

[0117] Thus, we can get the maximum supported packet injection rate of the Benchmark method. In the range The maximum supported packet injection rate of the JMDBS method is In the range Therefore, compared with the Benchmark method, the JMDBS method has better broadcast throughput performance.

[0118] Embodiment 2

[0119] The purpose of this embodiment is to provide a distributed multi-channel anti-interference stable dynamic broadcast scheduling system, including:

[0120] The model building module is configured to obtain network source nodes and packet flows, and build a multi-channel wireless network model according to network time and global accumulated wireless interference;

[0121] The packet injection module is configured to inject the packet flow at the source node into the multi-channel wireless network model using a random packet injection model;

[0122] The broadcast scheduling module is configured to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time using a distributed multi-channel anti-interference wireless static broadcast scheduling method;

[0123] Among them, the distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. Through the dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration, the dynamic broadcast scheduling process of injecting packets at all source nodes is divided into multiple iteration cycles of equal length. In each iteration cycle, the global broadcast scheduling problem of all packets injected into all source nodes is regarded as a multi-source node static global broadcast scheduling problem. Through the iterative multi-channel anti-interference wireless static broadcast scheduling method, the broadcast task of the injected packets is realized.

[0124] Embodiment 3

[0125] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0126] Embodiment 4

[0127] The purpose of this embodiment is to provide a computer-readable storage medium.

[0128] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0129] Embodiment 5

[0130] The purpose of this embodiment is to provide a computer program product containing instructions, which, when running on a computer, enables the computer to execute the methods and functions involved in any of the above embodiments.

[0131] The steps involved in the apparatus of the above embodiment correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0132] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0133] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A distributed multi-channel anti-interference stable dynamic broadcast scheduling method, characterized in that: include: Obtain network source nodes and packet flows, and build a multi-channel wireless network model based on network time and global accumulated wireless interference; A random packet injection model is used to inject packet flows at source nodes into a multi-channel wireless network model; the random packet injection model is an arrival pattern of data packet flows at all k source nodes in a wireless multi-hop network, and stipulates that the number of injected packets of data packet flows at all k source nodes in different time slots is random and independent and identically distributed with respect to different time slots and different source nodes; wherein 2≤k≤n, and n represents the total number of network nodes; A distributed multi-channel anti-interference wireless static broadcast scheduling method is used to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time. The distributed multi-channel anti-interference wireless static broadcast scheduling method adopts random channel switching and dynamic adjustment of transmission probability strategies to realize random channel switching and grouped probability transmission operations of nodes based on a dual mapping mechanism, specifically: In Γ = log n + 2 transmission probabilities A one-to-one mapping relationship is established between the Γ channels {0,1,2,…,log n+1}, so that for any i∈{0,1,2,…,log n+1}, the transmission probability is satisfied Corresponding channel number i; Then establish a double mapping, namely pseudo-random channel mapping; the pseudo-random channel mapping establishes a mapping table of physical channel numbers and logical channel numbers, and the physical channel numbers of all channels in the channel mapping table remain unchanged as the index of the channel mapping table; The distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. The dynamic broadcast scheduling process of injecting packets at all k source nodes is divided into multiple iteration cycles of equal length through a dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration. The global broadcast scheduling problem of injecting all packets of all source nodes in each iteration cycle is regarded as a multi-source node static global broadcast scheduling problem. The broadcast task of the injected packets is realized through the iterative multi-channel anti-interference wireless static broadcast scheduling method. The dynamic broadcast scheduling method of the two-stage static broadcast scheduling iteration further divides each iteration period i into two stages, namely, the best broadcast stage and the leak-filling broadcast stage; In iteration cycle i, the best broadcast phase completes as many injected packets as possible in iteration cycle i-1, while the leak-filling broadcast phase attempts to process all injected packets that have not completed the broadcast task in iteration cycle i and all previous iteration cycles.

2. A distributed multi-channel anti-interference stable dynamic broadcast scheduling method as claimed in claim 1, characterized in that: The multi-channel wireless network model takes into account the global cumulative wireless interference caused by multi-channel communication, malicious wireless interference and concurrent transmission between nodes on the same channel, and adopts a composite wireless interference model that combines signal-to-interference-noise ratio and malicious interference.

3. A distributed multi-channel anti-interference stable dynamic broadcast scheduling method as claimed in claim 1, characterized in that: The channel mapping table contains Γ! groups of logical channel numbers, each group of logical channel numbers is a permutation of all channel physical channel numbers and is different from each other; in each time slot, a group is randomly selected from the Γ! groups of logical channel numbers and is mapped one-to-one with the physical channel number.

4. A distributed multi-channel anti-interference stable dynamic broadcast scheduling method as claimed in claim 1, characterized in that: The random channel switching and probabilistic transmission operations of each network node v in each time slot t are as follows: Initially, all k source nodes are in an active state, all non-source nodes are in an inactive state, and the initial value of the transmission probability p of the active node is The inactive node uniformly and randomly selects a channel number and listens to the physical channel corresponding to the channel number; Active state nodes, each active node v tries to queue its message Q with high probability v Each packet in is sent to all its first-hop R B -Neighbor nodes.

5. A distributed multi-channel anti-interference stable dynamic broadcast scheduling system, characterized in that: include: The model building module is configured to obtain network source nodes and packet flows, and build a multi-channel wireless network model according to network time and global accumulated wireless interference; The packet injection module is configured to inject the packet flow at the source node into the multi-channel wireless network model using a random packet injection model; the random packet injection model is an arrival pattern of the data packet flow at all k source nodes in the wireless multi-hop network, and stipulates that the number of injected packets of the data packet flow at all k source nodes in different time slots is random and independent and identically distributed with respect to different time slots and different source nodes; wherein 2≤k≤n, and n represents the total number of network nodes; The broadcast scheduling module is configured to propagate all packet flows at all source nodes to all source nodes in the entire network in the shortest possible time using a distributed multi-channel anti-interference wireless static broadcast scheduling method; The distributed multi-channel anti-interference wireless static broadcast scheduling method adopts random channel switching and dynamic adjustment of transmission probability strategies to realize random channel switching and grouped probability transmission operations of nodes based on a dual mapping mechanism, specifically: In Γ = log n + 2 transmission probabilities A one-to-one mapping relationship is established between the Γ channels {0,1,2,…,log n+1}, so that for any i∈{0,1,2,…,log n+1}, the transmission probability is satisfied Corresponding channel number i; Then establish a double mapping, namely pseudo-random channel mapping; the pseudo-random channel mapping establishes a mapping table of physical channel numbers and logical channel numbers, and the physical channel numbers of all channels in the channel mapping table remain unchanged as the index of the channel mapping table; The distributed multi-channel anti-interference wireless static broadcast scheduling method is divided into two-stage scheduling iterations. The dynamic broadcast scheduling process of injecting packets at all k source nodes is divided into multiple iteration cycles of equal length through a dynamic broadcast scheduling method based on the two-stage static broadcast scheduling iteration. The global broadcast scheduling problem of injecting all packets of all source nodes in each iteration cycle is regarded as a multi-source node static global broadcast scheduling problem. The broadcast task of the injected packets is realized through the iterative multi-channel anti-interference wireless static broadcast scheduling method. The dynamic broadcast scheduling method of the two-stage static broadcast scheduling iteration further divides each iteration period i into two stages, namely, the best broadcast stage and the leak-filling broadcast stage; In iteration cycle i, the best broadcast phase completes as many injected packets as possible in iteration cycle i-1, while the leak-filling broadcast phase attempts to process all injected packets that have not completed the broadcast task in iteration cycle i and all previous iteration cycles.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 4 are performed.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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