CN113596949B - Routing method based on multi-source path interference optimization under multi-event triggering - Google Patents

Abstract

The invention relates to a routing method based on multi-source path interference optimization triggered by multiple events, comprising the following steps: network initialization; clustering strategy based on multi-event trigger; candidate relay selection based on interference avoidance mechanism; interference sensitivity based Relay election; power control and data multi-hop transmission. By introducing node state and interference sensitivity, the present invention ensures that transmission links of different events are completely disjoint and the degree of interference between links is small, effectively solves the problem of interference conflict in multi-path parallel transmission data, and improves network transmission efficiency.

Description

A routing method based on multi-source path interference optimization under multi-event triggering

Technical Field

The present invention relates to the field of communication technology, and in particular to a routing method based on multi-source path interference optimization under multi-event triggering.

Background Art

With the continuous improvement of communication technology, the development scale of wireless sensor networks is getting larger and larger. Large-scale sensor nodes are densely deployed in the monitoring area to monitor the environment or track target tasks in real time, respond to sensitive events in the environment, and take corresponding countermeasures. In large-scale wireless sensor networks, the use of all nodes for continuous real-time monitoring has a large demand for network energy consumption, which is easy to cause a large amount of unnecessary energy loss. Therefore, event-driven networks have been widely used in forest fire prevention, medical applications and other fields instead of time-driven networks.

In event-driven wireless sensor networks, when an event is not triggered, most of the common nodes are dormant, and the nodes only periodically collect a small amount of data. When an event occurs, the nodes are activated and collect and transmit data. Previous research on event-driven sensor networks is mostly based on routing algorithms triggered by a single event. If there are multiple event links transmitting data at the same time, interference conflicts will occur between different links, reducing the transmission efficiency of the network. In actual large-scale wireless sensor networks, the occurrence of events is often random and frequent. There may be multiple different events in different locations. The network must be able to collect multiple event information in a timely manner and transmit it to the same sink node (referred to as the sink node) safely and reliably.

The existing communication mechanisms based on time division multiple access (TDMA) and carrier sense multiple access/collision avoidance (CSMA/CA) have certain communication defects for wireless sensor networks driven by multiple events.

TDMA is a typical fixed allocation mechanism, which pre-allocates time slot resources to nodes in the network. Each node in the network sends information according to the allocated time slot resources. By dynamically reserving data time slots, conflicts caused by competition can be effectively avoided. However, in event-driven wireless sensor networks, events occur suddenly, and it is difficult for TDMA to pre-allocate time slots for randomly triggered activated nodes to transmit data. Moreover, the transmitted data changes dynamically under event triggering, and TDMA is not sensitive to changes in the transmission data flow, which can easily cause a large loss of bandwidth.

The CSMA mechanism is a typical random access mechanism. Each node in the network avoids conflicts by listening and randomly avoiding. Before sending data, the node needs to listen to the channel. If the channel is idle, it will send immediately. If the channel is busy, it will wait for a while until the data information in the channel is transmitted before initiating. If the data conflicts, it will try to fall back and retransmit the data information. The wireless communication network based on the CSMA mechanism can effectively reduce the probability of conflicts and can adapt well to the access of emergency nodes. However, with the increase of triggering events and the increase of density between transmission nodes, the CSMA mechanism will cause serious conflicts, resulting in a sharp drop in network throughput and reduced transmission efficiency.

The following are the main problems faced in designing a multi-source routing algorithm based on event triggering:

First, for wireless sensor networks triggered by multiple events, there are multiple transmission links for the transmission of event data. The data signals in different transmission links are superimposed together. This mutual interference between links not only leads to a large waste of network node energy, but also causes a sharp increase in data transmission delay, resulting in a decrease in network throughput, and seriously reducing the network's transmission efficiency. How to reduce the interference probability of node data transmission and improve transmission efficiency is a key issue in wireless sensor networks.

Secondly, for multi-event driven wireless sensor networks, the data transmission volume is large and the transmission energy consumption is high. How to design algorithms to build appropriate transmission paths to balance the energy consumption of each node and maximize the life cycle of the entire network is the difficulty and focus of the research.

In the existing research on wireless sensor network routing based on event-driven, most optimization algorithms ignore the very important goal of reducing network interference, and only design routing algorithms from the perspective of network energy consumption. This makes the constructed network topology interfere more, and the signals of many nodes collide, which increases the network energy consumption and communication delay caused by data retransmission, and reduces the transmission efficiency of the network.

At present, most routing algorithms that consider interference issues start from the perspectives of power control and node degree. Power-controlled routing algorithms build a suitable topology by reducing the communication power of nodes to reduce interference in the network. However, this type of method will make the network topology sparse, and the long communication distance between nodes may cause path disconnection. In addition, the sparse network structure has weak fault tolerance, and the failure or death of some nodes will cause the network to be disconnected. That is, this type of routing algorithm focuses on reducing network interference while not considering the two optimization goals of energy efficiency and network fault tolerance.

Another type of interference control routing algorithm uses node degree as a relay selection indicator. The more neighbor nodes the current node has, the greater the chance and degree of interference it may suffer, thereby reducing transmission interference. However, at a certain moment, not all nodes in the interference area of the current node will interfere with the node. Only those nodes that are transmitting at the same time will interfere with the node at this moment. In event-triggered wireless sensor networks, untriggered neighbor nodes are in a dormant state and do not participate in data transmission. Simply defining the interference suffered by a node by the number of surrounding nodes is not very accurate. Therefore, the interference problem needs to be reconsidered.

Summary of the invention

The technical problem to be solved by the present invention is to provide a routing method based on multi-source path interference optimization under multi-event triggering, which can ensure the reliability and real-time performance of multi-event data transmission, reduce communication interference and energy loss between multiple paths, thereby improving the transmission efficiency of the network and extending the service life of the network.

The technical solution adopted by the present invention to solve the technical problem is: to provide a routing method based on multi-source path interference optimization under multi-event triggering, comprising the following steps:

(1) Network initialization: The node obtains the minimum number of hops from the sink node and the ID of the upper node through periodic broadcast of data packets by the sink node and node relay forwarding, and divides the network into a hierarchical gradient topology structure; defines other event-occupied nodes within the communication range of neighbor nodes as heterogeneous interference nodes of the node; and divides the nodes into free state, occupied state, potential interference state and dead state;

(2) Clustering strategy based on multi-event triggering: When different events occur, the nodes that detect the events in the triggering area are activated; all activated nodes in a single event triggering area are regarded as a cluster set, and the node with the highest energy is selected from all activated nodes as the cluster head node. The remaining nodes are cluster member nodes that periodically collect event information and transmit it to the cluster head node through a single hop;

(3) Candidate relay selection based on interference avoidance mechanism: The cluster head node is used as the source node, the sink node is used as the destination node, and the node status and hop count level are used as constraints. Invalid neighbor nodes in the occupied state, potential interference state, and dead state are excluded, and the nodes in the upper node that are in the free state are selected as candidate relays. If there are no neighbor nodes in the free state, the nodes in the upper node that are in the potential interference state are selected as candidate relays.

(4) Relay election based on interference sensitivity: When the candidate relays are all nodes in a free state, the node residual energy and node distance are used as the relay election probability objective function, and the candidate relay with the largest function value is selected as the next hop node; when the candidate relay is a node in a potential interference state, interference sensitivity is introduced to evaluate the interference strength of other event transmissions on the candidate relay. The relay election probability objective function is constructed based on the node residual energy, node distance and interference sensitivity, and the candidate relay with the largest function value is selected as the next hop node;

(5) The node status in the routing information table of the next-hop relay node is updated to occupied and data transmission begins.

The node in the free state refers to a node that has not been triggered by an event, is not used as a relay node in the data transmission process, and has no relay node as a transmission link among its neighbor nodes; the node in the occupied state refers to a node that has been selected as a relay node in the data transmission link after the event is triggered; the node in the potential interference state refers to a node that has a neighbor node within the communication range that serves as a relay node for the data transmission of a certain event; the node in the dead state refers to a node that is unable to undertake the task of data transmission.

The definition of other event-occupied nodes within the communication range of the neighboring node as heterogeneous interference nodes of the node includes defining the ID mark of the heterogeneous node, the data packet length of the event to be transmitted, and the signal interference intensity.

The step (3) is specifically as follows: node i sends a routing request to a neighbor node j within the transmission radius, wherein the routing request includes the ID of the current node, the number of hops from the aggregation node, and the length of the data packet to be transmitted; after receiving the routing request, the neighbor node j updates the state information of node i in the routing table to the interference state, and adds the ID number of node i, the length of the data packet to be transmitted of node i, and the received signal strength; the neighbor node j replies to node i, wherein the reply response includes the ID of node j, heterogeneous interference node information, node state, and remaining energy; after receiving the reply response, node i determines the candidate relay according to the reply response.

其中，E_j为候选邻居节点j的剩余能量，

为所有候选邻居节点的平均剩余能量，d_j为候选邻居节点j与当前节点的距离，d_opt为最佳中继距离，α和β分别为节点剩余能量以及节点距离指标的权重系数。In step (4), when the candidate relays are all nodes in a free state, the relay election probability objective function

Where _Ej is the residual energy of candidate neighbor node j,

is the average residual energy of all candidate neighbor nodes, d _j is the distance between candidate neighbor node j and the current node, d _opt is the optimal relay distance, α and β are the weight coefficients of node residual energy and node distance index respectively.

其中，E_j为候选邻居节点j的剩余能量，

为所有候选邻居节点的平均剩余能量，d_j为候选邻居节点j与当前节点的距离，d_opt为最佳中继距离，IS_(i,j)为干扰敏感度，

为第k个事件传输链路对链路(i,j)的干扰产生概率，RSSI_k为第k个事件对链路(i,j)的干扰强度，α、β和η分别为节点剩余能量、节点距离以及干扰敏感度的权重系数。In step (4), when the candidate relay is a node in a potential interference state, the relay election probability objective function

Where _Ej is the residual energy of candidate neighbor node j,

is the average residual energy of all candidate neighbor nodes, d _j is the distance between candidate neighbor node j and the current node, d _opt is the optimal relay distance, IS _{(i, j)} is the interference sensitivity,

is the probability of interference generated by the k-th event transmission link on link (i, j), RSSI _k is the interference intensity of the k-th event on link (i, j), α, β and η are the weight coefficients of node residual energy, node distance and interference sensitivity respectively.

其中，E_Telec和E_Relec分别为节点发送和接收的基础能耗，ε为发射功耗电路的能耗系数，γ为无线传输的信道衰减因子。The optimal relay distance

Among them, E _Telec and E _Relec are the basic energy consumption of node sending and receiving respectively, ε is the energy consumption coefficient of the transmitting power consumption circuit, and γ is the channel attenuation factor of wireless transmission.

In the step (5), the transmission power of the node is adjusted according to the received signal strength of the node during data transmission.

Beneficial Effects

Due to the adoption of the above technical solution, the present invention has the following advantages and positive effects compared with the prior art:

Firstly, the present invention is applicable to large-scale wireless sensor networks based on multi-event triggering, and the nodes in the network that do not participate in data collection and transmission are all in a dormant state, which greatly reduces the energy loss of the network.

Secondly, the present invention designs an interference avoidance mechanism to address the transmission interference and load balancing problems in the process of multi-event data transmission. All nodes in the network are divided into four states: free, potential interference, occupied and dead. In the candidate relay election process, nodes in the occupied and potential interference states are excluded according to the node status information, and free nodes in the upper-level nodes are selected as candidate relays for the next hop. This mechanism can effectively avoid the conflict interference and excessive load problems caused by a single node simultaneously sending and receiving information from different transmission links. At the same time, the spatial distance between nodes is greater than the communication interference distance, so that different transmission links do not interfere with each other, which is conducive to improving transmission efficiency.

In addition, the present invention proposes interference sensitivity as an evaluation index of the relay election function, and obtains interference sensitivity based on the probability and interference intensity of other event links interfering with candidate links, which is used to measure the interference intensity of other event links on candidate links. The transmission link with large interference sensitivity is more interfered, the link quality is worse at this time, and the transmission efficiency is poor. By introducing interference sensitivity, the probability and intensity of interference between different links can be effectively reduced, the interference conflict problem caused by channel competition between transmission links can be alleviated, and the efficiency of data transmission can be improved.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of an embodiment of the present invention;

FIG2 is a schematic diagram of the state of a node in an embodiment of the present invention;

FIG3 is a schematic diagram of event-triggered clustering in an embodiment of the present invention;

4 is a flowchart of information collection based on multi-event triggering in an embodiment of the present invention;

5 is a flowchart of candidate relay selection based on an interference avoidance mechanism in an embodiment of the present invention;

FIG6 is a schematic diagram of an abnormal empty set in an embodiment of the present invention;

7 is a flow chart of a relay election strategy based on interference sensitivity in an embodiment of the present invention;

Figure 8 is a schematic diagram of a simple linear model;

FIG9 is a schematic diagram of a protocol interference model.

DETAILED DESCRIPTION

The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

The embodiment of the present invention relates to a routing method based on multi-source path interference optimization under multi-event triggering. The network used in the method consists of multiple isomorphic sensor nodes and a Sink node. The positions of the sensor nodes are fixed and have the same computing and communication capabilities. All nodes are in a dormant state when no event occurs. As shown in FIG1, the method includes the following steps:

S1 Network Initialization

First, initialize the node information of the network. The node obtains the minimum number of hops from the Sink node and the ID of the upper node through the periodic broadcast of the Sink node and the node relay forwarding, thereby dividing the network into a hierarchical gradient topology. In addition, in order to better describe the interference conflicts between different links, the network nodes in the dormant state are divided into four states: free, occupied, potential interference, and death. At the same time, considering that when the neighbor node of a node is within the communication interference range of other event transmission links, the transmission and reception of the neighbor node data will be interfered by the transmission of other links, and the degree of interference is related to the amount of data to be transmitted by the node under other event transmission. Therefore, other event occupied nodes within the communication range of the neighbor node are defined as heterogeneous interference nodes of the node. In the network initialization stage, all node states are in a free state, and the heterogeneous interference node information set is an empty set.

The number of hops from node _i to the sink node and the information of the upper node are determined by a data packet broadcasted by the sink node. The specific implementation steps are:

The Sink node first broadcasts a data packet packet(ID, hop＝0), where hop represents the number of hops from the Sink node. If a node receives the packet and the hop count is not set, it sets its own hop count to hop＝hop+1 according to the hop count in the data packet and saves the ID information of the sending node. Then it continues to broadcast a packet packet(ID, hop) to its neighboring nodes. When node i receives a data packet packet(hop _j ) from other node j, if hop _j ＜hop _i -1, node i updates its own hop count to hop _j +1, and at the same time, re-updates the upper node information. If hop _j ＝hop _i -1, the hop count of node i remains unchanged and saves the ID information of the sending node in the data packet. Repeat the above steps to continue broadcasting the data packet packet(hop _i ) to its neighbors until all nodes obtain the minimum hop count to the Sink node, and there is no data packet to be transmitted in the network. Finally, the node saves the hop count information and the upper node information and resumes the sleep state. The network can be divided into a hierarchical gradient topology structure by the minimum hop count of the node from the Sink node. Considering that the death of a node will change the minimum number of hops and the path from the node to the Sink node, the Sink node periodically repeats the broadcast process to update the network topology in real time.

In this implementation, the node state State is divided into four types: free, occupied, latent interference, and dead. The state diagram is shown in FIG2 . The specific setting rules are as follows:

A. Free state: not triggered by any event, not used as a relay node in the data transmission process, and none of its neighboring nodes is used as a relay node for the transmission link.

B. Occupied state: After the event is triggered, it has been selected as a relay node in the data transmission link to transmit the collected information.

C. Potential interference state: There are neighboring nodes within the communication range that serve as relay nodes for a certain event data transmission, and have a certain probability of receiving event information sent by other event transmission nodes, that is, nodes that may be interfered with by other event transmissions.

D. Death state: When the node energy is lower than a certain threshold, it is defined as dead and cannot undertake the task of data transmission.

The heterogeneous interference node is an occupied node of other event transmission links within the communication range. Under the influence of the heterogeneous interference node, all nodes within its communication range are in a potential interference state. Considering that different heterogeneous interference nodes have different interference strengths to nodes at different distances in the communication area due to different interference distances and the amount of data to be transmitted. The heterogeneous node information table is defined to include the ID mark of the heterogeneous node, the data packet length of the event to be transmitted, and the signal interference strength. The information is set as shown in Table 1.

Table 1: Heterogeneous node information table

Logo significance ID Heterogeneous interference node identification S _(i,j) Length of data packet to be transmitted by heterogeneous interference node RSSI _(i,j) Signal interference intensity of heterogeneous interference nodes

S2 Clustering Strategy Based on Multi-Event Triggering

After the network is initialized, the nodes are in a dormant state. When different events occur, the sensor nodes that detect the events in the trigger area are activated. All activated nodes in a single event trigger area are regarded as a cluster set. The node with the highest energy is selected from all activated nodes as the cluster head node. The remaining nodes are member nodes in the cluster and periodically collect event information and transmit it to the cluster head node through a single hop.

As shown in Figure 4, when an event is triggered, the nodes that perceive the event information are activated. Assuming that the single event triggering area is small and all activated nodes in the area are at the same gradient level, all activated nodes in a single triggering area are regarded as a cluster set. The clustering diagram is shown in Figure 3. The specific process of event triggering clustering is as follows:

First, cluster head node election is performed. All activated nodes in the event triggering area broadcast their own ID and residual energy information to surrounding nodes. From the broadcast information, the event activated node ID with the highest residual energy is confirmed and the activated node is used as the cluster head node, and the remaining activated nodes are used as ordinary nodes. The cluster head election probability formula is:

MaxE _rest (i) → current event cluster head node

Where E _res (i) is the residual energy of the i-th candidate activation node.

After the cluster head node is elected, the remaining activated nodes become member nodes in the cluster. Cluster member nodes periodically collect event information and send the information to the cluster head node in a single hop manner. The cluster head node integrates the received data.

S3 Candidate relay selection based on interference avoidance mechanism

After the information of different events converges to the cluster head node, the cluster head node is used as the source node and the sink node as the destination node, and the next-hop data transmission relay is reasonably selected to build an interference-free multi-source transmission link. In order to avoid interference between link transmissions and load balancing problems, an interference avoidance mechanism is designed. The node status and hop level are used as constraints to exclude invalid neighboring nodes in occupied state, potential interference state and dead state, and select nodes in the free state of the upper node as candidate relays. When there are many triggering events or they are close to the sink node area, if there are no neighboring nodes in the free state, the nodes in the potential interference state of the upper node are selected as candidate relays.

In this step, the transmission interference with other links is taken into consideration. According to the principle that communication links far away will not cause interference or cause very little interference, nodes that are completely disjoint and whose inter-link distance is greater than the communication interference distance are selected as candidate transmission relays. The interference avoidance mechanism is shown in Figure 5, and the specific implementation process is as follows:

First, node i sends a routing request Request to neighboring nodes within the transmission radius with a transmission power of _Pt. The Request data packet contains the ID of the current node, the number of hops from the aggregation node hop _i, and the length of the data packet to be transmitted S _{(i, j)} . Neighboring node j receives the Request data, and the signal receiving strength at this time is RSSI _{(i, j)} . Node i is a heterogeneous interference node of the neighboring node. The neighboring node updates the state State(j) information in the routing table to the interference state, and adds the ID number of node i, the length of the data packet to be transmitted S _{(i, j)} of the node, and the received signal strength RSSI _{(i, j)} to the heterogeneous interference node information table of the node.

节点状态剩余能量E_j信息。In order to avoid routing loops during the routing selection process and to reduce the number of transmission hops as much as possible, the number of hops from the next hop relay node to the sink node should be smaller than that of the current node. Therefore, after the upper neighbor node with a hop number of hop _i -1 from the sink node receives the Request packet, the neighbor node in the non-dead state replies to the current node i with a Respond packet with a transmission power of P _t , which includes the ID number, heterogeneous interference node information, and the like.

Node status remaining energy _Ej information.

After receiving the Respond data packet, the node determines the candidate relay set based on the returned information. When there are fewer triggering events or the node is far away from the Sink node area, the communication overlap area of different links is small, and the interference between links is small. At this time, the neighboring nodes in the free state are selected as candidate relays, so that the path nodes starting from different source nodes are completely disjoint and the distance between different path nodes is greater than the communication interference distance, thereby achieving complete interference avoidance and avoiding excessive network load on a single node.

When the number of triggering events increases or approaches the Sink node area, the overlap area of the data transmission paths triggered by different events is larger, the number of nodes in the occupied and interference states increases, and there may be no neighboring nodes in the free state among the neighboring nodes that reply to the message, as shown in Figure 6. At this time, all nodes in the potential interference state are selected as candidate relay nodes.

After node i determines the candidate relay set according to the node state constraint, it stores the candidate neighbor node information and the Respond signal receiving power P _r in the candidate set Respond data packet to form a candidate neighbor node information table.

S4 Relay election based on interference sensitivity

After determining the candidate relay nodes, construct the relay election probability objective function F(N) to select the next-hop relay. When all the candidate relay nodes are in a free state, select the node residual energy and node distance as the relay election function indicators, and select the node with large node residual energy and the closest distance to the optimal relay as the next-hop node; when the candidate relay nodes are in a potential interference state, there are heterogeneous interference nodes within their communication range, that is, the data transmission and reception may be interfered by the data transmission of multiple different events. Therefore, an interference sensitivity is introduced to evaluate the interference strength of other event transmissions on the candidate relay nodes. The relay election probability function is constructed by comprehensively considering the node residual energy, node distance and interference sensitivity, and the candidate relay with the largest function value is selected as the next-hop relay node.

As shown in Figure 7, when there are few triggering events or the node is far away from the Sink node area, after the S3 candidate relay selection step, the candidate relay nodes are all free-state nodes. At this time, complete interference avoidance is achieved. There is no data conflict caused by the same node sending and receiving data at the same time and communication interference of other event transmission links. On this basis, the node residual energy _Ej and the node distance _dj are selected as the selection indicators of the relay node to minimize the network energy consumption of data transmission, that is, the relay selection probability function of the jth node is:

为所有候选邻居节点的平均剩余能量，d_j为邻居节点j与当前节点的距离，d_opt为最佳中继距离，α和β分别为节点剩余能量以及节点距离指标的权重系数。Where _Ej is the residual energy of candidate neighbor node j,

is the average residual energy of all candidate neighbor nodes, d _j is the distance between neighbor node j and the current node, d _opt is the optimal relay distance, α and β are the weight coefficients of node residual energy and node distance index respectively.

其计算公式为：(1) For the objective function F(N _j )

The calculation formula is:

(2) For the distance d _j between the neighboring node j and the current node i, this embodiment uses the received signal power P _r to measure, and the distance and the received signal power satisfy the following relationship:

γlgd _j = lg(P _t ) - lg(P _r )

Where γ is the channel attenuation factor of wireless transmission.

(3) For the optimal relay distance d _opt , the formula is satisfied:

In the formula, E _Telec and E _Relec are the basic energy consumption of node sending and receiving, ε is the energy consumption coefficient of the transmitting power consumption circuit, and γ is the channel attenuation factor of wireless transmission. The derivation process is as follows:

From the first-order radio energy consumption model, we know that the energy consumed by a node sending lbit of data to a node with a distance d is:

E _Tx (l,d)＝l(E _Telec +εd ^γ ),2≤γ≤4

The energy consumption of a node receiving lbit of data is:

E _Rx (l) = lE _Release

Where E _Telec and E _Relec are the basic energy consumption of node sending and receiving respectively, ε is the energy consumption coefficient of the transmitting power consumption circuit, and γ is the channel attenuation factor of wireless transmission.

跳直线传输数据到目的节点中的各节点所耗能量和最小，称间距d为节点向汇聚节点传输数据的最优中继距离，

为最优跳数。Assume that the distance between the source node and the destination node is D, and the distance between all hops is d.

The energy consumed by each node in the straight line transmission of data to the destination node is minimized, and the distance d is called the optimal relay distance for the node to transmit data to the sink node.

is the optimal number of hops.

Assuming that the distance from the current node to the sink node is D, the simple linear model is shown in Figure 8. At this time, the total network energy consumption of the node transmitting lbit of data to the sink node is

Taking the derivative of the above formula with respect to d, we can get

Let E′ _D (d) = 0, we can get

Taking the second derivative of _ED (d) we get

It can be seen from the above formula that E″ _D (d) ≥ 0 always holds true. Therefore, E′ _D (d) is a monotonically increasing function. Let E′ _D (d) = 0 and the solution d is the optimal relay distance d _opt with the minimum E _D (d). That is, after knowing the inherent power consumption parameters of the node and the attenuation factor of the wireless environment, the optimal relay distance of the next hop of the node is

In order to extend the service life of the path, it is necessary to save the network energy consumption as much as possible and try to select nodes with more remaining energy as the next-hop relay. From the specific derivation and analysis, it can be seen that under the optimal relay distance, the network energy consumption value is the smallest. Therefore, the distance between the next-hop relay node and the current node should be as close to the optimal relay distance as possible.

When the number of triggering events increases or the area is close to the Sink node, the candidate relay nodes are all in a potential interference state. There are nodes occupied by other event data transmission within their communication range. There is competition for channel resources between the candidate relay and other event transmission nodes. When both perform data transmission at the same time, interference conflicts will occur (see Figure 9), and the strength of the interference and the probability of interference are related to the size of the link transmission data packet. The greater the communication volume of the interference link, the longer the communication time of its data transmission, the greater the probability of interference conflict P _i (j), the stronger the interference intensity, and the worse the link quality. Therefore, the interference sensitivity IS _{(i, j)} of the candidate neighbor node when it is used as the next-hop relay is introduced as the relay selection index, so that the node with the lowest probability of interference and intensity is given priority as the next-hop relay node. The relay election probability objective function F (N _j ) at this time is:

Where α, β, and η are the weight coefficients of node residual energy, node distance, and interference sensitivity, respectively.

Interference sensitivity IS _{(i, j)} reflects the degree to which the current link (i, j) is affected by other event transmission links during multi-source data transmission. It comprehensively considers the interference probability and interference intensity of other event transmissions. The specific formula is:

为第k个事件传输链路对链路(i,j)的干扰产生概率，RSSI_k为第k个事件对对链路(i,j)的干扰强度。In the formula,

is the probability of interference generated by the k-th event transmission link to link (i, j), and RSSI _k is the interference intensity of the k-th event to link (i, j).

不同事件的传输链路在同一信道同一时隙传送数据时存在一定冲突，因此，定义两条干扰链路发生干扰冲突的概率是在链路(i,j)占用信道时间段τ_(i,j)期间至少有一个其他事件链路节点发送的数据包到达节点j。具体计算过程如下：(1) For interference probability

There is a certain conflict when transmission links of different events transmit data in the same channel and the same time slot. Therefore, the probability of interference conflict between two interference links is defined as the probability that at least one data packet sent by another event link node reaches node j during the period τ _{(i, j)} of link (i, j) occupying the channel. The specific calculation process is as follows:

Assume that the packet arrival process conforms to the Poisson distribution process, where the probability density of the Poisson distribution is

Where λ is the total number of packets expected to be received within a certain time T, that is, the number of packets sent by the source node. k is the total number of packets actually received by the node within the time T.

S _{(i, j)} is the length of the data packet to be transmitted on the current link (i, j), r _{(i, j)} is the data transmission rate of the link (i, j), then the transmission time required for node _Ni to transmit a data packet to its next-hop relay node _Nj is

The probability that another event transmission interferes with node k transmitting data at the same time in the time period τ _{(i, j)} and a data packet sent reaches node j can be obtained from the probability density formula of Poisson distribution:

Where, _Sk is the number of packets sent during the interference event.

The probability of interference conflict between two interfering links is that during the period τ _{(i, j) of link (i,} j) occupying the channel, at least one data packet sent by node k from other event link arrives at node j. Then the probability of interference is

(2) For the interference intensity RSSI _k , the data sent by other event transmission links are affected by the link quality and transmission distance, and have different interference levels on the current node. Therefore, the signal reception strength received by the current node from the heterogeneous interference node is taken as the interference intensity of the kth event on the link (i, j).

S5 power control and data multi-hop transmission

After the next-hop relay is determined, the node status in the routing information table of the next-hop relay node is updated to occupied and data transmission begins. In order to reduce the energy loss caused by transmission power redundancy and extend the service life of the path, the transmission power of the node is adjusted according to the received signal strength of the node. The network repeats steps S3 and S4 until all relay nodes in the path are determined, and then each relay transmits the event trigger information to the Sink node with the optimal transmission power.

In this step, the optimal transmission power is defined as: P _{(i, j)} = P _t - (P _r - P _min ) + ΔP.

In the formula, _Pt is the signal transmission power of the neighboring node sending the Respond data packet, _Pr is the signal receiving power of the node receiving the data packet sent by the neighboring node, _Pmin is the minimum signal strength for the data packet to be correctly received, and ΔP≥0 is a fault-tolerant numerical item. If you want to further reduce energy consumption, you can adjust this value to a smaller value. If you want to make the transmission of the data packet more reliable, you can increase this value appropriately. By adjusting the transmission power according to the formula, you can reduce the energy waste caused by transmission power redundancy when sending data packets.

It is not difficult to find that compared with other routing algorithms, the present invention can effectively solve the interference conflict problem in multi-path parallel transmission of data and improve the transmission efficiency of the network. At the same time, for the network energy consumption problem caused by a large amount of data generated during multi-event transmission, the present invention can better balance the network energy consumption of nodes, save network energy loss, and increase the service life of the network. It has a good effect on network throughput, transmission delay, and network energy consumption.

Claims (5)

1. A routing method based on multi-event triggered multi-source path interference optimization, comprising the steps of:

(1) Network initialization: the node obtains the minimum hop count from the sink node and the ID of the upper node through the periodical broadcast data packet of the sink node and the relay forwarding of the node, and divides the network into a hierarchical gradient topological structure; defining other event occupying nodes in the communication range of the neighbor node as heterogeneous interference nodes of the node; dividing the nodes into a free state, an occupied state, a potentially interfering state and a dead state; the node in the free state is not triggered by an event and is not used as a relay node in the data transmission process, and the neighbor node of the node is not used as a relay node of a transmission link; the node in the occupied state refers to a relay node which is selected as a data transmission link after the event triggering; the node in the potential interference state refers to a relay node with a neighbor node in a communication range as a certain event data transmission; the node in the death state refers to a node which cannot bear a data transmission task;

(2) Clustering strategies based on multiple event triggers: when different events occur, the node which detects the event in the trigger area is activated; all activated nodes in a single event triggering area are regarded as a cluster, the node with the highest energy is selected from all the activated nodes to be used as a cluster head node, and other nodes are used as periodic acquisition event information of member nodes in the cluster and are transmitted to the cluster head node in a single-hop mode;

(3) Candidate relay selection based on an interference avoidance mechanism: the cluster head node is used as a source node, the sink node is used as a destination node, the states of the nodes and the hop count level are used as constraint conditions, invalid neighbor nodes in occupied states, potential interference states and death states are eliminated, and nodes in free states in the upper nodes are selected to be used as candidate relays;

if the neighbor node in the free state does not exist, selecting the node in the potential interference state in the upper node as a candidate relay;

(4) Relay election based on interference sensitivity: when the candidate relays are all nodes in a free state, the node residual energy is used, the node distance is used as a relay election probability objective function, and the selection function value is the largestAs a next hop node; when the candidate relay is a node in a potential interference state, introducing interference sensitivity to evaluate the interference strength of other event transmission to the candidate relay, constructing a relay election probability objective function by using the node residual energy, the node distance and the interference sensitivity, and selecting the candidate relay with the largest function value as a next hop node; when the candidate relays are nodes in a free state, the relay election probability objective function

Wherein E is _j The residual energy of the candidate neighbor node j is E, the average residual energy of all the candidate neighbor nodes is d _j Is the distance between the candidate neighbor node j and the current node, d _opt Alpha and beta are weight coefficients of node residual energy and node distance indexes respectively for the optimal relay distance; when the candidate relay is a node in a potentially interfering state, the relay election probability objective function +.>

Wherein E is _j The residual energy of the candidate neighbor node j is E, the average residual energy of all the candidate neighbor nodes is d _j Is the distance between the candidate neighbor node j and the current node, d _opt IS for the best relay distance _(i,j) For interference sensitivity +.>

P _i ^k (j) Generating probability for interference of kth event transmission link to link (i, j), RSSI _k For the interference intensity of the kth event to the link (i, j), alpha, beta and eta are respectively the weight coefficients of node residual energy, node distance and interference sensitivity;

(5) And updating the node state in the next hop relay node routing information table to be occupied, and then starting data transmission.

2. The routing method based on multi-event triggered multi-source path interference optimization according to claim 1, wherein defining the node occupied by other events in the communication range of the neighbor node as the heterogeneous interference node of the node includes defining an ID flag of the heterogeneous node, a packet length of the event to be transmitted, and a signal interference strength.

3. The routing method based on multi-event triggered multi-source path interference optimization of claim 1, wherein the step (3) specifically comprises: the node i sends a routing request to a neighbor node j in a transmission radius, wherein the routing request comprises the ID of the current node, the hop count from the sink node and the length of a data packet to be transmitted; after receiving the routing request, the neighbor node j updates the state information of the node i in the routing table into an interference state, and adds the ID number of the node i, the length of the data packet to be transmitted of the node i and the received signal strength; the neighbor node j replies a response to the node i, wherein the reply response comprises the ID of the node j, the information of the heterogeneous interference node, the node state and the residual energy; and after receiving the reply response, the node i determines a candidate relay according to the reply response.

4. The routing method based on multi-event triggered multi-source path interference optimization of claim 1, wherein the optimal relay distance

Wherein E is _Telec And E is _Relec The energy consumption is the basic energy consumption of node sending and receiving respectively, epsilon is the energy consumption coefficient of the transmitting power consumption circuit, and gamma is the channel attenuation factor of wireless transmission.

5. The routing method based on multi-event triggered multi-source path interference optimization of claim 1, wherein the step (5) adjusts the transmit power of the node according to the received signal strength of the node when transmitting data.

Images