Research On Task Allocation Mechanism Of Wireless Sensor Networks Based On Overlapping Clustering And Self-Adaptation Coalition

Wireless sensor network system is composed of a large number of low-cost sensor nodes through self-organization or multi-hop form,used to monitor the target area and collect the required data.Wireless sensor network systems usually need to perform some computationally intensive tasks,but single node have limited energy and resources,and once these nodes are deployed,humans will not be able to intervene.Therefore,the energy of the nodes in the network has become the main factor limiting the life cycle of the sensor network.How to reduce the energy consumption of the nodes has always been a research hotspot in the WSN.At the same time,WSN is a task-oriented application-oriented network system which can be used in environment data collection,disaster warning and battlefield monitoring scenarios.This requires high real-time processing tasks,how to ensure that tasks can be completed in real time and quickly also becomes a hot topic in the research of wireless sensor networks.In addition,with the development of information technology,the types of information that people need to collect also increase,leading to more types of sensor nodes forming the sensor network.WSN will be used to deal with the complex composition of the task,we call it a complex task,these complex tasks are usually composed of multiple types of resource requests,the need for different types of sensors to complete.Therefore,how to make the WSN prolong the network life and improve the task allocation efficiency when dealing with complex tasks has become the main problem of this paper.This paper focuses on the research of complex task allocation mechanism based on overlapping clusters and self-adaptation coalition WSNs:(1)Complex task allocation based on overlapping clustering networks.The existing method of task allocation in the clustering network makes the task can only be performed in a single cluster.However,in a single cluster,the energy and the number of sensor nodes are limited,and the performance of the network cannot be fully utilized.In order to solve the above problems,we propose an algorithm for complex task allocation in overlapping clustered wireless sensor networks.The algorithm divides the network into clusters and divides the complex task into multiple subtasks.Then it uses the fitness function to match the appropriate nodes for these subtasks.Finally,these subtasks are allocated.In traditional clustering networks,task allocation can only be performed in a single cluster.In overlapping clustering networks,some sensor nodes may belong to multiple clusters at the same time.The use of such nodes in the task allocation process enables collaboration between clusters and clusters,which can increase the probability of successful allocation of complex tasks.The simulation results show that the algorithm can significantly reduce the network energy consumption,extend the network life time,balance the network load,and can guarantee the timeliness of the task.(2)Self-adaptation-based coalition formation for complex task allocation.In distributed sensor networks,multiple sensor nodes are usually required to form a coalition to complete some complex tasks.Due to the limitations of communication and computing capabilities,it is impossible for a sensor node to directly establish coalition with all other sensor nodes.In the MAS,most of the existing coalition formation studies also ignore this issue,and those studies do not provide a clear explanation or assume that the sensor nodes are in a fully connected network,which is not desirable in practical applications.Meantime,in the task allocation strategy,the previous research centered on the first node assigned to the task,then find the nodes from the near and far to complete the remaining subtasks,but the performance of these nodes cannot be guaranteed,especially in the parallel task allocation,the probability of death node and task assignment failure is greater.In order to fully use the performance of the networks,reduce energy consumption of sensor nodes,balance network load,and improve task allocation efficiency,this paper proposes a complex task allocation mechanism based on self-adaptation coalition formation.During task allocation,nodes will receive multiple partners' task coordination requests.This mechanism allows nodes to evaluate these requests and dynamically adjust their relationship with these coalitions.Based on the two-way selection mechanism,nodes and coalitions can evaluate and select each other,and then continuously adjust the coalition structure,and eventually form suitable coalitions for the tasks.Finally,simulation experiments show the superiority of the algorithm.