Research On Task Allocation Algorithms In Wireless Sensor Networks

In wireless sensor network(WSN),tasks are usually divided into computing tasks,sensing tasks,and communication tasks.Performing tasks will consume-certain computing resources and occupy communication bandwidth.However,due to the very limited network resources,coupled with the poor computing power and limited energy of sensors,complex applications cannot be completed alone.Therefore,it is necessary to design an allocation algorithm to efficiently use existing resources to ensure the smooth execution of tasks.That is,in a dynamic network environment with limited energy,the tasks in the system are effectively allocated first,and then the specified tasks are scheduled to be executed on suitable nodes.This requires the algorithm.Performance indicators such as deadline,completion time,energy consumption,reliability,and load balancing must be combined.Chinese and foreign scholars have in-depth research on task assignment algorithms in the traditional network environment,but most of them do not consider energy constraints,so their algorithms cannot be directly applied to wireless sensor networks.This urgently requires the development of task assignment algorithms in the field of wireless sensor networks.the study.In addition,most of the existing researches focus on static task allocation algorithms,and the environment will change dynamically,such as the change of node state,so it is of great significance to carry out research on dynamic task allocation algorithms.The main contents of this article are as follows:1.This dissertation first discusses the problem of task assignment and related algorithms in wireless sensor networks.Since the current static task allocation algorithm has a single optimization goal,usually only one or two performance indicators are considered.The static task allocation algorithm proposed in this paper,in addition to the minimum calculation task completion time as the optimization goal,also reduces energy consumption and load Indicators such as equilibrium are used as optimization goals,and a multi-objective mathematical model for task allocation is established.Aiming at the characteristics of wireless sensor network task allocation subject to deadline constraints,node calculation and energy limitation,a hierarchically optimized computing task allocation algorithm is proposed.Prioritize computing tasks by setting thresholds according to deadlines,design a priority assignment algorithm for tasks with tight deadlines,and minimize task completion time;for tasks with more relaxed deadlines,subject to the constraints of deadlines Considering the energy-constrained characteristics of the wireless sensor network itself,design an algorithm that optimizes the goal of reducing energy consumption and balancing load to extend the life of the network.Simulation experiments show that the hierarchical optimization algorithm achieves better results in reducing energy consumption,reducing task completion time and balancing network load.2.The dynamic task allocation algorithm has higher requirements for wireless sensor network environment perception,but researchers do not consider the state changes of sensor nodes.The dynamic task allocation algorithm for sensing tasks proposed in this dissertation can make the sensor nodes as possible to sleep more to save energy.On the other hand,it can perceive the dynamic changes of the environment(such as the joining and leaving of nodes),adjust the distribution strategy in time,and minimize the energy consumption for the completion of the sensing task as the optimization goal.On the basis of perceiving the dynamic environment,the coverage and schedulability of the sensor network nodes are taken as the constraints of this problem.The improved ant colony algorithm is applied to the task allocation algorithm,and the optimal allocation scheme is obtained through iteration.At the same time,the information entropy is introduced to improve the probability of the nodes with sufficient residual energy to perform the task.Experiments show that this dynamic task allocation algorithm can reduce the total task completion time,total energy consumption and network load balance compared with the ant colony algorithm(MIACO)with migration strategy and the original ant colony optimization algorithm(ACO)achieved good results.Figure[17]table[1]reference[]...