A Study On Routing Algorithms Based On Opportunistic Thoughts For Wireless Sensor Networks

Recently,the rapid development of technologies such as sensors and microelectronics has brought performance enhancements and functional extensions to Wireless Sensor Networks(WSNs).For example,a self-organizing vehicle network can realize traffic warning and real-time planning of traffic routes on the high way.In the natural wildlife protection zone,sensors could be mounted on wild animals to form an ad hoc network,which can collect different data such as migration and populations.After a major disaster such like earthquakes or tsunamis occurs,when the ordinary communication system is paralyzed,a local communication network can be formed through the mobile handset.However,in some application environments,the network will be divided into several disconnected areas due to random movement of nodes,electromagnetic interference and selfishness of nodes or other reasons.If the source node and the destination node are in different areas,there will be no complete routing path between them,and the traditional routing algorithm will not work at all.In a high delay tolerant network,two nodes in different regions can communicate through the encounter opportunities brought by movement,which is called Opportunistic Thought.The network that uses this idea is also called Opportunistic Networks by some scholars.Based on the analysis of classical routing algorithms in opportunistic networks,the following aspects are studied in this thesis.1)This thesis comprehensively classifies and analyses the existing routing algorithms of Opportunistic networks,and simulates the classical routing algorithms such as Epidemic and PROPHET in different environments.According to the simulation results and the performance of classical routing algorithms in various aspects,two defects of most existing Opportunistic networks routing algorithms are summarized:high energy consumption of nodes and no consideration of the mobility characteristics of nodes.At the same time,the Epidemic algorithm,which is easy to deploy,is adopted to optimize and improve in this thesis.2)In this thesis,an energy-saving algorithm based on asynchronous sleeping mechanism-EASE,is proposed to solve the problem of node energy consumption.Traditional Epidemic routing algorithm replicates data packets,which leads to a significant increase in energy consumption.However,in the application environment of opportunistic thoughts,the energy of nodes can't be replaced at any time.The EASE algorithm proposed in this thesis allows nodes to decide whether to enter a dormant state or not according to their own energy situation,real-time state and other information.The algorithm guarantees that the nodes will not miss the possible communication opportunities by dynamically controlling the sleep duration.The simulation results show that EASE algorithm can greatly reduce the energy consumption of nodes while guaranteeing the information delivery rate.3)This thesis proposed a clustering routing algorithm-MOCA,based on the characteristics of node movement and the idea of anchor nodes.The algorithm divides the whole network into several regions and sets anchor nodes in each region,so that each node can record its own movement and get the sequence of the moving trajectories.Then the similarity of the moving trajectories of the two nodes is obtained by the maximum common subsequence method.Finally,according to this parameter and the historical encounter information of the nodes,the nodes in the network are clustered.The node can select whether to send a copy of the data packet to the encounter node by clustering information.The simulation results show that the MOCA algorithm can improve the transmission rate of the network,save network resources and reduce the number of data replicas in the network.