Research On Low Delay Opportunistic Routing In Wireless Sensor Networks

The technology of wireless sensor network has been widely used in various fields due to its characteristics of multi-hop,self-organizing and distributed computing.However,many problems are exposed in these applications.Where problems for short network life,low system throughput and poor real-time data are particularly serious.Opportunistic routing as a routing protocol which is designed for the wireless sensor network can improve the network throughput and prolong the network life,so it has attracted many researchers' attention.Although opportunistic routing is more suitable for delay-tolerant or intermittently connected networks,it is still the basic requirement to reduce the network delay and improve the realtime performance of the network.In the research of traditional opportunistic routing,only a few literature has considered the network delay.Secondly,a large number of literature only focused on one factor and ignored other factors.In order to reduce the end-to-end delay and improve the quality of network service as large as possible in the opportunistic routing,The following researches are carried out in this paper:(1)The expected end-to-end coordination delay(ECD)among candidate nodes is proposed firstly,and then we rank the priority of candidate forwarding set according to the proposed ECD,finally we proposed an opportunistic routing of optimal coordination delay among candidate forwarders.(2)Consider the design of opportunistic routing protocol in wireless sensor networks with multi-flow.Firstly,the modeling and analysis of multi-flow network environment are presented,and the global performance indexes of nodes such as residual energy,available bandwidth and buffer queue are presented.Secondly,the Qo S index of candidate forwarders are defined in the form of weight function.Finally,the learning automata algorithm is used to update the priority index of candidate forwarding set,and the design of forwarding priority ranking is completed.The simulation results show that the opportunistic routing of optimal coordination delay among candidate forwarders can reduce the average end-to-end delay and increase the throughput of the network in the intensive network.The algorithm combined with learning automata and Qo S index can effectively balance the resources of the network,and improve the quality of network service as a whole.