Data Collection In Mobile Sensor Network And Broadcast Algorithm Research

Mobile wireless sensor networks have a wide range of applications. Researchershave successfully attached wireless sensors to all kinds of mobile devices/entities suchas micro air vehicles, bikes, ground-based vehicles and animals to get information ofindustrial and urban environment, traffic, the diffusion degree of the flu virus in thecrowd and the living characteristics of Animal community. Since the topology of thenetworks changes frequently, moreover together with the limited sensor nodes’ storagespace, computing power and communication bandwidth, data aggregation in mobilewireless sensor networks faces great challenges. At present, there are just a littleresearchings on the data collection and broadcasting of mobile wireless sensor networks.Based on the above, this paper made the following contributions:1. This paper proposed Node Density and Distance based Probabilisticbroadcasting algorithm (NDDP). The algorithm which distributed and dynamicallydetermines forwarding probability based on node density and the distance betweencurrent node and the last hop can reduce network forwarding ratio in the condition ofhigh network receipt ratio, so saves the broadcasting energy. The theoretical averagevalue of the receipt ratio of NDDP is more than95%and the ns-2results is also morethan92%while the average value of the forwarding ratio is only5S N πr2(S is theacreage of network, N is the total number of nodes, r is radio range). Simulationexperiment results show that NDDP outperforms the two broadcasting algorithms inSmite and Sidewinder in stability and energy saving performance and thepreponderance increases together with node density.2. This paper proposed Node Density and Position based data collecting protocol(NDP). Firstly, Sink periodically broadcasts its content information using NDDP. And then proposed Grid algorithm to cluster nodes. The algorithm which chooses clusterhead dynamically according to network range and nodes’ position can restrict thenumber of cluster head when the coverage ratio is almost the whole network. Themission of a cluster head is to collect data package of its neighbours. After collecteddata, we propose a Less Hop and Directional diffusion algorithm to send the collecteddata from cluster head to predicted position of Sink. The information for prediction isfrom the content information which the common nodes receive from Sink periodically.Simulation experiment results show that NDP outperforms Smite in stability and energysaving performance and the preponderance increases together with node density.