Research On Data Transmission And Data Management For Delay-Tolerant Mobile Sensor Networks

For the special nerwork application, Delay-Tolerant Mobile Sensor Network(DT-MSN) is proposed as a new type of wireless sensor network with low node density and sparse network environment. Nodes in DT-MSN are no longer distributed statically to sample data but wore on the mobile carriers and move with them, which conduces to highly dynamic network topology, poor network connectivity and intermittent communication between nodes.Further, nodal mobility will easily lead to invalid data transmission, retransmission storm and reduce the success rate of data. Aadditionally, DT-MSN possesses high delay tolerability so that the real-time requirement of data is reduced. The sampled data needs not to send out in real time but to collect for statistical analysis which results in packet accumulation and has great impact of queue size. The limitations of nodal buffer and great data accumulation has brought data management problem.To achieve efficient data transimission and queue management, the network model of DT-MSN is established then the energy efficient MAC protocols, dynamic management of data queue and cross-layer optimization design are profoundly researched. The main results and innovations of the thesis are as follows:1. Energy efficient data transmission schemeFor the charactistics of highly dynamic and sparse topology in DT-MSN, an energy efficient MAC protocol dubbed Delay-Tolerant MAC (DT-MAC) is proposed, which uses asynchronous duty cycle, adopts a transfer mode initiated by the receiver, and introduces Initial Aware Frame (IAF) with multifunction of neighbor updating, transfer initiation, controls of contending as well as topology maintenance. Via reducing retransmission rate and the cost of control packets, it efficiently controls energy consumption and extends the lifetime of the whole network. Experiments on wireless sensor networking platform indicate that, in DT-MSNs with highly dynamic topology, both the sender and the receiver can achieve energy efficiency, lessen one-hop latency, and increase the network throughput.2. Dynamic data queue management strategy based on priorityTo slove the data management problem brought by the limitations of nodal buffer and great data accumulation, the priority based dynamic data queue management strategy is introduced in this thesis. A discrete-time Markov arrival process (MAP) priority queuing model and the hybrid preemptive queue process is developed. Based on Multi-dimension prioirty data management strategy, the packet loss is reduced while the nodal buffer limitation is relieved. In addition, by classing the sorted data queue, the burst messages will be preferred to transmitte and the urgent circumstances can be handled timely. The further experiments verify that the data delivery ratio is increased, packet loss is reduced and the mean packet delay is improved.3. Multi-cross-layer optimization designIn the cross-layer optimization design, messages from the routing layer, MAC layer and application layer are interacted and a multi-cross-layer optimization modle for DT-MSN is proposed to achieve energy efficiency, improve data transmission success and address the data queue management. For the highly dynamic network topology and poor network connectivity in DT-MSN, the routing layer and MAC layer are integrated and a system modle named Ant State Modle is raised. By the cross-layer interaction of neighbor discovery and routing update from pheromone release and pheromone trail updating, the sender can find the optimal sink, which improves the single-hop throught when nodes meet each other. In the integration of MAC layer and application layer, the priority-based quality of service(QoS) parameter is interacted, where priority dimension, priority measure as well as priority class are introduced to determine the priority value of data queue and resolve the order deviation of data priority between application layer and data link layer. Via multi-cross-layer optimization design of DT-MSN, the routing layer is flattened to achieve effective data tranfers as well as power saving while routing, and the high-priority packets can be received by the sink more timely and efficiently to complete dynamic and intelligent data management. Thus the overall network performance will be enhanced for the multi-cross-layer integration and optimization design.