Research On Wireless Sensor Network Routing Algorithm Under Uncertain Environment

The internet of things can connect human with things, and wireless sensor networks (WSNs) for sensing and gathering data have been the key technology of sensing things. With the prevalenece of wireless sensor network and the boost of its invertigation, researches on routing problem of wireless sensor network with limited resources, based on the assumptions of certain environment, become diffucult to meet the needs of applications.In wireless sensor networks, many aspects, such as deploy environment, wireless communication, quality of service and network topology, have uncertainties, which include randomness depicting whether an event happens and fuzziness depicting the subjective knowledge of an event. Investigations on routing problem of wireless sensor network in uncertain network environment need the corresponding uncertainty theory and optimization theory, which are used to describe the uncertain factors in routing procedure, such as interference models, propagation models, mobility models and quality of service. Therefore, theorencal bases and guarantees are provided for researching on routing algorithms of wireless sensor network in uncertain environment.In order to depict the uncertainties of routing for wireless sensor network in uncertain environment, the routing problems are modeled based on probability theory, fuzzy set theory, fuzzy random theory and optimization theory, particularly, the uncertainties of wireless interference, signal power fading, quality of service and routing optimization model are analysed and represented. In addition, the corresponding routing algorithms and simulation experiments are designed for further investigations on the routing algorithms of wireless sensor network in uncertain environment. The main works of the thesis are summarized as follows:(1) To describe the random characteristic of wireless data transmission under interference, the likelihoods of successful data transmission are deduced based on channel contention and physical interference model respectively, and the sender and receiver interference models of successful data transmission under interference are proposed by taking into account of both the sender and the receiver in a transmission. Furthermore, the interference-aware cross-layer routing metric is constructed, and the isotonic property of the weight function is proofed. In addition, the IACP (Interference-Aware Cross-layer Probabilistic routing) algorithm is designed, and its correctness and time-space complexity are analyzed. Simulation results based on the NS2platform show that, due to the influence of interference, the proposed IACP routing algorithm can achieve better packet delivery ratio, throughput, jitter and average delay in dense deployment under the different loads at the expense of the comparable average length of paths when comparied with the typical adhoc on-demand distance vector routing algorithm.(2) To describe the random fading of wireless signal power and random characteristic of wireless data transmission under interference, the probability interference model of successful data transmission under interference is deduced based on the probabilistic network model and the physical interference model. Moreover, the routing metric combining interference and routing convergence with residual energies of nodes is constructed, and the relations of the routing metric and the influence factors are discussed. Also, the PNMIR (Probabilistic Network Model based Interference-aware Routing) algorithm is designed, and its correctness and time-space complexity are discussed. Simulation experiments based on the NS2platform show that under the random waypoint mobility model, by simultaneously considering the energy consumption of a packet and average delay, the proposed PNMIR routing algorithm can achieve higher packet delivery ratios in different cases of the pause time and maximum moving speed when compared with the greedy perimeter stateless routing algorithm, which can better meet the needs of the application scenes with higher reliability.(3) To depict the twofold uncertainties, namely, fuzziness and randomness, in quality of service of wireless sensor network, fuzzy number and fuzzy probability are introduced, and the fuzzy random mutli-constrained multipath routing model, which unifiedly describe fuzziness and randomness in the constraints of quality of service, are extended from the mutli-constrained multipath routing model. Furthermore, the linearization of the fuzzy random programming routing model is completed, the FRMCMP (Fuzzy Random Multi-Constrained MultiPath routing) algorithm is designed and its correctness and time-space complexity are analyzed. Simulation results based on the NS2platform show that the proposed algorithm can achieve wider range in terms of on-time packet delivery ratio and average delay, and it can meet the different needs of practical applications for wireless sensor network, because the on-time packet delivery ratio and average delay are flexibly adjusted to different degrees by varing the confidence level.(4) To describe the routing optimization model that has fuzziness and randomness in both objectives and constraints for wireless sensor network, different fuzzy random multi-objective routing models are constructed based on the fuzzy random expected value model and its extension of standard deviation respectively, by combining them with multi-objective optimization theory. The computation methods of expected values and standard deviations of fuzzy random variable and function are discussed, and the HFRG (Hybrid Fuzzy Random Genetic algorithm) and FRMOO (Fuzzy Random Multi-Objective Optimization) routing algorithms are designed for solving problems by embedding fuzzy random simulations into the genetic algorithm based on Pareto sorting. Simulation experiments based on the Matlab platform and the C language show that the above routing algorithms can find multiple optimal paths at a time, possessing flexibility and efficiency. Meahwhile, they can achieve longer network lifetime, reasonable tradeoff in multiple performance metrics and good robustness when compared with the routing algorithms only considering randomness or fuzziness.In this thesis, supported by the National Natural Science Foundation of China entitled "Research on new schemes of data transmission for wireless multimedia sensor networks in uncertain environment"(Grant No.60970054) and "Research on theories and methods of temporal-space dynamics about propogation of malicious code in mobile wirless sensor networks"(Grant No.61173094), several routing models for wireless sensor networks are constructed based on the random uncertainty and fuzzy random uncertainty, the fuzziness and randomness in routing procedure are depicted by adopting the uncertainty theory, and multiple routing algorithms for wireless sensor networks in the uncertain environment are also designed, which enrich and improve the researches on the routing algorithms for wireless sensor networks.