Study On Coverage Algorithms For Heterogeneous Wireless Sensor Network

Wireless sensor networks(WSN) consist of low-cost, low-power tiny sensor nodes that can communicate with each other to perform sensing and data processing cooperatively. Integrated MEMS, wireless communication, sensing technology, embedded computing, distributed information processing and other technologies, WSN is an emerging research direction. Compared with the traditional networks, WSN is a data-centric wireless network with good self-organizing self-regulating and robust characteristics, and can be widely used in military, environmental science, health care, space exploration and many other kinds of commercial applications. How to choose coverage sehemes for different applications are the fundamental issues in wireless sensor networks. The coverage control schemes direct affect the energy-efficieney, communication-bandwidth and proeess-ability which are all limited in WSN. They also determine the improvement of the QoS of apperception, surveillance, sense and communication in WSN.Most of typical coverage protocols and algorithms for WSN may not be well-suited for the unique features of heterogeneous wireless sensor network(HWSN) and application requirements such as geographical irregularity of the sensed events. Due to these limitations, based on optimization theory, coverage of the HWSN research is carried out from two aspects in this thesis: the static sensor network and the mobile sensor network. The important research results are as follows:â‘ A optimal heterogeneous sensor differentiated deployment schemes based on simulated annealing algorithm is proposed to solve the problems of the high density of distributing heterogeneity nodes in WSN and geographical irregularity of the sensed event. The algorithm uses the cost of sensors deployment as objective function in the context of assuring the coverage and fault tolerant of networks. Finally, simulation results demonstrated that the proposed approach is suitable for solving deployment problems of HWSN. Compare with results from the software LINGO, the discrepancy between the results from the proposed method and LINGO software is decreasing, the proposed method spends less time and has better ability of convergence .â‘¡To the objectives of guaranteeing coverage of sensors, satisfaction of detection thresholds, and least energy consumption, a multi-objective differential evolution algorithm is proposed to solve HWSN sensor deployment in the observed area which is characterized by the geographical irregularity of the sensed events. In this algorithm, maximin fitness function is used to converge toward the Pareto optimal solutions. This function is designed to achieve both diversity and closeness to the universal Pareto front in multi-objective genetic algorithms without having to employ niche induction techniques. Thus the optimal heterogeneous sensor placement is obtained. The experimental results demonstrated that the proposed approach is suitable for solving deployment problems of HWSN. Simulation results have demonstrated that the proposed method is of high convergence speed, has good performance and flexibility.â‘¢A dynamic sensor deployment strategy for heterogeneous mobile wireless sensor networks is proposed, so-called virtual force-directed differential evolution algorithm (VFDE). To ensure efficient coverage of networks, VFDE combines the virtual force(VF) with differential evolution algorithm (DE), where the position vector of each population is updated according to not only the historical local and global optimal solutions but also the virtual forces of sensor nodes. The key motivation of this strategy is to use the virtual force to direct the updating of DE for improving the convergence speed, and DE is used to enhance the global searching ability. Simulation results demononstrate that VFDE has better perfomance on regional convergence and global searching than VF algorithm and DE algorithm, and it can implement dynamic heterogeneous mobile sensor deployment efficiently and rapidly.â‘£A optimal heterogeneous sensor node scheduling schemes based on weighted multiple coverage algorithm is proposed to solve the problems of different point coverage requirements in the area coverage. The algorithm uses the efficient coverage of sensors as objective function in the context of different qualities of coverage for different points of interest(POI) while satisfying the area coverage and sensor energy. Using of improved differential evolution algorithm to exchange the sensor status in the network, the proposed node scheduling scheme can enhance the network coverage performance and reduce the energy consumption. Simulation results demonstrate the effectiveness of the proposed approach. While satisfying special POI coverage requirement, it can also provide the maximum coverage for the area. Comparing with random scheduling algorithm, the proposed approach has higher coverage rate and energy efficiency.