Data Collection Technology By Using A Mobile Sink In Wireless Sensor Network

As a research hotspot, wireless sensor nodes (WSNs) attract a widespread attention. In general, sensor nodes are equipped with batteries, whose energy is limited. In addition, a large number of sensor nodes are deployed in terrible conditions. It is unpractical to recharge the energy for sensor nodes. Therefore, how to utilize energy of sensor nodes efficiently is one of the key issues. In the traditional WSNs, sensor nodes keep static after deployment and a Sink is placed at a particular location in the monitoring area. The sensed data is delivered to the Sink in one or multi-hop. As a result, the sensor nodes close to the Sink node have to act as relays and consume energy quickly, which leads to the Energy-hole problem. Resent researches show that this problem can be solved availably by introducing a mobile sink into WSNs. In this paper, the data collection technology by using a mobile sink is comprehensively researched with considering two cases:mobile sink with limited energy and limited network latency.As a mobile sink is introduced to WSNs, new problems are emerged. Mobile sink directly moves to the location of sensor nodes for data collection, which will produce large network latency; on the other hand, the energy consumption for moving of mobile Sink is far greater than the energy consumption for communication of sensor nodes. However, in many existed researches, the energy consumption of the mobile sink is ignored, which is unpractical. To solve these problems mentioned above, this paper puts forward an algorithm called an energy balanced path planning (EBPP) algorithm for periodic data collection. This algorithm consists of three steps:1) LEACH algorithm and Any Colony Algorithm are respectively used for clustering and rendezvous points initializations; 2) A heuristic path optimization method including building the racetrack and the inner lane, optimizing convex points and concave points, searching for shortcuts and removing redundant substitutes is utilized to further shorten the mobile sink path and reduce network latency; 3) Mobile sink visits each rendezvous point along the calculated path and collect data from these point in one hop. To evaluate the performance of EBPP algorithm, LEACH-TSP is used as a compare. The results show that the EBPP algorithm outperforms LEACH-TSP algorithm in network lifetime and network latency.For delay-sensitive applications, all sensory data must be submitted in the prescribed time. By proposing a rendezvous point selection strategy named WRP based on weight, the network lifetime is improved within a given network delay. In this strategy, mobile sink need to move to the location of rendezvous point for data collection, which can be improved by using the heuristic path optimization mentioned above. Correspondingly, an improved algorithm named IWRP is proposed in this paper. In IWRP, mobile sink moves into communication range of each rendezvous point for data collection. In this way, more rendezvous points can be selected in a given delay and thus the load of each rendezvous point can be alleviated. The simulation results show that the IWRP algorithm attains a longer network lifetime than WRP algorithm.In this paper, the energy efficient path plan algorithm and latency constrained path plan algorithm for mobile sink is theoretically studied. Numerical simulations are conducted to verify our conclusions. Our contributions will provide theoretical support for energy saving data collection application.