Research And Implementation Of Energy-efficient Routing Protocol Based On Particle Swarm Clustering Algorithm For WSN

Wireless sensor network is a new information acquisition platform based on multi-disciplinary including wireless communications, Micro-Electro-Mechanical Systems, System on a chip and low-power embedded technology, which is typically used to detect and monitor various types of objects in real-time monitoring area, and transmits the data to the sink node after gathering data from other sensor nodes.Wireless sensor network consists of large number of sensor nodes which are small in size, cheap, low energy. As the network deployment area is usually complex, the battery of sensors is not always rechargeable after deployment. Due to cost, size and other restrictions, the ways to provide energy (such as the use of solar energy) or to reduce power consumption of nodes are difficult to achieve, so the feasible method for saving energy is to improve network routing protocols and to optimize the network topology structure.This thesis presents an energy-efficient routing protocol based on particle swarm clustering algorithm for WSN, which makes improvements mainly from the following two aspects. First, network clustering is a kind of NP problem to optimize the network topology partitioning, and particle swarm algorithm can effectively solve this problem, but the convergence speed of the particle swarm algorithm is slower. To address the issues above, this thesis introduces the strategies of adaptive inertia weight based on different dimensions and different particles to effectively accelerate the convergence speed of the particle swarm optimization. In this thesis, a clustering algorithm based on the improved particle swarm optimization is proposed, which takes the remaining energy of nodes, the distribution within a cluster and the distribution among clusters into consideration. Second, a single hop and multi-hop dynamic and self-adaptive routing algorithm is designed in order to avoid long-distance communications between cluster heads and the sink node, which adopts the "threshold detection" mechanism to reduce cluster heads load near sink node, and it effectively reduces the energy consumption of cluster heads close to the sink node. Finally, the thesis combines the improved particle swarm clustering algorithm with the inter-clusters routing algorithm to form an adaptive energy-efficient cluster-routing protocol, referred to as AECRP.This thesis gives a detailed description about AECRP routing protocol and carries out some simulation comparison experiments under the same scene between AECRP protocol and LEACH protocol in OMNeT++network simulation platform. The results show that the clustering routing protocol not only balances the overall network energy consumption, delays dead time of the sensor node, but also provides more reliable data delivery, sends more data to the sink node, under the premise of the sacrifice acceptable convergence speed.