Research And Improvement Of Clustering Routing Algorithms For Wireless Sensor Networks

Wireless Sensor Network (WSN) is a kind of large-scale and infrastructure-lesswireless network, which is consisted of hundreds of tiny and cheap sensor nodes. WSNhas a broad application prospects in the military, environmental monitoring, medicalcare, etc. However, due to hardware limitation, energy of a sensor node is quiteconstrained, and it is costly to recharge. Wireless communication consumes mostenergy of a sensor node, so one efficient way to prolong the network lifetime is toimprove wireless communication efficiency.This dissertation researches into the mechanism of classical clustering routingalgorithm LEACH. LEACH uses random probability rotation to choose cluster heads,yet has deficiencies like unbalanced cluster-head distribution, rebounded amount ofcluster-heads, and ignorance of residual energy of sensor nodes. Cluster-head rangeadaptive adjustment clustering routing (CRACR) algorithm is proposed to solve thoseproblems. Firstly, node’s residual energy is introduced in as weight factor whilechoosing cluster-heads, thus node with more residual energy has higher probability tobe cluster-head. Secondly, adaptively control the communication range of broadcastpacket when a sensor node becomes cluster-head, this can ensure the amount ofcluster-head produced is near optimized. Finally, cluster-heads assign time slotaccording to the position and residual energy of nodes.In multi-hop clustering routing algorithm for WSN, nodes close to base station dieover quick for heavy traffic load, which is also call “hot spot” problem. A hopoptimized unequal clustering routing (HOUCR) algorithm for wireless sensor networksis proposed to solve “hot spot” problem in multi-hop routing. Firstly, HOUCRestablishes the relationship between distance and hop. Then routing path based onoptimal hop counts is created to reduce network energy consumption in each round.Secondly, HOUCR forms unequal cluster to realize energy balance and solves the “hopspot” problem.At last, CRACR and HOUCR are compared to LEACH using MATLABrespectively. Simulation results show that: CRACR outperforms LEACH at least55percent when the first node dies, that is to say, CRACR can generate optimized numberof cluster-heads and distribute more evenly; HOUCR outperforms LEACH at least150 percent when the first node dies, HOUCR solves the “hot spot” problem successfullyand reduces energy consumption in each round, thus prolongs the network lifetime.