Research On Coverage And Control Algorithm Based On Swarm Intelligence For UWSN

Underwater Wireless Sensor Network(UWSN)has been widely used in environmental monitoring,military security and other fields,which is composed of a large number of underwater nodes as an underwater monitoring system.Also it is one of the hot spots in the governments and scholars.The Research about underwater wireless sensor network involves many aspects,mainly include: location tracking,routing protocols,battery management and node deployment,etc.The coverage control is a basic work in the research of UWSN among them.Excellent coverage control network can guarantee the quality of service in UWSN.At the same time,it has good match and assist for other later study.As a result,designing a kind of efficient coverage control algorithm is of great necessity.According to the focus on the different stage in UWSN coverage control method,it is divided into the early stage how to deploy the nodes and the later stage which designs to maintain network coverage.What's more,coverage control algorithm based on swarm intelligence optimization has the characteristics of simple and effective.According to the existing algorithms,it considers the obstacles in the underwater environment.Then we put forward the following three deployment algorithm:Firstly,according to the characteristics that underwater environment exists obstacles,we put forward a kind of UWSN redeployment algorithm based on wolves search.According to the thought of the wolves in the search to guide mobile nodes,there are mainly three stages,active coverage,passive coverage and avoid obstacles in the moving process.In our algorithm,every node uses the least value to realize the coverage goals.The simulation results show that the algorithm can optimize the network coverage,and it has a function of avoiding obstacles.Secondly,according to the characteristics of large scale and complicated conditions in UWSN deployment,we put forward a kind of fruit flies inspired underwater sensor network deployment algorithm.The algorithm improves the fruit fly optimization.At the same time,it introduces OLPM model and European Starlings flying topology mechanism.It is a multi-objective optimization problem.It improves the coverage and connectivity function under the condition of obstacles.Thirdly,according to the problem of maintaining network coverage in the last of deployment,we design a UWSN dynamic layered double cluster algorithm based on krill swarm optimization.The algorithm adopts the non-uniform clustering method and the dynamic hierarchical mechanism,at the same time,it use the selecting principle of krill herd optimization to choose the optimal main cluster heads and the second optimal cluster heads.Three methods effectively solve the problem of early death of cluster nodes.They also prolong the network life time and decrease the consumption.In conclusion,the above designed three kinds of UWSN coverage control algorithm are happened under the background of underwater obstacle.It also has a practical significance.It uses the simple effectiveness of swarm intelligence optimization algorithm.What's more,it solves deployment of big scale in UWSN to lead to failure of the nodes easily.Three algorithms respectively solve the following problems.First of all,network coverage is optimized by algorithm one,and it avoids obstacles.Then,algorithm two is based on algorithm one.It optimizes the coverage rate,connectivity rate and the energy consumption.It can avoid obstacles.Finally,algorithm three is on the basis of the former two algorithms.It maintains the entire network of the late survival time.Meanwhile,it reduces the energy consumption of cluster heads.