Research On Sensors Deployed Optimization Theory And Method For Reliable Sensing In Internet Of Things

All kinds of data are obtained from physical world in Internet of things. These data are the object sources of a variety of applications and services in Internet of things. Due to sensor nodes performance, deployment costs as well as a variety of factors such as physical environment, it resulted in reliable sense differently. And nodes deployment optimization can improve the sense reliability of monitoring area. Most of the current research on deployment issues assumed that the ideal model or static sense scenario. In fact, there are many types of complex scenario applications in Internet of things. Some idealized assumptions limit of the practical application of these methods. And it can expand application range of Internet of things that researches of deployment optimized and deployment maintenance mechanism of dynamic event area. It is become the IoT deployment sense research hot spot in recent years. This paper focus on random events. As dynamic deployment optimization goal, it has systematically studied some important problems about sense nodes deployment optimization and maintenance mechanism. The main content is included two parts:nodes deployment strategy for reliable sense and nodes deployment maintenance mechanism. Former researches focus on heterogeneous nodes deployment of event area and barrier deployment of dynamic area. The deployment maintenance mechanism focus on sense hole recognized and hole repaired. In this paper, the main research contents and innovation points are as follows:1. Sparse deployment optimization on priority event based for reliable sense. At present, study in sense nodes deployment mostly focuses on coverage area of sense nodes maximized. Usually, sense quality of event area lacked to considering. In this paper, it assumed some sensor deployed in a large area. It just realized sparse deployment. Reliable sense is the optimization goal. According to the priority of the random events area distribution, it proved to maximize sense reliability condition in mathematics. Then it designed a distributed algorithm that realized sensor nodes position relocated. It can realize nodes deployment optimized and reliable sense of event area.2. Barrier deployment optimization algorithm for dynamic events area. Barrier deployment aimed at the target area boundary monitor for external intruders and internal escaped. Mostly traditional researches focus on static target boundary barrier covered deployment. And in many practical applications, the target boundary and overall is dynamic variation and mobile. Sensor nodes need to be quickly deployed to the target boundary and be able to quickly track changes of dynamic target. This paper studied barrier deployment optimization method which combined with intelligent fish algorithm. A mobile barrier deployment optimization algorithm is presented. It can quickly find the event area boundary and form an enclosed barrier to respond to movement and changed of event area. Some experimental results are showed this algorithm has smaller delay, shorter overall mobile node distance.3. Sense hole recognized method in IoT. There is some sense holes caused to sense nodes random deployed and nodes energy exhausted, damaged to exit, etc. It will influence the monitoring performance of IoT. How to identify sense holes is the prerequisite of optimization of network deployment. Most current sensing coverage holes recognized methods are based on the assume node precise location known. It limited in range of practical applications larger. We proposed a distributed coverage hole recognize method. It can quickly identify the network topology structure based on neighbor topology relation. Then based on the theory of triangle covered and discriminate method of Hamiltonian graph, it can recognize sense coverage holes. Finally, algorithms performance has compared by simulation analysis. It shown that proposed distributed algorithm be able to quickly and effectively recognize sense coverage holes in area.4. Sense hole repaired methods on mixed nodes deployment. Based on the front research of sense hole recognition, how to repair sense hole is another important issue in deployed maintenance mechanism. A repaired sense holes by mobile nodes is currently more feasible method. It assumed that mobile nodes and static nodes mixed in monitoring area. And the node sensing radius is under heterogeneous. It studied how to cover sense hole by mobile nodes relocation. It realized both mobile distance or energy consumption minimum and the coverage maximum. It is a NP-hard problem that mobile nodes moved to sense hole. It combined with genetic algorithm to solve the optimal problem. Simulation experiments showed that the proposed algorithm effectively balanced nodes energy consumption and sensing coverage.Finally it has taken a summary, and discussed next works.