A Research For Visual Barrier Coverage Algorithm In WVSN

Wireless Visual Sensor Networks (WVSNs) is constituted by many image-capturingsystem sensors which dispersed in the target area.It can not only provide monitoringfunctions like wireless sensor networks (WSNs) but also capture real-time images ofthe monitored scene, which will be better able to effectively monitor the target area inthis way. This capability has made the barrier coverage of WVSNs an issue of interestto many researchers.The notion of area of coverage can be considered as a measure of the qualityof service in sensor network, it is signifcant to design ef?cient sensor coverage s-trategies that would reduce communication and computation, prolong the lifetime ofthe network. Along with the coverage, the notion of network connectivity is equallyfundamental to a sensor network.Some research of wireless visual protective-barriercoverage problem as follows:(1)To maximize the network lifetime of protective-barrier coverage, we designeda visual protective-barrier coverage routing algorithm to solve visual protection withcoverage.WVSNs are generally deployed by aircraft in some areas which is diffcult toenter for people, so the supply of energy is the most important resource. How tooptimize the allocation of network so that makes useful of power energy effcient-ly is an important challenge for Wireless Sensor Networks to design.Firstly,the sinkcollects all of the information of sensors which deployed in the monitored scene andprocesses those centralized data,thus calculating the optimal confguration of the w-hole network.Secondly It sends back the control messages which will schedule eachsensor sensor by an active or sleep state. The algorithm can also contribute to improvethe perceived service quality and extend the network lifetime.(2) Considering the distributed and self-organizing features of wireless, we pro-posed a distributed optimum algorithm for target protective-barrier coverage.Above the visual protective-barrier coverage routing algorithm is centralized ex-ecuted, in which sink sensor or base station must get all the information of the wholenetwork and becomes the bottleneck of the whole network.Meanwhile, it would in- crease the network flow and increase the energy consumption for the information ofthe network management to be concentrated and dispatched. In order to overcomethese shortcomings of the centralized algorithms, considering the distributed and self-organizing feature of wireless sensor networks, we design a distributed protective-barrier coverage algorithm to solve the wireless visual protective-barrier coverageproblem.The algorithm is divided into two processes, the establishment process of thestart sensor and the candidate selection process.Because there are may be multiplestart sensors,we introduced the concept of the sensor’s greatest contribution to thewhole network and designed a function which converted the sensor’s feld of view intoits horizontal projection to solve the probem.Finally, we designed a distributed visualprotective-barrier coverage algorithm.(3) In view of the network model with adjustable probing direction, we designeda centralized coverage algorithm based on the angle adjustable.Above the two algorithm used fxed direction sensor model. In the direction con-tinuously adjustable sensor model, the sensor’s feld of view can can rotate around thesensor arbitrary.Comparing to the fxed direction model,this continuously adjustablesensor model needn’t re-deploy the sensor sensor and can rotate itself online real-time.In this way,it can regular the coverage area more flexible. Firstly,the algorith-m obtained adjacent sensor information by each sensor sensor communication ra-dius.Then the implementation of the candidate selection process and the decision-making process which depends on the message received. During the implementationof the sensor sensor,the probing direction will be set to form a visual protective-barriercoverage.Finally, the designed algorithms successful rate of constructing a visual protective-barrier coverage problem under different sensor distribution and the both sensor modelis also tested through simulations.