A Study On Coverage Problem In Mobile Perceptive Network

A perceptive network which consists of a plenty of sensor nodes,can cover and monitor objects,collect sensing data,and help human to improve the ability of information acquisition.Perceptive network has many potential applications in different fields,such as military surveillance,environmental monitoring,smart home,agricultural production and so on.Recently,with the development of micro-electro-mechanical technologies and embedded systems,mobile sensors and smart mobile devices become more and more popular.Correspondingly,mobile sensor network(MSN)and mobile crowdsensing network(MCSN)have attracted a lot of attention.In MSN,mobile sensors can be used to sweep targets,heal coverage hole,maintain connectivity and so on.They can play an irreplaceable role in the network.In MCSN,we can monitor objects by the sensors embedded in the mobile devices of users,and finish sensing tasks with the cooperation of many mobile users.This paper collectively refers to both MSN and MCSN as mobile perceptive network(MPN).In MPN,the coverage problem studies how to appropriately schedule the sensing devices to efficiently cover and sense the objects.This is a significant problem which can determine network performance and energy efficiency of sensors.Mainly based on approximation technique,this paper studies coverage problem in MPN under different circumstances.The specific research problems are listed as follows.1.Target coverage problem in MSN.When it is impossible to deploy the sensors directly,we can send mobile sensors from different stations to the surveillance region.The scheduling of mobile sensors determines the moving distance and consumed energy of sensors.Based on partition and shifting technique,this paper proposes an approximation to minimize the total moving distance of all sensors.2.Sweep coverage problem in MSN.When we do not have enough sensors,we can use mobile sensors to sweep around the targets and cover the targets periodically.The grouping of targets and the scheduling of mobile sensors determine network life-time and energy efficiency of sensors.Considering the impact of sensing range,this paper proposes algorithms based on binary search and greedy technique to optimize the sensor route.3.Route coverage problem in MCSN.After the users set the destination and the arrival time limit,they may hope to process sensing tasks in their own way and try to select a route to maximize the reward.Considering the budget of users and adopting temporal-spatial task model,this paper designs an approximation based on topological sorting and dynamic programming technique,which can recommend the route with maximum reward.4.Balanced coverage problem in MCSN.In order to improve the user experience,when the platform allocates sensing tasks,it may hope to distribute resources consumption uniformly and balance the load of different user devices.Considering the situation where the cost of a task can be different for different users,this paper proposes three algorithms based on dynamic programming,linear programming with combinatorial rounding,and local search technique,which balance the load of user devices.In summary,this paper provides effective solutions for coverage problem in MPN,which have both theoretical significance and technical value for improvement of network performance.