Research On Sensing Utility Driven Joint Charging Scheduling For Directional Sensors

In recent years,wireless power transfer technology has been developed rapidly,which provides a solution to the energy shortage problem of wireless sensor networks.In wireless rechargeable sensor networks,the use of wireless power transfer technology to replenish energy for sensors can realize the long-term stable operation of the network,which has been widely concerned by the academia.Some scholars have studied the charging scheduling problem to improve the sensing utility of the network,but the state-of-the-art methods ignored the impact of the sensor orientations on sensing performance.The appropriate sensing orientations can make the sensor perform at its best and improve the sensing quality.In order to improve sensing utility,this thesis studies the sensing utility driven joint scheduling problem of directional sensors and chargers based on the sensing model of directional sensor.The main contributions are as follows:（1）The sensing utility driven joint scheduling for static chargers is studied.The problem is to determine the sensors’sensing orientations,sensing duration,and the active duration of each charger under the given number of charging time slots.The problem studied can be decoupled into sensing scheduling problem and charging scheduling problem.For sensing scheduling problems,continuous and infinite sensing orientation space problem need to be solved.In this thesis,a polynomial time algorithm is proposed to find all the coverage of point of interests and corresponding optimal sensing orientation.Then,an approximate algorithm is proposed to solve the sensing scheduling problem.After that,the charging scheduling problem is transformed into a submodular function maximization problem with cardinality constraint.The proposed joint scheduling scheme can obtain the approximate ratio of ₂¹（1-_e¹）.The extensive simulations and field experiments confirm the effectiveness of our algorithm,which can improve the sensing utility by at least 20.4%compared with baseline algorithms.（2）The sensing utility driven joint scheduling for route selection of mobile charger is studied.Under the pre-planned charging routes,part of the routes needs to be selected to deploy mobile chargers,meanwhile,the sensing scheduling of sensors needs to be determined.By decoupling the problem,the sensing scheduling can be solved using the solution in the previous problem.For the charging route selection problem,it is necessary to select the routes under the constraint of the number of chargers.The problem is transformed into the submodular function maximization problem with the partition matroid constraint,and an ₄¹-approximation algorithm based on greedy strategy is proposed.In order to verify the superiority of the proposed algorithm,the extensive simulation experiments are conducted in this thesis.The results show that the sensing utility of our proposed algorithm is at least 13.1%higher than that of baseline algorithms.