The Research On Energy-Efficient Optimization Of Collaborative Data Gathering With Delay Constraints For Wireless Sensor And Actuator Networks

Abstract:The optimization of energy efficiency has been a key issue in wireless sensor and actuator networks (WSAN). Recent research has indicated that using dynamic topology control and distributed cooperation in WSAN to achieve collaborative data gathering can greatly increase the network energy efficiency. Under the background of heavy bridges and roadbed safety condition monitoring by WSAN, this paper investigates the multi-actuator load balance, path planning of actuators and transmission interference suppression and so on. Reinforcement learning, cooperative communication and game theory are adopted to propose an energy optimization scheme for WSAN with time delay constraints. The main work is as follows:Considering the WSAN applied in heavy bridge and roadbed safety condition monitoring, this paper analyzes the characteristics and problems of energy optimization, and proposes the system framework based on mobile data gathering and cooperative communication interference suppression. Reinforcement Learning is firstly adopted to divide the network into partitions to balance communication and energy load between actuators. Then the dynamic topology with energy sensing is generated in each partition. Based on it, the polling points selection and actuator path planning strategy are proposed. Finally, to suppress the interference from the neighbor nodes, a cooperative communication and game theory based interference suppression strategy is presented in this paper. The proposed scheme will provide an efficient solution for WSAN with low data gathering delay, high energy efficiency and high reliability.A core aim of WSAN is to improve the energy efficiency and to optimize the network life. This paper investigates the load balance of multi-hop data gathering problems and choose polling point of network data. First, a network dynamic spanning tree is constructed based on the residual energy of wireless sensors. Then in-degree priority polling point selection algorithm is proposed with global topology information and communication load based polling point selection algorithm is proposed with local topology information. The selected polling point restricts the number of hops, balancing the energy cost decentraly and regionally as a local network data gathering point.To satisfy the real-time requirements of WSANs, a heuristic actuator path planning algorithm with delay constraints is proposed. The algorithm first converts mobile actuator path planning problem into TSP optimization problem; then considering communication radius of polling point, the Race Search based nearest neighbor heuristic algorithm is adopted to get the optimal actuator movements, which can traverse all the polling points. Finally, the algorithm converts the time-delay constraints into distance constraints, and uses it in iterative process to obtain the optimal actuator path solution. In order to evaluate the performance of our algorithm, this paper proposes linear programming model describing the actuator path planning for actuators in space domain. The1-? optimal algorithm is used to achieve the theoretical optimal solution of mobile data gathering. In addition, Matlab tool is used to assess the effectiveness of our algorithm in large scale WS AN.This paper proposes an online fuzzy Q learning based energy balancing adaptive partition algorithm for multi-actuators. Every actuator is treated as an agent with learning and decision abilities, and is used to obtain the energy and state information of sensors. Then fuzzy reasoning is used to discretize the location and energy state. And Q learning state space and Q function are constructed. Then the partition center location is selected based on the current network energy distribution state. Corresponding Voronoi partition is produced to adaptively adjust the partition.Interference among the adjacent nodes caused by the unexpected data is the significant problem, which impacts the efficiency of the data transmission. A collaborative data transmission mechanism based on interference suppression is proposed. Firstly, the cooperative communication is introduced into WSAN, and the ability of anti-interference can be improved by relay transmission and cooperative interference. Considering the selfishness of the nodes, a spectrum sharing mechanism is introduced to motivate the relay node to participate in the cooperative interference suppression, and the Stackelberg game is used to analyze the process of the cooperative interference suppression. Then, a data transmit method with interference is obtained by solving the equilibrium to select the optimal strategy for cooperative information transmission. The method can suppress the interference among nodes, and can guarantee the fairness and rationality of the cooperative data transmission. The simulation results verify the effectiveness of the proposed algorithm.