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In this paper, we propose an automatic load-balanced partitioning strategy for parallel multilevel fast multipole algorithm(MLFMA) based on distributed-memory architectures to solve the large scale electromagnetic scattering problems. We focus on the automatic load-balancing partitioning strategy because that our original scheme requires that users input the transition level, which is usually determined on the users’ experience and sometimes lead to a bad load-balancing partition. By introducing the automatic load-balancing algorithm to our pervious partitioning technique, our implementation can automatically achieve the best load-balancing and consequently attain better parallel efficiency. To present the effectiveness of the new strategy, we analyze results of the previous implementation according to different inputs of transition level and compare them with the result of implementation using the new algorithm.

Internet of things applications using RFID sensors are a challenging task due to the limited capacity of batteries. Thus, energy efficient updating and maintenance have become more critical design with RFID sensor network. This paper is dedicated to combine energy harvesting and maintenance, sensor network, and resource discovery to develop a rechargeable sensor energy maintenance scheme. To deal with key sensor nodes and low energy path maintenance, the proposed approach consists of the following:(1)key point energy maintenance for RFID sensor through multi-path similarity analysis;(2)path energy maintenance for RFID sink through energy resource discovery. Use case application and simulation results show that the proposed methods reduce key sensor nodes energy maintenance time and energy maintenance path length for sensor nodes energy updating and maintenance.

In this paper,ant colony system(ACS)is applied to the dynamic service selection.We design the novel pheromone update rule and the path length between the service node is generated by the QoS parameters of the services. The optimal path in ACS is correspond to a set of optimal QoS parameters composition of services. When the QoS parameters of services are changed, the parameters of ACS will be changed automatically during the process of finding the shortest path. That will improve the reliability of the service selection.