Energy harvesting technologies allow wireless devices to be recharged by the surrounding environment, providing wireless sensor networks (WSNs) with higher performance and longer lifetime. However, directly building a...Energy harvesting technologies allow wireless devices to be recharged by the surrounding environment, providing wireless sensor networks (WSNs) with higher performance and longer lifetime. However, directly building a wireless sensor network with energy harvesting nodes is very costly. A compromise is upgrading existing networks with energy harvesting technologies. In this paper, we focus on prolonging the lifetime of WSNs with the help of energy harvesting relays (EHRs). EHRs are responsible for forwarding data for sensor nodes, allowing them to become terminals and thus extending their lifetime. We aim to deploy a minimum number of relays covering the whole network. As EHRs have several special properties such as the energy harvesting and depletion rate, it brings great research challenges to seek an optimal deployment strategy. To this end, we propose an approximation algorithm named Effective Relay Deployment Algorithm, which can be divided into two phases: disk covering and connector insertion using the partitioning technique and the Steinerization technique, respectively. Based on probabilistic analysis, we further optimize the performance ratio of our algorithm to (5 + 6/K) where K is an integer denoting the side length of a cell after partitioning. Our extensive simulation results show that our algorithm can reduce the number of EHRs to be deployed by up to 45% compared with previous work and thus validate the efficiency and effectiveness of our solution.展开更多
To fully exploit the performance benefits of relay station （RS）, in the two-hop cellular networks covering hotspots, when the number of RSs is predetermined, both RS deployment and frequency reuse scheme are jointly...To fully exploit the performance benefits of relay station （RS）, in the two-hop cellular networks covering hotspots, when the number of RSs is predetermined, both RS deployment and frequency reuse scheme are jointly optimized for the purpose of maximizing the system capacity based on the constraints of system demand of capacity and the maximum number of outage demand nodes （MNDN）. Further, considering the overhead of increasing RSs, it is desired to use minimum number of RSs. The joint RS deployment and frequency reuse scheme （JRDFR） problem is formulated into a mixed integer nonlinear programming, which is non-deterministic polynomial-time hard in general. A heuristic approach based on genetic algorithm is proposed to tackle the JRDFR problem. The computational experiment of the heuristic approach is achieved and optimized RS deployment and frequency reuse scheme is obtained. Finally, we discuss the impacts of MNDN and the number of RSs on the system performance.展开更多
基金This work was supported by the Key-Area Research and Development Program of Guangdong Province of China under Grant No.2020B0101390001the Shanghai Municipal Science and Technology Major Project of China under Grant No.2021SHZDZX0102+1 种基金the National Natural Science Foundation of China under Grant No.62072228the Fundamental Research Funds for the Central Universities of China,the Collaborative Innovation Center of Novel Software Technology and Industrialization of Jiangsu Province of China,and the Jiangsu Innovation and Entrepreneurship(Shuangchuang)Program of China.
文摘Energy harvesting technologies allow wireless devices to be recharged by the surrounding environment, providing wireless sensor networks (WSNs) with higher performance and longer lifetime. However, directly building a wireless sensor network with energy harvesting nodes is very costly. A compromise is upgrading existing networks with energy harvesting technologies. In this paper, we focus on prolonging the lifetime of WSNs with the help of energy harvesting relays (EHRs). EHRs are responsible for forwarding data for sensor nodes, allowing them to become terminals and thus extending their lifetime. We aim to deploy a minimum number of relays covering the whole network. As EHRs have several special properties such as the energy harvesting and depletion rate, it brings great research challenges to seek an optimal deployment strategy. To this end, we propose an approximation algorithm named Effective Relay Deployment Algorithm, which can be divided into two phases: disk covering and connector insertion using the partitioning technique and the Steinerization technique, respectively. Based on probabilistic analysis, we further optimize the performance ratio of our algorithm to (5 + 6/K) where K is an integer denoting the side length of a cell after partitioning. Our extensive simulation results show that our algorithm can reduce the number of EHRs to be deployed by up to 45% compared with previous work and thus validate the efficiency and effectiveness of our solution.
文摘To fully exploit the performance benefits of relay station （RS）, in the two-hop cellular networks covering hotspots, when the number of RSs is predetermined, both RS deployment and frequency reuse scheme are jointly optimized for the purpose of maximizing the system capacity based on the constraints of system demand of capacity and the maximum number of outage demand nodes （MNDN）. Further, considering the overhead of increasing RSs, it is desired to use minimum number of RSs. The joint RS deployment and frequency reuse scheme （JRDFR） problem is formulated into a mixed integer nonlinear programming, which is non-deterministic polynomial-time hard in general. A heuristic approach based on genetic algorithm is proposed to tackle the JRDFR problem. The computational experiment of the heuristic approach is achieved and optimized RS deployment and frequency reuse scheme is obtained. Finally, we discuss the impacts of MNDN and the number of RSs on the system performance.
