提出了一种新的粒子群优化方法――融合近邻交互的粒子群优化算法(Particle Swarm Optimization Combined with Near Neighbor Interaction,NNI_PSO).NNI_PSO在PSO算法的速度更新公式中增加了近邻交互部分,并结合"优胜劣汰",...提出了一种新的粒子群优化方法――融合近邻交互的粒子群优化算法(Particle Swarm Optimization Combined with Near Neighbor Interaction,NNI_PSO).NNI_PSO在PSO算法的速度更新公式中增加了近邻交互部分,并结合"优胜劣汰",引入动态邻域结构和惯性权值非线性变化.近邻交互有利于粒子快速向全局最优移动,"优胜劣汰"有利于维持种群多样性.将NNI_PSO应用于PSO领域五个著名的基准测试函数,并与其它两个著名的PSO改进算法对比,实验结果证明NNI_PSO在收敛速度和解的精度方面均有明显优势.NNI_PSO不仅提高了PSO算法执行的时间性能,而且有效地缓解了早熟收敛问题.展开更多
Considering that modern mobile terminals possess the capability to detect users' proximity,and offer means to directly communicate and share content with the people in close area,Device-to-Device(D2D) based Proxim...Considering that modern mobile terminals possess the capability to detect users' proximity,and offer means to directly communicate and share content with the people in close area,Device-to-Device(D2D) based Proximity Services(ProSe) have recently witnessed great development,which enable users to seek for and utilize relevant value in their physical proximity,and are capable to create numerous new mobile service opportunities.However,without a breakthrough in battery technology,the energy will be the biggest limitation for ProSe.Through incorporating the features of ProSe(D2D communication technologies,abundant built-in sensors,localization-dependent,and context-aware,etc.),this paper thoroughly investigates the energy-efficient architecture and technologies for ProSe from the following four aspects:underlying networking technology,localization,application and architecture features,context-aware and user interactions.Besides exploring specific energy-efficient schemes pertaining to each aspect,this paper offers a perspective for research and applications.In brief,through classifying,summarizing and optimizing the multiple efforts on studying,modeling and reducing energy consumption for ProSe on mobile devices,the paper would provide guide for developers to build energy-efficient ProSe.展开更多
文摘提出了一种新的粒子群优化方法――融合近邻交互的粒子群优化算法(Particle Swarm Optimization Combined with Near Neighbor Interaction,NNI_PSO).NNI_PSO在PSO算法的速度更新公式中增加了近邻交互部分,并结合"优胜劣汰",引入动态邻域结构和惯性权值非线性变化.近邻交互有利于粒子快速向全局最优移动,"优胜劣汰"有利于维持种群多样性.将NNI_PSO应用于PSO领域五个著名的基准测试函数,并与其它两个著名的PSO改进算法对比,实验结果证明NNI_PSO在收敛速度和解的精度方面均有明显优势.NNI_PSO不仅提高了PSO算法执行的时间性能,而且有效地缓解了早熟收敛问题.
基金supported by the National Natural Science Foundation of China under Grant 61171092the JiangSu Educational Bureau Project under Grant 14KJA510004Prospective Research Project on Future Networks(JiangSu Future Networks Innovation Institute)
文摘Considering that modern mobile terminals possess the capability to detect users' proximity,and offer means to directly communicate and share content with the people in close area,Device-to-Device(D2D) based Proximity Services(ProSe) have recently witnessed great development,which enable users to seek for and utilize relevant value in their physical proximity,and are capable to create numerous new mobile service opportunities.However,without a breakthrough in battery technology,the energy will be the biggest limitation for ProSe.Through incorporating the features of ProSe(D2D communication technologies,abundant built-in sensors,localization-dependent,and context-aware,etc.),this paper thoroughly investigates the energy-efficient architecture and technologies for ProSe from the following four aspects:underlying networking technology,localization,application and architecture features,context-aware and user interactions.Besides exploring specific energy-efficient schemes pertaining to each aspect,this paper offers a perspective for research and applications.In brief,through classifying,summarizing and optimizing the multiple efforts on studying,modeling and reducing energy consumption for ProSe on mobile devices,the paper would provide guide for developers to build energy-efficient ProSe.
