Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challe...Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.展开更多
传统边缘分布式存储系统中网络配置繁琐,优化网络所需的网络状态信息测量操作开销大,当终端设备对数据存储和检索的业务需求处于高峰时,会导致网络链路负载过重从而影响数据转发传输的性能。此外,现有分布式存储系统在进行数据的存储节...传统边缘分布式存储系统中网络配置繁琐,优化网络所需的网络状态信息测量操作开销大,当终端设备对数据存储和检索的业务需求处于高峰时,会导致网络链路负载过重从而影响数据转发传输的性能。此外,现有分布式存储系统在进行数据的存储节点选择时,只考虑了节点剩余存储空间,没有考虑网络状态和节点自身负载对系统存储性能的影响。为解决上述问题,设计和实现了一种基于软件定义网络(Software Defined Network,SDN)和无人机辅助的边缘分布式存储系统,利用SDN技术测量网络状态、网络节点自身负载和存储节点负载状态信息,通过无人机移动节点飞行到重负载网络节点的上方进行分流以平衡各条链路的流量负载;对于重负载网络节点和存储节点的选择,提出了一种基于多属性决策模型综合考虑网络状态和节点自身负载状态的节点选择算法,选择出重负载网络节点和合适的存储节点,然后通过对无人机的位置部署,实现网络链路流量的分流,平衡网络链路的流量负载。经实验测试,结果显示在无线Mesh网络拓扑中,所提无线边缘分布式存储系统的存储性能优于现有边缘分布式存储系统,存储时间明显缩短,在增加流量负载的情况下依然可以保持良好的存储性能,具有良好的负载均衡性能。展开更多
基金supported by the National Natural Science Foundation of China(6102100161133015+4 种基金61171065)the National Natural Science Foundation of China(973 Program)(2013CB329001)the National High Technology ResearchDevelopment Program(863 Program)(2013AA0106052013AA013500)
文摘Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.
文摘传统边缘分布式存储系统中网络配置繁琐,优化网络所需的网络状态信息测量操作开销大,当终端设备对数据存储和检索的业务需求处于高峰时,会导致网络链路负载过重从而影响数据转发传输的性能。此外,现有分布式存储系统在进行数据的存储节点选择时,只考虑了节点剩余存储空间,没有考虑网络状态和节点自身负载对系统存储性能的影响。为解决上述问题,设计和实现了一种基于软件定义网络(Software Defined Network,SDN)和无人机辅助的边缘分布式存储系统,利用SDN技术测量网络状态、网络节点自身负载和存储节点负载状态信息,通过无人机移动节点飞行到重负载网络节点的上方进行分流以平衡各条链路的流量负载;对于重负载网络节点和存储节点的选择,提出了一种基于多属性决策模型综合考虑网络状态和节点自身负载状态的节点选择算法,选择出重负载网络节点和合适的存储节点,然后通过对无人机的位置部署,实现网络链路流量的分流,平衡网络链路的流量负载。经实验测试,结果显示在无线Mesh网络拓扑中,所提无线边缘分布式存储系统的存储性能优于现有边缘分布式存储系统,存储时间明显缩短,在增加流量负载的情况下依然可以保持良好的存储性能,具有良好的负载均衡性能。
