王泽东,,
吴大鹏
1.重庆邮电大学通信与信息工程学院 重庆 400065
2.重庆高校市级光通信与网络重点实验室 重庆 400065
3.泛在感知与互联重庆市重点实验室 重庆 400065
基金项目:国家自然科学基金(61771082, 61871062)；重庆市高校创新团队建设计划(CXTDX201601020)
详细信息
作者简介:彭海英：女，1973年生，副教授，研究方向为光无线融合网络
王泽东：男，1993年生，硕士生，研究方向为光无线融合网络
吴大鹏：男，1979年生，教授，博士，研究方向为泛在无线网络、社会计算、互联网服务质量控制等
通讯作者:王泽东 917251201@qq.com
中图分类号:TN926, TP393计量
文章访问数:1857
HTML全文浏览量:909
PDF下载量:28
被引次数:0
出版历程
收稿日期:2019-06-05
修回日期:2020-02-28
网络出版日期:2020-04-09
刊出日期:2020-07-23
Energy Saving Mechanism with Incentive of Offloading Compression in Cloudlet Enhanced Fiber-Wireless Network
Haiying PENG,Zedong WANG,,
Dapeng WU
1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2. Chongqing Key Laboratory of Optical Communication and Networks, Chongqing 400065, China
3. Chongqing Key Laboratory of Ubiquitous Sensing and Networking, Chongqing 400065, China
Funds:The National Natural Science Foundation of China (61771082, 61871062); Chongqing Funded Project of Chongqing University Innovation Team Construction (CXTDX201601020)
摘要
摘要:针对云增强型光纤-无线(FiWi)网络能耗以及卸载的通信开销过大问题，该文提出一种自适应卸载压缩节能机制(ESAOC)，针对不同类型的业务属性和最大的容忍时延，结合光网络单元的负载变化和无线网状网的流量情况，通过统计的方式获得不同优先级卸载数据的平均到达率，再结合各个节点的压缩时延，动态调整业务的卸载压缩比，以降低卸载的通信开销；同时，建立排队模型分析卸载业务在MEC服务器的排队时延，协同调度无线侧中继节点，进而对光网络单元和终端设备进行协同休眠调度，最大化休眠时长，提高系统能源效率。结果表明，所提方法在有效降低整个网络能耗的同时能够保证卸载业务的时延性能。
关键词:光纤-无线网络/
自适应卸载压缩/
协同休眠/
节能
Abstract:In cloudlet enhanced Fiber-Wireless (FiWi) network, there is a problem that energy consumption and communication overhead of offloading are too large. An Energy Saving mechanism with Adaptive Offloading Compression (ESAOC) is proposed. According to the different types of service attributes and the maximum tolerant delay, combined with the load changes of the optical network unit and the traffic of the wireless mesh network, the ratio of the offloading compression of service is dynamically adjusted to reduce the communication overhead of the offloading by the average arrival rate of the offloaded data of different priorities obtained by means of statistical methods and combined with the delay of compression of each node. At the same time, a queuing model is established to analyze the delay of the offloading service in the MEC server and cooperatively schedule the relay node in wireless mesh network, thereby performing the schedule of collaborative sleeping on the optical network units and the terminal devices to maximize the duration of sleeping and improving the energy efficiency of system. The results show that the proposed mechanism can effectively reduce the network energy consumption while ensuring the delay performance of offloading service.
Key words:Fiber-Wireless (FiWi) network/
Adaptive offloading compression/
Collaborative sleep/
Energy saving
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