计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 240-246.doi: 10.11896/jsjkx.190900054
王妍1,2, 韩笑1, 曾辉1, 刘荆欣1, 夏长清2,3,4
WANG Yan1,2, HAN Xiao1, ZENG Hui1, LIU Jing-xin1, XIA Chang-qing2,3,4
摘要: 随着物联网、大数据和5G网络的快速发展及应用,传统的云计算模式已无法高效处理网络边缘设备所产生的海量计算任务,边缘计算应运而生。边缘计算环境下,计算任务将被迁移到接近数据源的计算设备上执行,这为拓展终端节点资源以及缓解云中心负载提供了新的解决方案。现有的任务迁移决策均是在任务迁移节点确定的前提下制定的,并未考虑存在多个任务迁移节点可选的情景,而边缘计算下任务迁移节点的选择直接影响着任务迁移的服务质量,因此文中构建了服务质量可信模型,分别从时间可信、行为可信、资源可信3个维度对任务迁移节点进行评价。为了解决任务迁移节点数量巨大带来的选择效率低的问题,采用基于聚类编码的skyline查询算法对任务迁移节点进行筛选,并利用灰色关联分析法进行任务迁移节点的最终选择。实验结果表明,所提基于服务质量可信的任务迁移节点选择策略的任务迁移成功率平均提高了36%,任务完成吞吐量平均提高了18%。
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[1]SHI W S,ZHANG X Z,WANG Y F,et al.Edge Coputing:State-of-the-Art and Future Directions[J].Journal of Computer Reaserch and Development,2019,56(1):69-89. [2]WANG B,LI B,HUI L.Oruta:privacy-preserving public auditing for shared data in the cloud[J].IEEE Transactions on Cloud Computing,2014,2(1):43-56. [3]SHI W S,SUN H,CAO J,et al.Edge Coputing:An Emerging Computing Model for the Internet of Everything Era[J].Journal of Computer Reaserch and Development,2017,54(5):907-924. [4]LV H Z,CHEN D,FAN B,et al.Standardization Progress and Case Analysis of Edge Computing[J].Journal of Computer Reaserch and Development,2018,55(3):487-511. [5]SATYANARAYANAN M,ZHUO C,HA K,et al.Cloudlets:at the leading edge of mobile-cloud convergence[C]//International Conference on Mobile Computing.2014:1-9. [6]GOSAIN A,BERMAN M,BRINN M,et al.Enabling Campus Edge Computing Using GENI Racks and Mobile Resources[C]//2016 IEEE/ACM Symposium on Edge Computing (SEC).ACM,2016:41-50. [7]NASTIC S,TRUONG H L,DUSTDAR S.A Middleware Infrastructure for Utility-Based Provisioning of IoT Cloud Systems[C]//Edge Computing.IEEE,2016:28-40. [8]ESPOSITO C,CASTIGLIONE A,POP F,et al.Challenges of Connecting Edge and Cloud Computing:A Security and Forensic Perspective[J].IEEE Cloud Computing,2017,4(2):13-17. [9]YANG K,JIA X,REN K,et al.DAC-MACS:Effective Data Ac-cess Control for Multiauthority Cloud Storage Systems[J].IEEE Transactions on Information Forensics & Security,2013,8(11):1790-1801. [10]ROMAN R,LOPEZ J,MAMBO M.Mobile edge computing,Fog et al.A survey and analysis of security threats and challenges[J].arXiv:1602.00484,2016. [11]JIA M,CAO J,YANG L.Heuristic offloading of concurrenttasks for computation-intensive applications in mobile cloud computing[C]//Computer Communications Workshops.IEEE,2014:352-357. [12]HUANG D,WANG P,NIYATO D.A Dynamic Offloading Algorithm for Mobile Computing[J].IEEE Transactions on Wireless Communications,2012,11(6):1991-1995. [13]MAO Y,ZHANG J,LETAIEF K B.Dynamic Computation Offloading for Mobile-Edge Computing with Energy Harvesting Devices[J].arXiv:1605.05488,2016. [14]DENG X N,GUSN P Y,WAN Z W,et al.Integrated Trust Based Resource Cooperation in Edge Computing[J].Journal of Computer Reaserch and Development,2018,55(3):449-477. [15]BÖRZSÖNYI S,KOSSMANN D,STOCKER K.The SkylineOperator[C]//International Conference on Data Engineering.2002. [16]LI Y Y,LI Z Y,DONG M X,et al.Efficient subspace skyline query based on user preference using MapReduce[J].Ad Hoc Networks,2015,35:105-115. [17]YAN W,ZHAN S,WANG J,et al.Skyline Preference Query Based on Massive and Incomplete Dataset[J].IEEE Access,2017,5(99):3183-3192. [18]LI N,DAS S K.A trust-based framework for data forwarding inopportunistic networks[J].Ad Hoc Networks,2013,11(4):1497-1509. [19]AHRENHOLZ J.Comparision of CORE network emulationplatforms[C]//Proc of MILCOM 2010.Piscataway,NJ:IEEE,2010:166-171. [20]FIGUEROA M,UTTECHT K,ROSENBERG J.A SOUND approach to security in mobile and cloud-oriented environments[C]//IEEE International Symposium on Technologies for Homeland Security.2015:147-156. |
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