基于SkipNet支持多属性范围查询的云资源共享设计

doi:10.11772/j.issn.1001-9081.2016.01.0072

计算机应用 ›› 2016, Vol. 36 ›› Issue (1): 72-76.DOI: 10.11772/j.issn.1001-9081.2016.01.0072

基于SkipNet支持多属性范围查询的云资源共享设计

孙利华¹, 陈世平^1,2

1. 上海理工大学光电信息与计算机工程学院, 上海 200093;
2. 上海理工大学信息化办公室, 上海 200093

收稿日期:2015-07-03 修回日期:2015-09-15 出版日期:2016-01-10 发布日期:2016-01-09
通讯作者: 孙利华(1990-),女,四川绵阳人,硕士研究生,主要研究方向:对等网络、云计算
作者简介:陈世平(1964-),男,浙江绍兴人,教授,博士,主要研究方向:计算机网络、分布式计算、云计算。
基金资助:
国家自然科学基金资助项目(61170277,61472256);上海市教委科研创新重点项目(12zz137);上海市一流学科建设项目(S1201YLXK);沪江基金资助项目(A14006)。

Cloud resource sharing design supporting multi-attribute range query based on SkipNet

SUN Lihua¹, CHEN Shipin^1,2

1. College of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2. Network and Information Center Office, University of Shanghai for Science and Technology, Shanghai 200093, China

Received:2015-07-03 Revised:2015-09-15 Online:2016-01-10 Published:2016-01-09
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61170277, 61472256), Scientific Research and Innovation Key Projects of Shanghai Municipal Education Commission (12zz137), Shanghai First Class Discipline Construction Project (S1201YLXK) and Shanghai Fund (A14006).

摘要/Abstract

摘要： 在云资源共享服务模式中,针对云资源多属性范围查询的问题,提出一种改进的E-SkipNet网络。首先,E-SkipNet在传统分布式哈希表(DHT)网络SkipNet的基础上将数据属性引入到节点NameID的设置中,将物理节点加入到单个属性域中,以支持多属性范围查询;其次,在原E-SkipNet网络的基础上,将物理节点同时映射成多个逻辑节点;同时加入多个属性域,并将资源按照不同的属性发布到不同逻辑节点上;最后,采用均匀位置保留哈希函数对资源进行映射存储,从而在各个属性域中保留属性值的顺序关系,从而支持范围查询。仿真结果表明,改进后的E-SkipNet网络与改进前的E-SkipNet和多属性可寻址网络(MAAN)相比,在路由效率方面分别提高了18.09%和20.47%。结果表明,改进后的E-SkipNet网络能支持更加高效的云资源多属性范围查询,在异构环境中能较好地实现负载均衡。

关键词: E-SkipNet, 云资源共享, 多属性, 区间查询, 属性域, 均匀位置保留哈希函数

Abstract: In cloud resource sharing service model, in order to realize the multi-attribute range query of cloud resources, an improved E-SkipNet network was proposed. Firstly, based on the traditional Distributed Hash Table (DHT) network SkipNet, data attributes were added to the setting of NameID and physical nodes were added to single attribute domain to support multi-attribute range queries in E-SkipNet. Secondly, on the basis of the original E-SkipNet network, the physical nodes were simultaneously mapped into multiple logical nodes and added to multiple attribute domains, and the resources were released in accordance with different attributes to different logical nodes in the improved E-SkipNet. Finally, the resources were mapped to logical nodes utilizing uniform locality preserving hashing function, which was the key to support efficient range query. The simulation results show that the routing efficiency of improved E-SkipNet network was respectively increased by 18.09% and 20.47% compared with E-SkipNet and Multi-Attribute Addressable Network (MAAN). The results show that the improved E-SkipNet can support more efficient cloud resource multi-attribute range queries and achieve load balancing in heterogeneous environment.

Key words: E-SkipNet, cloud resource sharing, multi-attribute, range query, attribute domain, uniform locality preserving hashing function

中图分类号:

TP393.027

孙利华, 陈世平. 基于SkipNet支持多属性范围查询的云资源共享设计[J]. 计算机应用, 2016, 36(1): 72-76.

SUN Lihua, CHEN Shipin. Cloud resource sharing design supporting multi-attribute range query based on SkipNet[J]. Journal of Computer Applications, 2016, 36(1): 72-76.

参考文献

[1] HUANG L. Semantic P2P networks: future architecture of cloud computing [C]// Proceedings of the 2nd International Conference on Networking and Distributed Computing. Washington, D.C.: IEEE Computer Society, 2011: 336-339.
[2] YU Y F, LAI K C. A semi-structured overlay for multi-attribute range queries in cloud computing [C]// Proceedings of the 13th IEEE International Conference on Computational Science and Engineering. Piscataway, NJ: IEEE, 2010: 88-95.
[3] TANG Y, XU J, SHOU S, et al. A lightweight multidimensional index for complex queries over DHTs [J]. IEEE transactions on parallel and distributed systems, 2011, 22(12): 2046-2054.
[4] HARVEY N, JONES M B, SAROIU S, et al. SkipNet: a scalable overlay network with practical locality properties [C]// Proceedings of the 4th USENIX Symposium on Internet Technologies and Systems. Berkeley, CA: USENIX Association, 2003: 184-188.
[5] 方启明,杨广文.E-SkipNet:一种支持多属性范围查询的DHT网络[J].小型微型计算机系统,2014,35(10):2308-2312.(FANG Q M, YANG G W. E-SkipNet: a DHT network supporting multi-attribute range queries [J]. Journal of Chinese computer systems, 2014, 35(10): 2308-2312.)
[6] CAI M, FRANK M, CHEN J, et al. MAAN: a multi-attribute addressable network for grid information services [C]// Proceedings of the 4th International Workshop on Grid Computing. Piscataway, NJ: IEEE, 2003: 184-191.
[7] BHARAMBE A R, AGRAWAL M, SESHAN S. Mercury: supporting scalable multi-attribute range queries [C]// Proceedings of the 2004 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications. New York: ACM, 2004: 353-366.
[8] 余星,胡德敏.基于P2P网络的云资源多维查询算法[J].计算机应用研究,2014,31(10):3061-3064.(YU X, HU D M. Cloud resources multidimensional queries algorithm based on peer-to-peer network [J]. Application research of computers, 2014, 31(10): 3061-3064.)
[9] TRANA D A, NGUYENB T. Hierarchical multidimensional search in peer-to-peer networks [J]. Computer communications, 2008, 31(2): 346-357.
[10] 邵一川,申德荣,赵宏伟.HilbertChord:一种网格资源管理的P2P框架[J].微计算机信息,2009,25(15):105-106.(SHAO Y C, SHEN D R, ZHAO H W. HilbertChord: a P2P framework for service resources management [J]. Control & automation, 2009, 25(15): 105-106.)
[11] YANG X, HU Y. A scalable index architecture for supporting multi-dimensional range queries in peer-to-peer networks [C]// Proceedings of the 2006 International Conference on Collaborative Computing: Networking, Applications and Worksharing. Piscataway, NJ: IEEE, 2006: 1-10.
[12] 周傲英,周敏奇,钱卫宁,等.大规模分布式系统中的多属性查询处理[J].计算机学报,2008,31(9):1563-1572.(ZHOU A Y, ZHOU M Q, QIAN W N, et al. Complex query processing in large-scale distributed system [J]. Chinese journal of computers, 2008, 31(9): 1563-1572.)
[13] 李璞,陈世平,李剑锋.一种基于对等网络的云资源定位算法[J].计算机应用研究,2013,30(2):570-573.(LI P, CHEN S P, LI J F. Cloud resources locating algorithm based on peer-to-peer network [J]. Application research of computers, 2013, 30(2): 570-573.)
[14] RAMABHADRAN S, RATNASAMY S, HELLERSTEIN J M, et al. Brief announcement: prefix hash tree [C]// Proceedings of the 23rd Annual ACM Symposium on Principles of Distributed Computing. New York: ACM, 2004: 368.
[15] 张蓉,钱卫宁,周傲英.一种支持多维数据范围查询的对等计算索引架构[J].计算机研究与发展,2009,46(4):529-540.(ZHANG R, QIAN W N, ZHOU A Y, et al. A P2P framework for supporting multi-dimensional range query [J]. Journal of computer research and development, 2009, 46(4): 529-540.)
[16] 李钊伟,陈世平.支持多维查找的资源共享设计[J].计算机应用研究,2013,30(7):2156-2184.(LI Z W, CHEN S P. Design of multidimensional queries on resource sharing [J]. Application research of computers, 2013, 30(7): 2156-2184.)
[17] MAYMOUNKOV P, MAZIERES D. Kademlia: a peer-to-peer information system based on the XOR metric [C]// Proceedings of the 1st International Workshop on Peer-to-Peer Systems. Berlin: Springer, 2002: 53-65.

基于SkipNet支持多属性范围查询的云资源共享设计

Cloud resource sharing design supporting multi-attribute range query based on SkipNet

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