SaaS多租户数据放置的优化调整策略研究

doi:10.3969/j.issn.1000-436x.2014.z2.010

通信学报 ›› 2014, Vol. 35 ›› Issue (Z2): 63-71.doi: 10.3969/j.issn.1000-436x.2014.z2.010

SaaS多租户数据放置的优化调整策略研究

李晓娜^1,²,李庆志²,孔兰菊²,闫中敏²

¹ 青岛大学软件技术学院，山东青岛 266071
² 山东大学计算机科学与技术学院，山东济南 250101

出版日期:2014-11-25 发布日期:2017-06-19
基金资助:
国家自然科学基金资助项目;国家自然科学基金资助项目;国家科技支撑计划基金资助项目;山东省自然科学基金资助项目;山东省科技发展计划基金资助项目;山东省自主创新基金资助项目

Research on the optimization adjustment strategy for the SaaS multi-tenant data placement

Xiao-na LI^1,²,Qing-zhong LI²,Lan-ju KONG²,Zhong-min YAN²

¹ Department of Software Technology,Qingdao University,Qingdao 266071,China
² Department of Computer Science and Technology,Shandong University,Jinan 250101,China

Online:2014-11-25 Published:2017-06-19
Supported by:
The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Key Technologies R＆D Program;The Natural Science Foundation of Shandong Province;Shandong Province Independent Innovation Major Special Project

摘要/Abstract

摘要：

摘要：采用副本技术的 SaaS 多租户数据为满足租户访问及服务提供商管理的需求，在云中多节点必须合理放置。针对多租户数据特征和节点负载情况，对负载超重节点或超轻节点，通过调整数据副本数目和位置进行放置策略维护及优化，在满足所有租户 SLA 需求的同时最小化服务提供商的成本代价，实现服务质量与管理成本 2个目标的均衡。并通过实验与随机放置策略和贪婪放置策略进行比较，证明该策略的可行性和有效性。

关键词: SaaS, 多租户数据库, SLA, 优化调整, 副本放置

Abstract:

The multi-tenant data stored in cloud using replica technology must be reasonably placed,meet the requirements for data access by tenants and management by service providers.According to the characteristics of multi-tenant data and the load of the nodes,for the outweight nodes and the ultralight nodes,through adjusting the number and position of the replicas to maintenance and optimization the placement strategy so that meet the SLA requirements at the same time minimize the overall cost,realize the balance between the quality of service and the cost of management.Experimental results through comparison with random placement strategy and greedy placement policy demonstrate the feasibility and effectiveness of the proposed strategy.

Key words: SaaS, multi-tenant database, SLA, optimization adjustment, replica placement

李晓娜,李庆志,孔兰菊,闫中敏. SaaS多租户数据放置的优化调整策略研究[J]. 通信学报, 2014, 35(Z2): 63-71.

Xiao-na LI,Qing-zhong LI,Lan-ju KONG,Zhong-min YAN. Research on the optimization adjustment strategy for the SaaS multi-tenant data placement[J]. Journal on Communications, 2014, 35(Z2): 63-71.

图/表 8

图1

表1

符号定义"

符号	说明
T={TA,TB,TC…}	定制租用SaaS应用的租户集合
TX ={TX_-group1,TX_-group2,…,TX_-groupy…}	采用共享数据库共享模式存储的多租户数据，经过数据划分，租户 TX 形成的数据集合，group数目因租户而异
RTX_-groupy	数据TX_-groupy的副本数目，满足R_min≤RTX_-groupy≤R_max，R_min是确保云中数据可用性设置的最小副本数，R_max是为减少副本开销设置的最大副本值
Master节点	Master节点，存储控制元数据信息
DN={DN₁,DN₂…DN_i,…}	数据节点集合，是数据存储和读写的载体。
$D N i = {C_{D N_{i}}, {\bar{S}}_{D N_{i}}, {\bar{λ}}_{D N_{i}}}$	分别表示数据节点DN_i的计算能力、DN_i存储空间的上限值、DN_i在负载均衡状态下的理想负载
AN={AN₁,AN₂,…,AN_i,…}	应用节点集合，其上部署SaaS应用，租户可从多个节点定制租赁应用，但应用不会跨界点部署
$R_{X, y}^{i} = 1$	对数据TX_-groupy的访问请求自应用节点AN_i发出
$M_{X, y}^{i} = 1$	表示数据TX_-groupy的一个副本存储在节点DN_i上

表1

图2

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图7

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SaaS多租户数据放置的优化调整策略研究

Research on the optimization adjustment strategy for the SaaS multi-tenant data placement

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