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

Abstract

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

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.

Figures/Tables 8

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

References 17

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