Scalable SaaS Indexing Algorithms with Automated Redundancy and Recovery Management

Software-as-a-Service (SaaS) is a new software delivery model with MultiTenancy Architecture (MTA). An SaaS system is often mission critical as it often supports a large number of tenants, and each tenant supports a large number of users. This paper proposes a scalable index management algorithm based on B+ tree but with automated redundancy and recovery management as the tree maintains two copies of data. The redundancy and recovery management is done at the SaaS level as data are duplicated with tenant information rather than at the PaaS level where data are duplicated in chunks. Using this approach, an SaaS system can scale out or in based on the dynamic workload. This paper also uses tenant similarity measures to cluster tenants in a multi-level scalability architecture where similar tenants can be grouped together for efficient processing. The scalability mechanism also includes an automated migration strategies to enhance the SaaS performance. The proposed scheme with automated recovery and scalability has been simulated, the results show that the proposed algorithm can scale well with increasing workloads.

[1]  S. B. Yao,et al.  Efficient locking for concurrent operations on B-trees , 1981, TODS.

[2]  Colleen Roe,et al.  Server-Side Design Principles for Scalable Internet Systems , 2002, IEEE Softw..

[3]  Wenchao Zhou,et al.  A batch of PNUTS: experiences connecting cloud batch and serving systems , 2011, SIGMOD '11.

[4]  Hongjun Lu,et al.  T-tree or B-tree: main memory database index structure revisited , 2000, Proceedings 11th Australasian Database Conference. ADC 2000 (Cat. No.PR00528).

[5]  Wei-Tek Tsai,et al.  SaaS performance and scalability evaluation in clouds , 2011, Proceedings of 2011 IEEE 6th International Symposium on Service Oriented System (SOSE).

[6]  Rudolf Bayer,et al.  Concurrency of operations on B-trees , 1994, Acta Informatica.

[7]  Wei-Tek Tsai,et al.  Two-Tier Multi-tenancy Scaling and Load Balancing , 2010, 2010 IEEE 7th International Conference on E-Business Engineering.

[8]  Wei-Tek Tsai,et al.  Testing the scalability of SaaS applications , 2011, 2011 IEEE International Conference on Service-Oriented Computing and Applications (SOCA).

[9]  A. Fox,et al.  Cloudstone : Multi-Platform , Multi-Language Benchmark and Measurement Tools for Web 2 . 0 , 2008 .

[10]  Raymond A. Paul,et al.  Consumer-centric service-oriented architecture: a new approach , 2006, The Fourth IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, and the Second International Workshop on Collaborative Computing, Integration, and Assurance (SEUS-WCCIA'06).

[11]  Wei-Tek Tsai,et al.  Scalable Architectures for SaaS , 2012, 2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops.

[12]  Deshuai Wang,et al.  A Heuristic Data Allocation Method for Multi-tenant SaaS Application in Distributed Database Systems , 2011, 2011 International Conference on Information Management, Innovation Management and Industrial Engineering.

[13]  Xiaohu Yang,et al.  Data Based Application Partitioning and Workload Balance in Distributed Environment , 2006, 2006 International Conference on Software Engineering Advances (ICSEA'06).

[14]  Xu Cheng,et al.  A multi-tenant oriented performance monitoring, detecting and scheduling architecture based on SLA , 2009, 2009 Joint Conferences on Pervasive Computing (JCPC).