Secure and efficient multi-tenant database management system for cloud computing environment

被引:2
作者
Pallavi G.B. [1 ]
Jayarekha P. [2 ]
机构
[1] Dept. of CSE, BMSCE, VTU, Bangalore
[2] Dept. of ISE, BMSCE, VTU, Bangalore
关键词
Federated cloud; Multi-tenancy; Reputation; Scheduling; SLA; Trust;
D O I
10.1007/s41870-019-00416-5
中图分类号
学科分类号
摘要
Multi-tenancy is one of the important feature of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) deployed in cloud infrastructure has gained wide interest in both academics as well as industries, as it provides scalability and economic benefit for both cloud service provider and end users. However, low trust on the rented computational resources prevents users from utilizing the same. Further, in multitenant systems the communication channels and other computational resources are shared, inducing privacy and security issues. As tenants are anonymous in nature, a user may not find a trustworthy co-tenant and tenants depend on cloud service provider to assign trustworthy co-tenants. However, cloud service provider allows maximum co-tenancy irrespective of the behaviors of tenants to maximize resource utilization. Of late, a number of approaches have been presented based on reputation management mechanism to identify good and malicious tenants. However, state-of-art models are not efficient when behavior of malicious tenant changes rapidly. In order to overcome the said research challenge, this work presents a secure and efficient multi-tenant database management system (SEMTDBMS) for cloud computing environment. SEMTDBMS first analyzes security requirement of tenant workers and suggests a secureness weight metric for selection of tenant worker. Subsequently, a novel workload scheduler for scheduling workload among tenants has been presented. Experiments are conducted considering OLTP benchmark such as TPC-C and Yahoo! Cloud Serving Benchmark (YCSB) benchmark with and without security compliances. SEMTDBMS show significant performance improvement in terms of latency and throughput over state-of-art model. © 2020, Bharati Vidyapeeth's Institute of Computer Applications and Management.
引用
收藏
页码:703 / 711
页数:8
相关论文
共 26 条
  • [1] Mell P., Grance T., The NIST Definition of Cloud Computing, (2009)
  • [2] Aulbach S., Grust T., Jacobs D., Kemper A., Rittinger J., Multi-tenant databases for software as a service: schema-mapping techniques, SIGMOD '08 Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1195-1206, (2008)
  • [3] Krebs R., Momm C., Kounev S., Metrics and techniques for quantifying performance isolation in cloud environments, Elsevier Sci Comput Progr J (SciCo), 90, pp. 116-134, (2013)
  • [4] Breslow A.D., Tiwari A., Schulz M., Carrington L., Tang L., Mars J., Enabling fair pricing on hpc systems with node sharing, Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 37, pp. 1-12, (2013)
  • [5] Gmach D., Rolia J., Cherkasova L., CCGRID '12: Proceedings of the 2012 12Th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (Ccgrid 2012), pp. 539-546, (2012)
  • [6] Gens F., Mahowald R.P., Villars R.L., 2009, IDC Cloud Computing, (2010)
  • [7] IDC Ranking of Issues of Cloud Computing Model., (2009)
  • [8] Bates A., Mood B., Pletcher J., Pruse H., Valafar M., Butler K., On detecting co-resident cloud instances using network flow watermarking techniques, Int J Inf Secur, 13, 2, pp. 171-189, (2014)
  • [9] Azar Y., Kamara S., Menache I., Raykova M., Shepard B., Colocation- resistant clouds, Proceedings of the 6Th Edition of the ACM Workshop on Cloud Computing Security, Ser. CCSW’14., pp. 9-20, (2014)
  • [10] Koeune F., Standaert F.-X., Foundations of security analysis and design iii, A Tutorial on physical security and side-channel attacks, pp. 78-108, (2005)