Adaptive task scheduling method in multi-tenant cloud computing
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ORIGINAL RESEARCH
Adaptive task scheduling method in multi-tenant cloud computing Ashalatha Ramegowda1
•
Jayashree Agarkhed1 • Siddarama R. Patil2
Received: 23 August 2018 / Accepted: 7 November 2019 Ó Bharati Vidyapeeth’s Institute of Computer Applications and Management 2019
Abstract Cloud security is the primary need for the vital Information Technology industry. It adopts dynamic qualities and enhances various heterogeneous resources for its applications. Cloud environment enables virtual technologies using virtual machine placement method. Therefore any virtual machines can move between any physical devices for achieving cost optimization and network traffic minimization sake. Multi-tenancy means the use of multiple systems applications or data from various organizations residing on a single physical device. Here a single instance of the application software running on the service providers’ platform can be accessed by multiple clients simultaneously. Multi-tenancy concept refers to both public as well as private cloud model which relates to all the three layers in cloud computing system. Adaptive particle swarm optimization is proposed in this paper which also addresses the multi-tenancy process which enables high resource utilization service under cloud storage network. Keywords Cloud computing Virtual machines Quality of service Multi-tenancy VM scheduling
& Ashalatha Ramegowda [email protected] Jayashree Agarkhed [email protected] Siddarama R. Patil [email protected] 1
Department of C.S.E., P.D.A. College of Engineering, Kalaburagi, India
2
Department of E&CE, P.D.A. College of Engineering, Kalaburagi, India
1 Introduction Cloud computing is model for executing Information Technology (IT) services enormously. Virtual Machines (VMs) are used for resource consolidation under a single infrastructure service [1]. Load balancers are hugely helpful for resource sharing and optimization in multi-zone cloud environment [2, 3]. The workload distribution has effective strategy using multiple levels for achieving high performance of the cloud system in energy efficient fashion [4]. Cloud Service Providers (CSP) considers software applications as an essential service for cloud customers’ usage. A single physical computer machine is shared by n number of clients using different VMs under multi-tenancy category. Resource virtualization system guarantees high reliability and quality of service (QoS) in multi-tenant cloud storage network [5]. Cloud security is the significant need for the critical information technology Industry [6]. The VM based processes comprise the variety of incoming workloads under shared infrastructure service. The scheduling concept raises the utilization of the resources and maximum profit benefits using Service Level Agreements (SLAs) in the cloud system. The dynamic resource allocation adopts virtualization technology through resource optimization methodology [7]. The Live Virtual Machine Migration (LVMM) scheme accomplishes consolidation of workloads using cloud
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