An Efficient ECK-Secured FCM-Based Firefly Optimization Algorithm for Dynamic Resource Sharing in Multi-Tenant SaaS Service Clouds

An Efficient ECK-Secured FCM-Based Firefly Optimization Algorithm for Dynamic Resource Sharing in Multi-Tenant SaaS Service Clouds

Pallavi G. B.
Copyright: © 2023 |Pages: 14
DOI: 10.4018/IJCAC.319033
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Abstract

Multi-tenancy in cloud computing is one of the foremost approaches to share one application instance among different customers and it is generally used by Software as a service (SaaS) providers. The main objective of the proposed work is to minimize the down time of virtual machines essential for resource provisioning using cluster based secure dynamic resource sharing. The proposed secure dynamic resource sharing approach allocates the service tenants to matched Virtual Machines(VMs) and allocates the VMs into physical host machines using the elliptic curve key based firefly optimization approach. First the functional characteristics of service users are grouped into clusters using FCM (Fuzzy C_means clustering) algorithm as tenants. After clustering, the tenant users are checked for authorization with the help of elliptic curve key value. When the users in the tenants are authorized then the grouped services are scheduled dynamically using the firefly optimization algorithm. The result of the work is appraised in terms of resource utilization, execution time, speed, and speedup.
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1. Introduction

Cloud computing is an emerging technology proposed to support different storage and computing services accomplished on the internet. This technology can be utilized for authorizing comfortable, on-demand network connection towards an allocated puddle of configurable computing resources. For example, server, storage, networks, application and services which could be rapidly provided and discharged using minimum service provider interaction and management force (Armbrust et al., 2010; Bezemer & Zaidman, 2010). Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Services (PaaS) are the various types of services used in cloud computing. Cloud computing distributes substructure, stage, and software and is accessible as subscription-based services in a pay-as-you-go ideal to customers (Guo et al., 2007).

SaaS is an innovative delivery model of software that provides a single application for multiple users via internet. This service is beneficial to IT companies as they can use the applications without the need to purchase and maintain their own IT infrastructure. Also, service providers achieve full economy of scale by hosting such SaaS application using a multitenant model.

The SaaS suppliers, acquiring the power to scale up or down the operation to solitary devour and pay for the resources that are essential in that period of point and it is an enticing ability, and it will be lower cost than functioning on hardware from conventional treating (Ju et al., 2012).

Multi-tenancy in SaaS is a critical technology in which multiple tenants are granted computing resources at the same period and reached great effectiveness of operation (Kullback & Leibler, 1951).

Multi-tenancy being a hierarchical model, suitable approaches are imposed on the virtual machines at each stage noted to great control and separation of customers. The inordinate management of resources and arranging the customers at different stages according to their necessities are the benefits of multi-tenancy (Kwok & Mohindra, 2008). A multi-tenant web application framework is used to maintain the heritage, changes, and runtime customizations of customer interfaces providing different client-side web operation technologies (Momm & Theilmann, 2011). Resource allocation is performed on the treated systems by utilizing Service Performance Isolation Infrastructure (SPIN). Multi-tenancy is maintained by executing SPIN model and indicated the segregation effectiveness on the Trade6 benchmark (Turner et al., 2003). Service level agreement (SLA) based multi-tenant focused on identifying, monitoring, and scheduling design is used to reduce the irregular utilization of system resources (Wu et al., 2011)).

Multi-tenancy is focused on maintaining huge customers through databases and examples. OTPP viz., On-line Tenant Placement Problem is a problem in the SaaS, and it is reduced by a novel resource evaluation of consumption model for multi-tenant design and to discover the difficulty of OTPP (Yang et al., 2011). To determine the position of tenants a hybrid technique is used which is denoted as Tenant Placement Strategy (TPS). Heuristic technique, genetic algorithm, case-based reasoning (CBR) is utilized in the TPS (Zhang et al., 2010). Multi-tenant operations are arranged on the normal relational databases by utilizing an innovative hybrid schema-sharing method (Zhu et al., 2011).

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