Abstract

Multi-cloud is a vendor-based heterogeneous cloud paradigm in recent era of computing with dynamic infrastructural deployment. Multi-cloud provides all the essential and on-demand requirements of a virtual environment from various domains under a single service level agreement (SLA). Consumers from multitier domains can access all the available resources placed in a shared pool on service provider’s side, as per their requirement. The shared pool of resources creates complexity in assigning the best and suitable resource to a particular virtual instance under the same services provider end. The complexity of resources in terms of accessibility from the various domains, dynamic allocation, security, and quality of services (QoS) raises concerns in the multi-cloud infrastructure. This complexity raise concern relates to optimal provisioning and cost management. In the proposed work a hybrid technique with a shuffled leapfrog algorithm and ubiquitous binary search (SLFA-UBS) to resolve these issues with optimal provisioning, dynamic allocation and better resource selection. The proposed work will help to create a need-based and demand-based resource pool with the appropriate selection of each resource. The proposed model also supports resource optimization with dynamic provisioning, cost-effective solution to achieve QoS in multi-cloud deployment on service provider end.

Highlights

  • Multi-Cloud is a blend of cloud paradigms, which provides various on demand services with dynamic and elastic resource allocation in a multitier environment

  • Cloud services work under the signed service level agreement (SLA) and standard of architecture (SOA) between a cloud provider and a broker

  • Results showed that the hybrid shuffled leapfrog algorithm (SLFA)-Ubiquitous binary search (UBS) algorithm performs continually constant with the increase of the number of tasks on the horizontal axis

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Summary

INTRODUCTION

Multi-Cloud is a blend of cloud paradigms, which provides various on demand services with dynamic and elastic resource allocation in a multitier environment. In this architecture, there are lot of security and allocation concerns in terms of end user’s rights transparency, shared pool of resources and services, dynamic and runtime allocation, cost management and efficacy. There are many pre-defined techniques for the allocation and optimization of the resources in hybrid cloud environment e.g. scheduling techniques, feature based allocation, priority allocation, clustering and scaling based algorithms These techniques are useful to overcome dynamic allocation and provisioning in private or hybrid cloud model but these techniques have lack to overcome issues related to multi-cloud model, resources optimization and cost management. This paper further contains three sections i) related work ii) proposed work iii) optimal hybridization iv) result and discussion v) conclusion

RELATED WORK
PROPOSED WORK
HYBRID OPTIMIZATION AND CLASSIFICATION
Shuffled Leapfrog Algorithm
External Research
Genetic Algorithms
Hybrid SFLA and UBS
Throughput
Turnaround Time
Execution Time
CONCLUSION
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