Load Balancing Approach in Cloud Computing

Majid Mehmood

doi:10.4172/2165-7866.1000153

Abstract

Cloud computing is a utility to deliver services and resources to the users through high speed internet. It has a number of types and hybrid cloud is one of them. Delivering services in a hybrid cloud is an uphill task. One of the challenges associated with this paradigm is the even distribution among the resources of a hybrid cloud, often refereed as load balancing. Through load balancing resource utilization and job response time can be improved. This will lead to better performance results. Energy consumption and carbon emission can also be reduced if the load is evenly distributed. Hence, in this paper we have conducted a survey of the load balancing algorithms in order to compare the pros and cons of the most widely used load balancing algorithms.

Highlights

Cloud computingCloud computing is a utility to deliver services and resources to the users through high speed internet [1]
Many challenges are associated with hybrid clouds as elaborated in [15,16,17]
Load balancing: Load balancing is one of the main challenges faced in hybrid cloud computing, as there is a need for an even and dynamic distribution of load between the nodes in private and public clouds

Summary

Introduction

Cloud computing is a utility to deliver services and resources to the users through high speed internet [1]. If some problem occurs in the private cloud the load is transferred to the public infrastructure. This way, hybrid clouds help in increasing the uptime. Reliability: As the communication between a private and public cloud occurs through a network connection, the availability of connection is again an issue as connection often breaks Are these connections secure or not and would the migration of tasks to the public cloud help reduce the response time or not, are the questions that need to be addressed. Load balancing: Load balancing is one of the main challenges faced in hybrid cloud computing, as there is a need for an even and dynamic distribution of load between the nodes in private and public clouds. A detailed view of classification is presented below [23]

Related Work

Findings

Conclusion