Global Server Load Balancing with Networked Load Balancers for Geographically Distributed Cloud Data-Centres

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The characteristic of high scalability, elasticity and availability of infinite computing resources have obliged many organizations to deploy mission critical and user centric applications in the cloud computing environment. To avoid any single point of failure in the cloud system the cloud service provider provide redundancy at all levels in the datacenter but the recent natural disasters have made the datacenter itself a single point of failure. Thus, to deploy applications in the datacenters dispersed across geographic regions has become the need of the hour. Efficient load balancing among these datacenters is critical to increase user responsiveness and seamless failover in case of natural disasters. In this research paper we critically analysed the state-of-the art techniques used for Global Server Load Balancing and have proposed a novel model of networked load balancers for load balancing across the datacenters in cloud computing environment. The proposed model overcomes the shortcomings of existing DNS based load balancing by considering current load status of datacenter, by making time to live of DNS server cache redundant and by finding the exact location by real IP of end user.

Published In : IJCSN Journal Volume 6, Issue 6

Date of Publication : December 2017

Pages : 682-688

Figures :05

Tables : --

Amit Gajbhiye : Department of Computer Engineering and Applications NITTTR, Bhopal, India.

Dr. Shailendra Singh : Department of Computer Engineering and Applications NITTTR, Bhopal, India.

Global Server Load Balancing, Domain Name System, Load Balancing, Disaster Recovery, Cloud Computing

In this paper, we have proposed a new model for global server load balancing which gives resilient and intelligently balanced datacenters. Balancing load at two levels this framework considers the current health status of datacenter to deliver services from the least loaded datacenter to reduce the response time. It calculates the geographic location of end user with the help of its IP address to deliver services from the least loaded datacenter which is nearest to the user.

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