• Siddharth V Jain
• Sriram N.
• Shyamala G.

The goal of this paper is to find methods to reduce the costs incurred by Network Service Providers, and in turn, increase their profits. As distributed cloud services are increasingly becoming the go to option for all kinds of enterprises and end users, there is an increased demand for more service providers at lower rates. Hence there is a need for efficient use of hardware and also money effective way of running the services. We start by formulating and employing an online algorithm that, based upon the geographical location of the user, geographical location of the data centers, source of information, the routing paths, hop counts etc. will deliver the requested information at minimal cost and in a timely manner. The cost reduction part of the algorithm lies in the fact that it takes into account the prices of electricity in the places where the data centers are present, and tries to avoid high priced locations. Also grouping data based on the size of the file and grouping the data centers according to the memory and bandwidth available, increases the efficiency in the allotment of the data centers. The present day clouds are focusing on provisioning web services for developers like Amazon Elastic Compute Cloud, Go Grid etc. And then there are cloud services such as Simple Storage Service and Amazon Simple DB which are taking a. Different route by providing data storage and management services and it is very important for services like these to have good caching and storage structures to optimize their profits. There are various models which can be used to charge for the service like Amazon Web Service charge for the infrastructure elements they provide, meaning charging for each instance of CPU, I/O or bandwidth being used. The current static pricing strategies are based on pay-as-you go schemes and they may not be the best way to make money. The need of the hour for the service providers is to have dynamic pricing scheme, wherein a simple price-demand model is used which is re-evaluated as and when errors, model mismatches and external disturbances occur along with taking into consideration the real time system behavior feedback and infrastructure efficiency monitoring. Thus we need an optimal pricing model which is based on the efficiency of the system architecture and dynamic enough to incorporate market influences.

PROFIT MAXIMIZATION IN DISTRIBUTED CLOUD COMPUTING

"PROFIT MAXIMIZATION IN DISTRIBUTED CLOUD COMPUTING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.266-269, May-2019, Available :http://www.jetir.org/papers/JETIR1905H45.pdf

"PROFIT MAXIMIZATION IN DISTRIBUTED CLOUD COMPUTING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp266-269, May-2019, Available at : http://www.jetir.org/papers/JETIR1905H45.pdf