TOWARDS ENERGY EFFICIENT CLOUD COMPUTING USING DEPENDENCY GRAPH
Journal Title: International Journal of Computer Engineering & Technology (IJCET) - Year 2019, Vol 10, Issue 2
Abstract
Nowadays, research are being directed in the field of large system models. These large system models generally manages the distributed environment to break down and understand behavior of the systems. A large number of the system give simulation of the distributed environment to run their experiments. Hence, when there is an expansion in demand of cloud and distributed system, side by side it is important to maintain the power consumption and efficiency of the framework. This is a most challenging assignment to perform. In this paper, we give energy optimizing model with the help of migration manager to manage the productivity of the entire system. We will contrast DVFS algorithm with on Demand and Conservative mode of operation in cloud. We will exhibit our experiment in CloudSim software
Authors and Affiliations
PREETILATA SAHU AND DIPTI VERMA
Keywords
Related Articles
- EP ID EP46536
- DOI 10.34218/IJCET.10.2.2019.009
- Views 175
- Downloads 0
A ROBUST ORGANIZATIONAL POLICY FOR TASK AND RESOURCE ALLOCATION: A NOVEL FRAMEWORK
In a Multi-Agent System existing formalisms for implementing organizational policies assign specific roles to each agent. Examples are hierarchical organization, contract net protocol, social reasoning mechanism, and t...
APP FOR PLACING ORDERS AND BARGAINING WITH AI AT A RESTAURANT
The proposed system attempts to implement various new technologies to an app for enabling users to place orders and bargain the prices with a machine learning powered bot. Such a system can provide new experience to th...
AN EFFICIENT ALGORITHM FOR MINING HIGH UTILITY RARE ITEMSETS OVER UNCERTAIN DATABASES
In modern era, due to the broad applications of uncertain data, mining itemsets over uncertain databases has paying much more attention. Association Rule Mining (ARM) is a well known and most popular technique of Data...
FORESTALLING GROWTH RATE IN TYPE II DIABETIC PATIENTS USING DATA MINING AND ARTIFICIAL NEURAL NETWORKS: AN INTENSE SURVEY
The race for urbanization and thirst for high living status leads to unhealthy life. As the result a rapid growth in number of diabetic patients in urban areas approaching to its deadline. In this situation it become a...
MACHINE LEARNING ALGORITHMS FOR HETEROGENEOUS DATA: A COMPARATIVE STUDY
In the present digital era massive amount of data is being continuously generated at exceptional and increasing scales. This data has become an important and indispensable part of every economy, industry, organization,...