A New Strategy to Optimize the Load Migration Process in Cloud Environment
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 7
Abstract
Cloud computing is a model of internet-based service that provides easy access to a set of changeable computational sources through internet for users based on their demand. Load balancing in cloud have to manage service provider resources appropriately. Load balancing in cloud computing is the process of load distribution between distributed computational nodes for optimal use of resources and have to decrease latency in order to prevent a situation in which some nodes overloaded and some others under-loaded or be in the idle mode. Load migration is a potential solution for most of critical conditions such as load imbalance. However, many load migration methods are only based on one purpose. Practically, considering just one objective for migration can be in contrary to the other objectives and may lose optimal solution to work in existing situation. Therefore, having a strategy to make load migration process purposeful is essential in cloud environment. The main idea of this research is to reduce cost and increase efficiency in order to be compatible with cloud different conditions. In the recommended method, it is tried to improve load migration process using several different criteria simultaneously and apply some changes in previous methods. The simulated annealing algorithm is employed to implement the recommended strategy in the present research. Obtained result show desired performance and efficiency in general. This algorithm is highly flexible by which several important criteria can be calculated simultaneously.
Authors and Affiliations
Hamid Mirvaziri, ZhilaTajrobekar
A New Network on Chip Design Dedicated to Multicast Service
The qualities of service presented in the network on chip are considered as a network performance criteria. However, the implementation of a quality of service, such as multicasting, shows difficulties, especially at the...
A Parallel Community Detection Algorithm for Big Social Networks
Mining social networks has become an important task in data mining field, which describes users and their roles and relationships in social networks. Processing social networks with graph algorithms is the source for dis...
WordNet based Implicit Aspect Sentiment Analysis for Crime Identification from Twitter
Crime analysis has become an interesting field that deals with serious public safety issues recognized around the world. Today, investigating Twitter Sentiment Analysis (SA) is a continuing concern within this field. Asp...
State-of-the-Art and Open Challenges in RTS Game-AI and Starcraft
This paper presents a review of artificial intelligence for different approaches used in real-time strategy games. Real-time strategy (RTS) based games are quick combat games in which the objective is to dominate and des...
A General Model for Similarity Measurement between Objects
The problem to detect the similarity or the differ-ence between objects are faced regularly in several domains of applications such as e-commerce, social network, expert system, data mining, decision support system, etc....