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Improving Central and Remote Access Units in Cloud Based Wi-Fi Network for Better Client and Service
Author(s) -
R Kavitha,
G.Sathiyabama
Publication year - 2019
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit195118
Subject(s) - computer science , cloud computing , distributed computing , mobile cloud computing , load balancing (electrical power) , scalability , mobile device , cloud testing , cloudlet , mobile computing , computer network , cloud computing security , database , operating system , geometry , mathematics , grid
People show attention to cloud computing since it is efficient and scalable. But maintaining the stability of processing so many jobs in the cloud computing environment with load balancing is a very difficult problem and receives much attention by researchers. Load balancing in cloud computing platform has performance impact also. Good load balancing makes cloud computing more efficient and increases user satisfaction. This paper introduces a better load balance model for public cloud based on cloud partitioning concept with a switch mechanism to choose various strategies in different situations. The algorithm applies game theory to load balancing strategy and improves the efficiency in the public cloud environment. MCC is a concept which aims to mitigate these limitations by extending the capabilities of smart devices by employing cloud services, as required. In MCC both the data storage and processing occur external to the mobile device, while in cloud computing it is usually only the data storage which is external. In this following a some of these architectures as categorized in augmented execution, elastic partitioned/modularized applications, application mobility, ad-hoc mobile cloud and add a fifth category; cyber foraging. This system addresses whether MCC techniques can be used to extend the capabilities of resource-constrained mobile-devices to provide the illusion of infinite, elastic resources on demand. The existing system limitations of mobile-devices, and identified five key limited resources as being CPU, memory, battery, data usage and time. In this research explored existing solutions for these limitations and identified offloading computation and storage from the device as a possible solution.

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