Resource Allocation Strategy with Lease Policy and Dynamic Load Balancing
Author(s) -
Pooja S. Kshirsagar,
Anita Mukund Pujar
Publication year - 2017
Publication title -
international journal of modern education and computer science
Language(s) - English
Resource type - Journals
eISSN - 2075-017X
pISSN - 2075-0161
DOI - 10.5815/ijmecs.2017.02.03
Subject(s) - computer science , cloud computing , load balancing (electrical power) , lease , resource allocation , resource (disambiguation) , distributed computing , scope (computer science) , marketing buzz , work (physics) , resource management (computing) , operations research , computer network , operating system , world wide web , business , geometry , mathematics , finance , engineering , grid , mechanical engineering , programming language
Cloud Computing has managed to attract the entire buzz in the growing era of technology due to its ondemand services for resource request. Despite of the enormous growth of cloud computing, there are many problems related to resource allocation in cloud that are still unaddressed. Current work for resource allocation strategy focuses on various methods to place Virtual Machine per appropriate requests. The current state of art focuses on the dynamic nature of the work load on cloud. But there is still scope of improvement in the resource allocation strategies that have been proposed in terms of well-balanced network even at the resource contention. This study proposes a hybrid model composed of lease methodology and dynamic load balancing algorithm, with an attempt to overcome the problems of resource contention and starvation and a well-balanced network even at the input of varying loads. An attempt to increase the CPU utilization and throughput along with no request rejection is taken. The work also retains the lease options for its clients thus maintaining the anti-starvation for preemptible requests.
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