Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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Prioritization of Overflow Tasks to Improve Performance of Mobile Cloud

Prioritization of Overflow Tasks to Improve Performance of Mobile Cloud
Abstract-Synopsis-Documentation

Prioritization of Overflow Tasks to Improve Performance of Mobile Cloud


Abstract

Mobile devices may offload their applications to avirtual machine running on a cloud host. This application mayfork new tasks which require virtual machines of their own onthe same physical machine. Achieving satisfactory performancelevel in such a scenario requires flexible resource allocationmechanisms in the cloud data center. In this paper we presenttwo such mechanisms which use prioritization:one in which forked tasks are given full priority over newlyarrived tasks, and another in which a threshold is establishedto control the priority so that full priority is given to the forkedtasks if their number exceeds a predefined threshold.We analyze the performance of both mechanisms using a Markovianmultiserver queueing system with two priority levels tomodel the resource allocation process, and a multi-dimensionalMarkov system based on a Birth-Death queueing system withfinite population, to model virtual machine provisioning. Ourperformance results indicate that the threshold-based priorityscheme not only performs better, but can also be tuned to achievethe desired performance level.


Architecture:



PROPOSED SYSTEM

Proposed solutions to address the issues of computational power. Personal use is permitted, but republication/redistribution requires  mobile devices by offloading computing tasks has been an approach for extending the concept of VM-based clone cloud offloading from LAN surrogates to cloud servers.

Proposed a polynomial time approximation scheme (FPTAS) algorithm to solve thelatency problem. The model proposed in is based on the wireless network cloud concept and a multi-objective linear optimization approach using an event-based finite state model and dynamic constraint programming method has been used to determine the appropriate transmission power, cloud offloading and optimum QoS profiles.

Proposed a randomized auction mechanism based on an application of smoothed analysis and randomized reduction, for dynamic distributed cloud data centers

PROPOSED SYSTEM ALGORITHMS

o Heuristic algorithm.

o Polynomial time approximation  algorithm

o Decision algorithm


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