Network Aware and Power-Based Resource Allocation in Mobile Ad Hoc Computational Grid

Shah, Sayed Chhattan; Chauhdary, Sajjad Hussain; Bilal, Muhammad; Park, Myong Soon

doi:10.1109/hpcc.2014.73

Cited by 1 publication

(1 citation statement)

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“…The work is important considering the execution of more number of jobs while consuming the same amount of energy when compared with random allocation of tasks. Shah et al proposed a network‐aware and power‐based resource allocation considering the network properties and power consumption in transmission so as to save the battery for making better task allocation decisions since nodes run on limited power source. Since mobile devices are powered by limited power sources that makes it a critical parameter while scheduling the task, Hirsch et al proposed a battery‐aware job‐stealing approach for CPU‐based application for successful execution of tasks within a cluster of mobile nodes.…”

Section: Literature Surveymentioning

confidence: 99%

A quantum‐inspired binary gravitational search algorithm–based job‐scheduling model for mobile computational grid

Singh

Raza

2017

Concurrency and Computation

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Owing to the advancements in low-power consumption processors and high-power storage in a small-sized battery, the cost of handheld mobile devices, eg, mobiles, tabs, or personal digital assistants, have reduced to a great extent. This has enabled people to have at least 1 smartphone in general with this number increasing exponentially. However, the increasing use of these mobile devices results in an equal increase in the underused processing capacity of these devices too. This encourages the research aiming to use this processing power by forming a mobile computational grid. Because of the inherent limitations of bandwidth, battery, and computational power, job scheduling on these devices demands an efficient scheduling approach to harness the true potential of the grid. The problem becomes even more challenging considering the dynamic nature of these mobile devices. Job scheduling being nondeterministic polynomial time-complete allows the use of evolutionary approaches by exploring and exploiting the search space efficiently. The exploration gets boosted even more with the use of quantum-computing concepts. This work proposes a quantum-inspired Newtonian approach of attraction based on gravitational search algorithm for scheduling the jobs on mobile computational grid. Simulation study has been performed to evaluate the performance of the model over various dimensions. A comparative study has been performed with quantum-genetic algorithm. Simulation result establishes the effectiveness of model under various test conditions. KEYWORDS genetic algorithm (GA), gravitational search algorithm (GSA), mobile grid computing (MGC), quantum computing (QC), quantum-inspired genetic algorithm (QGA), turnaround time (TAT)

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Section: Literature Surveymentioning

confidence: 99%