Economical job scheduling in wireless grid

Birje, Mahantesh N.; Manvi, Sunilkumar S.; Bulla, Chetan

doi:10.1109/icectech.2011.5941835

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…Wireless access point (WAP) and mobile nodes act as 2 noncooperative players that offer alternating bargaining so as to achieve fair pricing that helps efficient job allocation to the mobile nodes so as to maximize the revenue for the grid users. Birje et al 38 which in turn helps in better resource allocation. Further, the various parameters under performance evaluation confirm that as the mobility increases, task execution also increases, but at the same time monitoring overhead too increases.…”

Section: Emergency Servicesmentioning

confidence: 99%

“…Wireless access point (WAP) and mobile nodes act as 2 noncooperative players that offer alternating bargaining so as to achieve fair pricing that helps efficient job allocation to the mobile nodes so as to maximize the revenue for the grid users. Birje et al proposed an economical job‐scheduling strategy based on load‐prediction technique predicting the availability of resources with the aim for better resource scheduling. The work is claimed to be cost effective while reducing the job‐rejection ratio.…”

Section: Literature Surveymentioning

confidence: 99%

“…Birje et al38 proposed an economical job-scheduling strategy based on load-prediction technique predicting the availability of resources with the aim for better resource scheduling. In grid infrastructure, the resources are heterogeneous, distributed across the globe, sharing their unused processing cycles to meet a common objective(s).…”

mentioning

confidence: 99%

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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: Emergency Servicesmentioning

confidence: 99%

“…Wireless access point (WAP) and mobile nodes act as 2 noncooperative players that offer alternating bargaining so as to achieve fair pricing that helps efficient job allocation to the mobile nodes so as to maximize the revenue for the grid users. Birje et al proposed an economical job‐scheduling strategy based on load‐prediction technique predicting the availability of resources with the aim for better resource scheduling. The work is claimed to be cost effective while reducing the job‐rejection ratio.…”

Section: Literature Surveymentioning

confidence: 99%