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Hybrid Delay Optimization and Workload Assignment in Mobile Edge Cloud Networks

DOI: 10.4236/oalib.1104854, PP. 1-12

Subject Areas: Cloud Computing

Keywords: Offloading, Machine Learning, Process Delay, Transmission Delay, Delay Constraint, Augmented Reality, Video Analytics

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Abstract

Nowadays, the usage of mobile devices is progressively increased. Until, delay sensitive applications (Augmented Reality, Online Banking and 3D Game) are required lower delay while executed in the mobile device. Mobile Cloud Computing provides a rich resource environment to the constrained-resource mobility to run above mentioned applications, but due to long distance between mobile user application and cloud server introduces hybrid delay (i.e., network delay and process delay). To cope with the hybrid delay in mobile cloud computing for delay sensitive applications, we have proposed novel hybrid delay task assignment (HDWA) algorithm. The preliminary objective of the HDWA is to run the application on the cloud server in an efficient way that minimizes the response time of the application. Simulation results show that proposed HDWA has better performance as compared to baseline approaches.

Cite this paper

Mahesar, A. R. , Lakhan, A. , Sajnani, D. K. and Jamali, I. A. (2018). Hybrid Delay Optimization and Workload Assignment in Mobile Edge Cloud Networks. Open Access Library Journal, 5, e4854. doi: http://dx.doi.org/10.4236/oalib.1104854.

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