5G-EECC: Energy-Efficient Collaboration-Based Content Sharing Strategy in Device-to-Device Communication

Author:

Khan Nauman1,Khan Imran Ali1,Arshed Jawad Usman2,Afzal Mehtab3,Ahmed Muhammad Masroor4,Arif Muhammad5ORCID

Affiliation:

1. Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Pakistan

2. Department of Computer Science, University of Baltistan, Skardu, Pakistan

3. Department of Software Engineering, FoIT, University of Central Punjab (UCP), Lahore, Pakistan

4. Department of Computer Science, Capital University of Science & Technology, Islamabad, Pakistan

5. Department of Computer Science & IT, The University of Lahore, Lahore, Pakistan

Abstract

In the past few years, mobile data traffic has seen exponential growth due to the emergence of smart applications. Although throughput enhancement techniques such as macro- and femtocells reduce cell size, they are relatively expensive to implement. Mobile device-to-device (D2D) communication has emerged as a solution to support the growing popularity of multimedia content for local service in next-generation 5G cellular networks. Content sharing is the prominent feature, which helps D2D communication in reducing offload traffic on the network, improving the energy efficiency of the device, and reducing backhaul connectivity costs. In traditional mapping approaches such as one to one or one to many, a massive amount of traffic is distributed among the devices resulting in high-energy consumption. In this paper, we propose a novel energy-efficient content sharing scheme called Energy-Efficient Collaboration-based Content (EECC) sharing strategy in D2D communication that shares content equally across devices based on their capacities and battery life under mobility. The proposed work includes cluster formation, cluster head selection, and helper node selection. In addition, we relied on a cooperative caching policy to ensure that content is distributed efficiently. The simulation results indicate a 12.05% reduction in energy compared to the state-of-the-art technique with a 2-gigabyte video file. To evaluate scalability, we increased the file size from 3 to 4 gigabytes, yet the performance in terms of energy consumption remained the same.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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