JOURNAL ARTICLE

Energy-Efficient Computation Offloading in Cellular Networks

Abstract

Computationally intensive applications may quickly drain mobile device batteries. One viable solution to address this problem utilizes computation offloading. The tradeoff is that computation offloading introduces additional communication, with a corresponding energy cost. Yet, previous research into computation offloading has failed to account for the special characteristics of cellular networks that impact mobile device energy consumption. In this paper, we aim to develop energy efficient computation offloading algorithms for cellular networks. We analyze the effects of the long tail problem on task offloading, formalize the computation offloading problem, and use Dijkstra's algorithm to find the optimal decision. Since this optimal solution relies on perfect knowledge of future tasks, we further propose an online algorithm for offloading. We have implemented this latter algorithm on Android-based smartphones. Both experimental results from this implementation and trace-driven simulation show that our algorithm can significantly reduce the energy of computation offloading in cellular networks.

Keywords:
Computation offloading Computer science Computation Energy consumption Cellular network Mobile device Distributed computing Android (operating system) Server Dijkstra's algorithm Efficient energy use Computer network Embedded system Edge computing Algorithm Internet of Things Theoretical computer science Graph Shortest path problem Engineering

Metrics

51
Cited By
10.34
FWCI (Field Weighted Citation Impact)
23
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Green IT and Sustainability
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
IoT Networks and Protocols
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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