JOURNAL ARTICLE

Joint Optimization for Computation Offloading and Resource Allocation in Internet of Things

Abstract

Internet of Things (IoT) is a promising technology to connect tremendous devices together, where the major challenges are that the available energy is limited and computing capability is low. In this paper, we propose an efficient IoT computing tasks offloading mechanism based on cooperative communication and mobile cloud computing (MCC) system. The problem will be formulated as a joint optimization problem of computation and radio resource allocation aiming to minimize the system energy consumption, under the constraints of latency and transmission power. We will first propose a joint iterative computation offloading and resource allocation algorithm to solve the non-convex optimization problem. To further reduce the computation complexity, we also propose a matching based sub- optimal algorithm to solve this problem. Simulation results demonstrate that the proposed iterative algorithm achieves the goal to substantially reduce energy consumption by offloading computation. Moreover, the sub-optimal algorithm significantly reduces the computation complexity with only a small portion of performance loss.

Keywords:
Computation offloading Computer science Distributed computing Resource allocation Computation Energy consumption Optimization problem Cloud computing Lyapunov optimization Mathematical optimization Edge computing Computer network Algorithm Engineering Artificial intelligence

Metrics

18
Cited By
2.83
FWCI (Field Weighted Citation Impact)
20
Refs
0.91
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
Blockchain Technology Applications and Security
Physical Sciences →  Computer Science →  Information Systems
Molecular Communication and Nanonetworks
Physical Sciences →  Engineering →  Biomedical Engineering
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