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

被引:0
作者
Guan, Mengling [1 ]
Bai, Bo [3 ]
Wang, Li [1 ,2 ]
Jin, Shi [4 ]
Han, Zhu [5 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China
[2] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China
[3] Huawei Technol, Future Network Theory Lab, Lab 2012, Shanghai, Peoples R China
[4] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China
[5] Univ Houston, Dept Elect & Engn, Houston, TX 77004 USA
来源
2017 IEEE 86TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL) | 2017年
关键词
Mobile cloud computing; fog computing; computation offloading; resource allocation; Internet of Things;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页数:5
相关论文
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