期刊
COMPUTER COMMUNICATIONS
卷 173, 期 -, 页码 183-191出版社
ELSEVIER
DOI: 10.1016/j.comcom.2021.04.005
关键词
MEC; Application offloading; Resource allocation; IoT
资金
- Bengbu University, China [BBXY2020KYQD02]
- Key research and development projects in Anhui Province, China [202004a05020043]
- National Science Foundation for Young Scientists of China [61701322]
- Suzhou science and technology project, China [SZ2018GG01, SZ2018GG01xp]
- Anhui province's key R&D projects, China [201904f06020051]
- Young and Middle-aged Science and Technology Innovation Talent Support Plan of Shenyang, China [RC190026]
With the advancement in IoT technology, Mobile Edge Computing (MEC) emerges as a new method to address the limited computation capacity of IoT devices. The proposed system cooperatively allocates computation and communication resources to minimize the overhead of IoT devices, as well as reduce latency and energy consumption. Results show that the system provides significant improvements compared to traditional models.
With the advancement in the development of the Internet of Things (IoT) technology, as well as the industrial IoT, various applications and services are benefiting from this emerging technology such as smart healthcare systems, virtual realities applications, connected and autonomous vehicles, to name a few. However, IoT devices are known for being limited computation capacities which is crucial to the device's availability time. Traditional approaches used to offload the applications to the cloud to ease the burden on the end user's devices, however, greater latency and network traffic issues still persist. Mobile Edge Computing (MEC) technology has emerged to address these issues and enhance the survivability of cloud infrastructure. While a lot of attempts have been made to manage an efficient process of applications offload, many of which either focus on the allocation of computational or communication protocols without considering a cooperative solution. In addition, a single-user scenario was considered. Therefore, we study multi-user IoT applications offloading for a MEC system, which cooperatively considers to allocate both the resources of computation and communication. The proposed system focuses on minimizing the weighted overhead of local IoT devices, and minimize the offload measured by the delay and energy consumption. The mathematical formulation is a typical mixed integer nonlinear programming (MINP), and this is an NP-hard problem. We obtain the solution to the objective function by splitting the objective problem into three sub-problems. Extensive set of evaluations have been performed so as to get the evaluation of the proposed model. The collected results indicate that offloading decisions, energy consumption, latency, and the impact of the number of IoT devices have shown superior improvement over traditional models.
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