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.

随着物联网（IoT）技术以及工业物联网的发展，各种应用程序和服务都将从这种新兴技术中受益，例如智能医疗系统，虚拟现实应用程序，联网和自动驾驶汽车等。一些。但是，IoT设备因其有限的计算能力而闻名，这对于设备的可用性时间至关重要。传统的方法用于将应用程序卸载到云上，以减轻最终用户设备的负担，但是，更大的延迟和网络流量问题仍然存在。移动边缘计算（MEC）技术已经出现，可以解决这些问题并增强云基础架构的生存能力。尽管已经进行了许多尝试来管理应用程序卸载的有效过程，其中许多都集中在计算协议或通信协议的分配上，而没有考虑协作解决方案。此外，还考虑了单用户方案。因此，我们研究了MEC系统的多用户IoT应用程序卸载，该系统协同考虑同时分配计算和通信资源。拟议的系统专注于最小化本地物联网设备的加权开销，并最小化由延迟和能耗测得的卸载。数学公式是典型的混合整数非线性规划（MINP），这是一个NP难题。通过将目标问题分为三个子问题，我们获得了目标函数的解。已经进行了广泛的评估，以便对所提出的模型进行评估。