2L-MC3: A Two-Layer Multi-Community-Cloud/Cloudlet Social Collaborative Paradigm for Mobile Edge Computing

Abstract

Mobile edge computing (MEC) is providing a promising solution for augmenting the computing and storage capacity of mobile devices by exploiting the available resources at the network edge. Among the various Internet of Things (IoT) applications, MEC could help us to narrow the gap between the requirements of IoT applications and the limited resources of IoT devices and to achieve the energy-efficient communication and computing. Importantly, the upper and edge infrastructure of cloud computing should effectively collaborate for executing the complex tasks which are requested by mobile users. In particular, community cloud computing, as a novel computational model for a specific community with common concerns (such as security, compliance, and jurisdiction), can make full use of the spare resources of networked computers to provide the facilities so that the community gains services from them. However, how to allocate the subtasks into community clouds and edge community clouds (cloudlets) is becoming a critical challenge. To tackle this challenge, this paper first proposes a two-layer multicommunity-cloud/doudlet social collaborative paradigm, called 2L-MC3 for MEC. Further, we formulate a problem on tasks allocation in community clouds/cloudlets by jointly taking task offloading, tasks and clouds profiles into account. To address this problem, we devise a bi-level programming model for tasks allocation. Extensive simulations are conducted for demonstrating that the proposed approach can achieve the relative global performance for satisfying the each metric comparing to the other approaches.