Towards Hierarchical Mobile Edge Computing: An Auction-Based Profit Maximization Approach

TL;DR

This paper introduces a hierarchical mobile edge computing model with an auction-based resource allocation strategy to optimize profit and QoS across multiple cloudlet tiers in IoT networks.

Contribution

It proposes a novel three-level cloudlet hierarchy and a two-scale auction-based approach for resource allocation in hierarchical MEC systems.

Findings

Enhanced profit through auction-based resource management

Effective QoS satisfaction for IoT users

Hierarchical cloudlet model improves resource efficiency

Abstract

The multi-tiered concept of Internet of Things (IoT) devices, cloudlets and clouds is facilitating a user-centric IoT. However, in such three tier network, it is still desirable to investigate efficient strategies to offer the computing, storage and communications resources to the users. To this end, this paper proposes a new hierarchical model by introducing the concept of field, shallow, and deep cloudlets where the cloudlet tier itself is designed in three hierarchical levels based on the principle of LTE-Advanced backhaul network. Accordingly, we explore a two time scale approach in which the computing resources are offered in an auction-based profit maximization manner and then the communications resources are allocated to satisfy the users' QoS.