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

arXiv: https://arxiv.org/abs/1612.00122 · HTML: https://mlsanity.com/paper/1612.00122/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Dec 2016.

## Built on by (most cited first, 2 of 2)

- [Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey](https://mlsanity.com/paper/2302.02573/) (2023)
- [Smart Traffic Monitoring System using Computer Vision and Edge Computing](https://mlsanity.com/paper/2109.03141/) (2021)

## Abstract (arXiv)

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.