Mobile Device Association and Resource Allocation in Small-Cell IoT Networks with Mobile Edge Computing and Caching
Tianqing Zhou, Yali Yue, Dong Qin, Xuefang Nie, Xuan Li, Chunguo Li

TL;DR
This paper proposes a joint mobile device association and resource allocation framework for small-cell IoT networks with mobile edge computing and caching, aiming to minimize weighted delays and improve system performance.
Contribution
It introduces a novel alternating optimization algorithm based on coalitional game theory for joint MD association and resource allocation in small-cell IoT networks.
Findings
The proposed algorithm outperforms traditional association methods in reducing delays.
Resource partitioning mechanisms effectively mitigate interference.
Simulation results validate the efficiency of the joint optimization approach.
Abstract
To meet the need of computation-sensitive (CS) and high-rate (HR) communications, the framework of mobile edge computing and caching has been widely regarded as a promising solution. When such a framework is implemented in small-cell IoT (Internet of Tings) networks, it is a key and open topic how to assign mobile edge computing and caching servers to mobile devices (MDs) with CS and HR communications. Since these servers are integrated into small base stations (BSs), the assignment of them refers to not only the BS selection (i.e., MD association), but also the selection of computing and caching modes. To mitigate the network interference and thus enhance the system performance, some highly-effective resource partitioning mechanisms are introduced for access and backhaul links firstly. After that a problem with minimizing the sum of MDs' weighted delays is formulated to attain a goal…
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Taxonomy
TopicsCaching and Content Delivery · IoT and Edge/Fog Computing · Advanced Wireless Communication Technologies
