Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Cross-layer optimization for cooperative content distribution in multihop device-to-device networks

Xu, Chen, Feng, Junhao, Zhou, Zhenyu, Wu, Jun and Perera, Charith 2019. Cross-layer optimization for cooperative content distribution in multihop device-to-device networks. IEEE Internet of Things 6 (1) , pp. 278-287. 10.1109/JIOT.2017.2741718

[img]
Preview
PDF - Accepted Post-Print Version
Download (1MB) | Preview

Abstract

With the ubiquity of wireless network and the intelligentization of machines, Internet of Things (IoT) has come to people's horizon. Device-to-device (D2D), as one advanced technique to achieve the vision of IoT, supports a high speed peer-to-peer transmission without fixed infrastructure forwarding which can enable fast content distribution in local area. In this paper, we address the content distribution problem by multihop D2D communication with decentralized content providers locating in the networks. We consider a cross-layer multidimension optimization involving frequency, space, and time, to minimize the network average delay. Considering the multicast feature, we first formulate the problem as a coalitional game based on the payoffs of content requesters, and then, propose a time-varying coalition formation-based algorithm to spread the popular content within the shortest possible time. Simulation results show that the proposed approach can achieve a fast content distribution across the whole area, and the performance on network average delay is much better than other heuristic approaches.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 2327-4662
Date of First Compliant Deposit: 11 August 2020
Date of Acceptance: 13 August 2017
Last Modified: 25 Nov 2020 14:19
URI: http://orca.cf.ac.uk/id/eprint/134087

Citation Data

Cited 9 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics