Implementation of network-coded cooperation for energy efficient content distribution in 5g mobile small cells
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
The continuous increase of mobile data traffic calls for the design of energy-efficient content distribution mechanisms, to be incorporated in the fifth generation of mobile networks, 5G. One of the biggest concerns of the companies and the research community is to reduce the energy consumption in both the user equipments (UEs) and the network equipment. In this article, we present a novel content distribution framework called Network-Coded Cooperative (NCC) Networks, which benefits from the interplay between mobile clouds (MC) and Random Linear Network Coding (RLNC) to reduce the overall energy consumption in the devices that take part in the communication. This novel framework leads to reduced energy consumption by offloading the cellular interface to a link with greater energy efficiency, for instance, WiFi, within the mobile small cell. We evaluate the performance of our framework analytically and in practical implementation (i.e., testbed) in terms of throughput, energy savings, packet decoding ratio, latency, and synchronicity. In comparison to the conventional content distribution system, for the case of four users, the analytical model and the testbed implementation show energy savings of more than 12% and 8%, respectively. Furthermore, network usage is reduced, losses are neutralized, and the content is synchronously distributed to all users.
Details
Original language | English |
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Pages (from-to) | 185964-185980 |
Number of pages | 17 |
Journal | IEEE access |
Volume | 8 |
Publication status | Published - 2020 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0001-7008-1537/work/158767467 |
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ORCID | /0000-0001-8469-9573/work/161891189 |
Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Cellular networks, Content distribution, Cooperative communication, Energy efficiency, Mobile small cells, Network coding, Random linear network coding (RLNC), Traffic offload