Content Caching and Distribution in Smart Grid Enabled Wireless Networks

TL;DR

This paper proposes a smart grid-enabled wireless network framework with distributed caching, green energy sharing, and optimized user association to reduce on-grid power consumption while ensuring reliable multimedia content delivery.

Contribution

It introduces a novel joint resource allocation and user association scheme that leverages green energy sharing and multicasting in smart grid-enabled wireless networks.

Findings

Significant reduction in on-grid energy consumption achieved.

Effective utilization of green energy sharing among nodes.

Improved reliability and performance in multimedia content delivery.

Abstract

To facilitate wireless transmission of multimedia content to mobile users, we propose a content caching and distribution framework for smart grid enabled OFDM networks, where each popular multimedia file is coded and distributively stored in multiple energy harvesting enabled serving nodes (SNs), and the green energy distributively harvested by SNs can be shared with each other through the smart grid. The distributive caching, green energy sharing and the on-grid energy backup have improved the reliability and performance of the wireless multimedia downloading process. To minimize the total on-grid power consumption of the whole network, while guaranteeing that each user can retrieve the whole content, the user association scheme is jointly designed with consideration of resource allocation, including subchannel assignment, power allocation and power flow among nodes, where the user association scheme decides which SN serves which user. First, the optimal power allocated to each subchannel and the power flows among nodes are derived analytically. Then, the user association problem is decoupled from the subchannel assignment problem, and the proposed user association scheme has leveraged the multicasting nature of the content download process. To decide which subchannel is assigned to which node, the number of subchannels assigned to each node is first determined, according to the green energy generating rate and the associated traffic offload, and then the corresponding subchannels are selected from the total assigned system spectrum. Simulation results demonstrate that bringing content, green energy and serving node closer to the end user can notably reduce the on-grid energy consumption.