inis 22(30): e2

Research Article

Content Delivery From the Sky: Drone-Aided Load Balancing for Mobile-CDN

Download455 downloads
  • @ARTICLE{10.4108/eai.9-3-2022.173606,
        author={T. Bilen and B. Canberk},
        title={Content Delivery From the Sky: Drone-Aided Load Balancing for Mobile-CDN},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={9},
        number={30},
        publisher={EAI},
        journal_a={INIS},
        year={2022},
        month={3},
        keywords={Mobile Content Delivery Networks, Drone, Load Balancing, Barabasi-Albert Model, Queuing Model},
        doi={10.4108/eai.9-3-2022.173606}
    }
    
  • T. Bilen
    B. Canberk
    Year: 2022
    Content Delivery From the Sky: Drone-Aided Load Balancing for Mobile-CDN
    INIS
    EAI
    DOI: 10.4108/eai.9-3-2022.173606
T. Bilen1,*, B. Canberk2
  • 1: Computer Engineering Department, Faculty of Computer and Informatics, Istanbul Technical University, Istanbul-Turkey
  • 2: Artificial Intelligence and Data Engineering Department, Faculty of Computer and Informatics, Istanbul Technical University, Istanbul-Turkey
*Contact email: bilent@itu.edu.tr

Abstract

The Base Station based Mobile-CDN architecture redirects the content request of mobile users to other base stations during storage misses. These request redirections increase the latency of a mobile client through unbalanced load distributions among base stations. To solve the unbalanced load distribution and latency problems, we propose to deliver the content from the sky by deploying drones as aerial content delivery points. This drone based deployment enables a more effective and inexpensive solution without changing Mobile-CDN architecture. Here, we select different queuing theoretical models for drones and base stations due to the drones’ small capacity. With base station modeling, we can decide the loaded base stations to transfer the drones by utilizing the Barabasi-Albert Model. With drone modeling, we can obtain blocking probabilities with the Erlang-B parameter to determine additional drone transfer. According to simulations, the latency of mobile client originating requests are reduced by 25% compared to conventional Base Station based Mobile-CDN architecture.