Democratizing Cost-Effective Network Operations for Private Mobile Networking

Abstract

IoT 事業者からのプライベートLTE 等の自営網への期待が高まる一方で，無線通信の知識を持たない事業者にとって高効率なネットワーク運用の実現は困難である．本発表では，ネットワーク層のAI により事業者が意識することなく高効率なネットワーク運用を可能とすることを目的としたEdge Concierge を提案する．Edge Concierge実現に向けて，MEC において自己学習可能なコンテキスト推定技術を提案する．最後に，スマートシティを想定した評価結果を紹介する．

We observe two major revolutionary trends in network operations: democratization of cost-effective and flexible communication means for vertical players, such as public safety, by private mobile networking combined with edge computing, and automatic and autonomic network operations empowered by Artificial Intelligence (AI). Further innovations are required for making private networking readily available for vertical players who are reluctant to acquire expertise in complex network operations. We propose Edge Concierge, whose concept is to democratize cost-effective and flexible network operations using network layer AI at mobile edge computing (MEC) middle boxes. We evaluate our proposed system by taking public safety context of smart cities as an example use case.