Learning-aided Hybrid SDC Control in Mobile Ad Hoc Networks

Abstract Software Defined Coalition (SDC) is a promising architecture for flexibly controlling network resources in tactical environments. In highly dynamic mobile ad hoc network scenarios, however, the SDC controllers may be fragmented from the mobile nodes they manage rendering impossible their in-time resource reconfiguration and causing severe network performance degradation. To address this challenge, we explore the idea of complementing the SDC controllers with distributed control mechanisms running locally at the mobile nodes in a hybrid architecture design. We then apply learning methods to dynamically tune the coordination among the two control paradigms, centralized and distributed. We show the benefits of our hybrid approach in a demo emulating a real tactical ad hoc network scenario using the Anglova tactical ad hoc network dataset.
  • Qiaofeng Qin (Yale)
  • Konstantinos Poularakis (Yale)
  • Leandros Tassiulas (Yale)
  • Dave Conway-Jones (IBM UK)
  • Andreas Martens (IBM UK)
  • Paul Yu (ARL)
Date Sep-2020
Venue 4th Annual Fall Meeting of the DAIS ITA, 2020