2022/05/31 by Yang Cai, Jaime Llorca, Cai, Yang +5 · 1 citation
Computer Science · #FOS: Computer and information sciences #FOS: Electrical engineering #Mobile Ad Hoc Networks #Network Traffic and Congestion Control #Networking and Internet Architecture (cs.NI) #Software-Defined Networks and 5G #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2205.15557
openalex publication_date 2022/05/31 · openalex created_date 2022/11/19 · openalex updated_date 2026/07/28
Distributed computing (cloud) networks, e.g., mobile edge computing (MEC), are playing an increasingly important role in the efficient hosting, running, and delivery of real-time stream-processing applications such as industrial automation, immersive video, and augmented reality. While such applications require timely processing of real-time streams that are simultaneously useful for multiple users/devices, existing technologies lack efficient mechanisms to handle their increasingly multicast nature, leading to unnecessary traffic redundancy and associated network congestion. In this paper, we address the design of distributed packet processing, routing, and duplication policies for optimal control of multicast stream-processing services. We present a characterization of the enlarged capacity region that results from efficient packet duplication, and design the first fully distributed multicast traffic management policy that stabilizes any input rate in the interior of the capacity region while minimizing overall operational cost. Numerical results demonstrate the effectiveness of the proposed policy to achieve throughput- and cost-optimal delivery of stream-processing services over distributed computing networks.