Optimal Multicast Service Chain Control: Packet Processing, Routing, and Duplication

TL;DR

This paper develops a distributed control policy for multicast stream-processing in cloud networks, optimizing throughput and operational costs by efficient packet duplication, routing, and processing.

Contribution

It introduces the first fully distributed multicast traffic management policy that stabilizes any feasible input rate while minimizing costs in distributed computing networks.

Findings

The policy achieves throughput-optimal multicast delivery.

It minimizes operational costs compared to existing methods.

Numerical results confirm effectiveness in real network scenarios.

Abstract

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.