Distributed Load Management Algorithms in Anycast-based CDNs

TL;DR

This paper develops and evaluates distributed algorithms for load management in anycast-based CDNs, addressing the challenges of partial routing control and proposing solutions that balance optimality and complexity.

Contribution

It introduces a convex optimization framework with a fully-distributed algorithm using FastControl packets and analyzes a practical greedy heuristic for load balancing.

Findings

The convex optimization approach effectively manages load distribution.

The greedy heuristic is simpler but has stability limitations.

Trace-driven simulations compare the algorithms' performance.

Abstract

Anycast is an internet addressing protocol where multiple hosts share the same IP-address. A popular architecture for modern Content Distribution Networks (CDNs) for geo-replicated services consists of multiple layers of proxy nodes for service and co-located DNS-servers for load-balancing among different proxies. Both the proxies and the DNS-servers use anycast addressing, which offers simplicity of design and high availability of service at the cost of partial loss of routing control. Due to the very nature of anycast, redirection actions by a DNS-server also affects loads at nearby proxies in the network. This makes the problem of optimal distributed load management highly challenging. In this paper, we propose and evaluate an analytical framework to formulate and solve the load-management problem in this context. We consider two distinct algorithms. In the first half of the paper, we pose the load-management problem as a convex optimization problem. Following a Kelly-type dual decomposition technique, we propose a fully-distributed load-management algorithm by introducing FastControl packets. This algorithm utilizes the underlying anycast mechanism itself to enable effective coordination among the nodes, thus obviating the need for any external control channel. In the second half of the paper, we consider an alternative greedy load-management heuristic, currently in production in a major commercial CDN. We study its dynamical characteristics and analytically identify its operational and stability properties. Finally, we critically evaluate both the algorithms and explore their optimality-vs-complexity trade-off using trace-driven simulations.