A Distributed Control Law for Load Balancing in Content Delivery Networks

Abstract

In this paper, we face the challenging issue of defining and implementing an effective law for load balancing in Content Delivery Networks (CDNs). We base our proposal on a formal study of a CDN system, carried out through the exploitation of a fluid flow model characterization of the network of servers. Starting from such characterization, we derive and prove a lemma about the network queues equilibrium. This result is then leveraged in order to devise a novel distributed and time-continuous algorithm for load balancing, which is also reformulated in a time-discrete version. The discrete formulation of the proposed balancing law is eventually discussed in terms of its actual implementation in a real-world scenario. Finally, the overall approach is validated by means of simulations.

Existing System

In a queue-adjustment strategy, the scheduler is located after the queue and just before the server. The scheduler might assign the request pulled out from the queue to either the local server or a remote server depending on the status of the system queues. In a rate-adjustment model, instead the scheduler is located just before the local queue: Upon arrival of a new request, the scheduler decides whether to assign it to the local queue or send it to a remote server. In a hybrid-adjustment strategy for load balancing, the scheduler is allowed to control both the incoming request rate at a node and the local queue length. Thus in Existing systems, Upon arrival of a new request, indeed, a CDN server can either elaborate locally the request or redirect it to other servers according to a certain decision rule, which is based on the state information exchanged by the servers. Such an approach limits state exchanging overhead to just local servers.

Proposed System

In a similar way, in this paper we first design a suitable load-balancing law that assures equilibrium of the queues in a balanced CDN by using a fluid flow model for the network of servers. Then, we discuss the most notable implementation issues associated with the proposed load-balancing strategy. We present a new mechanism for redirecting incoming client requests to the most appropriate server, thus balancing the overall system requests load. Our mechanism leverages local balancing in order to achieve global balancing. This is carried out through a periodic interaction among the system nodes.

Architecture