Strategies for Replica Placement in Tree Networks

TL;DR

This paper explores and compares different replica placement policies in tree networks, analyzing their costs, server heterogeneity effects, and providing efficient heuristics for complex instances.

Contribution

Introduces two new replica placement policies, assesses their impact on costs, and offers polynomial heuristics for NP-complete problems in tree networks.

Findings

New policies affect total replication costs significantly

Server heterogeneity impacts placement strategies

Heuristics perform well compared to lower bounds

Abstract

In this paper, we discuss and compare several policies to place replicas in tree networks, subject to server capacity and QoS constraints. The client requests are known beforehand, while the number and location of the servers are to be determined. The standard approach in the literature is to enforce that all requests of a client be served by the closest server in the tree. We introduce and study two new policies. In the first policy, all requests from a given client are still processed by the same server, but this server can be located anywhere in the path from the client to the root. In the second policy, the requests of a given client can be processed by multiple servers. One major contribution of this paper is to assess the impact of these new policies on the total replication cost. Another important goal is to assess the impact of server heterogeneity, both from a theoretical and a practical perspective. In this paper, we establish several new complexity results, and provide several efficient polynomial heuristics for NP-complete instances of the problem. These heuristics are compared to an absolute lower bound provided by the formulation of the problem in terms of the solution of an integer linear program.