A Local Facility Location Algorithm for Large-scale Distributed Systems

In a facility location problem (FLP) we are given a set of facilities and a set of clients, each of which is to be served by one facility. The goal is to decide which subset of facilities to open, such that the clients will be served at a minimal cost. In this paper we investigate the FLP in a setting where the cost depends on data known only to the clients. This setting typifies modern distributed systems: peer-to-peer file sharing networks, Grid systems, and wireless sensor networks. All of them need to perform network organization, data placement, collective power management, and other tasks of this kind. We propose a local and efficient algorithm that solves FLP in these settings. The algorithm presented here is extremely scalable, entirely decentralized, requires no routing capabilities, and is resilient to failures and changes in the data throughout its execution.