Optimization policy for file replica placement in fog domains

TL;DR

This paper introduces a novel data replication placement policy in fog computing that enhances data availability, reduces latency, and optimizes network usage by leveraging complex network models and graph algorithms.

Contribution

It proposes a new placement policy based on network topology and centrality metrics, outperforming existing methods in latency and network efficiency.

Findings

Shortest latency times achieved, especially for writing operations

Reduced network usage compared to other policies

Similar data availability to FogStore

Abstract

Fog computing architectures distribute computational and storage resources along the continuum from the cloud to things. Therefore, the execution of services or the storage of files can be closer to the users. The main objectives of fog computing domains are to reduce the user latency and the network usage. Availability is also an issue in fog architectures because the topology of the network does not guarantee redundant links between devices. Consequently, the definition of placement polices is a key challenge. We propose a placement policy for data replication to increase data availability that contrasts with other storage policies that only consider a single replica of the files. The system is modeled with complex weighted networks and topological features, such as centrality indices. Graph partition algorithms are evaluated to select the fog devices that store data replicas. Our approach is compared with two other placement policies: one that stores only one replica and FogStore, which also stores file replicas but uses a greedy approach (the shortest path). We analyze 22 experiments with simulations. The results show that our approach obtains the shortest latency times, mainly for writing operations, a smaller network usage increase, and a similar file availability to FogStore.