An Extension to iFogSim to Enable the Design of Data Placement Strategies

Abstract

Fog computing consists in extending Cloud services down to the network edge by using resources such as base stations, routers and switches. It presents a dense, heterogeneous and geo-distributed infrastructure which pushes to investigate how data are placed within this infrastructure in order to minimize service latency, network utilization and energy consumption. iFogSim is a Fog and IoT environments simulator dedicated to manage IoT services in a Fog infrastructure. In this paper, we present an extension to iFogSim to be able to model and simulate scenarios with strategies aiming to optimize data placement in Fog and IoT contexts. Data placement problem is NP-Hard due to the large number of Fog nodes and the high amount of data to be placed. Thus, we added a support to divide and conquer strategies to subdivide the issued infrastructure into several parts hence reducing the data placement computing time. Moreover, the extension involves a generic smart city scenario with different workloads making it possible for the users to investigate the behavior of their strategies using various workloads. In order to optimize the execution time of the simulations, we parallelized the Floyd-Warshall algorithm. This algorithm is used in iFogSim to compute all shortest paths between nodes in order to simulate data transmission. We have evaluated this extension using the proposed smart city scenario with various infrastructure configurations. The experiments show that our extension has a small overhead in terms of simulation time and memory utilization.