Research Article
A Simulation Platform for Large-Scale Internet of Things Scenarios in Urban Environments
@INPROCEEDINGS{10.4108/icst.urb-iot.2014.257268, author={Giacomo Brambilla and Marco Picone and Simone Cirani and Michele Amoretti and Francesco Zanichelli}, title={A Simulation Platform for Large-Scale Internet of Things Scenarios in Urban Environments}, proceedings={The First International Conference on IoT in Urban Space}, publisher={ACM}, proceedings_a={URB-IOT}, year={2014}, month={11}, keywords={internet of things discrete event simulation urban environments smart cities}, doi={10.4108/icst.urb-iot.2014.257268} }
- Giacomo Brambilla
Marco Picone
Simone Cirani
Michele Amoretti
Francesco Zanichelli
Year: 2014
A Simulation Platform for Large-Scale Internet of Things Scenarios in Urban Environments
URB-IOT
ICST
DOI: 10.4108/icst.urb-iot.2014.257268
Abstract
The Internet of Things (IoT) refers to the interconnection of billions of IP-enabled devices, denoted as "smart objects", with limited capabilities, in terms of computational power and memory capacity, which typically operate in constrained environments, in an Internet-like structure. Large-scale systems and applications that rely on such a high number of devices, due to their complexity, need careful analysis and test, before being deployed to target environments. Traditional IoT simulators do not focus on the simulation of large scale deployments, as they are intended to evaluate and analyze low-level networking aspects, with groups of smart objects arranged in specific topologies.
In this paper, we illustrate an efficient simulation methodology, which is particularly suitable to test IoT systems with a large number of interconnected devices in Urban environments from an application-layer perspective. The main advantages of such an approach are: i) the capability to simulate large-scale systems with thousands of geographically distributed devices; ii) the maximization of code reuse; and iii) the high generality of simulated nodes, which can be characterized by multiple network interfaces and protocols, as well as different mobility, network, and energy consumption models.