13 research outputs found
The Quest for Scalability and Accuracy in the Simulation of the Internet of Things: an Approach based on Multi-Level Simulation
This paper presents a methodology for simulating the Internet of Things (IoT)
using multi-level simulation models. With respect to conventional simulators,
this approach allows us to tune the level of detail of different parts of the
model without compromising the scalability of the simulation. As a use case, we
have developed a two-level simulator to study the deployment of smart services
over rural territories. The higher level is base on a coarse grained,
agent-based adaptive parallel and distributed simulator. When needed, this
simulator spawns OMNeT++ model instances to evaluate in more detail the issues
concerned with wireless communications in restricted areas of the simulated
world. The performance evaluation confirms the viability of multi-level
simulations for IoT environments.Comment: Proceedings of the IEEE/ACM International Symposium on Distributed
Simulation and Real Time Applications (DS-RT 2017
Towards a Model-driven Performance Prediction Approach for Internet of Things Architectures
Indisputable, security and interoperability play major concerns in Internet of Things (IoT) architectures and applications. In this paper, however, we emphasize the role and importance of performance and scalability as additional, crucial aspects in planning and building sustainable IoT solutions. IoT architectures are complicated system-of-systems that include different developer roles, development processes, organizational units, and a multilateral governance. Its performance is often neglected during development but becomes a major concern at the end of development and results in supplemental efforts, costs, and refactoring. It should not be relied on linearly scaling for such systems only by using up-to-date technologies that may promote such behavior. Furthermore, different security or interoperability choices also have a considerable impact on performance and may result in unforeseen trade-offs. Therefore, we propose and pursue the vision of a model-driven approach to predict and evaluate the performance of IoT architectures early in the system lifecylce in order to guarantee efficient and scalable systems reaching from sensors to business applications
Modeling the Internet of Things: a simulation perspective
This paper deals with the problem of properly simulating the Internet of
Things (IoT). Simulating an IoT allows evaluating strategies that can be
employed to deploy smart services over different kinds of territories. However,
the heterogeneity of scenarios seriously complicates this task. This imposes
the use of sophisticated modeling and simulation techniques. We discuss novel
approaches for the provision of scalable simulation scenarios, that enable the
real-time execution of massively populated IoT environments. Attention is given
to novel hybrid and multi-level simulation techniques that, when combined with
agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches,
can provide means to perform highly detailed simulations on demand. To support
this claim, we detail a use case concerned with the simulation of vehicular
transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High
Performance Computing and Simulation (HPCS 2017
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
MoSIoT: Modeling and Simulating IoT Healthcare-Monitoring Systems for People with Disabilities
The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases. However, to achieve their full potential, these devices must efficiently address the customization demanded by different IoT HMS scenarios. This work introduces a new approach, called Modeling Scenarios of Internet of Things (MoSIoT), which allows healthcare experts to model and simulate IoT HMS scenarios defined for different disabilities and diseases. MoSIoT comprises a set of models based on the model-driven engineering (MDE) paradigm, which first allows simulation of a complete IoT HMS scenario, followed by generation of a final IoT system. In the current study, we used a real scenario defined by a recognized medical publication for a patient with Alzheimer’s disease to validate this proposal. Furthermore, we present an implementation based on an enterprise cloud architecture that provides the simulation data to a commercial IoT hub, such as Azure IoT Central.This work was supported by the Spanish Ministry of Science and Innovation under contract PID2019-111196RB-I00, called “Development of IoT Systems for People with Disabilities” (Access@IoT), and also was partially funded by the GVA through the AICO/2020/143 project
A context-aware encryption protocol suite for edge computing-based IoT devices
Heterogeneous devices are connected with each other through wireless links within a cyber physical system. These devices undergo resource constraints such as battery, bandwidth, memory and computing power. Moreover, the massive interconnections of these devices result in network latency and reduced speed. Edge computing offers a solution to this problem in which devices transmit the preprocessed actionable data in a formal way, resulting in reduced data traffic and improved speed. However, to provide the same level of security to each piece of information is not feasible due to limited resources. In addition, not all the data generated by Internet of things devices require a high level of security. Context-awareness principles can be employed to select an optimal algorithm based on device specifications and required information confidentiality level. For context-awareness, it is essential to consider the dynamic requirements of data confidentiality as well as device available resources. This paper presents a context-aware encryption protocol suite that selects optimal encryption algorithm according to device specifications and the level of data confidentiality. The results presented herein clearly exhibit that the devices were able to save 79% memory consumption, 56% battery consumption and 68% execution time by employing the proposed context-aware encryption protocol suite
A Simulation Platform for Large-Scale Internet of Things Scenarios in Urban Environments
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 speci c topologies. In this paper, we illustrate an e cient 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