Internet of Things (IoT) aims to bring every object (e.g. smart cameras, wearable, environmental sensors, home appliances, and vehicles) online, hence generating massive amounts of data that can overwhelm storage systems and data analytics applications. Cloud computing offers services at the infrastructure level that can scale to IoT storage and processing requirements. However, there are applications such as health monitoring and emergency response that require low latency, and delay caused by transferring data to the cloud and then back to the application can seriously impact their performances. To overcome this limitation, Fog computing paradigm has been proposed, where cloud services are extended to the edge of the network to decrease the latency and network congestion. To realize the full potential of Fog and IoT paradigms for real-time analytics, several challenges need to be addressed. The first and most critical problem is designing resource management techniques that determine which modules of analytics applications are pushed to each edge device to minimize the latency and maximize the throughput. To this end, we need a evaluation platform that enables the quantification of performance of resource management policies on an IoT or Fog computing infrastructure in a repeatable manner. In this paper we propose a simulator, called iFogSim, to model IoT and Fog environments and measure the impact of resource management techniques in terms of latency, network congestion, energy consumption, and cost. We describe two case studies to demonstrate modeling of an IoT environment and comparison of resource management policies. Moreover, scalability of the simulation toolkit in terms of RAM consumption and execution time is verified under different circumstances.
The FIT IoT-LAB @cite_19 is a testbed equipped with thousands of wireless nodes located in six different sites across France. It allows users to evaluate and test their novel ideas ranging from low level protocols to advanced Analytic and services in a very large scale wireless IoT environment. Major services offered by IoT-LAB include: 1) Remote access to sensors and gateways: the testbed provides users with APIs to flash any firmware, design, build, and compile applications; 2) Access to the serial ports of reserved IoT devices; 3) Internet access for nodes with end-to-end IP connection using IPv6 and 6LoWPAN; 4) Power consumption monitoring per device; 5) and robots to test and improve real-time decision making in IoT context.
@cite_19
2202090419
This paper introduces the FIT IoT-LAB testbed, an open testbed composed of 2728 low-power wireless nodes and 117 mobile robots available for experimenting with large-scale wireless IoT technologies, ranging from low-level protocols to advanced Internet services. IoT-LAB is built to accelerate the development of tomorrow's IoT technology by offering an accurate open-access and open-source multi-user scientific tool. The IoT-LAB testbed is deployed in 6 sites across France. Each site features different node and hardware capabilities, but all sites are interconnected and available through the same web portal, common REST interfaces and consistent CLI tools. The result is a heterogeneous testing environment, which covers a large spectrum of IoT use cases and applications. IoT-LAB is a one-of-a-kind facility, allowing anyone to test their solution at scale, experiment and fine-tune new networking concept. The Internet of Things has drawn lots of research attention as the growing number of devices connected to the Internet. Long Term Evolution-Advanced (LTE-A) is a promising technology for wireless communication and it's also promising for IoT. The main challenge of incorporating IoT devices into LTE-A is a large number of IoT devices attempting to access the network in a short period which will greatly reduce the network performance. In order to improve the network utilization, we adopted a hierarchy architecture using a gateway for connecting the devices to the eNB and proposed a multiclass resource allocation algorithm for LTE based IoT communication. Simulation results show that the proposed algorithm can provide good performance both on data rate and latency for different QoS applications both in saturated and unsaturated environment. Despite technological advances, most smart objects in the Internet of Things (IoT) cannot be accessed using technologies designed and developed for interacting with powerful Internet servers. IoT use cases involve devices that not only have limited resources, but also they are not always connected to the Internet and are physically exposed to tampering. In this paper, we describe the design, development, and evaluation of a smart contract-based solution that allows end-users to securely interact with smart devices. Our approach enables access control, Thing authentication, and payments in a fully decentralized setting, taking at the same time into consideration the limitations and constraints imposed by both blockchain technologies and the IoT paradigm. Our prototype implementation is based on existing technologies, i.e., Ethereum smart contracts, which makes it realistic and fundamentally secure. With the development of new technologies, these last years have witnessed the emergence of a new paradigm: the Internet of Things (IoT) and of the physical world. We are now able to communicate and interact with our surrounding environment through the use of multiple tiny sensors, RFID technologies or small wireless robots. This allows a set of new applications and usages to be envisioned ranging from logistic and traceability purposes to emergency and rescue operations going through the monitoring of volcanos or forest fires. However, all this comes with several technical and scientific issues like how to ensure the reliability of wireless communications in disturbed environments, how to manage efficiently the low resources (energy, memory, etc.) or how to set a safe and sustainable (both hardware and software) platform maintenance. All these issues are addressed by researchers all around the world but solutions designed for IoT need to face real experimentations to be validated. To ease such experimentations for IoT, several experimental testbeds have been deployed offering diverse and heterogeneous services and tools. In this article, we study the different requirements and features such facilities should offer. We survey the different experimental facilities currently available for the community, describe their characteristics. In particular, we detail the different hardware used for sensor networks and robot platforms and the scope of services the different facilities offer with a specific focus on testbeds which enable experimentations with mobility. We expect this survey assist a potential user to easily choose the one to use regarding his own needs. Finally, we identify existing gaps and difficulties and investigate new directions for such facilities.