Internet of Things — A paradigm shift of future Internet applications

Author(s):  
Sarita Agrawal ◽  
Manik Lal Das
Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 78
Author(s):  
Pedro Victor Borges ◽  
Chantal Taconet ◽  
Sophie Chabridon ◽  
Denis Conan ◽  
Thais Batista ◽  
...  

The rising popularity of the Internet of Things (IoT) has led to a plethora of highly heterogeneous, geographically dispersed devices. In recent years, IoT platforms have been used to provide a variety of services to applications such as device discovery, context management, and data analysis. However, the lack of standardization currently means that each IoT platform comes with its own abstractions, APIs, and interactions. As a consequence, programming the interactions between an application and an IoT platform is often time consuming, error prone, and depends on the developers’ level of knowledge about the IoT platform. To address these issues, we propose offering to application developers on the client side the possibility to declare variables that are automatically mapped to sensors and whose values are transparently updated with sensor observations. For this purpose, we introduce IoTVar, a middleware between IoT applications and platforms. In IoTVar, all the necessary interactions with IoT platforms are managed by proxies. This paper presents IoTVar integrated with the FIWARE platform, which is used for developing IoT Future Internet applications. We also report results of some experiments performed to evaluate IoTVar, showing IoTVar reduces the effort required to declare and manage IoT variables and its impact in terms of CPU, memory, and energy.


Author(s):  
Amar Abane ◽  
Mehammed Daoui ◽  
Samia Bouzefrane ◽  
Soumya Banerjee ◽  
Paul Muhlethaler

IP has been designed for Internet decades ago to connect computers and share expensive resources such as tape drives and printers. Nowadays, Internet of Things and other emerging applications use Internet to fetch and exchange content such as monitoring data and movies. This content-centric use of Internet highlights the limitations of the IP architecture. IETF Working Groups spend significant efforts to adapt the traditional IP stack to IoT systems, but the shortcomings of IP remain difficult to hide. In this context, the recently emerged Named Data Networking (NDN) architecture promises a better support of IoT systems and future Internet applications. This paper describes a realistic IoT architecture based on NDN. In practice, an integration of NDN in IoT devices over low-power wireless technologies is designed, deployed and evaluated considering a Smart Farming application scenario. This work aims to show that NDN is more suitable than IP for IoT systems, by giving another look at IP-based solutions for the IoT such as 6LoWPAN. For that, we design a simple packet compression scheme and a lightweight forwarding strategy that is compliant with the NDN vision while managing constrained devices. Evaluation result demonstrate the flexibility of NDN to support IoT environments.


2021 ◽  
Vol 11 (1) ◽  
pp. 377
Author(s):  
Michele Scarpiniti ◽  
Enzo Baccarelli ◽  
Alireza Momenzadeh ◽  
Sima Sarv Ahrabi

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.


2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Federica Paganelli ◽  
David Parlanti

Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users’ quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of “smart things” on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Internet of Things. The proposed solution adopts a peer-to-peer approach for guaranteeing scalability, robustness, and easy maintenance of the overall system. While most existing peer-to-peer discovery services proposed for the IoT support solely exact match queries on a single attribute (i.e., the object identifier), our solution can handle multiattribute and range queries. We defined a layered approach by distinguishing three main aspects: multiattribute indexing, range query support, peer-to-peer routing. We chose to adopt an over-DHT indexing scheme to guarantee ease of design and implementation principles. We report on the implementation of a Proof of Concept in a dangerous goods monitoring scenario, and, finally, we discuss test results for structural properties and query performance evaluation.


Crimen ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 255-271
Author(s):  
Sanja Milivojević ◽  
Elizabeth Radulski

The Internet of Things (IoT) is poised to revolutionise the way we live and communicate, and the manner in which we engage with our social and natural world. In the IoT, objects such as household items, vending machines and cars have the ability to sense and share data with other things, via wireless, Bluetooth, or Radio Frequency IDentification (RFID) technology. "Smart things" have the capability to control their performance, as well as our experiences and decisions. In this exploratory paper, we overview recent developments in the IoT technology, and their relevance for criminology. Our aim is to partially fill the gap in the literature, by flagging emerging issues criminologists and social scientists ought to engage with in the future. The focus is exclusively on the IoT while other advances, such as facial recognition technology, are only lightly touched upon. This paper, thus, serves as a starting point in the conversation, as we invite scholars to join us in forecasting-if not preventing-the unwanted consequences of the "future Internet".


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