When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Survey on Lightweight Primitives and Protocols for RFID in Wireless Sensor Networks

The use of radio frequency identification (RFID) technologies is becoming widespread in all kind of wireless network-based applications. As expected, applications based on sensor networks, ad-hoc or mobile ad hoc networks (MANETs) can be highly benefited from the adoption of RFID solutions. There is a strong need to employ lightweight cryptographic primitives for many security applications because of the tight cost and constrained resource requirement of sensor based networks. This paper mainly focuses on the security analysis of lightweight protocols and algorithms proposed for the security of RFID systems. A large number of research solutions have been proposed to implement lightweight cryptographic primitives and protocols in sensor and RFID integration based resource constraint networks. In this work, an overview of the currently discussed lightweight primitives and their attributes has been done. These primitives and protocols have been compared based on gate equivalents (GEs), power, technology, strengths, weaknesses and attacks. Further, an integration of primitives and protocols is compared with the possibilities of their applications in practical scenarios

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Energy Management in RFID-Sensor Networks: Taxonomy and Challenges

Ubiquitous Computing is foreseen to play an important role for data production and network connectivity in the coming decades. The Internet of Things (IoT) research which has the capability to encapsulate identification potential and sensing capabilities, strives towards the objective of developing seamless, interoperable and securely integrated systems which can be achieved by connecting the Internet with computing devices. This gives way for the evolution of wireless energy harvesting and power transmission using computing devices. Radio Frequency (RF) based Energy Management (EM) has become the backbone for providing energy to wireless integrated systems. The two main techniques for EM in RFID Sensor Networks (RSN) are Energy Harvesting (EH) and Energy Transfer (ET). These techniques enable the dynamic energy level maintenance and optimisation as well as ensuring reliable communication which adheres to the goal of increased network performance and lifetime. In this paper, we present an overview of RSN, its types of integration and relative applications. We then provide the state-of-the-art EM techniques and strategies for RSN from August 2009 till date, thereby reviewing the existing EH and ET mechanisms designed for RSN. The taxonomy on various challenges for EM in RSN has also been articulated for open research directives

RF Localization in Indoor Environment

In this paper indoor localization system based on the RF power measurements of the Received Signal Strength (RSS) in WLAN environment is presented. Today, the most viable solution for localization is the RSS fingerprinting based approach, where in order to establish a relationship between RSS values and location, different machine learning approaches are used. The advantage of this approach based on WLAN technology is that it does not need new infrastructure (it reuses already and widely deployed equipment), and the RSS measurement is part of the normal operating mode of wireless equipment. We derive the Cramer-Rao Lower Bound (CRLB) of localization accuracy for RSS measurements. In analysis of the bound we give insight in localization performance and deployment issues of a localization system, which could help designing an efficient localization system. To compare different machine learning approaches we developed a localization system based on an artificial neural network, k-nearest neighbors, probabilistic method based on the Gaussian kernel and the histogram method. We tested the developed system in real world WLAN indoor environment, where realistic RSS measurements were collected. Experimental comparison of the results has been investigated and average location estimation error of around 2 meters was obtained

Towards Secure and Scalable Tag Search approaches for Current and Next Generation RFID Systems

The technology behind Radio Frequency Identification (RFID) has been around for a while, but dropping tag prices and standardization efforts are finally facilitating the expansion of RFID systems. The massive adoption of this technology is taking us closer to the well known ubiquitous computing scenarios. However, the widespread deployment of RFID technology also gives rise to significant user security issues. One possible solution to these challenges is the use of secure authentication protocols to protect RFID communications. A natural extension of RFID authentication is RFID tag searching, where a reader needs to search for a particular RFID tag out of a large collection of tags. As the number of tags of the system increases, the ability to search for the tags is invaluable when the reader requires data from a few tags rather than all the tags of the system. Authenticating each tag one at a time until the desired tag is found is a time consuming process. Surprisingly, RFID search has not been widely addressed in the literature despite the availability of search capabilities in typical RFID tags. In this thesis, we examine the challenges of extending security and scalability issues to RFID tag search and suggest several solutions. This thesis aims to design RFID tag search protocols that ensure security and scalability using lightweight cryptographic primitives. We identify the security and performance requirements for RFID systems. We also point out and explain the major attacks that are typically launched against an RFID system. This thesis makes four main contributions. First, we propose a serverless (without a central server) and untraceable search protocol that is secure against major attacks we identified earlier. The unique feature of this protocol is that it provides security protection and searching capacity same as an RFID system with a central server. In addition, this approach is no more vulnerable to a single point-of-failure. Second, we propose a scalable tag search protocol that provides most of the identified security and performance features. The highly scalable feature of this protocol allows it to be deployed in large scale RFID systems. Third, we propose a hexagonal cell based distributed architecture for efficient RFID tag searching in an emergency evacuation system. Finally, we introduce tag monitoring as a new dimension of tag searching and propose a Slotted Aloha based scalable tag monitoring protocol for next generation WISP (Wireless Identification and Sensing Platform) tags

Internet of Things Strategic Research Roadmap

Internet of Things (IoT) is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network