Research in: RFID privacy and security, antennas, polymer electronics-based RFID devices. Section 3 we outline the primary challenges for RFID technology today, and then in. Http:www.aimuk.orgpdfsComp04-4.pdf 10 August 2007.of Defense, led to a large number of research and commercialization efforts in the. RFID Systems: Research Trends and Challenges Edited by Miodrag Bolic. Aiming at providing an outstanding survey of recent advances in RFID technology, this book brings together interesting research results and.several challenges and obstacles to RFID adoption, as well as emerging technologies relevant. There are many kinds of RFID systems used in different applications and settings. Ongoing research into smart dust and motes is being.Robust Design, Sigma Delta Converters, RFID, 2011, p. pdf 2013-10-08 04: 48 33. RFID Systems Research Trends and Challenges, 2010, p.

Wireless Sensor and Robot Networks, pp. 1-15 (2014) No AccessChapter 1: Enhancing Routing Performance in Mobile Wireless Sensor Networks through the Use of Controlled MobilityNicolas Gouvy, Nathalie Mitton, and David Simplot-RylNicolas GouvyUniversité Lille 1, FranceInria Lille — Nord Europe, France, Nathalie MittonInria Lille — Nord Europe, France, and David Simplot-RylInria Lille — Nord Europe, Francehttps://doi.org/10.1142/9789814551342_0001Cited by:0 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Abstract: Node mobility has long been considered as a hazard in wireless sensor networks, causing a degradation of performance or even persistent routing failures. The advance of technology has made possible a new vision in which mobility allows the improvement of performances and new applications. In this chapter, we focus on some of the contributions that take advantage of controlled mobility in wireless sensor networks to improve message delivery performances. FiguresReferencesRelatedDetails Wireless Sensor and Robot NetworksMetrics History PDF download

HELLO protocol or neighborhood discovery is essential in wireless ad hoc networks. It makes the rules for nodes to claim their existence/aliveness. In the presence of node mobility, no fix optimal HELLO frequency and optimal transmission range exist to maintain accurate neighborhood tables while reducing the energy consumption and bandwidth occupation. Thus a Turnover based Frequency and transmission Power Adaptation algorithm (TFPA) is presented in this paper. The method enables nodes in mobile networks to dynamically adjust both their HELLO frequency and transmission range depending on the relative speed. In TFPA, each node monitors its neighborhood table to count new neighbors and calculate the turnover ratio. The relationship between relative speed and turnover ratio is formulated and optimal transmission range is derived according to battery consumption model to minimize the overall transmission energy. By taking advantage of the theoretical analysis, the HELLO frequency is adapted dynamically in conjunction with the transmission range to maintain accurate neighborhood table and to allow important energy savings. The algorithm is simulated and compared to other state-of-the-art algorithms. The experimental results demonstrate that the TFPA algorithm obtains high neighborhood accuracy with low HELLO frequency (at least 11% average reduction) and with the lowest energy consumption. Besides, the TFPA algorithm does not require any additional GPS-like device to estimate the relative speed for each node, hence the hardware cost is reduced.

In k-anycasting, a sensor wants to report event information to any k sinks in the network. In this paper, we describe KanGuRou, the first position-based energy efficient k-anycast routing which guarantees the packet delivery to k sinks as long as the connected component that contains s also contains at least k sinks. A node s running KanGuRou first computes a tree including k sinks with weight as low as possible. If this tree has m ≥ 1 edges originated at node s, s duplicates the message m times and runs m times KanGuRou over a subset of defined sinks. We present two variants of KanGuRou, each of them being more efficient than the other depending of application settings. Simulation results show that KanGuRou allows up to 62% of energy saving compared to plain anycasting.

We propose a radically new family of geometric graphs, i.e., Hypocomb (HC), Reduced Hypocomb (RHC), and Local Hypocomb (LHC). HC and RHC are extracted from a complete graph; LHC is extracted from a Unit Disk Graph (UDG). We analytically study their properties including connectivity, planarity, and degree bound. All these graphs are connected (provided that the original graph is connected) planar. Hypocomb has unbounded degree while Reduced Hypocomb and Local Hypocomb have maximum degree 6 and 8, respectively. To our knowledge, Local Hypocomb is the first strictly localized, degree-bounded planar graph computed using merely 1-hop neighbor position information. We present a construction algorithm for these graphs and analyze its time complexity. Hypocomb family graphs are promising for wireless ad hoc networking. We report our numerical results on their average degree and their impact on FACE routing. We discuss their potential applications and pinpoint some interesting open problems for future research.

In this paper, we address the problem of peer-to-peer networking for data dissemination among actors in wireless sensor and actor networks (WSANs), which consist of static sensors, responsible for environment monitoring, and mobile actors, in charge of data collection and task performing. This problem has not been received much attention although peer-to-peer networking has achieved great successes in other networks such as the Internet and mobile ad hoc networks (MANETs). Unlike the Internet and MANETs, WSANs contain static sensors that are energy-constrained and actors that cannot communicate with each other directly. These unique characteristics make the data dissemination problem in WSANs extremely challenging. We present an Energy-Efficient Message Dissemination protocol (EMD) to solve this problem in delay-tolerant WSANs. EMD is grounded on a novel principle of "Carry-Disseminate-Store-and-Forward" proposed for the first time here. While traveling, a source actor disseminates messages (data) to sensors upon contact, which will store the messages and forward them to other actors when they come into communication range. The actors receiving the messages from sensors work as source actors and help to distribute the messages. We theoretically analyze the data dissemination strategy under which the original source actor can distribute its messages to all other actors at minimum communication cost within a given delay bound. Through extensive simulations we demonstrate the performance of EMD.

Wireless sensor networks have gained much attention these last years thanks to the great set of applications that accelerated the technological advances. Such networks have been widely investigated and many books and articles have been published about the new challenges they pose and how to address them. One of these challenges is node mobility: sensors could be moved unexpectedly if deployed in an uncontrolled environment or hold by moving object/animals. Beyond all this, a new dimension arises when this mobility is controlled, i.e. if these sensors are embedded in robots. These robots cohabit with sensors and cooperate together to perform a given task collectively by presenting hardware constraints: they still rely on batteries; they communicate through short radio links and have limited capacities. In this book, we propose to review new challenges brought about by controlled mobility for different goals and how they are addressed in the literature in wireless sensor and Robot networks, ranging from deployment to communications.

In k-anycasting, a sensor wants to report event information to any k sinks in the network. This is important to gain in reliability and efficiency in wireless sensor and actor networks. In this paper, we describe KanGuRou, the first position-based energy efficient k-anycast routing which guarantees the packet delivery to k sinks as long as the connected component that contains s also contains sufficient number of sinks. A node s running KanGuRou first computes a tree including k sinks among the M available ones, with weight as low as possible. If this tree has m ≥ 1 edges originated at node s, s duplicates the message m times and runs m times KanGuRou over a subset of defined sinks. Simulation results show that KanGuRou allows up to 62% of energy saving compared to plain anycasting.

Wireless sensor networks are of energy-constrained nature, which calls for energy efficient protocols as a primary design goal. Thus, minimizing energy consumption is a main challenge.We are concerned in howcollected data by sensors, can be processed to increase the relevance of certain mass of data and reduce the overall data traffic. Since sensor nodes are often densely deployed, the data collected by nearby nodes are either redundant or correlated. One of the great challenges for the aforementioned problem is to exploit temporal and spatial correlation among the source nodes. Our work is composed of two main tasks: 1- A predictive modeling task that aims to capture the temporal correlation among collected data. 2- A data similarity detection task that measures the data similarity based on the spatial correlation.

We consider a path-scheduling problem at a resource constrained node A that transmits two types of flows to a given destination through alternate paths. Type-1 flow is assumed to have a higher priority than type-2 flow thus, it is never rejected upon arrival. Type-2 flow, on the other hand, may be denied admission to the queue. Once accepted to the system, a packet joins queue 1 and is guaranteed service independent of its type. Instead of being rejected from service, packets have the option to be served at a slower server behind a second queue (queue 2) at node A. The slow server is intended mostly to serve low priority packets, therefore, type-1 packets are charged a switching cost in the event they are sent to queue 2. Transmitted packets receive a reward depending on which queue they were served at. The reward represents the resources saved for making that decision. A good path-scheduling policy at node A can reduce resource consumption at node A, extend the life of the efficient path, maximizes the service of both flows and guarantees the service of at least the high priority flow to the full extent. We propose and solve the path-scheduling problem for node A, which maximizes the average reward of successfully transmitting flows to a given sink, by dynamically assigning packets to one of the queues based on the packet type, the instantaneous queue lengths and the average reward for the associated path. We formulated the path-scheduling problem as a Markov decision process and show that the optimal policy is threshold-type.

The coverage of Points of Interest (PoI) is a classical requirement in mobile wireless sensor applications. Optimizing the sensors self-deployment over a PoI while maintaining the connectivity between the sensors and the base station is thus a fundamental issue. This paper addresses the problem of autonomous deployment of mobile sensors that need to cover a predefined PoI with a connectivity constraint. In our algorithm, each sensor moves toward a PoI but has also to maintain the connectivity with a subset of its neighboring sensors that are part of the Relative Neighborhood Graph (RNG). The Relative Neighborhood Graph reduction is chosen so that global connectivity can be provided locally. Our deployment scheme minimizes the number of sensors used for connectivity thus increasing the number of monitoring sensors. Analytical results, simulation results and practical implementation are provided to show the efficiency of our algorithm.

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

In typical mobile wireless sensor networks, flows sent from collecting sensors to a sink could traverse inefficient resource expensive paths and experience arbitrary delays. This is particularly problematic in event-based sensor network where flows are of great importance. In this paper, we are interested in energy-aware routing algorithms that explicitly take advantage of node mobility to improve energy consumption of computed paths. Mobility is a two-sword edge however. Moving a node may render the network disconnected and results in early termination of information delivery. To mitigate these problems, we propose a family of routing algorithm called Connectivity preservation Mobile routing protocols for actuator and sensor NETworks CoMNet, that uses local information and modifies the network topology to support resource efficient transmissions. Our extensive simulations show that CoMNet has high energetic performance improvement compared to existing routing algorithms. More importantly, we show that CoMNet guarantees network connectivity and efficient resource consumption.