Annalen der Physik

A graph is just a bunch of points with lines between some of them, like a map of cities linked by roads. A rather simple notion. Nevertheless, the theory of graphs has broad and important applications, because so many things can be modeled by graphs. For example, planar graphs — graphs in which none of the lines cross are— important in designing computer chips and other electronic circuits. Also, various puzzles and games are solved easily if a little graph theory is applied.

A Theory of Graphs

A history of graph entropy measures

Facilitating Cooperation for Wireless Systems Cooperative Communications: Hardware, Channel & PHY focuses on issues pertaining to the PHY layer of wireless communication networks, offering a rigorous taxonomy of this dispersed field, along with a range of application scenarios for cooperative and distributed schemes, demonstrating how these techniques can be employed. The authors discuss hardware, complexity and power consumption issues, which are vital for understanding what can be realized at the PHY layer, showing how wireless channel models differ from more traditional models, and highlighting the reliance of PHY algorithm performance on the underlying channel models. Numerous transparent and regenerative relaying protocols are described in detail for a variety of transparent and regenerative cooperative schemes. Key Features: Introduces background, concepts, applications, milestones and thorough taxonomy Identifies the potential in this emerging technology applied to e.g. LTE/WiMAX, WSN Discusses latest wireless channel models for transparent and regenerative protocols Addresses the fundamentals as well as latest emerging PHY protocols Introduces transparent distributed STBC, STTC, multiplexing and beamforming protocols Quantifies regenerative distributed space-time, channel and network coding protocols Explores system optimization, such as distributed power allocation and relay selection Introduces and compares analog and digital hardware architectures Quantifies complexity, memory and power consumption of 3G UMTS & 4G LTE/WiMAX relay Highlights future research challenges within the cooperative communications field This book is an invaluable guide for professionals and researchers in communications fields. It will also be of interest to graduates of communications and electronic engineering courses. It forms part of an entire series dedicated to cooperative wireless systems.

Cooperative Communications: Hardware, Channel and PHY

Heterogeneous Internet of Things (HetIoT) is an emerging research field that has strong potential to transform both our understanding of fundamental computer science principles and our future living. HetIoT is being employed in increasing number of areas, such as smart home, smart city, intelligent transportation, environmental monitoring, security systems, and advanced manufacturing. Therefore, relaying on strong application fields, HetIoT will be filled in our life and provide a variety of convenient services for our future. The network architectures of IoT are intrinsically heterogeneous, including wireless sensor network, wireless fidelity network, wireless mesh network, mobile communication network, and vehicular network. In each network unit, smart devices utilize appropriate communication methods to integrate digital information and physical objects, which provide users with new exciting applications and services. However, the complexity of application requirements, the heterogeneity of network architectures and communication technologies impose many challenges in developing robust HetIoT applications. This paper proposes a four-layer HetIoT architecture consisting of sensing, networking, cloud computing, and applications. Then, the state of the art in HetIoT research and applications have been discussed. This paper also suggests several potential solutions to address the challenges facing future HetIoT, including self-organizing, big data transmission, privacy protection, data integration and processing in large-scale HetIoT.

How Can Heterogeneous Internet of Things Build Our Future: A Survey

Numerous localization protocols in Wireless Sensor Networks are based on Received Signal Strength Indicator. Because absolute positioning is not always available, localization based on RSSI is popular. More, no extra hardware is needed unlike solutions based on infra-red or ultrasonic. Moreover, the theory gives a RSSI as a function of distance. However, using RSSI as a distance metric involves errors in the measured values, resulting path-loss, fading, and shadowing effects. We present experimentation results from three large WSNs, each with up to 250 nodes. Based on our findings from the 3 systems, the relation between RSSI and distance is investigated according to the topology properties and the radio environment. We underline the intrinsic limitations of RSSI as a distance metric, in terms of accuracy and stability. Contrary to what we assumed, collaborative localization protocol based on Spring-Relaxation algorithm can not smooth the distance-estimation errors obtained with RSSI measurements.

Is RSSI a Good Choice for Localization in Wireless Sensor Network

Wireless sensor networks (WSNs) are data centric networks to which data aggregation is a central mechanism. Nodes in such networks are known to be of low complexity and highly constrained in energy. This requires novel distributed algorithms to data aggregation, where accuracy, complexity and energy need to be optimized in the aggregation of the raw data as well as the communication process of the aggregated data. To this end, we propose in this work a distributed data aggregation scheme based on an adaptive Auto-Regression Moving Average (ARMA) model estimation using a moving window technique and running over suitable communications protocols. In our approach, we balance the complexity of the algorithm and the accuracy of the model so as to facilitate the implementation. Subsequent analysis shows that an aggregation efficiency of up to 60% can be achieved with a very fine accuracy of 0.03 degree. And simulation results confirm that this distributed algorithm provides significant energy savings (over 80%) for mass data collection applications.

Optimized Data Aggregation in WSNs Using Adaptive ARMA

This paper considers security in wireless sensor networks (WSNs), focusing at the routing layer. We propose to analyze the behavior of some routing protocols according to attacks stemming from compromised nodes. Such malicious nodes could disrupt the routing functionality (node replication, Sybil attacks or Black-Grey-Sink holes). For such adversary models traditional cryptographic solutions are not enough by themselves but need to be completed by algorithmic solutions considering “beyond cryptography” approaches. Emphasizing internal attacks, with security features of routing in mind, we define the resiliency as the ability of a network to continue to operate in presence of k compromised nodes, i.e. the capacity of a network to endure and overcome internal attacks. In this context, we analyze four particular routing protocols (DSR, Gradient based, Greedy forwarding and Random walk routing). Using intensive simulations, we test their resiliency in presence of several compromised nodes in several adversary models.

Resiliency of wireless sensor networks: Definitions and analyses

Understanding the performances of backoff algorithms in multi-hop ad hoc networks is a key feature to design efficient medium access protocols. The 802.11 binary exponential backoff algorithm and all the enhancements done to this algorithm have been studied in depth in a single hop context. Very few analytical studies are carried out on 802.11 backoff algorithms in a multi-hop context due to the difficulty of modeling. In this paper we propose an analytical study, based on a stochastic process algebra, of four backoff algorithms on two multi-hop scenarios. Performances of each backoff algorithms are computed from efficiency and fairness point of view

/pdf/performance-evaluation-of-backoff-algorithms-in-802-11-ad-n6abtndbcy.pdf

Performance evaluation of backoff algorithms in 802.11 ad-hoc networks

Data dissemination has been put forward as an important mechanism for WSN. The dissemination schemes allow sink nodes to diffuse information in the network. It is known as an energy-consuming phase. In this paper, we propose to resolve this problem in two steps: firstly using a localized self-organization scheme which generates a non-directed backbone; secondly, sink node sends a request through this backbone to create a directed dissemination structure in the network. Our scheme effectively reduces the data traffic during the dissemination phase and saves energy when compared to other schemes. It is also extended to run properly in multiple sinks and mobile sink scenarios. The results also put forward the benefits of using a self-organization scheme for data dissemination.

Fabrice Valois

Papers

Is RSSI a Good Choice for Localization in Wireless Sensor Network

Optimized Data Aggregation in WSNs Using Adaptive ARMA

Resiliency of wireless sensor networks: Definitions and analyses

Performance evaluation of backoff algorithms in 802.11 ad-hoc networks

On the Data Dissemination in WSNs