"It is stunningly thorough and takes readers meticulously through the design, conguration and operation of IPv6-based, low-power, potentially mobile radio-based networking" Vint Cerf, Vice President and Chief Internet Evangelist, Google This book provides a complete overview of IPv6 over Low Power Wireless Area Network (6LoWPAN) technology In this book, the authors provide an overview of the 6LoWPAN family of standards, architecture, and related wireless and Internet technology Starting with an overview of the IPv6 Internet of Things, readers are offered an insight into how these technologies fit together into a complete architecture The 6LoWPAN format and related standards are then covered in detail In addition, the authors discuss the building and operation of 6LoWPAN networks, including bootstrapping, routing, security, Internet ingration, mobility and application protocols Furthermore, implementation aspects of 6LoWPAN are covered Key Features: Demonstrates how the 6LoWPAN standard makes the latest Internet protocols available to even the most minimal embedded devices over low-rate wireless networks Provides an overview of the 6LoWPAN standard, architecture and related wireless and Internet technology, and explains the 6LoWPAN protocol format in detail Details operational topics such as bootstrapping, routing, security, Internet integration, mobility and application protocols Written by expert authors with vast experience in the field (industrial and academic) Includes an accompanying website containing tutorial slides, course material and open-source code with examples (http://6lowpannet ) 6LoWPAN: The Wireless Embedded Internet is an invaluable reference for professionals working in fields such as telecommunications, control, and embedded systems Advanced students and teachers in electrical engineering, information technology and computer science will also find this book useful

6LoWPAN: The Wireless Embedded Internet

A realistic power consumption model of wireless communication subsystems typically used in many sensor network node devices is presented. Simple power consumption models for major components are individually identified, and the effective transmission range of a sensor node is modeled by the output power of the transmitting power amplifier, sensitivity of the receiving low noise amplifier, and RF environment. Using this basic model, conditions for minimum sensor network power consumption are derived for communication of sensor data from a source device to a destination node. Power consumption model parameters are extracted for two types of wireless sensor nodes that are widely used and commercially available. For typical hardware configurations and RF environments, it is shown that whenever single hop routing is possible it is almost always more power efficient than multi-hop routing. Further consideration of communication protocol overhead also shows that single hop routing will be more power efficient compared to multi-hop routing under realistic circumstances. This power consumption model can be used to guide design choices at many different layers of the design space including, topology design, node placement, energy efficient routing schemes, power management and the hardware design of future wireless sensor network devices

A Realistic Power Consumption Model for Wireless Sensor Network Devices

Jamming represents the most serious security threat in the field of wireless sensor networks (WSNs), as it can easily put out of order even WSNs that utilize strong highlayer security mechanisms, simply because it is often ignored in the initial WSN design. The objective of this article is to provide a general overview of the critical issue of jamming in WSNs and cover all the relevant work, providing the interested researcher pointers for open research issues in this field. We provide a brief overview of the communication protocols typically used in WSN deployments and highlight the characteristics of contemporary WSNs, that make them susceptible to jamming attacks, along with the various types of jamming which can be exercised against WSNs. Common jamming techniques and an overview of various types of jammers are reviewed and typical countermeasures against jamming are also analyzed. The key ideas of existing security mechanisms against jamming attacks in WSNs are presented and open research issues, with respect to the defense against jamming attacks are highlighted.

A survey on jamming attacks and countermeasures in WSNs

We describe our experiences deploying BikeNet, an extensible mobile sensing system for cyclist experience mapping leveraging opportunistic sensor networking principles and techniques. BikeNet represents a multifaceted sensing system and explores personal, bicycle, and environmental sensing using dynamically role-assigned bike area networking based on customized Moteiv Tmote Invent motes and sensor-enabled Nokia N80 mobile phones. We investigate real-time and delay-tolerant uploading of data via a number of sensor access points (SAPs) to a networked repository. Among bicycles that rendezvous en route we explore inter-bicycle networking via data muling. The repository provides a cyclist with data archival, retrieval, and visualization services. BikeNet promotes the social networking of the cycling community through the provision of a web portal that facilitates back end sharing of real-time and archived cycling-related data from the repository. We present: a description and prototype implementation of the system architecture, an evaluation of sensing and inference that quantifies cyclist performance and the cyclist environment; a report on networking performance in an environment characterized by bicycle mobility and human unpredictability; and a description of BikeNet system user interfaces. Visit [4] to see how the BikeNet system visualizes a user's rides.

/pdf/the-bikenet-mobile-sensing-system-for-cyclist-experience-10dlzn01m9.pdf

The BikeNet mobile sensing system for cyclist experience mapping

Smart object technology, sometimes called the Internet of Things, is having a profound impact on our day-to-day lives. Interconnecting Smart Objects with IP is the first book that takes a holistic approach to the revolutionary area of IP-based smart objects. Smart objects are the intersection of networked embedded systems, wireless sensor networks, ubiquitous and pervasive computing, mobile telephony and telemetry, and mobile computer networking. This book consists of three parts, Part I focuses on the architecture of smart objects networking, Part II covers the hardware, software, and protocols for smart objects, and Part III provides case studies on how and where smart objects are being used today and in the future. The book covers the fundamentals of IP communication for smart objects, IPv6, and web services, as well as several newly specified low-power IP standards such as the IETF 6LoWPAN adaptation layer and the RPL routing protocol. This book contains essential information not only for the technical reader but also for policy makers and decision makers in the area of smart objects both for private IP networks and the Internet.



Shows in detail how connecting smart objects impacts our lives with practical implementation examples and case studies 
Provides an in depth understanding of the technological and architectural aspects underlying smart objects technology 
Offers an in-depth examination of relevant IP protocols to build large scale smart object networks in support of a myriad of new services 

Table of Contents

Part I: The Architecture Chapter 1: What are Smart objects? Chapter 2: The IP protocol architecture Chapter 3: Why IP for smart objects? Chapter 4: IPv6 for Smart Object Networks and The Internet of Things Chapter 5: Routing Chapter 6: Transport Protocols Chapter 7: Service Discovery Chapter 8: Security for Smart Objects Chapter 9: Web services For Smart Objects Chapter 10: Connectivity models for smart object networks 
Part II: The Technology Chapter 11: What is a Smart Object? Chapter 12: Low power link layer for smart objects networks Chapter 13: uIP A Lightweight IP Stack Chapter 14: Standardization Chapter 15: IPv6 for Smart Object Networks - A Technology Refresher Chapter 16: The 6LoWPAN Adaptation Layer Chapter 17: RPL Routing in Smart Object Networks Chapter 18: The IPSO Alliance Chapter 19: Non IP Technology

Part III: The Applications Chapter 20: Smart Grid Chapter 21: Industrial Automation Chapter 22: Smart Cities and Urban Networks Chapter 23: Home Automation Chapter 24: Building Automation Chapter 25: Structural Health Monitoring Chapter 26: Container Tracking

Interconnecting Smart Objects with IP: The Next Internet

The research topic of sensor networks has been around for some time. With improvements in device size, power consumption, communications, and computing technology, sensor networks are becoming more popular for an ever increasing range of applications. Since 2002, there has been an increased in the popularity of commercial applications based on ultra wideband. This, in turn, has ignited interest in the use of this technology for sensor networks and fuelled research in the area. Impulse-radio-based UWB technology has a number of inherent properties that are well suited to sensor network applications. In particular, UWB systems have potentially low complexity and low cost, have noise-like signal, are resistant to severe multipath and jamming, and have very good time domain resolution allowing for location and tracking applications. This article examines one example of a UWB sensor network for outdoor sport and lifestyle applications.

UWB wireless sensor networks: UWEN - a practical example

This paper provides an analytical model for the study of energy consumption in multihop wireless embedded and sensor networks where nodes are extremely power constrained. Low-power optimization techniques developed for conventional ad hoc networks are not sufficient as they do not properly address particular features of embedded and sensor networks. It is not enough to reduce overall energy consumption, it is also important to maximize the lifetime of the entire network, that is, maintain full network connectivity for as long as possible. This paper considers different multihop scenarios to compute the energy per bit, efficiency and energy consumed by individual nodes and the network as a whole. The analysis uses a detailed model for the energy consumed by the radio at each node. Multihop topologies with equidistant and optimal node spacing are studied. Numerical computations illustrate the effects of packet routing, and explore the effects of coding and medium access control. These results show that always using a simple multihop message relay strategy is not always the best procedure.

Energy Optimization in Multihop Wireless Embedded and Sensor Networks

In this paper, we propose a detailed energy survey of the physical, data link, and network layer by analytical techniques. We also show the impact of regular sleep periods on node energy consumption and present a comparison analysis of single-hop vs. multi-hop communications in the energy realm. A detailed energy expenditure analysis of not only the physical layer but also the link and network layer provides a basis for developing new energy efficient wireless sensor networks. Regular, coordinated sleeping extends the lifetime of sensor nodes, but systems can only benefit from sleeping in terms of transmitted packets if the data arrival rate to the system is low. Energy efficiency is the driving motivation for it can be considered the most important factor for wireless sensor networks because of the power constraints set by battery operation. Radio solutions in the lower ISM bands are attractive because of their relatively easy implementation and low power consumption. However, the data rates of these commercial radios are also relatively low, limiting transmittable frame sizes to a few tens of octets along with strict duty cycle requirements. From the analysis we extract key parameters of selected MAC protocols and show that some traditional mechanisms, such as binary exponential backoff, have some inherent problems. We also argue that single-hop communications has up todo% lower energy consumption than multi-hop forwarding within the feasible transmission distances of an ISM radio. Index Terms-Energy efficiency, Wireless sensor net- works, Medium access control (MAC) protocols, multi-hop communications a duty cycIe (Z), (3), which is normally 10% for the 434MHz band and 1% for the 868MHz band. The duty cycle is defined as the ratio, expressed as a percentage, of the maximum transmitter on-time, relative to a one hour period. When a sensor network is expected to work continuously, this duty cycle has to be taken into account and it can affect the energy efficiency of a network. In this paper we perform cross-layer analysis by pre- senting topology, medium access control (MAC) and ra- dio transceiver energy consumption models that work in unison. The hear topology model represents a common network after network layer route discovery has been accomplished. We use an energy consumption model for the transmission and reception of MAC frames originally presented in (4), develop a coordinated sleep group energy consumption model, and analytically investigate the effect of sleep on sensor networks using three MAC protocols. From the analysis we show that although in an ideal scenario multi-hop communications perform better than single-hop communications, realistic energy models and especially the MAC protocol design have a significant impact. We propose a multi-group sleep model for our nanoMAC protocol, and show that reg- ular sleep periods have a significant, energy reducing impact on node energy consumption with low traf!fic rates. The radio transceiver energy model takes into account several important radio parameters and we use the RFM TRlOOO and RFM radio designers guide (5) for realistic transceiver parameters. The main metric used is absolute energy, consumption per useful transmitted bit. This means only the MAC or thc network protocol data unit (PDU) will be considered and all the other communicated bits, headers, control frames, preambles, etc. are considered as overhead. The rest of the paper is organized as follows. Some related work is discussed in Section IT and in Section 111 we look at the radio propagation energy model. Section TV presents the network topology and energy

https://www.inets.rwth-aachen.de/pub/Cross_Layer_Enery_Analysis.pdf

Cross-layer Energy Analysis of Multi-hop Wireless Sensor Networks

This paper studies the effect of coding on the energy consumption in wireless embedded networks. An analytical model of the radio energy consumption is developed to study how different DC balanced codes affect the energy consumption for the one-hop case. A Rayleigh fading channel is assumed. The analysis is extended to include multihop scenarios in order to study the tradeoff between coding overhead and energy consumption. The numerical results obtained show that energy efficiencies of the codes used in a multihop routing scenario are strongly dependent on the channel conditions and on the number of hops used.

http://www.researchgate.net/profile/Carlos_Pomalaza-Raez/publication/4183894_Coding_for_energy_efficient_wireless_embedded_networks/links/02e7e520e37cc9b007000000.pdf

Coding for energy efficient wireless embedded networks

We present an energy analysis technique applicable to medium access control (MAC) and multihop communications. Furthermore, the technique's application gives insight on using multihop forwarding instead of single-hop communications. Using the technique, we perform an energy analysis of carrier-sense-multiple-access (CSMA-) based MAC protocols with sleeping schemes. Power constraints set by battery operation raise energy efficiency as the prime factor for wireless sensor networks. A detailed energy expenditure analysis of the physical, the link, and the network layers together can provide a basis for developing new energy-efficient wireless sensor networks. The presented technique provides a set of analytical tools for accomplishing this. With those tools, the energy impact of radio, MAC, and topology parameters on the network can be investigated. From the analysis, we extract key parameters of selected MAC protocols and show that some traditional mechanisms, such as binary exponential backoff, have inherent problems.

https://link.springer.com/content/pdf/10.1155/WCN.2005.523.pdf

Z. Shelby

Papers

UWB wireless sensor networks: UWEN - a practical example

Energy Optimization in Multihop Wireless Embedded and Sensor Networks

Cross-layer Energy Analysis of Multi-hop Wireless Sensor Networks

Coding for energy efficient wireless embedded networks

Multihop medium access control for WSNs: an energy analysis model