Wireless Sensor Network Designs
1 Networked Embedded Systems 1
1.1. Introduction 1
1.2. Object-Oriented Design 3
1.3. Design Integration 4
1.4. Design Optimization 6
1.5. Co-design and Reconfiguration 9
1.6. Java-Driven Co-design and Prototyping 12
1.6.1. Java-Based Co-design 13
1.6.2. Run-Time Management 15
1.6.3. Embedded Systems Platform 17
1.7. Hardware and Software Prototyping 20
1.8. Multiple Application Support 23
1.8.1. FPGA-Based System Architecture 25
1.9. Summary 27
Problems 28
Learning Objectives 28
Practice Problems 29
Practice Problem Solutions 29
1.1. Introduction 1
1.2. Object-Oriented Design 3
1.3. Design Integration 4
1.4. Design Optimization 6
1.5. Co-design and Reconfiguration 9
1.6. Java-Driven Co-design and Prototyping 12
1.6.1. Java-Based Co-design 13
1.6.2. Run-Time Management 15
1.6.3. Embedded Systems Platform 17
1.7. Hardware and Software Prototyping 20
1.8. Multiple Application Support 23
1.8.1. FPGA-Based System Architecture 25
1.9. Summary 27
Problems 28
Learning Objectives 28
Practice Problems 29
Practice Problem Solutions 29
2 Smart Sensor Networks 31
2.1. Introduction 31
2.2. Vibration Sensors 32
2.3. Smart Sensor Application to Condition Based Maintenance 34
2.4. Smart Transducer Networking 42
2.5. Controller Area Network 46
2.6. Summary 58
Problems 60
Learning Objectives 60
Practice Problems 60
Practice Problem Solutions 60
3 Power-Aware Wireless Sensor Networks 63
3.1. Introduction 63
3.2. Distributed Power-Aware Microsensor Networks 65
3.3. Dynamic Voltage Scaling Techniques 71
3.4. Operating System for Energy Scalable Wireless Sensor Networks 75
3.5. Dynamic Power Management in Wireless Sensor Networks 79
3.6. Energy-Efficient Communication 81
3.7. Power Awareness of VLSI Systems 85
3.8. Summary 95
Problems 97
Learning Objectives 97
Practice Problems 97
Practice Problem Solutions 98
3.1. Introduction 63
3.2. Distributed Power-Aware Microsensor Networks 65
3.3. Dynamic Voltage Scaling Techniques 71
3.4. Operating System for Energy Scalable Wireless Sensor Networks 75
3.5. Dynamic Power Management in Wireless Sensor Networks 79
3.6. Energy-Efficient Communication 81
3.7. Power Awareness of VLSI Systems 85
3.8. Summary 95
Problems 97
Learning Objectives 97
Practice Problems 97
Practice Problem Solutions 98
4 Routing in Wireless Sensor Networks 101
4.1. Introduction 101
4.2. Energy-Aware Routing for Sensor Networks 102
4.3. Altruists or Friendly Neighbors in the Pico Radio Sensor Network 109
4.3.1. Energy-Aware Routing 111
4.3.2. Altruists or Friendly Neighbors 114
4.3.3. Analysis of Energy Aware and Altruists Routing Schemes 116
4.4. Aggregate Queries in Sensor Networks 120
4.4.1. Aggregation Techniques 125
4.4.2. Grouping 133
4.5. Summary 135
Problems 136
Learning Objectives 136
Practice Problems 137
Practice Problem Solutions 137
4.1. Introduction 101
4.2. Energy-Aware Routing for Sensor Networks 102
4.3. Altruists or Friendly Neighbors in the Pico Radio Sensor Network 109
4.3.1. Energy-Aware Routing 111
4.3.2. Altruists or Friendly Neighbors 114
4.3.3. Analysis of Energy Aware and Altruists Routing Schemes 116
4.4. Aggregate Queries in Sensor Networks 120
4.4.1. Aggregation Techniques 125
4.4.2. Grouping 133
4.5. Summary 135
Problems 136
Learning Objectives 136
Practice Problems 137
Practice Problem Solutions 137
5 Distributed Sensor Networks 141
5.1. Introduction 141
5.2. Bluetooth in the Distributed Sensor Network 142
5.2.1. Bluetooth Components and Devices 144
5.2.2. Bluetooth Communication and Networking 146
5.2.3. Different Technologies 151
5.3. Mobile Networking for Smart-Dust 154
5.3.1. Smart-Dust Technology 154
5.3.2. Communication and Networking 159
5.4. Summary 162
Problems 163
Learning Objectives 163
Practice Problems 163
Practice Problem Solutions 163
5.1. Introduction 141
5.2. Bluetooth in the Distributed Sensor Network 142
5.2.1. Bluetooth Components and Devices 144
5.2.2. Bluetooth Communication and Networking 146
5.2.3. Different Technologies 151
5.3. Mobile Networking for Smart-Dust 154
5.3.1. Smart-Dust Technology 154
5.3.2. Communication and Networking 159
5.4. Summary 162
Problems 163
Learning Objectives 163
Practice Problems 163
Practice Problem Solutions 163
6 Clustering Techniques in Wireless Sensor Networks
6.1. Introduction 165
6.2. Topology Discovery and Clusters in Sensor Networks 166
6.2.1. Topology Discovery Algorithm 169
6.2.2. Clusters in Sensor Networks 171
6.2.3. Applications of Topology Discovery 177
6.3. Adaptive Clustering with Deterministic Cluster-Head Selection 181
6.4. Sensor Clusters’ Performance 185
6.4.1. Distributed Sensor Processing 187
6.5. Power-Aware Functions in Wireless Sensor Networks 192
6.5.1. Power Aware Software 196
6.6. Efficient Flooding with Passive Clustering 198
6.6.1. Passive Clustering 203
6.7. Summary 207
Problems 208
Learning Objectives 208
Practice Problems 209
Practice Problem Solutions 209
6.1. Introduction 165
6.2. Topology Discovery and Clusters in Sensor Networks 166
6.2.1. Topology Discovery Algorithm 169
6.2.2. Clusters in Sensor Networks 171
6.2.3. Applications of Topology Discovery 177
6.3. Adaptive Clustering with Deterministic Cluster-Head Selection 181
6.4. Sensor Clusters’ Performance 185
6.4.1. Distributed Sensor Processing 187
6.5. Power-Aware Functions in Wireless Sensor Networks 192
6.5.1. Power Aware Software 196
6.6. Efficient Flooding with Passive Clustering 198
6.6.1. Passive Clustering 203
6.7. Summary 207
Problems 208
Learning Objectives 208
Practice Problems 209
Practice Problem Solutions 209
7 Security Protocols for Wireless Sensor Networks 213
7.1. Introduction 213
7.2. Security Protocols in Sensor Networks 214
7.2.1. Sensor Network Security Requirements 216
7.2.2. Authenticated Broadcast 219
7.2.3. Applications 223
7.3. Communication Security in Sensor Networks 225
7.4. Summary 230
Problems 230
Learning Objectives 230
Practice Problems 231
Practice Problem Solutions 231
7.1. Introduction 213
7.2. Security Protocols in Sensor Networks 214
7.2.1. Sensor Network Security Requirements 216
7.2.2. Authenticated Broadcast 219
7.2.3. Applications 223
7.3. Communication Security in Sensor Networks 225
7.4. Summary 230
Problems 230
Learning Objectives 230
Practice Problems 231
Practice Problem Solutions 231
8 Operating Systems for Embedded Applications 235
8.1. Introduction 235
8.2. The Inferno Operating System 236
8.3. The Pebble Component-Based Operating System 242
8.3.1. Protection Domains and Portals 246
8.3.2. Scheduling and Synchronization 250
8.3.3. Implementation 253
8.3.4. Embedded Applications 258
8.4. Embedded Operating System Energy Analysis 264
8.5. Summary 270
Problems 271
Learning Objectives 271
Practice Problems 272
Practice Problem Solutions 272
8.1. Introduction 235
8.2. The Inferno Operating System 236
8.3. The Pebble Component-Based Operating System 242
8.3.1. Protection Domains and Portals 246
8.3.2. Scheduling and Synchronization 250
8.3.3. Implementation 253
8.3.4. Embedded Applications 258
8.4. Embedded Operating System Energy Analysis 264
8.5. Summary 270
Problems 271
Learning Objectives 271
Practice Problems 272
Practice Problem Solutions 272
9 Network Support for Embedded Applications 275
9.1. Introduction 275
9.2. Bluetooth Architecture 277
9.3. Bluetooth Interoperability with the Internet and Quality of Service 283
9.4. Implementation Issues in Bluetooth-Based Wireless Sensor Networks 288
9.5. Low-Rate Wireless Personal Area Networks 297
9.6. Data-Centric Storage in Wireless Sensor Networks 306
9.7. Summary 314
Problems 315
Learning Objectives 315
Practice Problems 315
Practice Problem Solutions 316
9.1. Introduction 275
9.2. Bluetooth Architecture 277
9.3. Bluetooth Interoperability with the Internet and Quality of Service 283
9.4. Implementation Issues in Bluetooth-Based Wireless Sensor Networks 288
9.5. Low-Rate Wireless Personal Area Networks 297
9.6. Data-Centric Storage in Wireless Sensor Networks 306
9.7. Summary 314
Problems 315
Learning Objectives 315
Practice Problems 315
Practice Problem Solutions 316
10 Applications of Wireless Sensor Networks 323
10.1. Introduction 323
10.2. Application and Communication Support for Wireless Sensor Networks 325
10.3. Area Monitoring and Integrated Vehicle Health Management Applications 334
10.3.1. Development Platform 338
10.3.2. Applications 343
10.4. Building and Managing Aggregates in Wireless Sensor Networks 345
10.5. Habitat and Environmental Monitoring 349
10.5.1. Island Habitat Monitoring 350
10.5.2. Implementation 355
10.6. Summary 360
Problems 362
Learning Objectives 362
Practice Problems 362
Practice Problem Solutions 363
References 369
Index 385
10.1. Introduction 323
10.2. Application and Communication Support for Wireless Sensor Networks 325
10.3. Area Monitoring and Integrated Vehicle Health Management Applications 334
10.3.1. Development Platform 338
10.3.2. Applications 343
10.4. Building and Managing Aggregates in Wireless Sensor Networks 345
10.5. Habitat and Environmental Monitoring 349
10.5.1. Island Habitat Monitoring 350
10.5.2. Implementation 355
10.6. Summary 360
Problems 362
Learning Objectives 362
Practice Problems 362
Practice Problem Solutions 363
References 369
Index 385
PREFACE
The emergence of compact, low-power, wireless communication sensors
and actuators in the technology supporting the ongoing miniaturization of
processing and storage, allows for entirely new kinds of embedded system.
These systems are distributed and deployed in environments where they
may not have been designed into a particular control path, and are often very
dynamic. Collections of devices can communicate to achieve a higher level of
coordinated behavior.
Wireless sensor nodes deposited in various places provide light, temperature,
and activity measurements. Wireless nodes attached to circuits
or appliances sense the current or control the usage. Together they form a
dynamic, multi-hop, routing network connecting each node to more powerful
networks and processing resources.
Wireless sensor networks are application-specific, and therefore they have
to involve both software and hardware. They also use protocols that relate to
both the application and to the wireless network.
Wireless sensor networks are consumer devices supporting multimedia
applications, for example personal digital assistants, network computers, and
mobile communication devices. Emerging embedded systems run multiple
applications, such as web browsers, and audio and video communication
applications. These include capturing video data, processing audio streams,
and browsing the World Wide Web (WWW). There is a wide range of data
gathering applications, energy-agile applications, including remote climate
monitoring, battlefield surveillance, and intra-machine monitoring. Example
applications are microclimate control in buildings, environmental monitoring,
home automation, distributed monitoring of factory plants or chemical
processes, interactive museums, etc. An application of collective awareness
is a credit card anti-theft mode. There is also a target tracking application,
and applications ranging from medical monitoring and diagnosis to target
detection, hazard detection, and automotive and industrial control. In short,
there are applications in military (e.g. battlefields), commercial (e.g. distributed
mobile computing, disaster discovery systems, etc.), and educational
environments (e.g. conferences, conventions, etc.) alike.
This book introduces networked embedded systems, smart sensors, and
wireless sensor networks. The focus of the book is on the architecture,
applications, protocols, and distributed systems support for these networks.
Wireless sensor networks use new technology and standards. They involve
small, energy-efficient devices, hardware/software co-design, and networking
support. Wireless sensor networks are becoming an important part of
everyday life, industrial and military applications. It is a rapidly growing area
as new technologies are emerging, and new applications are being developed.
The characteristics of modern embedded systems are the capability to communicate
over the networks and to adapt to different operating environments.
Designing an embedded system’s digital hardware has become increasingly
similar to software design. The wide spread use of hardware description
languages and synthesis tools makes circuit design more abstract. A cosynthesis
method and prototyping platform can be developed specifically for
embedded devices, combining tightly integrated hardware and software
components.
Users are demanding devices, appliances, and systems with better capabilities
and higher levels of functionality. In these devices and systems, sensors
are used to provide information about the measured parameters or to identify
control states. These sensors are candidates for increased built-in intelligence.
Microprocessors are used in smart sensors and devices, and a smart sensor
can communicate measurements directly to an instrument or a system. The
networking of transducers (sensors or actuators) in a system can provide flexibility,
improve system performance, and make it easier to install, upgrade
and maintain systems.
The sensor market is extremely diverse and sensors are used in most
industries. Sensor manufacturers are seeking ways to add new technology in
order to build low-cost, smart sensors that are easy to use and which meet
the continuous demand for more sophisticated applications. Networking is
becoming pervasive in various industrial settings, and decisions about the use
of sensors, networks, and application software can all be made independently,
based on application requirements.
The IEEE (Institute of Electrical and Electronics Engineers) 1451 smart
transducer interface standards provide the common interface and enabling
technology for the connectivity of transducers to microprocessors, control
and field networks, and data acquisition and instrumentation systems. The
standardized Transducer Electronic Data Sheet (TEDS) specified by IEEE
1451.2 allows for self-description of sensors. The interfaces provide a standardized
mechanism to facilitate the plug and play of sensors to networks.
The network-independent smart transducer object model, defined by IEEE
1451.1, allows sensor manufacturers to support multiple networks and protocols.
This way, transducer-to-network interoperability can be supported.
IEEE standards P1451.3 and P1451.4 will meet the needs of analog transducer
users for high-speed applications. Transducer vendors and users, system integrators,
as well as network providers can benefit from the IEEE 1451 interface
standards. Networks of distributed microsensors are emerging as a solution
for a wide range of data gathering applications. Perhaps the most substantial
challenge faced by designers of small but long-lived microsensor nodes, is
the need for significant reductions in energy consumption. A power-aware
design methodology emphasizes the graceful scalability of energy consumption
with factors such as available resources, event frequency, and desired
output quality, at all levels of the system hierarchy. The architecture for a
power-aware microsensor node highlights the collaboration between software
that is capable of energy-quality tradeoffs and hardware with scalable
energy consumption.
Power-aware methodology uses an embedded micro-operating system to
reduce node energy consumption by exploiting both sleep state and active
power management. Wireless distributed microsensor networks have gained
importance in awide spectrum of civil and military applications. Advances in
MEMS (Micro Electro Mechanical Systems) technology, combined with lowpower,
low-cost, Digital Signal Processors (DSPs) and Radio Frequency (RF)
circuits have resulted in feasible, inexpensive, wireless microsensor networks.
A distributed, self-configuring network of adaptive sensors has significant
benefits. They can be used for remote monitoring in inhospitable and toxic
environments. A large class of benign environments also requires the deployment
of a large number of sensors, such as intelligent patient monitoring,
object tracking, and assembly line sensing. The massively distributed nature
of these networks provides increased resolution and fault tolerance as compared
with a single sensor node. Networking a large number of low-power
mobile nodes involves routing, addressing and support for different classes
of service at the network layer. Self-configuring wireless sensor networks
consist of hundreds or thousands of small, cheap, battery-driven, spread-out
nodes, bearing a wireless modem to accomplish a monitoring or control task
jointly. Therefore, an important concern is the network lifetime: as nodes
run out of power, the connectivity decreases and the network can finally be
partitioned and become dysfunctional.
and actuators in the technology supporting the ongoing miniaturization of
processing and storage, allows for entirely new kinds of embedded system.
These systems are distributed and deployed in environments where they
may not have been designed into a particular control path, and are often very
dynamic. Collections of devices can communicate to achieve a higher level of
coordinated behavior.
Wireless sensor nodes deposited in various places provide light, temperature,
and activity measurements. Wireless nodes attached to circuits
or appliances sense the current or control the usage. Together they form a
dynamic, multi-hop, routing network connecting each node to more powerful
networks and processing resources.
Wireless sensor networks are application-specific, and therefore they have
to involve both software and hardware. They also use protocols that relate to
both the application and to the wireless network.
Wireless sensor networks are consumer devices supporting multimedia
applications, for example personal digital assistants, network computers, and
mobile communication devices. Emerging embedded systems run multiple
applications, such as web browsers, and audio and video communication
applications. These include capturing video data, processing audio streams,
and browsing the World Wide Web (WWW). There is a wide range of data
gathering applications, energy-agile applications, including remote climate
monitoring, battlefield surveillance, and intra-machine monitoring. Example
applications are microclimate control in buildings, environmental monitoring,
home automation, distributed monitoring of factory plants or chemical
processes, interactive museums, etc. An application of collective awareness
is a credit card anti-theft mode. There is also a target tracking application,
and applications ranging from medical monitoring and diagnosis to target
detection, hazard detection, and automotive and industrial control. In short,
there are applications in military (e.g. battlefields), commercial (e.g. distributed
mobile computing, disaster discovery systems, etc.), and educational
environments (e.g. conferences, conventions, etc.) alike.
This book introduces networked embedded systems, smart sensors, and
wireless sensor networks. The focus of the book is on the architecture,
applications, protocols, and distributed systems support for these networks.
Wireless sensor networks use new technology and standards. They involve
small, energy-efficient devices, hardware/software co-design, and networking
support. Wireless sensor networks are becoming an important part of
everyday life, industrial and military applications. It is a rapidly growing area
as new technologies are emerging, and new applications are being developed.
The characteristics of modern embedded systems are the capability to communicate
over the networks and to adapt to different operating environments.
Designing an embedded system’s digital hardware has become increasingly
similar to software design. The wide spread use of hardware description
languages and synthesis tools makes circuit design more abstract. A cosynthesis
method and prototyping platform can be developed specifically for
embedded devices, combining tightly integrated hardware and software
components.
Users are demanding devices, appliances, and systems with better capabilities
and higher levels of functionality. In these devices and systems, sensors
are used to provide information about the measured parameters or to identify
control states. These sensors are candidates for increased built-in intelligence.
Microprocessors are used in smart sensors and devices, and a smart sensor
can communicate measurements directly to an instrument or a system. The
networking of transducers (sensors or actuators) in a system can provide flexibility,
improve system performance, and make it easier to install, upgrade
and maintain systems.
The sensor market is extremely diverse and sensors are used in most
industries. Sensor manufacturers are seeking ways to add new technology in
order to build low-cost, smart sensors that are easy to use and which meet
the continuous demand for more sophisticated applications. Networking is
becoming pervasive in various industrial settings, and decisions about the use
of sensors, networks, and application software can all be made independently,
based on application requirements.
The IEEE (Institute of Electrical and Electronics Engineers) 1451 smart
transducer interface standards provide the common interface and enabling
technology for the connectivity of transducers to microprocessors, control
and field networks, and data acquisition and instrumentation systems. The
standardized Transducer Electronic Data Sheet (TEDS) specified by IEEE
1451.2 allows for self-description of sensors. The interfaces provide a standardized
mechanism to facilitate the plug and play of sensors to networks.
The network-independent smart transducer object model, defined by IEEE
1451.1, allows sensor manufacturers to support multiple networks and protocols.
This way, transducer-to-network interoperability can be supported.
IEEE standards P1451.3 and P1451.4 will meet the needs of analog transducer
users for high-speed applications. Transducer vendors and users, system integrators,
as well as network providers can benefit from the IEEE 1451 interface
standards. Networks of distributed microsensors are emerging as a solution
for a wide range of data gathering applications. Perhaps the most substantial
challenge faced by designers of small but long-lived microsensor nodes, is
the need for significant reductions in energy consumption. A power-aware
design methodology emphasizes the graceful scalability of energy consumption
with factors such as available resources, event frequency, and desired
output quality, at all levels of the system hierarchy. The architecture for a
power-aware microsensor node highlights the collaboration between software
that is capable of energy-quality tradeoffs and hardware with scalable
energy consumption.
Power-aware methodology uses an embedded micro-operating system to
reduce node energy consumption by exploiting both sleep state and active
power management. Wireless distributed microsensor networks have gained
importance in awide spectrum of civil and military applications. Advances in
MEMS (Micro Electro Mechanical Systems) technology, combined with lowpower,
low-cost, Digital Signal Processors (DSPs) and Radio Frequency (RF)
circuits have resulted in feasible, inexpensive, wireless microsensor networks.
A distributed, self-configuring network of adaptive sensors has significant
benefits. They can be used for remote monitoring in inhospitable and toxic
environments. A large class of benign environments also requires the deployment
of a large number of sensors, such as intelligent patient monitoring,
object tracking, and assembly line sensing. The massively distributed nature
of these networks provides increased resolution and fault tolerance as compared
with a single sensor node. Networking a large number of low-power
mobile nodes involves routing, addressing and support for different classes
of service at the network layer. Self-configuring wireless sensor networks
consist of hundreds or thousands of small, cheap, battery-driven, spread-out
nodes, bearing a wireless modem to accomplish a monitoring or control task
jointly. Therefore, an important concern is the network lifetime: as nodes
run out of power, the connectivity decreases and the network can finally be
partitioned and become dysfunctional.
Deployment of large networks of sensors requires tools to collect and
query data from these networks. Of particular interest are aggregates whose
operations summarize current sensor values in part or all of an entire sensor
network. Given a dense network of a thousand sensors querying for example,
temperature, users want to know temperature patterns in relatively large
regions encompassing tens of sensors, and individual sensor readings are of
little value.
Networks of wireless sensors are the result of rapid convergence of three
key technologies: digital circuitry, wireless communications, and MEMS.
Advances in hardware technology and engineering design have led to reductions
in size, power consumption, and cost. This has enabled compact,
autonomous nodes, each containing one or more sensors, computation and
communication capabilities, and a power supply. Ubiquitous computing is
based on the idea that future computers merge with their environment until
they become completely invisible to the user. Ubiquitous computing envisions
everyday objects as being augmented with computation and communication
capabilities. While such artifacts retain their original use and appearance,
their augmentation can seamlessly enhance and extend their usage, thus
opening up novel interaction patterns and applications. Distributed wireless
microsensor networks are an important component of ubiquitous computing,
and small dimensions are a design goal for microsensors. The energy supply
of the sensors is a main constraint of the intended miniaturization process. It
can be reduced only to a specific degree since energy density of conventional
energy sources increases slowly. In addition to improvements in energy density,
energy consumption can be reduced. This approach includes the use of
energy-conserving hardware. Moreover, a higher lifetime of sensor networks
can be accomplished through optimized applications, operating systems, and
communication protocols. Particular modules of the sensor hardware can be
turned off when they are not needed. Wireless distributed microsensor systems
enable fault-tolerant monitoring and control of a variety of applications.
Due to the large number of microsensor nodes that may be deployed, and the
long system lifetimes required, replacing the battery is not an option. Sensor
systems must utilize minimal energy while operating over a wide range of
operating scenarios. These include power-aware computation and communication
component technology, low-energy signaling and networking, system
partitioning considering computation and communication trade-offs, and a
power-aware software infrastructure. Routing and data dissemination in sensor
networks requires a simple and scalable solution. The topology discovery
algorithm for wireless sensor networks selects a set of distinguished nodes,
and constructs a reachability map based on their information. The topology
discovery algorithm logically organizes the network in the form of clusters
and forms a tree of clusters rooted at the monitoring node. The topology
discovery algorithm is completely distributed, uses only local information,
and is highly scalable.
To achieve optimal performance in a wireless sensor network, it is important
to consider the interactions among the algorithms operating at the
different layers of the protocol stack. For sensor networks, one question is
how the self-organization of the network into clusters affects the sensing
performance. Thousands to millions of small sensors form self-organizing
wireless networks, and providing security for these sensor networks is not
easy since the sensors have limited processing power, storage, bandwidth,
and energy. Aset of Security Protocols for Sensor Networks (SPINS), explores
the challenges for security in sensor networks. SPINS include: TESLA (the
micro version of the Timed, Efficient, Streaming, Loss-tolerant Authentication
Protocol), providing authenticated streaming broadcast, and SNEP (Secure
Network Encryption Protocol) providing data confidentiality, two-party data
authentication, and data freshness, with low overhead. An authenticated
routing protocol uses SPINS building blocks. Wireless networks, in general,
are more vulnerable to security attacks than wired networks, due to the
broadcast nature of the transmission medium. Furthermore, wireless sensor
networks have an additional vulnerability because nodes are often placed in
a hostile or dangerous environment, where they are not physically protected.
The essence of ubiquitous computing is the creation of environments saturated
with computing and communication in an unobtrusive way. WWRF
(Wireless World Research Forum) and ISTAG (Information Society Technologies
Advisory Group) envision a vast number of various intelligent devices,
embedded in the environment, sensing, monitoring and actuating the physical
world, communicating with each other and with humans. The main
features of the IEEE 802.15.4 standard are network flexibility, low cost, and
low power consumption. This standard is suitable for many applications in
the home requiring low data rate communications in an ad hoc self-organizing
network.
The IEEE 802.15.4 standard defines a low-rate wireless personal area
network (LR-WPAN) which has ultra-low complexity, cost, and power, for
low data rate wireless connectivity among inexpensive fixed, portable, and
moving devices. The IEEE 802.15.4 standard defines the physical (PHY)
layer and Media Access Control (MAC) layer specifications. In contrast to
traditional communication networks, the single major resource constraint in
sensor networks is power, due to the limited battery life of sensor devices.
Data-centric methodologies can be used to solve this problem efficiently. In
Data Centric Storage (DCS) data dissemination frameworks, all event data
are stored by type at designated nodes in the network and can later be
retrieved by distributed mobile access points in the network. Resilient Data-
Centric Storage (R-DCS) is amethod of achieving scalability and resilience by
replicating data at strategic locations in the sensor network. Various wireless
technologies, like simple RF, Bluetooth, UWB (ultrawideband) or infrared
can be used for communication between sensors. Wireless sensor networks
require low-power, low-cost devices that accommodate powerful processors,
a sensing unit, wireless communication interface and power source, in a
robust and tiny package. These devices have to work autonomously, to require
no maintenance, and to be able to adapt to the environment. Wireless Sensor
Network Designs focuses on the newest technology in wireless sensor networks,
networked embedded systems, and their applications. A real applicationsoriented
approach to solving sensor network problems is presented. The book
includes a broad range of topics from networked embedded systems and
smart sensor networks, to power-aware wireless sensor networks, routing,
clustering, security, and operating systems along with networks support.
The book is organized into ten chapters, with the goal to explain the newest
sensor technology, design issues, protocols, and solutions to wireless sensor
network architectures.
As previously discussed, Chapter 1 describes networked embedded systems,
their design, prototyping, and application support. Chapter 2 introduces
smart sensor networks and their applications. Chapter 3 introduces
power-aware wireless sensor networks. Routing in wireless sensor networks
and the aggregation techniques are discussed in Chapter 4. Distributed sensor
networks are presented in Chapter 5, and clustering techniques in wireless
sensor networks are introduced in Chapter 6. Chapter 7 presents security
protocols in sensor networks. Operating systems for embedded applications
are discussed in Chapter 8. Chapter 9 presents network support for embedded
applications. Applications of wireless sensor networks are studied in
Chapter 10.
KEYWORDS:
Index
access point (AP), 152
Active Message (AM), 327, 364
actuator, 34, 58, 110, 112
Ad Hoc On Demand Distance Vector
Routing (AODV), 103, 105, 190
address space identifier (ASID), 254, 255
Advanced Configuration and Power
Interface (ACPI), 78
AES-128 (advanced encryption standard
128-bit cryptographic keys), 302
aggregate queries, 120, 121
altruist, 109, 114, 115
analog to digital converter (ADC), 33, 35,
52, 57, 66, 323, 334, 340, 356, 357, 361
application programming interface
(API), 11, 15, 16, 24, 47, 54, 122, 197,
198, 230, 291, 196, 318
application specific integrated circuit
(ASIC), 23, 28, 93
Asynchronous Connectionless (ACL)
link, 276, 282–284, 315, 317
attribute-based addressing, 101
authenticated broadcast, 219, 222
authentication, 241
Automatic Repeat Request (ARQ), 276,
281, 283
base station (BS), 215, 225, 337
base station transceiver (BTS), 151,
156–163
Baseband (BB) protocol, 278
Berkeley Software Distribution (BSD),
258, 259
Binary Phase Shift Keying (BPSK),
305
bit error rate (BER)
Bluetooth, 110, 142, 144–153, 162, 275,
277–288, 290, 293–298, 300, 314–319
broadcasting, 84, 222
C/OS, 265, 271, 341
Carrier Sense Multiple Access (CSMA),
117, 119, 120, 122, 199, 302, 332
carrier sense multiple access / collision
avoidance (CSMA/CA), 104, 110, 159,
302
Cellular IP, 287, 288
central processor unit (CPU), 19, 79, 80,
144, 243, 251
certifying authority (CA), 241
channel interface module (CIM), 46
cipher-block chaining (CBC), 217
class-based addressing, 104, 105
Wireless Sensor Network Designs A. Ha´c
. 2003 John Wiley & Sons, Ltd ISBN: 0-470-86736-1
386 INDEX
cluster head, 71, 72, 181–184, 198,
203–205, 207, 209
cluster, 171, 178, 185, 191, 192, 203, 208,
209
clustering, 81, 181, 198, 199, 202, 319
code generation, 20
codesign and reconfiguration, 2, 9
Complementary Metal-Oxide
Semiconductor (CMOS), 67, 68, 97, 98,
334, 343, 356
condition based maintenance, 24, 58, 325
connectivity map, 177
continuous variable slope delta
modulation (CVSD), 276, 281, 284
controller area network (CAN), 46, 47,
54, 55, 56, 59
Corner Cube Retroreflector (CCR), 156,
157, 160
cosynthesis method and prototyping
platform, 2, 4
counter mode (CTR), 217, 218
cue, 189, 343
Cyclic Redundancy Check (CRC), 276,
281, 283, 301, 317
data aggregation, 67, 70, 193, 194, 293,
319, 349
Data Encryption Standard (DES), 242
Data Encryption Standard – Cipher
Block Chaining (DES-CBC), 218, 242
data fusion, 72
data link layer (DLL), 298, 299, 320
data-centric storage (DCS), 276, 306,
308–310, 314, 322
DES cipher-block chaining (DES-CBC),
242
DES electronic code book (DES-ECB),
242
design integration, 4
Destination Sequenced Distance Vector
Routing protocol (DSDV), 105
Digital Cordless Telephone (DCT), 338,
339, 341
Digital Signal Processing (DSP), 64, 75,
93, 95, 192, 196
direct sequence spread spectrum (DSSS),
152, 302, 305, 321
directed diffusion, 81
Distance Vector Multicast Routing
Protocol (DVMRP), 161
distributed aggregate management
(DAM), 346
distributed hash-table (DHT), 308, 309
Distributed Multidrop System (DMS), 38
distributed sensor networks, 141
dynamic power management (DMP), 76,
79
Dynamic Source Routing (DSR), 190
dynamic voltage scaling (DVS), 64, 68,
69, 73–75, 79, 95, 97–99
dynamically reconfigurable
field-programmable gate array
(DPGA) board, 4–7, 10, 11, 14–19, 29
Electronically Erasable Programmable
Read Only Memory (EEPROM), 54,
122, 333, 356, 357, 361
embedded application, 235, 258, 275
embedded Cygnus operating system
(eCOS), 67, 74, 271
embedded device, 12
embedded operating system, 26, 264, 265
embedded system, 1–8, 12, 64, 261, 357
embedded systems platform, 17
encryption algorithm, 2
energy aware routing (EAR), 101–103,
106, 107, 109–113, 115–117, 119, 120,
136
energy-efficient communication, 81
energy-quality (E-Q), 64, 65, 69, 70, 76,
208
epoch, 224
Ethernet, 47, 56, 111
External Storage (ES), 308
Fast Fourier Transform (FFT), 33, 194
Field Programmable Gate Array (FPGA),
5, 9, 10, 14, 16, 17, 20, 22–30, 93
Finite Impulse Response (FIR), 17, 69
FIR filter, 17, 69, 72, 75, 196
INDEX 387
First Node Dies (FND), 181, 184
flooding, 84, 112, 198, 199, 200, 211
Forward Error Correction (FEC), 195,
196, 276, 281, 283, 317
FPGA architecture, 25
Frame Check Sequence (FCS), 301
Frequency Hopping Spread Spectrum
(FHSS), 153, 154, 275, 283
friendly neighbor, 109, 114
garbage collection, 260
gateway, 147, 198, 204, 205, 290, 291, 293,
295–297, 318, 319, 336, 359
General Purpose Interface Bus (GPIB), 35
Geographical Adaptive Fidelity (GAF),
359
global positioning system (GPS), 186, 199
Global Standard for Mobile (GSM), 188
Great Duck Island (GDI), 351, 352, 358,
359
Greedy Perimeter Stateless Routing
(GPSR), 306, 308, 309, 315, 322
grouping, 133
guaranteed time slots (GTS), 301
Half of the Nodes Alive (HNA), 181, 184
hardware abstraction layer (HAL), 340,
341
hardware and software codesign, 3
Heating, Ventilation, and Air
Conditioning (HVAC), 298
high-level synthesis (HLS), 20, 30
HiperLAN/2, 152
Host Controller Interface (HCI), 144, 146
IEEE 1451 Standards for Smart
Transducer Interface for Sensors and
Actuators, 32–49, 52, 54–61
IEEE 802.11, 82, 114, 115, 150, 152, 206,
298, 299, 358
IEEE 802.15, 152, 276, 298–306,
314–316, 320, 321
IETF Unidirectional Link Routing
Working Group, 161
implicit entry-exit pair (IEEP), 267, 268
IMT2000 (International Mobile
Telecommunication), 23, 24
in-network aggregation, 125, 133, 135
Industry Scientific Medical (ISM), 67,
143, 152, 153, 280, 281, 283, 294, 302,
316, 321, 340
Inferno operating system, 236, 239–241,
261, 274
Information Society Technologies
Advisory Group (ISTAG), 276
infrared data association (IrDA), 279,
286
infrared object exchange (IrOBEX), 279
Integrated Circuit (IC), 302
Integrated Device Technology (IDT), 261
Integrated Electronics, PiezoElectric
(IEPE), 40, 41
Inter Integrated Circuit, 143, 356, 357
International Telecommunication
Union – Telecommunication
Standardization Sector (ITU-T), 301
Internet Engineering Task Force (IETF),
161, 287
Internet Protocol (IP), 42, 203, 204,
286–288, 306, 307, 322
Internet, 4, 12, 46, 283, 317
interprocess communication (IPC), 243,
265, 266, 269, 270
interprotection domain call, 262, 264
interrupt handler, 263
interrupt latency, 263, 264
interrupt service routine (ISR), 265
interrupt, 251, 252, 254
JaCoP (Java driven codesign and
prototyping environment), 2, 12, 13,
16–18, 29
Java Beans specification, 13, 17
Java Native Interface (JNI), 11, 15, 24, 27
Java programming language, 12, 39, 259,
260
Java virtual machine (JVM), 10, 15, 19,
22, 27, 29
Joint Test Action Group (JTAG), 339
388 INDEX
Large Scale Office Scenario (LSOSC),
118, 119, 120
LaserMirror Scanner (LMS), 70
Last Node Dies (LND), 181, 184
Light Emitting Diode (LED), 145
line-of-bearing (LOB), 194
line-of-sight, 161, 164
Link Manager (LM), 278
Link State Routing (LSR), 105
Linked Cluster algorithm (LCA), 191,
192
Linux, 11, 14, 18, 146, 149, 265, 268, 271,
357
local area network (LAN), 46, 150, 286,
287
Local Storage (LS), 308
logical link control (LLC), 278, 299, 300,
320, 321
Logical Link Control and Adaptation
Protocol (L2CAP), 146
Low Energy Adaptive Clustering
Hierarchy (LEACH), 81, 181, 182, 184,
193
Low Power Oscillator (LPO), 281, 282,
284
low-rate wireless personal area network
(LR-WPAN), 298, 301, 306, 314
Management Information Base (MIB),
168
master, 146, 153, 163, 281–285, 294–296,
317, 319
maximum transmission unit (MTU), 279,
286, 317
Media Access Control (MAC), 81, 82, 83,
96, 103, 104, 109–111, 113, 114, 116,
117, 120, 137, 159, 186, 187, 292,
298–304, 314, 320, 321, 324, 332, 358,
359, 360
MAC common part sublayer
(MCPS-SAP), 300, 321
MAC footer (MFR), 300
MAC header (MHR), 300
MAC layer management entity
(MLME-SAP), 300, 321
MAC protocol data unit (MPDU), 300
MAC service data unit (MSDU), 300
message authentication code (MAC),
216, 218–225, 232
Message Digest 4 (MD4), 241
Message Digest 5 (MD5), 221, 241, 242
Micro Controller Unit (MCU), 145
Micro Electro Mechanical Systems
(MEMS), 65, 67, 75, 95, 141, 151, 154,
157, 161, 165, 192, 288, 292, 314, 334,
345
micro-Adaptive Multi-domain
Power-aware Sensors (µAMPS), 71,
72, 73, 84, 95
micro-TESLA, 213–215, 217, 220–222,
224, 230, 231, 233
microcontroller, 35
microprocessor, 31, 58
microsensor, 35, 64, 65, 72, 77, 81, 192,
338
Million Instructions Per Second (MIPS),
92, 144, 236, 243, 245, 253, 254, 261
minimum shift keying (MSK), 305
mobile ad hoc network (MANET), 185,
187, 190, 198–201, 203, 208
Mobile IP, 287
mote, 121, 152, 156–158, 359
Motion Pictures Experts Group (MPEG),
237, 260
MPR Node (MPRN), 201
multifunction systems, 2
multimode systems, 2
Multipoint Relay (MPR), 201–103
Network Capable Application Processor
(NCAP), 36–38, 43, 45–49, 52–56, 59,
61
networked embedded system, 2, 9,
11–30
nucleus, 251, 253, 255
object-oriented design, 3, 13, 88
Offset Quadrature Phase Shift Keying
(O-QPSK), 305
Open Shortest Path First (OSPF), 161
INDEX 389
open systems interconnection (OSI)
reference model, 299
operating system (OS), 235, 236,
242–245, 264, 266–270, 273, 341
operation, administration, and
maintenance (OA&M), 237
output feedback mode (OFB), 217
passive clustering, 198–200, 203–207,
210
PC Interface (PCI), 5, 11, 15, 18, 23, 24
Pebble operating system, 235, 242–245,
252, 253, 255, 257–259, 261, 271, 273
Perimeter Refresh Protocol, 309
Personal Area Network (PAN), 152, 301,
302
Personal Computer (PC), 4, 5, 14, 18, 19,
125, 277, 285, 291, 297–299, 320, 341
personal digital assistant (PDA), 23, 24,
153, 188, 259, 275, 277, 286, 291, 298,
352, 355
Phase Lock Loop (PLL), 68, 69, 73
physical (PHY) layer, 298, 300, 314, 321
physical layer protocol data unit
(PPDU), 304
physical layer service data unit (PSDU),
304
piconet, 146, 147, 153, 282, 284, 294, 296,
316, 317, 319
Plan 9 operating system, 238, 244
plug-and-play, 58
Point Coordination Function (PCF), 114
portal manager, 253, 274
portal traversal, 248
portal, 244, 246, 247, 249, 250, 252,
255–258, 261, 271, 272, 273, 336
power management (PM), 76, 78
power-aware design, 65
power-aware wireless sensor networks,
63
Printed Circuit Board (PCB), 73
profiling, 3
programming language C++, 242, 260,
327
programming language C, 145, 238–240,
242, 258, 260, 271, 340, 341, 364
programming language Limbo, 238, 239,
240, 259
programming language Pascal, 238
protection domain (PD), 246–249, 272
Pseudo-Noise (PN), 305
Quality of Service (QoS), 2, 93, 152, 283,
305, 315
Quantum Effect Design (QED), 261
radio frequency (RF), 75, 95, 154, 162,
192, 215, 275, 278, 288, 290, 314, 318,
323, 330, 340
random access memory (RAM), 7, 18, 52,
54, 57, 58, 67, 133
reachability map, 177
Read Only Memory (ROM), 54, 67
Received Signal Strength Indicator
(RSSI), 84, 281
Reduced Instruction Set Computer
(RISC), 18, 93, 144, 153, 335, 339
request to send / clear to send
(RTS/CTS), 159
Resilient Data-Centric Storage (R-DCS),
276, 307, 310, 312
Resource Reservation Protocol (RSVP),
288
reuse library, 3
RF Module (RFM), 122
RFCOMM, 279
RFM (RF Monolithics), 330, 331, 355
Route Reply (RREP), 106
Route Request (RREQ), 105, 106
Routing Information Protocol (RIP), 161
routing, 123, 190
RS232, 143, 144, 339, 341
run-time system (RTS), 20, 22, 23
runtime management, 15
S-MAC (sensor-MAC), 360
scatternet, 153, 294, 295, 316, 319
scratch-pad memory, 7
Secure Hash Algorithm (SHA), 241, 242
390 INDEX
Secure Network Encryption Protocol
(SNEP), 213, 217–219, 221, 223, 225,
230
Security Protocols for Sensor Networks
(SPINS), 213, 216, 217, 223, 230, 231
self-configuring wireless sensor
network, 109
self-organizing wireless network, 276
semaphore, 247, 250, 262
sensor fusion, 338
Serial Peripheral Interface (SPI) protocol,
52, 339
service access point (SAP), 299, 300
Service Discovery Protocol (SDP), 296
service-specific convergence sublayer
(SSCS), 299, 300, 321
signal to interference ratio (SIR)
signal to noise ratio (SNR), 66, 96
Simple Mail Transfer Protocol (SMTP),
355
simulated annealing, 8
sink, 112, 118, 176
slave, 146, 147, 153, 163, 281–285, 294,
295, 317, 319
Small to Medium Enterprise (SME),
56
Smart Dust, 151, 152, 154, 158, 159,
164
smart sensor, 31, 34, 58, 121
Smart Transducer Interface Module
(STIM), 37–41, 43, 45–49, 51–56, 58,
61
software synthesis, 4
source, 112, 138
special function register (SFR), 57, 58
specification, 3
static RAM (SRAM), 144, 339, 340
station-to-station (STS), 241
steam-based function (SBF), 25
StrongARM, 67–69, 72, 76, 78, 84, 339,
357
Structured Query Language (SQL), 102,
121, 124, 126, 134, 135, 347
Structured Replication in DCS (SR-DCS)
scheme, 309
Styx protocol, 238
Surface Mount Device (SMD), 151
symmetric block cipher (RC6), 227
symmetric key stream cipher (RC4), 242
Synchronous Connection Oriented
(SCO) link, 276, 282–284, 315, 317
synthesis, 9
system call entry-exit pair (SCEEP), 267,
268
System Developers Toolkit (SDT), 341
system programming interface (SPI), 53,
145
Systems Performance Evaluation
Consortium (SPEC92), 92
target tracking, 214
thread, 6, 190, 248, 251, 262–264
Time Division Duplex (TDD), 283, 294
time division multiple access (TDMA),
160, 337, 341, 358
Timed, Efficient, Streaming,
Loss-tolerant Authentication Protocol
(TESLA), 215, 220
TinyOS, 152, 323, 324, 326–328, 330–333,
360, 362, 364
topology discovery, 166, 169, 171, 177,
209
Transaction Control Protocol (TCP), 288
Transaction Control Protocol/Internet
Protocol (TCP/IP), 36, 46, 279, 286,
317, 358
Transducer Bus Interface Module
(TBIM), 38, 43, 47, 48, 60
Transducer Electronic Data Sheet
(TEDS), 32, 33, 38, 39, 42–44, 47–49,
51, 54, 57–59, 60
Transducer Independent Interface (TII),
37, 49, 51, 54, 57
translation lookaside buffer (TLB), 243,
253–255
transmit power control (TPC), 152
ubiquitous computing, 325
Ultra Wide Band (UWB), 288, 290, 314,
318
INDEX 391
universal asynchronous receiver
transmitter (UART), 144, 145, 326, 330
Universal Serial Bus (USB), 144
Unix, 236, 240, 256, 257, 260, 262
untrusted location, 215
User Datagram Protocol (UDP), 286
Very Large Scale Integration (VLSI), 64,
85, 92, 95
VHDL (VHSIC Hardware Description
Language), 4, 10, 14, 22, 30, 325
VHSIC (Very High Scale Integrated
Circuit), 325
VHSIC Hardware Description Language
(VHDL), 4, 10, 14, 22, 30, 325
vibration sensors, 32–34
Video Cassette Recorder (VCR), 298
virtual memory (VM), 11, 15, 243, 248,
249, 253
VLSI systems, 64, 85, 97
voltage controlled oscillator (VCO), 68
weak freshness, 219, 232
Web-based applications, 3
wide area network (WAN), 353, 354
wireless application protocol (WAP),
279, 286
Wireless Integrated Network Sensors
(WINS), 162, 324, 334–338, 340, 341,
343–345, 362, 363, 365, 366
Wireless Local Area Network (WLAN),
150, 152
Wireless World Research Forum
(WWRF), 276
World Wide Web (WWW), 2
zone routing protocol (ZRP), 190, 191
query data from these networks. Of particular interest are aggregates whose
operations summarize current sensor values in part or all of an entire sensor
network. Given a dense network of a thousand sensors querying for example,
temperature, users want to know temperature patterns in relatively large
regions encompassing tens of sensors, and individual sensor readings are of
little value.
Networks of wireless sensors are the result of rapid convergence of three
key technologies: digital circuitry, wireless communications, and MEMS.
Advances in hardware technology and engineering design have led to reductions
in size, power consumption, and cost. This has enabled compact,
autonomous nodes, each containing one or more sensors, computation and
communication capabilities, and a power supply. Ubiquitous computing is
based on the idea that future computers merge with their environment until
they become completely invisible to the user. Ubiquitous computing envisions
everyday objects as being augmented with computation and communication
capabilities. While such artifacts retain their original use and appearance,
their augmentation can seamlessly enhance and extend their usage, thus
opening up novel interaction patterns and applications. Distributed wireless
microsensor networks are an important component of ubiquitous computing,
and small dimensions are a design goal for microsensors. The energy supply
of the sensors is a main constraint of the intended miniaturization process. It
can be reduced only to a specific degree since energy density of conventional
energy sources increases slowly. In addition to improvements in energy density,
energy consumption can be reduced. This approach includes the use of
energy-conserving hardware. Moreover, a higher lifetime of sensor networks
can be accomplished through optimized applications, operating systems, and
communication protocols. Particular modules of the sensor hardware can be
turned off when they are not needed. Wireless distributed microsensor systems
enable fault-tolerant monitoring and control of a variety of applications.
Due to the large number of microsensor nodes that may be deployed, and the
long system lifetimes required, replacing the battery is not an option. Sensor
systems must utilize minimal energy while operating over a wide range of
operating scenarios. These include power-aware computation and communication
component technology, low-energy signaling and networking, system
partitioning considering computation and communication trade-offs, and a
power-aware software infrastructure. Routing and data dissemination in sensor
networks requires a simple and scalable solution. The topology discovery
algorithm for wireless sensor networks selects a set of distinguished nodes,
and constructs a reachability map based on their information. The topology
discovery algorithm logically organizes the network in the form of clusters
and forms a tree of clusters rooted at the monitoring node. The topology
discovery algorithm is completely distributed, uses only local information,
and is highly scalable.
To achieve optimal performance in a wireless sensor network, it is important
to consider the interactions among the algorithms operating at the
different layers of the protocol stack. For sensor networks, one question is
how the self-organization of the network into clusters affects the sensing
performance. Thousands to millions of small sensors form self-organizing
wireless networks, and providing security for these sensor networks is not
easy since the sensors have limited processing power, storage, bandwidth,
and energy. Aset of Security Protocols for Sensor Networks (SPINS), explores
the challenges for security in sensor networks. SPINS include: TESLA (the
micro version of the Timed, Efficient, Streaming, Loss-tolerant Authentication
Protocol), providing authenticated streaming broadcast, and SNEP (Secure
Network Encryption Protocol) providing data confidentiality, two-party data
authentication, and data freshness, with low overhead. An authenticated
routing protocol uses SPINS building blocks. Wireless networks, in general,
are more vulnerable to security attacks than wired networks, due to the
broadcast nature of the transmission medium. Furthermore, wireless sensor
networks have an additional vulnerability because nodes are often placed in
a hostile or dangerous environment, where they are not physically protected.
The essence of ubiquitous computing is the creation of environments saturated
with computing and communication in an unobtrusive way. WWRF
(Wireless World Research Forum) and ISTAG (Information Society Technologies
Advisory Group) envision a vast number of various intelligent devices,
embedded in the environment, sensing, monitoring and actuating the physical
world, communicating with each other and with humans. The main
features of the IEEE 802.15.4 standard are network flexibility, low cost, and
low power consumption. This standard is suitable for many applications in
the home requiring low data rate communications in an ad hoc self-organizing
network.
The IEEE 802.15.4 standard defines a low-rate wireless personal area
network (LR-WPAN) which has ultra-low complexity, cost, and power, for
low data rate wireless connectivity among inexpensive fixed, portable, and
moving devices. The IEEE 802.15.4 standard defines the physical (PHY)
layer and Media Access Control (MAC) layer specifications. In contrast to
traditional communication networks, the single major resource constraint in
sensor networks is power, due to the limited battery life of sensor devices.
Data-centric methodologies can be used to solve this problem efficiently. In
Data Centric Storage (DCS) data dissemination frameworks, all event data
are stored by type at designated nodes in the network and can later be
retrieved by distributed mobile access points in the network. Resilient Data-
Centric Storage (R-DCS) is amethod of achieving scalability and resilience by
replicating data at strategic locations in the sensor network. Various wireless
technologies, like simple RF, Bluetooth, UWB (ultrawideband) or infrared
can be used for communication between sensors. Wireless sensor networks
require low-power, low-cost devices that accommodate powerful processors,
a sensing unit, wireless communication interface and power source, in a
robust and tiny package. These devices have to work autonomously, to require
no maintenance, and to be able to adapt to the environment. Wireless Sensor
Network Designs focuses on the newest technology in wireless sensor networks,
networked embedded systems, and their applications. A real applicationsoriented
approach to solving sensor network problems is presented. The book
includes a broad range of topics from networked embedded systems and
smart sensor networks, to power-aware wireless sensor networks, routing,
clustering, security, and operating systems along with networks support.
The book is organized into ten chapters, with the goal to explain the newest
sensor technology, design issues, protocols, and solutions to wireless sensor
network architectures.
As previously discussed, Chapter 1 describes networked embedded systems,
their design, prototyping, and application support. Chapter 2 introduces
smart sensor networks and their applications. Chapter 3 introduces
power-aware wireless sensor networks. Routing in wireless sensor networks
and the aggregation techniques are discussed in Chapter 4. Distributed sensor
networks are presented in Chapter 5, and clustering techniques in wireless
sensor networks are introduced in Chapter 6. Chapter 7 presents security
protocols in sensor networks. Operating systems for embedded applications
are discussed in Chapter 8. Chapter 9 presents network support for embedded
applications. Applications of wireless sensor networks are studied in
Chapter 10.
KEYWORDS:
Index
access point (AP), 152
Active Message (AM), 327, 364
actuator, 34, 58, 110, 112
Ad Hoc On Demand Distance Vector
Routing (AODV), 103, 105, 190
address space identifier (ASID), 254, 255
Advanced Configuration and Power
Interface (ACPI), 78
AES-128 (advanced encryption standard
128-bit cryptographic keys), 302
aggregate queries, 120, 121
altruist, 109, 114, 115
analog to digital converter (ADC), 33, 35,
52, 57, 66, 323, 334, 340, 356, 357, 361
application programming interface
(API), 11, 15, 16, 24, 47, 54, 122, 197,
198, 230, 291, 196, 318
application specific integrated circuit
(ASIC), 23, 28, 93
Asynchronous Connectionless (ACL)
link, 276, 282–284, 315, 317
attribute-based addressing, 101
authenticated broadcast, 219, 222
authentication, 241
Automatic Repeat Request (ARQ), 276,
281, 283
base station (BS), 215, 225, 337
base station transceiver (BTS), 151,
156–163
Baseband (BB) protocol, 278
Berkeley Software Distribution (BSD),
258, 259
Binary Phase Shift Keying (BPSK),
305
bit error rate (BER)
Bluetooth, 110, 142, 144–153, 162, 275,
277–288, 290, 293–298, 300, 314–319
broadcasting, 84, 222
C/OS, 265, 271, 341
Carrier Sense Multiple Access (CSMA),
117, 119, 120, 122, 199, 302, 332
carrier sense multiple access / collision
avoidance (CSMA/CA), 104, 110, 159,
302
Cellular IP, 287, 288
central processor unit (CPU), 19, 79, 80,
144, 243, 251
certifying authority (CA), 241
channel interface module (CIM), 46
cipher-block chaining (CBC), 217
class-based addressing, 104, 105
Wireless Sensor Network Designs A. Ha´c
. 2003 John Wiley & Sons, Ltd ISBN: 0-470-86736-1
386 INDEX
cluster head, 71, 72, 181–184, 198,
203–205, 207, 209
cluster, 171, 178, 185, 191, 192, 203, 208,
209
clustering, 81, 181, 198, 199, 202, 319
code generation, 20
codesign and reconfiguration, 2, 9
Complementary Metal-Oxide
Semiconductor (CMOS), 67, 68, 97, 98,
334, 343, 356
condition based maintenance, 24, 58, 325
connectivity map, 177
continuous variable slope delta
modulation (CVSD), 276, 281, 284
controller area network (CAN), 46, 47,
54, 55, 56, 59
Corner Cube Retroreflector (CCR), 156,
157, 160
cosynthesis method and prototyping
platform, 2, 4
counter mode (CTR), 217, 218
cue, 189, 343
Cyclic Redundancy Check (CRC), 276,
281, 283, 301, 317
data aggregation, 67, 70, 193, 194, 293,
319, 349
Data Encryption Standard (DES), 242
Data Encryption Standard – Cipher
Block Chaining (DES-CBC), 218, 242
data fusion, 72
data link layer (DLL), 298, 299, 320
data-centric storage (DCS), 276, 306,
308–310, 314, 322
DES cipher-block chaining (DES-CBC),
242
DES electronic code book (DES-ECB),
242
design integration, 4
Destination Sequenced Distance Vector
Routing protocol (DSDV), 105
Digital Cordless Telephone (DCT), 338,
339, 341
Digital Signal Processing (DSP), 64, 75,
93, 95, 192, 196
direct sequence spread spectrum (DSSS),
152, 302, 305, 321
directed diffusion, 81
Distance Vector Multicast Routing
Protocol (DVMRP), 161
distributed aggregate management
(DAM), 346
distributed hash-table (DHT), 308, 309
Distributed Multidrop System (DMS), 38
distributed sensor networks, 141
dynamic power management (DMP), 76,
79
Dynamic Source Routing (DSR), 190
dynamic voltage scaling (DVS), 64, 68,
69, 73–75, 79, 95, 97–99
dynamically reconfigurable
field-programmable gate array
(DPGA) board, 4–7, 10, 11, 14–19, 29
Electronically Erasable Programmable
Read Only Memory (EEPROM), 54,
122, 333, 356, 357, 361
embedded application, 235, 258, 275
embedded Cygnus operating system
(eCOS), 67, 74, 271
embedded device, 12
embedded operating system, 26, 264, 265
embedded system, 1–8, 12, 64, 261, 357
embedded systems platform, 17
encryption algorithm, 2
energy aware routing (EAR), 101–103,
106, 107, 109–113, 115–117, 119, 120,
136
energy-efficient communication, 81
energy-quality (E-Q), 64, 65, 69, 70, 76,
208
epoch, 224
Ethernet, 47, 56, 111
External Storage (ES), 308
Fast Fourier Transform (FFT), 33, 194
Field Programmable Gate Array (FPGA),
5, 9, 10, 14, 16, 17, 20, 22–30, 93
Finite Impulse Response (FIR), 17, 69
FIR filter, 17, 69, 72, 75, 196
INDEX 387
First Node Dies (FND), 181, 184
flooding, 84, 112, 198, 199, 200, 211
Forward Error Correction (FEC), 195,
196, 276, 281, 283, 317
FPGA architecture, 25
Frame Check Sequence (FCS), 301
Frequency Hopping Spread Spectrum
(FHSS), 153, 154, 275, 283
friendly neighbor, 109, 114
garbage collection, 260
gateway, 147, 198, 204, 205, 290, 291, 293,
295–297, 318, 319, 336, 359
General Purpose Interface Bus (GPIB), 35
Geographical Adaptive Fidelity (GAF),
359
global positioning system (GPS), 186, 199
Global Standard for Mobile (GSM), 188
Great Duck Island (GDI), 351, 352, 358,
359
Greedy Perimeter Stateless Routing
(GPSR), 306, 308, 309, 315, 322
grouping, 133
guaranteed time slots (GTS), 301
Half of the Nodes Alive (HNA), 181, 184
hardware abstraction layer (HAL), 340,
341
hardware and software codesign, 3
Heating, Ventilation, and Air
Conditioning (HVAC), 298
high-level synthesis (HLS), 20, 30
HiperLAN/2, 152
Host Controller Interface (HCI), 144, 146
IEEE 1451 Standards for Smart
Transducer Interface for Sensors and
Actuators, 32–49, 52, 54–61
IEEE 802.11, 82, 114, 115, 150, 152, 206,
298, 299, 358
IEEE 802.15, 152, 276, 298–306,
314–316, 320, 321
IETF Unidirectional Link Routing
Working Group, 161
implicit entry-exit pair (IEEP), 267, 268
IMT2000 (International Mobile
Telecommunication), 23, 24
in-network aggregation, 125, 133, 135
Industry Scientific Medical (ISM), 67,
143, 152, 153, 280, 281, 283, 294, 302,
316, 321, 340
Inferno operating system, 236, 239–241,
261, 274
Information Society Technologies
Advisory Group (ISTAG), 276
infrared data association (IrDA), 279,
286
infrared object exchange (IrOBEX), 279
Integrated Circuit (IC), 302
Integrated Device Technology (IDT), 261
Integrated Electronics, PiezoElectric
(IEPE), 40, 41
Inter Integrated Circuit, 143, 356, 357
International Telecommunication
Union – Telecommunication
Standardization Sector (ITU-T), 301
Internet Engineering Task Force (IETF),
161, 287
Internet Protocol (IP), 42, 203, 204,
286–288, 306, 307, 322
Internet, 4, 12, 46, 283, 317
interprocess communication (IPC), 243,
265, 266, 269, 270
interprotection domain call, 262, 264
interrupt handler, 263
interrupt latency, 263, 264
interrupt service routine (ISR), 265
interrupt, 251, 252, 254
JaCoP (Java driven codesign and
prototyping environment), 2, 12, 13,
16–18, 29
Java Beans specification, 13, 17
Java Native Interface (JNI), 11, 15, 24, 27
Java programming language, 12, 39, 259,
260
Java virtual machine (JVM), 10, 15, 19,
22, 27, 29
Joint Test Action Group (JTAG), 339
388 INDEX
Large Scale Office Scenario (LSOSC),
118, 119, 120
LaserMirror Scanner (LMS), 70
Last Node Dies (LND), 181, 184
Light Emitting Diode (LED), 145
line-of-bearing (LOB), 194
line-of-sight, 161, 164
Link Manager (LM), 278
Link State Routing (LSR), 105
Linked Cluster algorithm (LCA), 191,
192
Linux, 11, 14, 18, 146, 149, 265, 268, 271,
357
local area network (LAN), 46, 150, 286,
287
Local Storage (LS), 308
logical link control (LLC), 278, 299, 300,
320, 321
Logical Link Control and Adaptation
Protocol (L2CAP), 146
Low Energy Adaptive Clustering
Hierarchy (LEACH), 81, 181, 182, 184,
193
Low Power Oscillator (LPO), 281, 282,
284
low-rate wireless personal area network
(LR-WPAN), 298, 301, 306, 314
Management Information Base (MIB),
168
master, 146, 153, 163, 281–285, 294–296,
317, 319
maximum transmission unit (MTU), 279,
286, 317
Media Access Control (MAC), 81, 82, 83,
96, 103, 104, 109–111, 113, 114, 116,
117, 120, 137, 159, 186, 187, 292,
298–304, 314, 320, 321, 324, 332, 358,
359, 360
MAC common part sublayer
(MCPS-SAP), 300, 321
MAC footer (MFR), 300
MAC header (MHR), 300
MAC layer management entity
(MLME-SAP), 300, 321
MAC protocol data unit (MPDU), 300
MAC service data unit (MSDU), 300
message authentication code (MAC),
216, 218–225, 232
Message Digest 4 (MD4), 241
Message Digest 5 (MD5), 221, 241, 242
Micro Controller Unit (MCU), 145
Micro Electro Mechanical Systems
(MEMS), 65, 67, 75, 95, 141, 151, 154,
157, 161, 165, 192, 288, 292, 314, 334,
345
micro-Adaptive Multi-domain
Power-aware Sensors (µAMPS), 71,
72, 73, 84, 95
micro-TESLA, 213–215, 217, 220–222,
224, 230, 231, 233
microcontroller, 35
microprocessor, 31, 58
microsensor, 35, 64, 65, 72, 77, 81, 192,
338
Million Instructions Per Second (MIPS),
92, 144, 236, 243, 245, 253, 254, 261
minimum shift keying (MSK), 305
mobile ad hoc network (MANET), 185,
187, 190, 198–201, 203, 208
Mobile IP, 287
mote, 121, 152, 156–158, 359
Motion Pictures Experts Group (MPEG),
237, 260
MPR Node (MPRN), 201
multifunction systems, 2
multimode systems, 2
Multipoint Relay (MPR), 201–103
Network Capable Application Processor
(NCAP), 36–38, 43, 45–49, 52–56, 59,
61
networked embedded system, 2, 9,
11–30
nucleus, 251, 253, 255
object-oriented design, 3, 13, 88
Offset Quadrature Phase Shift Keying
(O-QPSK), 305
Open Shortest Path First (OSPF), 161
INDEX 389
open systems interconnection (OSI)
reference model, 299
operating system (OS), 235, 236,
242–245, 264, 266–270, 273, 341
operation, administration, and
maintenance (OA&M), 237
output feedback mode (OFB), 217
passive clustering, 198–200, 203–207,
210
PC Interface (PCI), 5, 11, 15, 18, 23, 24
Pebble operating system, 235, 242–245,
252, 253, 255, 257–259, 261, 271, 273
Perimeter Refresh Protocol, 309
Personal Area Network (PAN), 152, 301,
302
Personal Computer (PC), 4, 5, 14, 18, 19,
125, 277, 285, 291, 297–299, 320, 341
personal digital assistant (PDA), 23, 24,
153, 188, 259, 275, 277, 286, 291, 298,
352, 355
Phase Lock Loop (PLL), 68, 69, 73
physical (PHY) layer, 298, 300, 314, 321
physical layer protocol data unit
(PPDU), 304
physical layer service data unit (PSDU),
304
piconet, 146, 147, 153, 282, 284, 294, 296,
316, 317, 319
Plan 9 operating system, 238, 244
plug-and-play, 58
Point Coordination Function (PCF), 114
portal manager, 253, 274
portal traversal, 248
portal, 244, 246, 247, 249, 250, 252,
255–258, 261, 271, 272, 273, 336
power management (PM), 76, 78
power-aware design, 65
power-aware wireless sensor networks,
63
Printed Circuit Board (PCB), 73
profiling, 3
programming language C++, 242, 260,
327
programming language C, 145, 238–240,
242, 258, 260, 271, 340, 341, 364
programming language Limbo, 238, 239,
240, 259
programming language Pascal, 238
protection domain (PD), 246–249, 272
Pseudo-Noise (PN), 305
Quality of Service (QoS), 2, 93, 152, 283,
305, 315
Quantum Effect Design (QED), 261
radio frequency (RF), 75, 95, 154, 162,
192, 215, 275, 278, 288, 290, 314, 318,
323, 330, 340
random access memory (RAM), 7, 18, 52,
54, 57, 58, 67, 133
reachability map, 177
Read Only Memory (ROM), 54, 67
Received Signal Strength Indicator
(RSSI), 84, 281
Reduced Instruction Set Computer
(RISC), 18, 93, 144, 153, 335, 339
request to send / clear to send
(RTS/CTS), 159
Resilient Data-Centric Storage (R-DCS),
276, 307, 310, 312
Resource Reservation Protocol (RSVP),
288
reuse library, 3
RF Module (RFM), 122
RFCOMM, 279
RFM (RF Monolithics), 330, 331, 355
Route Reply (RREP), 106
Route Request (RREQ), 105, 106
Routing Information Protocol (RIP), 161
routing, 123, 190
RS232, 143, 144, 339, 341
run-time system (RTS), 20, 22, 23
runtime management, 15
S-MAC (sensor-MAC), 360
scatternet, 153, 294, 295, 316, 319
scratch-pad memory, 7
Secure Hash Algorithm (SHA), 241, 242
390 INDEX
Secure Network Encryption Protocol
(SNEP), 213, 217–219, 221, 223, 225,
230
Security Protocols for Sensor Networks
(SPINS), 213, 216, 217, 223, 230, 231
self-configuring wireless sensor
network, 109
self-organizing wireless network, 276
semaphore, 247, 250, 262
sensor fusion, 338
Serial Peripheral Interface (SPI) protocol,
52, 339
service access point (SAP), 299, 300
Service Discovery Protocol (SDP), 296
service-specific convergence sublayer
(SSCS), 299, 300, 321
signal to interference ratio (SIR)
signal to noise ratio (SNR), 66, 96
Simple Mail Transfer Protocol (SMTP),
355
simulated annealing, 8
sink, 112, 118, 176
slave, 146, 147, 153, 163, 281–285, 294,
295, 317, 319
Small to Medium Enterprise (SME),
56
Smart Dust, 151, 152, 154, 158, 159,
164
smart sensor, 31, 34, 58, 121
Smart Transducer Interface Module
(STIM), 37–41, 43, 45–49, 51–56, 58,
61
software synthesis, 4
source, 112, 138
special function register (SFR), 57, 58
specification, 3
static RAM (SRAM), 144, 339, 340
station-to-station (STS), 241
steam-based function (SBF), 25
StrongARM, 67–69, 72, 76, 78, 84, 339,
357
Structured Query Language (SQL), 102,
121, 124, 126, 134, 135, 347
Structured Replication in DCS (SR-DCS)
scheme, 309
Styx protocol, 238
Surface Mount Device (SMD), 151
symmetric block cipher (RC6), 227
symmetric key stream cipher (RC4), 242
Synchronous Connection Oriented
(SCO) link, 276, 282–284, 315, 317
synthesis, 9
system call entry-exit pair (SCEEP), 267,
268
System Developers Toolkit (SDT), 341
system programming interface (SPI), 53,
145
Systems Performance Evaluation
Consortium (SPEC92), 92
target tracking, 214
thread, 6, 190, 248, 251, 262–264
Time Division Duplex (TDD), 283, 294
time division multiple access (TDMA),
160, 337, 341, 358
Timed, Efficient, Streaming,
Loss-tolerant Authentication Protocol
(TESLA), 215, 220
TinyOS, 152, 323, 324, 326–328, 330–333,
360, 362, 364
topology discovery, 166, 169, 171, 177,
209
Transaction Control Protocol (TCP), 288
Transaction Control Protocol/Internet
Protocol (TCP/IP), 36, 46, 279, 286,
317, 358
Transducer Bus Interface Module
(TBIM), 38, 43, 47, 48, 60
Transducer Electronic Data Sheet
(TEDS), 32, 33, 38, 39, 42–44, 47–49,
51, 54, 57–59, 60
Transducer Independent Interface (TII),
37, 49, 51, 54, 57
translation lookaside buffer (TLB), 243,
253–255
transmit power control (TPC), 152
ubiquitous computing, 325
Ultra Wide Band (UWB), 288, 290, 314,
318
INDEX 391
universal asynchronous receiver
transmitter (UART), 144, 145, 326, 330
Universal Serial Bus (USB), 144
Unix, 236, 240, 256, 257, 260, 262
untrusted location, 215
User Datagram Protocol (UDP), 286
Very Large Scale Integration (VLSI), 64,
85, 92, 95
VHDL (VHSIC Hardware Description
Language), 4, 10, 14, 22, 30, 325
VHSIC (Very High Scale Integrated
Circuit), 325
VHSIC Hardware Description Language
(VHDL), 4, 10, 14, 22, 30, 325
vibration sensors, 32–34
Video Cassette Recorder (VCR), 298
virtual memory (VM), 11, 15, 243, 248,
249, 253
VLSI systems, 64, 85, 97
voltage controlled oscillator (VCO), 68
weak freshness, 219, 232
Web-based applications, 3
wide area network (WAN), 353, 354
wireless application protocol (WAP),
279, 286
Wireless Integrated Network Sensors
(WINS), 162, 324, 334–338, 340, 341,
343–345, 362, 363, 365, 366
Wireless Local Area Network (WLAN),
150, 152
Wireless World Research Forum
(WWRF), 276
World Wide Web (WWW), 2
zone routing protocol (ZRP), 190, 191
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