Zippity Zigbee, zippity ay!

Picture this scene in the not too distant future: An instrument technician at a busy industrial site obtains clearance to install a new process sensor. He mounts the sensor to the prepared tapping point and makes sure everything is tight. He obtains clearance from the control center to crack open the isolating valve and commission the new sensor. The two-way on his belt crackles, and the duty operator in the control-center confirms the new sensor reading has appeared at his DCS monitor.

The instrument tech packs away his wrench and heads in for a coffee. The installation took him less than an hour. The sensor used a new wireless technology known as Zigbee, self-powered by a small internal battery.

Zigbee is coming. Whether you intend to use wireless or not, by the end of this decade, most instrumentation and automation products will have embedded wireless as a standard feature. Zigbee, also known as wireless mesh, is a new open wireless standard for wireless sensors.

Wireless in the control and automation world is evolving quickly. What was simply a novelty a few years ago is now becoming an established technology in industry. Ignoring this new technology won't be an option; I&C practitioners will need to come to grips with wireless as they have for every other new technology.

Other markets using sensing and control, such as HVAC, building management, and security, are already going wireless. The change process has started, and wireless will dominate these markets. Industrial wireless will follow in the same way Ethernet migrated to the industrial environment, driven by its low price and dominance in the outside world. Zigbee was principally developed for the volume markets of HVAC, security, and home automation. At its heart is an embedded low RF power transceiver, powered from an integral lithium battery.

Low power is the key to Zigbee. Most importantly it keeps the RF design simple, which keeps the price down, probably the prime concern for the HVAC and security markets. Low RF power also means low battery consumption. Having to connect power wires to a wireless sensor defeats the purpose, so wireless sensors need to be battery powered, and low RF power means an acceptable battery life.

Unfortunately low RF power also means short wireless operating distance, but Zigbee gets around this problem by forming a mesh. Zigbee transceivers can talk to each other, passing on wireless messages. Each sensor or node only has to transmit as far as the next node. A group of Zigbee devices automatically form a mesh, with each wireless message routing via the optimum path. If one device fails, the mesh self-heals, re-routing messages via the next best path.

And with future Zigbee chips envisaged at around $20 each, you can see why Zigbee will revolutionize HVAC and security. Sensors in these industries are already low cost, but wiring is expensive. Wireless sensors in HVAC means a lot more thermostats giving better control and lower energy costs. Wireless sensors in security means a much higher level of monitoring for the same outlay.

You probably wouldn't use an HVAC thermostat to monitor your hydro-cracker, and you won't need to. Zigbee can also fit into an industrial temperature transmitter as well as industrial flowmeters, level gauges, pressure transmitters, pH probes, and position sensors. In fact, it can fit all of the automation and process sensors we use every day.

But just because it is there doesn't mean you'll use it. We all know of products packed with high-tech features that don't see wide use. The same could happen with Zigbee. Industrial wireless products have been available for years, and there are concerns regarding latency delays and security. Wireless is not suitable for high-speed control applications, and this is unlikely to change. But it has proven reliable for most monitoring and slower control applications, that is, nearly 80% of automation and process applications. Technology has addressed security concerns, and to a large degree, has overcome them. The high cost of wiring has always been a constraint to collecting the nice-to-have plant data and turning it into useful information. Wireless can remove that constraint. But Zigbee has an added implicit weakness over traditional wireless because of its reliance on the mesh.

In the HVAC and security industry, customers will retrofit entire installations. Sensors are low-cost; it was the wiring that made installations expensive. It will be easy and inexpensive to cover buildings with HVAC and security sensors. A large wireless mesh will be easy to form. But industrial sensors are much more expensive. How many plants and factories are going to retrofit a large number of instrumentation sensors to form a mesh?

An added problem is RF propagation in an industrial environment will fade out long before a building environment. Steelwork is much harder to transmit through than drywall or masonry. Zigbee transmissions fade out in less than 100 feet in a lot of industrial applications. The reliance on the Zigbee mesh will be even greater.

Zigbee in the industrial environment will suffer from the eternal chicken-or-the-egg quandary. Which comes first, the sensor or the mesh? Without the mesh, Zigbee is limited. But without a large number of sensors, the mesh won't form. Early adopters will need to install a large number of Zigbee sensors before a mesh can form to transport the wireless signals.

The "Zigbee wireless sensor range in a typical plant" diagram is an example of an early adopter of Zigbee technology. Four wireless sensors have been installed, however none of them have the range to reach the control center, nor do they have the range to link to each other.

A solution to this constraint is to integrate tomorrow's technology with today's. Existing wireless networks known as wireless information backbones (WIBs) use higher-power wireless to penetrate through the obstacles of modern plants. A WIB differs from Zigbee because it is not intended to embed into sensors but acts as a higher-level wireless network, transferring multiplexed information throughout a plant or factory.

A WIB is a wireless network of gateways, providing connectivity to a large number of different or similar data buses. As its name implies, it is a wireless backbone for sharing information. You could think of it as wireless protocol conversion, but this would be too simple an explanation. It is a peer-to-peer network that can handle multiple protocol conversions, interconnecting multiple fieldbuses, or databus LANs. And it's all done wirelessly.

The advantage that the WIB has over Zigbee is power, RF power. Unlike Zigbee, which throttles its RF output to a few milliwatts, WIB nodes generate the full 1W of RF power allowed under FCC rules. A typical WIB node using 1W of RF power can penetrate through most plants and factories. A WIB has a similar mesh capability as Zigbee but rarely needs to use it. And a WIB solves the other problem facing Zigbee, the same problem hindering many data acquisition concepts, compatibility with the installed mass of existing fieldbuses and control room devices.

So why is Zigbee technology needed at all? The answer: cost. Because of its mass production and simple design, Zigbee devices will be a fraction of the cost of WIB devices. The wireless plant of the future will likely comprise two layers of wireless networks: Zigbee clusters for the sensor layer, and WIB networks for the controller layer.

WIB nodes would include an embedded Zigbee transceiver. Information from the local Zigbee cluster would then be transmitted via the backbone to other WIB nodes, and transferred to physical devices via Ethernet, Profibus, DeviceNet, Modbus, and the like. Will the two wireless systems interfere? They certainly could if they used the same wireless bands. However, most Zigbee products are likely to use the 2.4GHz band, which already has low-cost components available from mass-produced wireless systems in the commercial market, Wifi and Bluetooth. And most WIB systems use the 900MHz band, which gives better transmission performance in industrial environments. So the two technologies can coexist without interference or congesting a single wireless band.

ZigBee Technology

The idea behind ZigBee is to develop a standardized specification upon which low-power wireless sensor networks can operate and be interoperable. The ZigBee specification sits on top of the physical (PHY) and medium access control (MAC) layers of the IEEE802.15.4 standard (Fig 1).

The IEEE802.15.4 standard is focused on low-rate personal area networking with key unique features of low-power, packet-based, highly-secure, large networks at low-cost that will co-exist with other wireless networks (such as Wi-Fi). These make ZigBee suitable for reliable, low-power, wireless data communications for monitoring and control devices.

The ZigBee standard provides more complex network topologies such as tree and mesh networks, standardization and compliance, profiles for various applications and marketing activities. ZigBee divides the network into three layers, layer 1 being the PHY and MAC (IEEE802.15.4), layer 2 being the mesh network and layer 3 being the profiles. Each layer has separate compliance, so for instance, Jennics silicon products with the IEEE802.15.4 MAC in ROM is layer 1 compliant and multiple ZigBee stack vendors are then level 2 compliant.

The level 1 network layer (unique to the IEEE802.15.4 PHY and MAC) was established in 2003 and provides a number of features which are keys to wireless sensor networks pervading industrial, commercial buildings and home applications. As an example, networks will not be deployed in a commercial building unless they have the features of low-power, high level of security, long range, small size and will not interfere with a Wi-Fi network.

The level 2 network layer provides tree or mesh networking and has been established since 2005. Typically a mesh network comprises controllers (or full-function devices), routers and endpoints or reduced function devices (RFD). The key feature of a mesh network is to be able to dynamically add and remove devices (whether routers or endpoints) and the network adapts around the changes. A wide variety of network topologies can be configured, from long, thin networks to wide, fat networks.

At level 3 the ZigBee Alliance creates a number of profiles for common applications. This is at an early stage and will develop over time.

Application Diversity

There are a lot of talks in wireless markets of killer applications. Wireless sensor network products and applications wont have a single killer application, but hundreds of killer applications. The key to understanding the potential diversity of applications is to start from the standpoint of how to enable a specific application, rather than how to implement the standard. In other words, dont think ZigBee, but instead, think applications.

Applications based on this standard are not just limited to one specific market. Its possible to create networks from simple point-to-point networks to ZigBee compliant mesh networks in anything from industrial and commercial buildings, to home automation, personal healthcare and more.

In a typical home automation scenario (Fig 2), intelligent sensors can provide flexible control of lighting, heating, cooling, watering, appliances and security systems C from anywhere in the home. The potential benefits include the ability to adjust the home environment to run more efficiently and to reduce utility costs. In such an environment, the interoperable nature of the ZigBee standard means that even off-the-shelf products should work together in the networked environment. The fact that ZigBee is targeted at applications requiring low power, such as light switches and sensors, means that many of the sensors and nodes can operate using standard batteries for possibly years.

Another main advantage of ZigBee-based networks in a home automation application or even any industrial or other application is that builders and contractors can easily reconfigure heating, lighting, and security systems to accommodate additional sensors and nodes.

ZigBee Evolution

When looking at the how ZigBee is doing in terms of market acceptance and the potential applications it might address, its worth looking at the key challenges that any wireless standard faces and particularly how Wi-Fi and Bluetooth evolved.

The key factors that determine the potential market of a wireless standard are:

- Market awareness: systems developers need to know how to build solutions based on the standard;
- Worldwide standards: these are necessary to overcome the interoperability and co-existence requirements of products based on the standard;
- Technical and cost challenge: the chips that enable the standard must not add significant overhead to the product in terms of size or cost;
- Ease of use: the technology must be easy to implement and use in order to develop products based on the standard.

Both Wi-Fi and Bluetooth reached a critical mass when these factors were met, and in particular they became easy to use at the right price point. It was independent specialist fabless semiconductor companies that enabled products based on these standards to come to market quickly.

The wireless sensor market has reached that same point in its critical mass, with a diverse range of applications; the standard is published, and the technical and cost challenges are now addressed with products. Pricing of under US$5 in low volumes is acceptable to early adaptors and significant price reductions (to under US$2) can be expected as high-volume mass markets are built.

One of the earlier challenges for ZigBee on the standards front was the number of proprietary systems, niche company standards, and use of inappropriate standards (Bluetooth in low-power applications). There is now clear market demand for ZigBee-based products given the availability of a worldwide standard and easy-to-use enabling silicon that meets the technical and cost challenges.

Eliminating Complexity

Despite reaching critical mass, a barrier to entry for developers is the perceived complexity of the ZigBee standard. Many other wireless standards have not met this problem as they only served a small number of high-volume applications rather than the broad range of applications and markets covered by ZigBee.

If the wireless sensor network developer is able to approach the challenge from a solution-orientated viewpoint rather that standard-based angle, then there is more of a chance that the application can be implemented using the standard.

ZigBee provides the foundation to wirelessly communicate with its mesh network stacks, interoperability and co-existence with other networks.

One of the key challenges to the adoption of the standard on a wider scale in the many different markets it is suitable for is for vendors to offer solutions for the application rather than ZigBee products. When the standard is transparent to the user, then ZigBee will surely reach mass market acceptance.

by Jim Lindop, CEO, Jennic

Wireless Multimedia Sensor Networks

We deployed an experimental testbed at the BWN-lab based on currently-off-the-shelf advanced devices to demonstrate the efficiency of our newly developed algorithms and protocols for multimedia communications through wireless sensor networks. The architecture of our testbed is as follows:

Architecture of the BWN-lab Multimedia Wireless Sensor Network Testbed

Our laboratory has a sensor network testbed with 6 imotes from Intel and 50 micaz scalar motes from Crossbow. We plan to increase the number of micaz sensors in order to deploy a higher scale testbed that allows testing more complex algorithms and assess the scalability of the communication protocols under examination.

The testbed includes three different types of multimedia sensors:

• Low-end imaging sensors
• Medium-quality webcam-based multimedia sensors
• High-end pan-tilt cameras mounted on mobile robots

Low-end imaging sensors such as CMOS cameras can be interfaced with Xbow's micaz motes based on the Cyclops platform. Cyclops is an electronic interface between a CMOS camera module and a wireless mote such as MICA2 or MICAz, and contains programmable logic and memory for high-speed data communication.

The medium-end video sensors are based on Logitech webcams interfaced with Stargate platforms. Stargate is a high-performance processing platform designed for sensor, signal processing, control, robotics, and wireless sensor networking applications.

The high-end video sensors consist of pan-tilt cameras installed on a robotic platform. The objective is to develop a high-quality mobile platform that can perform adaptive sampling based on event features detected by low-end motes. The mobile actor, as we call it, can redirect high-resolution cameras to a region of interest when events are detected by lower-tier, low-resolution video sensors that are densely deployed.

The testbed also includes storage and computational hubs. These are needed to store large multimedia content and perform computationally intensive multimedia processing algorithms.

44 MICAZ motes equipped with whip antennas and placed in a rectangular grid formation.

6 Intel Imotes with Bluetooth radios forming a tree shaped scatternet. (Courtesy of Lama Nachman at Intel Research)

Acroname GARCIA, a mobile robot with a mounted pan-tilt camera and endowed with 802.11 as well as ZigBee interfaces.

GARCIA deployed on the sensor test-bed. It acts as a mobile sink, and can move to the area of interest for closer visual inspection.. It can also coordinate with other actors and has built-in collision avoidance capability.

44 MICAZ motes equipped with whip antennas and placed in a rectangular grid formation.

STARGATE based multimedia sensor interfaced with the MICAZ sensor testbed. This allows for video monitoring through the camera-STARGATE interface and communication to the sink through the on-board sensor mote or independently linking with a laptop through the 802.11 card.

The Technology

Our Technology

 WSN (Wireless Sensor Networks) provides an advanced solution for forest monitoring.  The wireless sensor network is composed of sensor nodes, relay nodes, and the base station.  Cellular networks can also be used considering the difficulty of achieving the necessary radio range coverage.

The base station will receive the sensing data from distributed relay nodes. The base station can use cellular networks or satellites to transmit the data to the end user, where the user-friendly web-based applications are provided. Users can access a real-time display of forest information and also dynamically configure the information of interest on the web application.

Here is a diagram illustrating a wireless sensor network for forest monitoring:

  

  Base Sensor Unit

The sensor nodes will be operated using Zigbee topology, an easy, low-cost, power-friendly flexible implementations technology. The power boosted gateway will collect the sensed data and transmit to an authenticated server station using satellite communication. Collected data will be stored in the database server, which will serve the user's web-interfaced queries.

Sensor Types

Below a few examples of sensors that can be installed on the base sensor unit, which will be installed on individual trees.

Pressure Sensor

CO2 Sensor

Humidity Temperature Sensor

Advantages of Wireless Sensor Networks:

-Greater resolution both in time and space
-WSN facilitate the collection of diverse types of data at frequent intervals over large areas (e.g., temperature, image, PAR).
-WSN enable ecologists and field biologists to unobtrusively collect new types of data, providing new insights on processes.
-Real-time data flows allow researchers to react rapidly to events, thus extending the laboratory to the field.
-The numbers and locations of sensors can be chosen/optimized/changed
-In general, the system is fault-tolerant. Any  failure can be detected in real time.
-Observing under extreme conditions
-Reacting to events as they unfold (e.g., to  change sampling rates, to begin  experiments after soil moisture has reached  a threshold)
-Controlled sensing: Sensing parameters  can be remotely changed/ modified (e.g.,  frequency of sensing, data rate, type of  data, sensing features, etc.)

Challenges

-Power requirements
-Extreme weather conditions
-Constraints: WSN design and deployment  will depend on the environment in which they  will operate as well as the needs of  ecologists.
-Transmission range
-Harsh environment

iSense Sensor Networking Kits

coalesenses offer different kits containing certain collections of hardware and software for particularly attractive prices.

iSense Sensor Network Starter Kit

The iSense Sensor Network Starter Kit provides an easy start into the world of wireless sensor networking with iSense hardware and software.

Distributed over three iSense sensor nodes, a broad variety of sensors is included:

• temperature and luminance sensor
• magnetic sensor for vehicle detection
• accelerometer and passive infrared sensor

In addition, an iSense Gateway Module with a USB cable for data transfer to and from a PC as well as an iSense Measurement Module for connecting custom sensors and PCBs are included in the starter Kit.

All this comes with a full collection of software (compiler, firmware, tools and sample applications), documentation and a guide to the first steps of wireless sensor networking.

iSense Sensor Network Classroom Kit

With the iSense Sensor Network Classroom Kit, coalesenses is offering special discount pricing to European educational institutions to support all kinds of hands-on-experiences such as wireless sensor networking laboratories and other experimental courses.

The Classroom Kit contains 25 wirelessly programmable nodes plus 5 iSense Gateway Modules for connection to PCs. All this comes with a full collection of software (compiler, firmware, tools and sample applications), documentation and a guide to the first steps of wireless sensor networking. On top, we offer educational materials for a 2 day wireless sensor network laboratory course.

In addition, an optionally available sensor kit that contains 20 iSense Environmental Sensor Modules (temperature and light sensor) can be ordered at a reduced kit price.

The Classroom Kit is available to all European educational institutions that offer practical courses on wireless sensor networking.

Wireless Sensor Network Topologies

The development of network technologies has prompted sensor folks to consider alternatives that reduce costs and complexity and improve reliability. Early sensor networks used simple twisted shielded–pair (TSP) implementations for each sensor. Later, the industry adopted multidrop buses (e.g., Ethernet). Now we’re starting to see true web-based networks (e.g., the World Wide Web) implemented on the factory floor.

Figure 1. In point-to-point network topologies, each sensor node requires a separate twisted shielded–pair wire connection. The cost is high, configuration management is difficult, and nearly all the information processing is done by the host.

As wireless sensors become real commodities on the market, new options or new arguments for old options are causing professionals to consider network strategies once ruled out. Let’s look at the three classic network topologies (point-to-point, multidrop, and web), assess their strengths and weaknesses, and look at how the rules have changed now that wireless systems are coming online.

In addition, to build functional sensor networks, you’ll probable have to integrate hardware and software from multiple vendors (see the sidebar “Network Questions,”). So along with everything else, you have to come to terms with standards and protocols—those that exist, those that are emerging, and those needed to ensure interoperability on the factory floor.

Point-to-Point Networks

Theoretically, these systems are the most reliable because there is only one single point of failure in the topology—the host itself (see Figure 1). You can improve the system by adding redundant hosts, but wiring two hosts can be a problem. The 4–20 mA standard allows multiple readout circuits if the standard loads are used at each readout. Problems can arise if readout devices load the circuit beyond its capability, but most designers are familiar with the limitations and are sufficiently careful.

Figure 2. In a multidrop network, each sensor node puts its information onto a common medium. This requires careful attention to protocols in hardware and software. The single-wire connection represents a potential single-point failure. But some vendors supply redundant connections to mitigate this potential problem.

Some networks provide frequency-modulated (FM) signals on the wires to carry multiple sensor readings on separate FM channels. Some standards (e.g., the HART bus) support multiplexing of digital signals on the existing analog wiring in older plants. These architectures blur the distinction between point-to-point and multidrop networks.

Early wireless networks were simple radio-frequency (RF) implementations of this topology. These networks used RF modems to convert the RS-232 signal to a radio signal and back again. Fluke (Everett, Wash ington) developed a digital voltmeter that could be configured to accept a voltage signal and transmit the signal over a dedicated radio frequency channel. The reliability of these implementations was sometimes suspect because most were designed with simple FM coding. Interference and multipath propagation effects caused significant degradation in factory environments, so many networks proved to be unreliable unless designers were particularly careful. The Federal Communications Commission licensed companies and devices to operate at the allocated frequencies.

Complete wireless local area networks (LANs) were implemented using this technique.These were successful in the office environment but didn’t fare as well in factories. Many designers implemented remote data acquisition systems with this topology by using a data concentrator in the field to feed the data to a radio transmitter for transmission to the hosts, where the signals were demultiplexed into the original sensor signals.

Multidrop Networks

Figure 3. In a web topology, all nodes are potentially connected to all other nodes. Connectivity among a large collection of sensors gets complex because all nodes must have a connection to all other nodes. Some connections can be eliminated by using repeaters and routers to make virtual connections. The World Wide Web is a good example of this topology.

Multidrop buses began to appear in the late 70s and early 80s. One of these, Modbus from Modicon (Schneider Auto mation, North Andover, Massa chusetts), led the way into the industrial sphere, followed by several proprietary and open buses (e.g., the Manufacturing Auto mation Protocol, QBus, and VME Bus).

The emergence of intelligent sensors and microcomputers capable of operating in industrial environments irrevocably changed the sensor network landscape. Multidrop networks (buses) reduced the number of wires required to connect field devices to the host, but they also introduced another single point of failure—the cable. Several suppliers of industrial-grade products offered redundant cabling designs, but these came with an increase in complexity (see Figure 2).

Once the industry began the migration to multidrop buses, problems associated with digitization began to emerge. With the previous point-to-point systems, digitization occurred in the host, where a single clock could be used to time stamp when the analog signals from multiple sensors were acquired. With the distributed intelligence required to implement a multidrop network, synchronization of clocks became a critical issue in some applications. This remains an important design parameter for any distributed digital system.

Figure 4. An architecture consisting of a decoder for each channel and a direct-sequence spread-spectrum receiver can perform simultaneous sampling because the same baseband signal goes to each decoder. But the decoders represent a significant cost, power, and size limitation.

The introduction of Ethernet in the mid-80s was a landmark in standardization, if not technological innovation. A group of large companies agreed that the future of computer networking required an open interconnect standard that would allow multiple-vendor systems to work together with minimal difficulty.

Researchers looked closely at the carrier sense multiple access with collision detection (CSMA/CD) protocol when they investigated the behavior of networks under stress. But they considered most industrial applications too time critical for such a nondeterministic protocol. Now, fifteen years later, most factories have converted their shop floor networks to Ethernet because it is the best compromise between cost and performance. Many companies now offer solutions that use Ethernet to implement suitable robust industrial networks.

Wireless systems use the same types of protocols to implement multidrop topologies, simulating hard-wired connections with RF links. The IEEE-802.11 standard was the first wireless standard that promised to bring the interoperability of Ethernet connectivity to wireless networks. Many of these, however, are not compatible at the over-the-air level.

Security Requirements in Wireless Sensor Networks

1.1 Confidentiality

Confidentiality requirement is needed to ensure that sensitive information is well protected and not revealed to unauthorized third parties.

The confidentiality objective is required in sensors’ environment to protect information traveling between the sensor nodes of the network or between the sensors and the base station from disclosure, since an adversary having the appropriate equipment may eavesdrop on the communication. By eavesdropping, the adversary could overhear critical information such as sensing data and routing information. Based on the sensitivity of the data stolen, an adversary may cause severe damage since he can use the sensing data for many illegal purposes i.e. sabotage, blackmail. For example, competitors may use the data to produce a better product i.e. safety monitoring sensor application. Furthermore, by stealing routing information the adversary could introduce his own malicious nodes into the network in an attempt to overhear the entire communication.

If we consider eavesdropping to be a network level threat, then a local level threat could be a compromised node that an adversary has in his possession. Compromised nodes are a big threat to confidentiality objective since the adversary could steal critical data stored on nodes such as cryptographic keys that are used to encrypt the communication.

1.2 Authentication

As in conventional systems, authentication techniques verify the identity of the participants in a communication, distinguishing in this way legitimate users from intruders.

In the case of sensor networks, it is essential for each sensor node and base station to have the ability to verify that the data received was really send by a trusted sender and not by an adversary that tricked legitimate nodes into accepting false data. If such a case happens and false data are supplied into the network, then the behavior of the network could not be predicted and most of times will not outcome as expected.

Authentication objective is essential to be achieved when clustering of nodes is performed. clustering involves grouping nodes based on some attribute such as their location, sensing data etc and that each cluster usually has a cluster head that is the node that joins its cluster with the rest of the sensor network (meaning that the communication among different clusters is performed through the cluster heads). In these cases, where clustering is required, there are two authentication situations which should be investigated; first it is critical to ensure that the nodes contained in each cluster will exchange data only with the authorized nodes contained and which are trusted by the specified cluster (based on some authentication protocol). Otherwise, if nodes within a cluster receive data from nodes that are not trusted within the current community of nodes and further process it, then the expected data from that cluster will be based on false data and may cause damage. The second authentication situation involves the communication between the cluster heads of each cluster; communication must be established only with cluster heads that can prove their identity. No malicious node should be able to masquerade as a cluster head and communicate with a legitimate cluster head, sending it false data or either compromising exchanged data.

1.3 Integrity

Moving on to the integrity objective, there is the danger that information could be altered when exchanged over insecure networks. Lack of integrity could result in many problems since the consequences of using inaccurate information could be disastrous, for example for the healthcare sector where lives are endangered.

Integrity controls must be implemented to ensure that information will not be altered in any unexpected way. Many sensor applications such as pollution and healthcare monitoring rely on the integrity of the information to function with accurate outcomes; it is unacceptable to measure the magnitude of the pollution caused by chemicals waste and find out later on that the information provided was improperly altered by the factory that was located near by the monitored lake. Therefore, there is urgent need to make sure that information is traveling from one end to the other without being intercepted and modified in the process.

1.4 Freshness

One of the many attacks launched against sensor networks is the message replay attack where an adversary may capture messages exchanged between nodes and replay them later to cause confusion to the network. Data freshness objective ensures that messages are fresh, meaning that they obey in a message ordering and have not been reused. To achieve freshness, network protocols must be designed in a way to identify duplicate packets and discard them preventing potential mix-up.

1.5 Secure Management

Management is required in every system that is constituted from multi components and handles sensitive information. In the case of sensor networks, we need secure management on base station level; since sensor nodes communication ends up at the base station, issues like key distribution to sensor nodes in order to establish encryption and routing information need secure management. Furthermore, clustering requires secure management as well, since each group of nodes may include a large number of nodes that need to be authenticated with each other and exchange data in a secure manner. In addition, clustering in each sensor network can change dynamically and rapidly. Therefore, secure protocols for group management are required for adding and removing members, and authenticating data from groups of nodes.

1.6 Availability

Availability ensures that services and information can be accessed at the time that they are required. In sensor networks there are many risks that could result in loss of availability such as sensor node capturing and denial of service attacks. Lack of availability may affect the operation of many critical real time applications like those in the healthcare sector that require a 24 / 7 operation that could even result in the loss of life. Therefore, it is critical to ensure resilience to attacks targeting the availability of the system and find ways to fill in the gap created by the capturing or disablement of a specific node by assigning its duties to some other nodes in the network.

1.7 Quality of Service

Quality of Service objective is a big headache to security. And when we are speaking about sensor networks with all the limitations they have, quality of service becomes even more constrained. Security mechanisms must be lightweight so that the overhead caused for example by encryption must be minimized and not affect the performance of the network. Performance and quality in sensor networks involve the timely delivery of data to prevent for example propagation of pollution and the accuracy with which the data reported match what is actually occurring in their environment.

What Is a Wireless Sensor Network?

Introduction

A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. The distributed measurement nodes communicate wirelessly to a central gateway, which provides a connection to the wired world where you can collect, process, analyze, and present your measurement data. To extend distance and reliability in a wireless sensor network, you can use routers to gain an additional communication link between end nodes and the gateway. 

National Instruments Wireless Sensor Networks offer reliable, low-power measurement nodes that operate for up to three years on 4 AA batteries and can be deployed for long-term, remote operation. The NI WSN protocol based on IEEE 802.15.4 and ZigBee technology provides a low-power communication standard that offers mesh routing capabilities to extend network distance and reliability. The wireless protocol you select for your network depends on your application requirements. To learn more about other wireless technologies for your application, read the “Selecting the Right Wireless Technology” white paper.

WSN Applications

Embedded monitoring covers a large range of application areas, including those in which power or infrastructure limitations make a wired solution costly, challenging, or even impossible. You can position wireless sensor networks alongside wired systems to create a complete wired and wireless measurement and control system.

A WSN system is ideal for an application like environmental monitoring in which the requirements mandate a long-term deployed solution to acquire water, soil, or climate measurements. For utilities such as the electricity grid, streetlights, and water municipals, wireless sensors offer a lower-cost method for collecting system health data to reduce energy usage and better manage resources. In structural health monitoring, you can use wireless sensors to effectively monitor highways, bridges, and tunnels. You also can deploy these systems to continually monitor office buildings, hospitals, airports, factories, power plants, or production facilities. 

WSN System Architecture

In a common WSN architecture, the measurement nodes are deployed to acquire measurements such as temperature, voltage, or even dissolved oxygen. The nodes are part of a wireless network administered by the gateway, which governs network aspects such as client authentication and data security. The gateway collects the measurement data from each node and sends it over a wired connection, typically Ethernet, to a host controller. There, software such as the NI LabVIEW graphical development environment can perform advanced processing and analysis and present your data in a fashion that meets your needs. 

Figure 2. Common Wireless Sensor Network Architecture

Power and Network Standards

A WSN measurement node contains several components including the radio, battery, microcontroller, analog circuit, and sensor interface. In battery-powered systems, you must make important trade-offs because higher data rates and more frequent radio use consume more power. Today, battery and power management technologies are constantly evolving due to extensive research.

Often in WSN applications, three years of battery life is a requirement, so many of the WSN systems today are based on ZigBee or IEEE 802.15.4 protocols due to their low-power consumption. The IEEE 802.15.4 protocol defines the Physical and Medium Access Control layers in the networking model, providing communication in the 868 to 915 MHz and 2.4 GHz ISM bands, and data rates up to 250 kb/s. ZigBee builds on the 802.15.4 layers to provide security, reliability through mesh networking topologies, and interoperability with other devices and standards. ZigBee also allows user-defined application objects, or profiles, which provide customization and flexibility within the protocol.

In addition to long-life requirements, you must consider the size, weight, and availability of batteries as well as international standards for shipping batteries. The low cost and wide availability of carbon zinc and alkaline batteries make them a common choice. Energy harvesting techniques are also becoming more prevalent in wireless sensor networks. With devices that use solar cells or collect heat from their environment, you can reduce or even eliminate the need for battery power. 

Processor Trends

To extend battery life, a WSN node periodically wakes up to acquire and transmit data by powering on the radio and then powering it back off to conserve energy. The WSN radio must efficiently transmit a signal and allow the system to go back to sleep with minimal power use. Likewise, the processor must also be able to wake, power up, and return to sleep mode efficiently. Microprocessor technology trends for WSNs include reducing power consumption while maintaining or increasing processor speed. Much like your radio choice, the power consumption and processing speed trade-off is a key concern when selecting a processor for WSNs. This makes PowerPC and ARM-based architectures a difficult option for battery-powered devices. A more common architecture option includes the TI MSP430 MCU, which is designed for low-power operation. Depending on the specific processor, power consumption in sleep mode can range from 1 to 50 µW, while in on-mode the consumption can range from 8 to 500 mW.

Networking Topologies

You can use several network topologies to coordinate the WSN gateway, end nodes, and router nodes. Router nodes are similar to end nodes in that they can acquire measurement data, but you also can use them to pass along measurement data from other nodes. The first, and most basic, is the star topology, in which each node maintains a single, direct communication path with the gateway. This topology is simple but restricts the overall distance that your network can achieve.

To increase the distance a network can cover, you can implement a cluster, or tree, topology. In this more complex architecture, each node still maintains a single communication path to the gateway but can use other nodes to route its data along that path. This topology suffers from a problem, however. If a router node goes down, all the nodes that depend on that router node also lose their communication paths to the gateway.

The mesh network topology remedies this issue by using redundant communication paths to increase system reliability. In a mesh network, nodes maintain multiple communication paths back to the gateway, so that if one router node goes down, the network automatically reroutes the data through a different path. The mesh topology, while very reliable, does suffer from an increase in network latency because data must make multiple hops before arriving at the gateway.

Figure 3. WSN Network Topologies 

The NI Wireless Sensor Network Advantage

With the National Instruments WSN platform, you can customize and enhance a typical WSN architecture to create a complete wired and wireless measurement system for your application. NI software integration provides the flexibility to choose a Windows-based host controller for your WSN system or a real-time controller such as NI CompactRIO, giving you the ability to integrate reconfigurable I/O with your wireless measurements. With either host controller, you can use LabVIEW and the NI-WSN software with LabVIEW project integration and drag-and-drop programming to easily configure your WSN system, extract high-quality measurement data, perform analysis, and present your data.

In addition, LabVIEW integration delivers the ability to stretch the connectivity of your WSN from the enterprise and database level all the way through the Internet to end client devices, such as an iPhone or laptop. You can use this complete system architecture to acquire data from virtually anywhere with an NI wireless sensor network, process and host that data on a server, and then access the data conveniently and remotely from a wireless smart device. To learn more about the options in WSN measurement system architectures, visit the NI WSN Measurement Systemswhite paper.