Wireless Sensor Networks - Introduction

1. Wireless Sensor Networks - Introduction • Sensors in WSN • Sensing node • Wireless Sensor Netwworks • Communication in WSN • Challenges and Constraints • Selected applications of WSN

2. 1. Sensors in WSN Data acquisition and actuation • Signal conditioning • amplification (or attenuation) to change • thesignal magnitude • filters to the signal to remove unwanted noisewithin certain frequency ranges (e.g., highpass filters can be used to remove 50 or 60 Hznoise picked up by surrounding power lines) • Anactuator can be: • a valve controlling the flow of hotwater, • a motor that opens or closes a door or window, • a pump that controls the amount offuel injected into an engine.

3. 2. Sensing node • The components of a sensing node include: • sensing and actuation unit • processing unit • communication unit • power unit • other application-dependent units

4. The term sensor node is the most general. The terms Smart Dust, mote and COTS (commercial off-the-shelf) mote are used somewhat interchangeably in the industry.

5. 3. Wireless sensor networks Awireless sensor has not only a sensing component, but also on-board processing, communication, and storage capabilities. With these enhancements, a sensornode is often not only responsible for data collection, but also for in-network analysis, correlation, and fusion of its own sensor data and data from other sensor nodes. When manysensors cooperatively monitor large physical environments, they form a wireless sensor network (WSN). Sensor nodes communicate not only with each other but also with a base station (BS) using their wireless radios, allowing them to disseminate their sensor data to remote processing, visualization, analysis, and storage systems.

6. 4. Communication in WSN • The well-known IEEE 802.11 family of standards was introduced in 1997 and is the mostcommon wireless networking technology for mobile systems. • It uses different frequencybands, for example, • 2.4-GHz band is used by IEEE 802.11b and IEEE 802.11g, • 5 GHz for IEEE 802.11a. • Data rates provided by IEEE 802.11 are typicallymuch higher than needed • This has led to the development of a variety of protocols that bettersatisfy the networks’ need for low power consumption and low data rates. • For example,the IEEE 802.15.4 protocol has been designed for short-rangecommunications in low-power sensor networks and is supported by most academicand commercial sensor nodes. Single-hop versus multi-hop communication in sensor networks. When the transmission ranges of the radios of all sensor nodes are large enough and the sensors can transmit their data directly to the base station, they can form a star topology. In mesh topology, sensor nodes must not only capture and disseminate their own data, but also serve as relays for other sensor nodes, that is, they must collaborate to propagate sensor data towards the base station.

7. Standards for Transport Protocols

8. 5. Challenges and Constraints 5.1. Energy The most often met constraint is that sensor nodesoperatewith limited energy budgets. Typically, they are powered through batteries, which mustbe either replaced or recharged (e.g., using solar power). For some nodes,neither option is appropriate, that is, they will simply be discarded once their energy sourceis depleted. For nonrechargeable batteries, a sensor node should be ableto operate until either its mission time has passed or the battery can be replaced (monitoringglacial movements may need sensors that can operate for several years while a sensor in abattlefield scenario may only be needed for a few hours or days). The energy consumption of CMOS-based processors is primarily due to switching energy and leakage energy: ECPU = Eswitch + Eleakage = CtotalV dd2+ VddIleakt where Ctotal is the total capacitance switched by the computation, Vdd is the supply voltage,Ileak is the leakage current, and t is the duration of the computation. Switchingenergy still dominates the energy consumption of processors. It is expected that in futureprocessor designs, the leakage energy will be responsible for more than half the energyconsumption.

9. 5.2. Self-Management Sensor nodes must be self-managing in that they configure themselves,operate and collaborate with other nodes, and adapt to failures, changes in the environment,and changes in the environmental stimuli without human intervention. Ad Hoc Deployment Sensors serving the assessment ofbattlefield or disaster areas could be thrown from airplanes over the areas of interest, butmany sensor nodes may not survive such a drop and may never be able to begin their sensingactivities. The surviving nodes must autonomously perform a variety of setupand configuration steps, including the establishment of communications with neighboringsensor nodes, determining their positions, and the initiation of their sensing responsibilities. Unattended Operation Many sensor networks, once deployed, must operate without human intervention, that is, configuration, adaptation, maintenance, and repair must be performed in an autonomous fashion. A self-managing device will monitor its surroundings, adapt to changes in the environment, and cooperate with neighboring devices to form topologies or agree on sensing, processing, and communication strategies.

10. 5.3. Wireless Networking Attenuationlimits the range of radio signals, that is,a radio frequency (RF) signal fades (i.e., decreases in power) while it propagates through amedium and while it passes through obstacles. The relationship between the received power PR and transmitted power PT of an RF signal can be expressed using the inverse-square law: An increasing distance between a sensor node and a base station rapidlyincreases the required transmission power. Therefore, it is more energy-efficient to split alarge distance into several shorter distances, leading to the challenge of supporting multi-hopcommunications and routing. Due to this challenge networks employ duty cyclesto preserve energy, that is, many sensor nodes use a power conservation policy where radios are switched off when they are not in use. As a consequence, during these down-times, the sensor node cannot receive messages from its neighbors nor can it serve as a relay for other sensors. Therefore, some networks rely on wakeup on demandstrategies to ensure that nodes can be woken up whenever needed. Usually this involves devices with two radios, a low-power radio used to receive wakeup calls and a high-power radio that is activated in response to a wakeup call. Another strategy is adaptive duty cycling, when not all nodes are allowed to sleep at the same time. Instead, a subset of the nodes in a network remain active to form a network backbone.

11. 5.4. Decentralized Management Centralizedalgorithms (e.g., executed at the base station) to implement network management solutions such as topology management or routing may be ifeasible due to yhe large scale and the energy constraints. Instead, sensornodes must collaborate with their neighbors to make localized decisions, that is, withoutglobal knowledge. As a consequence, the results of these decentralized (or distributed)algorithms will not be optimal, but they may be more energy-efficient than centralized solutions.

12. 5.5. Design Constraints While the capabilities of traditional computing systems continue to increase rapidly, the primarygoal of wireless sensor design is to create smaller, cheaper, and more efficient devices. Due to this, typicalsensor nodes have the processing speeds and storage capacities of computer systemsfrom several decades ago. Theseconstraints and requirements also impact the software design at various levels, for example,operating systems must have small memory footprints and must be efficient in their resourcemanagement tasks. However, the lack of advanced hardware features (e.g., support for parallelexecutions) facilitates the design of small and efficient operating systems. A sensor’shardware constraints also affect the design of many protocols and algorithms executed ina WSN. While in-network processing can be employed to eliminate redundant information, some sensorfusion and aggregation algorithms may require more computational power and storagecapacities than can be provided by low-cost sensor nodes. Therefore, many software architecturesand solutions (operating system, middleware, network protocols) must be designedto operate efficiently on very resource-constrained hardware.

13. 5.6. Security The remote and unattendedoperation of sensor nodes increases their exposure to malicious intrusions and attacks. One of the most challenging security threats is a denial-of-serviceattack, whose goal is to disrupt the correct operation of a sensor network. This can beachieved using a variety of attacks, including a jamming attack , where high-powered wireless signals are used to prevent successful sensor communications. While there are numeroustechniques and solutions for distributed systems that prevent attacks, many of these incur significant computational, communication,and storage requirements, which often cannot be satisfied by resource-constrained sensornodes. As a consequence, sensor networks require new solutions for key establishment anddistribution, node authentication, and secrecy.

14. 5.7. Other Challenges Comparison of traditional networks and wireless sensor networks While traditional computer networks are based on established standards, many protocols and mechanisms in wireless sensor networks are proprietary solutions, while standards-basedsolutions emerge only slowly. Standards are important for interoperability and facilitate thedesign and deployment of WSN applications; therefore, a key challenge in WSN designremains the standardization of promising solutions and the harmonization of competingstandards.

15. 6. Selected applications of WSN Home control Home control applications provide control, conservation, convenience and safety. Body-worn medical sensors (e.g. heartbeat sensors) are also emerging.

16. Building Automation • Building automation provide control, conservation, flexibility and safety as follows: • management of lighting, heating, • cooling and safety • control of systems to improve conservation • optimized HVAC management • rapid reconfiguring the lighting system to create adaptable workspaces • enable to network and integrate data from multiple access control points.

17. Industrial Automation • Industrial automation applications provide : • process control systems reliability • reduce energy costs • identification of poorly performing equipment and inefficient operations • provide detailed data to improve preventive maintenance • help deploy monitoring networks to enhance employee and public safety.

18. Medical Applications PDA displaying real-time vital signs of multiple patients.

19. Security Applications • Military sensor networks detect • information about enemy movements, • explosions etc. • law enforcement and national security applications (figure) • sensor networks to detect chemical, biological, radiological and explosive attacks and material • environmental changes in forests, oceans and so on • monitoring of vehicle traffic on highways or in congested parts of a city • parking lot occupation sensor networks • borders monitoring with sensors ans sattelite uplinks. Real time monitoring and sensor interrogation

20. Highway Monitoring Traffic in US is growing at three times the rate of population growth. Traffic Pulse Technology (US) is an example of a system using stationary WNs, which collects data through sensor network, processes and stores the data in a data center. Temperature, pollution levels are collected in real-time. Digital sensor network gathers lane-by-lane data on travel speeds, lane occupancy and vehicle counts. The data are transmitted to the data center for reformatting (every 60 seconds). Typical highway traffic-sensing installation

21. Civil Engineering Applications Sensor technology is aplicable for buildings, bridges and other structures. The picture shows a prototype WSN developed at the University of California, Berkeley, and deployed at the Golden Gate Bridge in San Francisco. The bridge has a center span that sustains a maximum transverse deflection (due to wind or earthquake) of 27.7 ft and maximum upward and downward deflections of 5.8 ft and 10.8 ft, respectively. The towers are 500 ft high above the roadway and 746 ft high above the water. The tops of the towers can have transverse deflections of up to 12.5 in. and toward the shore longitudinal deflections of 22 in. Sixty-four wireless sensor nodes were deployed on this bridge to establish a structural health monitoring network. The nodes were distributed over the main span and the tower, collecting ambient vibrations synchronously, at a rate of 1 kHz, with less than 10 μs jitter and with an accuracy of 30 μG. Data is collected reliably over a 46-hop network. The deployment scenario of nodes on the GoldenGate Bridge: a) the nodes are deployed onboth sides of the span. b) a two-dimensional view of the placement of nodes on the bridge.