Wireless Sensor Networks (WSN)

2Abstract:

Advances in silicon technology have led to the development of next-generation, low-cost, low-power, multifunctional, sensor devices. These devices communicate wirelessly to transmit their readings. They are called wireless sensors and present a new facet in the field of communication and computer networks. Wireless sensors are compact devices that integrate communication, computation and microelectrical mechanical (MEMS) devices into a single chip.

A sensor network is a collection of communicating sensing devices or nodes. A large number of sensors can be spread across a geographical area and networked in many applications that require unattended operations, hence producing a wireless sensor network (WSN). The power of WSNs lies in the ability to deploy large numbers of such tiny sensor nodes. While the capability of any single device is minimal, the composition of hundreds of devices offers a significant opportunity for parallel, accurate and reliable data acquisition.

Introduction:

With the recent technological advances in wireless communications,integrated digital circuits, and micro electro mechanical systems (MEMS); development of wireless sensor networks has been enabled and become dramatically feasible.

Wireless sensor networks (WSNs) are large networks made of a numerous number of sensor nodes with sensing, computation, and wireless communications capabilities.

Many various routing, power management, and data dissemination protocols have been designed for wireless sensor networks (WSNs) dependent on both the network architecture and the applications that it is designed for. In this paper, we present the state of the art of wireless sensor networks' architecture and design features. Also, in this paper, we introduce recent work on routing protocols for WSNs and their design goals and challenges. Also, an overview of the application that WSNs assist in is presented. Finally, several open research questions of wireless sensor networks management and issues are suggested and put forward.

Wireless sensor network (WSN) is the result of the combination of sensor techniques, embedded techniques, distributed information processing, and communication mechanisms. A WSN is a network that is made of hundreds or

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3thousands of these sensor nodes which are densely deployed in an unattended environment with the capabilities of sensing, wireless communications and computations

WSN is a network made of a numerous number of sensor nodes with sensing, wireless communications and computation capabilities. These sensor nodes are scattered in an unattended environment situated far from the user

Routing Protocols for WSNs

A. Flooding

Flooding [5] is an old routing mechanism that may also be used in sensor

networks. In Flooding, a node sends out the received data or the management

packets to its neighbors by broadcasting, unless a maximum number of hops for that packet are reached or the destination of the packets is arrived. here are some deficiencies for this routing technique [ Implosion: is the case where a duplicated data or packets are sent to the same node. Overlap: if two sensor nodes cover an overlapping measuring region, both of them will sense/detect the same data. As a result, their neighbor nodes will receive duplicated data or messages. Resource blindness: A WSN protocol must be energy resource-aware and adapts its sensing, communication and computation to the state of its energy.

B. Gossiping

Gossiping protocol is an alternative to flooding mechanism. In Gossiping, nodes can forward the incoming data/packets to randomly selected neighbor node. Once a gossiping node receives the messages, it can forward the data back to that neighbor or to another one randomly selected neighbor node. This technique assists in energy conservation by randomization. Gossiping can solve the implosion problem.

C. SPIN

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4SPIN (Sensor Protocols for Information via Negotiation) is a family of adaptive protocols for WSNs. Their design goal is to avoid the drawbacks of flooding protocols mentioned above by utilizing data negotiation and resource-adaptive algorithms.

D. Directed di_usion

Directed di_usion is another data dissemination and aggregation protocol. It is a data-centric and application aware routing protocol for WSNs. It aims at naming all data generated by sensor nodes by attribute-value pairs.

E. LEACH

LEACH (Low Energy Adaptive Clustering Hierarchy) is a self-organizing, adaptive clustering-based protocol that uses randomized rotation of cluster-heads to evenly distribute the energy load among the sensor nodes in the network

F. PEGASIS

PEGASIS (Power-E_client GAthering in Sensor Information Systems) is a greedy chain-based power e_cient algorithm.The key features of PEGASIS are

The BS is fixed at a far distance from the sensor nodes. The sensor nodes are homogeneous and energy constrained with

uniform energy. No mobility of sensor nodes.

G. GEAR

GEAR (Geographical and Energy Aware Routing) is a recursive data dissemination protocol WSNs. It uses energy aware and geographically informed neighbor selection Heuristics to rout a packet to the targeted region

Applications

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5Various fields of applications of wireless sensor networks are:

A. Area Monitoring:

Area monitoring is a common application of WSNs. In area monitoring, the WSN is deployed over a region where some phenomenon is to be monitored. A military example is the use of sensors detects enemy intrusion; a civilian example is the geo-fencing of gas or oil pipelines.

B. Environmental/Earth Monitoring: The term Environmental Sensor Networks, has evolved to cover many applications of WSNs to earth science research. This includes sensing volcanoes, oceans ,glaciers, forests .

C. Air pollution Monitoring:

Wireless sensor networks have been deployed in several cities (Stockholm, London or Brisbane) to monitor the concentration of dangerous gases for citizens. These can take advantage of the ad-hoc wireless links rather than wired installations, which also make them more mobile for testing readings in different areas. There are various architectures that can be used for such applications as well as different kinds of data analysis and data mining that can be conducted.

D. Forest fire Detection:

A network of Sensor Nodes can be installed in a forest to detect when a fire has started. The nodes can be equipped with sensors to measure temperature, humidity and gases which are produced by fire in the trees or vegetation. The early detection is crucial for a successful action of the firefighters; thanks to Wireless Sensor Networks, the fire brigade will be able to know when a fire is started and how it is spreading.

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6E. Landslide Detection:

A landslide detection system,makes use of a wireless sensor network to detect the slight movements of soil and changes in various parameters that may occur before or during a landslide. Through the data gathered it may be possible to know the occurrence of landslides long before it actually happens.

F. WaterQulity Monitoring:

Water quality monitoring involves analyzing water properties in dams, rivers, lakes & oceans, as well as underground water reserves. The use of many wireless distributed sensors enables the creation of a more accurate map of the water status, and allows the permanent deployment of monitoring stations in locations of difficult access, without the need of manual data retrieval.

G. Natural disaster Prevention:

Wireless sensor networks can effectively act to prevent the consequences of natural disasters, like floods. Wireless nodes have successfully been deployed in rivers where changes of the water levels have to be monitored in real time.

Industrial Monitoring H. Machine Health Monitoring:

Wireless sensor networks have been developed for machinery condition-based maintenance (CBM) as they offer significant cost savings and enable new functionalities. In wired systems, the installation of enough sensors is often limited by the cost of wiring. Previously inaccessible locations, rotating machinery, hazardous or restricted areas, and mobile assets can now be reached with wireless sensors.

I. Data logging:

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7Wireless sensor networks are also used for the collection of data for monitoring of environmental information, this can be as simple as the monitoring of the temperature in a fridge to the level of water in overflow tanks in nuclear power plants. The statistical information can then be used to show how systems have been working. The advantage of WSNs over conventional loggers is the “live” data feed that is possible.

J. Industrial sense and control applications:

In recent research a vast number of wireless sensor network communication protocols have been developed. While previous research was primarily focused on power awareness, more recent research have begun to consider a wider range of aspects, such as wireless link reliability, real-time capabilities, or quality-of-service. These new aspects are considered as an enabler for future applications in industrial and related wireless sense and control applications, and partially replacing or enhancing conventional wire-based networks by WSN techniques.

K. Green houses:

Wireless sensor networks are also used to control the temperature and humidity levels inside commercial greenhouses. When the temperature and humidity drops below specific levels, the greenhouse manager must be notified via e-mail or cell phone text message, or host systems can trigger misting systems, open vents, turn on fans, or control a wide variety of system responses.

L. Others:

Acoustic Detection Seismic Detection Military Surveillance Inventory Tracking Medical Monitoring

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8 Smart Spaces Process Monitoring Agriculture Sector Medical Sector

WSN Management

The behavior of WSN is highly unpredictable and dynamic. All these factors have to be incorporated by various sensor network models that describe the current network's states. Some of the possible suggested models are:

A. Network Topology Model:

It describes the actual topology map and the connectivity and/or reachability of the network.

B. Residual Energy Model:

Describes the remaining energy level of the nodes or the network. Using this information as well as the data from network topology coupled together; would make it possible to identify the weak areas.

C. Cost Model:

Describes the cost of equipment, energy, and human cost to maintain the desired performance levels of the network.

D. Usage Patterns Model:

Represents the activity of the network in terms of period of time for nodes' activity, quantity of data transmitted per sensor unit or the movements made by the target, and tracking of hot spots in the network to avoid hot spot problem.

E. Behavioral Model:

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9Describes the behavior of the network. Since sensor networks are highly unpredictable, dynamic, and unreliable, statistical and probabilistic models may be much more e_cient in estimating the network behavior than estimating the network behavior than deterministic models.

F. Coverage Area Model:

A sensing coverage area map that represents the actual sensor's view of the environment and communications coverage map that describes the communication coverage area from the range of the RF transceiver.

Operating systems used in WSN

A WSN typically consists of hundreds or thousands of sensor nodes. These nodes have the capability to communicate with each other using multi-hop communication. Typical applications of these WSN include but not limited to monitoring, tracking, and controlling.

The basic functionality of an operating system is to hide the low-level details of the sensor node by providing a clear interface to the external world.

Processor management, memory management, device management, scheduling policies, multi-threading, and multitasking are some of the LowLevel services to be provided by an operating system.

In addition to the services mentioned above, the operating system should also provide services like support for dynamic loading and unloading of modules, providing proper concurrency mechanisms, Application Programming Interface (API) to access underlying hardware, and enforce proper power management policies.

A. TinyOS:

TinyOS is an open source, flexible, component based, and application-specific operating system designed for sensor networks. TinyOS can support concurrent programs with very low memory requirements. The OS has a footprint that fits in 400 bytes. The TinyOS component library includes network protocols, distributed services, sensor drivers, and data acquisition tools.

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10B. Contiki OS

Contiki is a lightweight open source OS written in C for WSN sensor nodes. Contiki is a highly portable OS and it is build around an event-driven kernel. Contiki provides preemptive multitasking that can be used at the individual process level. A typical Contiki configuration consumes 2 kilobytes of RAM and 40 kilobytes of ROM. A full Contiki installation includes features like: multitasking kernel, preemptive multithreading, proto-threads, TCP/IP networking, IPv6, a Graphical User Interface, a web browser, a personal web server, a simple telnet client, a screensaver, and virtual network computing.

C. MANTIS:

The MultimodAl system for NeTworks of In-situ wireless Sensors (MANTIS) provides a new multithreaded operating system for WSNs. MANTIS is a lightweight and energy efficient operating system. It has a footprint of 500 bytes, which includes kernel, scheduler, and network stack. The MANTIS Operating System (MOS) key feature is that it is portable across multiple platforms, i.e., we can test MOS applications on a PDA or a PC [28]. Afterwards, the application can be ported to the sensor node. MOS also supports remote management of sensor nodes through dynamic programming. MOS is written in C and it supports application development in C.

D. Nano-RK:

Nano-RK is a fixed, preemptive multitasking real-time OS for WSNs. The design goals for Nano-RK are multitasking, support for multi-hop networking, support for priority-based scheduling, timeliness and schedulability, extended WSN lifetime, application resource usage limits, and small footprint. Nano-RK uses 2 Kb of RAM and 18 Kb of ROM. Nano-RK provides support for CPU, sensors, and network bandwidth reservations. Nano-RK supports hard and soft real-time applications by the means of different real-time scheduling algorithms, e.g., rate monotonic scheduling and rate harmonized scheduling. Nano-RK provides networking support through socket-like abstraction. Nano-RK supports FireFly and MicaZ sensing platforms.

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11E. Lite OS:

LiteOS [35] is a Unix-like operating system designed for WSNs at the University of Illinois at Urbana-Champaign. The motivations behind the design of a new OS for WSN are to provide a Unix-like OS for WSN, provide system programmers with a familiar programming paradigm (thread-based programming mode, although it provides support to register event handlers using callbacks), a hierarchical file system, support for object-oriented programming in the form of LiteC++, and a Unix-like shell. The footprint of LiteOS is small enough to run on MicaZ nodes having an 8 MHz CPU, 128 bytes of program flash, and 4 Kbytes of RAM. LiteOS is primarily composed of three components: LiteShell, LiteFS, and the Kernel.

F. EPOS:

EPOS (Embedded Parallel Operating System) is a component-based framework for the generation of dedicated runtime support environments. The EPOS system framework allows programmers to develop platform-independent applications and analysis tools allow components to be automatically adapted to fulfill the requirements of these particular applications. By definition, one instance of the system aggregates all the necessary support for its dedicated application and nothing else.

Table 1. Operating Systems Summary

Architecture

Programming model

Scheduling

Memory Management and Protection

Communication Protocol Support

Resource Sharing

Support for Real-time Applications

TinyOS

Monolithic

Primarily event Driven, suppor

FIFO Static Memory Management

Active Message

Virtualization and Completion

No

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12t for TOS threads has been added

with memory protection

Events

Contiki

Modular Protothreads and events

Events are fired as they occur. Interrupts execute w.r.t. priority

Dynamic memory management and linking. No process address space protection.

uIP and Rime

Serialized Access

No

MANTIS

Layered Threads

Five priority classes and further priorities in each priority class.

Dynamic memory management supported but use is discouraged, no memory protection.

At Kernel Level COMM layer. Networking Layer is at user level. Application is free to use custom

Through Semaphores.

To some extent at process scheduling level (Implementation of priority scheduling within

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13routing protocols.

different processes types)

Nano-RK

Monolithic

Threads

Rate Monotonic and rate harmonized scheduling

Static Memory Management and No memory protection

Socket like abstraction for networking

Serialized access through mutexes and semaphores. Provide an implementation of Priority Ceiling Algorithm for priority inversion.

Yes

LiteOS

Modular Threads and Events

Priority based Round Robin Scheduling

Dynamic memory management and it provides memory protect

File based communication

Through synchronization primitives

No

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14ion to processes.

Miscellaneous:

OS/Feature

Communication Security

File System Support

Simulation Support

Programming Language

Shell

TinyOS TinySec Single level file system

TOSSIM NesC Not available

Contiki ContikiSec Coffee file system

Cooja C Unix-like shell runs on sensor mote

MANTIS Not available

Not available

Through AVRORA

C Unix-like shell runs on sensor mote

Nano-RK Not available

Not available

Not available

C Not available

LiteOS Not available

LiteFS Through AVRORA

LiteC++ Shell that runs on base station

Future research directions in OS:

Support for Real-Time Applications, Secondary Storage Management Virtual Memory Support, Memory Management and Security ,Support for Multiple Applications, Robust Communication Protocol Stack Security, Database Management System ImplementationLocalization and Clock Synchronization API Support, APIs for Signal and Image Processing. [1] [2]

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WSN Architecture:

A. Transport layer:

This layer is specifically needed when a system is organized to access other networks. Providing a reliable hop by hop is more energy efficient than end to end.Other protocol used in this layer is STCP (Sensor Transmission Control Protocol) PORT (Price-Oriented Reliable Transport Protocol) PSFQ (pump slow fetch quick).

B. Network layer:

The major function of this layer is routing. This layer has a lot of challengesdepending on the application but apparently, the major challenges are in the power saving, limited memory and buffers, sensor does not have a global ID and have to be self organized.

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16C. Data link layer:

Responsible for multiplexing data streams, data frame detection, MAC, and error control, ensures reliability of point–point or point– multipoint. Errors or unreliability comes from:

Co- channel interference at the MAC layer and this problem is solved by MAC protocols.

Multipath fading and shadowing at the physical layer and this problem is solved by forward error correction (FEC) and automatic repeat request (ARQ).

D. Physical layer:

Can provide an interface to transmit a stream of bits over physical medium. Responsible for frequency selection, carrier frequency generation, signal detection, Modulation and data encryption.

E. Application layer:

Responsible for traffic management and provide software for different applications that translate the data in an understandable form or send queries to obtain certain information. Sensor networks deployed in various applications in different fields, for example; military, medical, environment, agriculture fields.

F. MAC layer:

Responsible for Channel access policies, scheduling, buffer management anderror control. In WSN we need a MAC protocol to consider energy efficiency, reliability, low access delay and high throughput as major priorities.

Different Networking Technologies for Wireless Sensor Networks:

A. Bluetooth:

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17IEEE 802.15.1 standard, popularly known as Bluetooth, offers moderate data rates at lower energy levels. Due to this, it is ideally suited for high end WSN applications that require higher data rates with harder real time constraints. Bluetooth is used in star topology because of its basic characteristics. Bluetooth devices communicate with each other using set of standard Bluetooth profiles defined by standard body.

B. ZigBee:

IEEE 802.15.4 standard, popularly known as ZigBee, offers low data rates at very low energy levels. Due to this, it is ideally suited for applications requiring infrequent smaller data transfers where battery life is an important issue. However, location estimation based on narrow band DSSS can achieve accuracy only in the order of several meters.

ZigBee coordinator is responsible for managing the network and supervising network formation; ZigBee routers have routing capabilities and they are responsible for linking group of end devices or routers; and ZigBee end devices are simple network end points capable of communicating with other devices in the network.

C. UWB:

Ultra wide band is a technology for transmitting information spread over a large bandwidth (>500 MHz) and it is ideally suited for short distance, high speed communications with very low power budget. As it is based on wide band technology, it can achieve very high geo-location accuracy to the sub-meter levels. UWB provides one of the best options for WSN networking only limited by its shorter range.

D. Wi-Fi:

Wi-Fi represents group of WLAN technologies defined under IEEE 802.11 standard body. In addition to transmission standards like 802.11a/b/g/n, it also includes 802.11s standard for mesh networking. Wi-Fi technologies are capable of

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18providing very high throughput (>100 Mbps) at longer range but required very high power budget. Also, Wi-Fi can locate end point location to the accuracy of several meters only. Because of this limitation, use of Wi-Fi is mostly restricted to devices with fixed power supply.

Wireless Sensor Networks vs. Ad Hoc Networks (MANET):

WSN MANETApplications and equipments

Small sensor nodes with constrained hardware and energy supply.

In general, unattended operation

Powerful nodes with large batteries(laptops)

In general, more elaborateApplications.e.g VoIP, with human interaction.

Redundancy

High Low

Data rate Low High Application specific

Infinite number of application in terms of devices,protocols,density etc.

Although, a few scenarios not as many as in wsns.

Environment interaction

Lot of environmental interactions

Low data rates, but also data bursts –new traffic patterns

More conventional human driven applications with well understood traffic characteristics.

Scale Huge amount of sensor Significantly

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19nodes-more scalable solutions required(e.g. protocols without node identifiers)

less nodes than in wsns.

Energy Tighter requirements, mostly no recharge or replacement of batteries possible

Energy constrained, but often energy can be recharged

Self Configurability

Almost equal to MANETs, but different data traffic and energy trade -offs.

One of the main features in MANETs

Dependability and QoS

Individual node is irrelevant as long as network is working

New QoS concepts necessary.

Each node should be reliable

Qos determined by applications such as VoIP jitter.

Data centric

Redundant deployment makes data centric protocols attractive.

Slightly limited resources, but in general normal os and applications can run on the nodes.

Simplicity & scarceness

Os and s/w must be simpler than on ‘normal’ PCs

Breaking of strict network layers isolation to achieve simplicity

Slightly limited resources, but in general normal os and application can run on the nodes

mobility Mostly stationary use, but movement for certain applications possible e.g. tracking applications

Movement can be

One of the main features of MANETs-caused by moving nodes

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20correlated e.g. sensors carried by a river

Movement can be correlated by moving groups

Advantages of WSN:

1. Implementation cost is cheaper than wired network.2. Ideal for temporary network setups.3. Ideal for the non reachable such as across river or mountains or rural

areas.

Challenges of WSN:

1. Lower speed compared to wired network.2. Less secure because hacker's laptop can act as access point.3. More complex to configure than wired network.4. Can be affected by surrounding's. For example, walls(blocking),

Microwave oven (interference), far distance.5. Sensor node has low battery power, so as battery goes down, node

Goes down and so does the whole network.6. Like any other wireless technology, it is easy for hackers to hack WSNs. For most

of the applications security & integrity of data is most important hence we have to select networking technology as well as security algorithms accordingly.

7. Due to limited resources and dynamic topology, it is very difficult to design a reliable routing scheme for WSNs.

8. Quite a few applications like solar energy monitoring, irrigation and air quality monitoring are associated with harsh environments. Independent of enclosure design, sensors will be exposed to the outdoor conditions and it is extremely crucial to take environmental conditions into consideration while designing WSN system.

9. Dynamic topologies and integration with internet affect factors like Quality-of-service requirements, security, packet errors and variable-link capacity.

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2110. Energy conservation is a very critical part of WSN because of small battery size. We need to look at traffic scheduling as well as remote wake-up features to optimize power consumption.

Conclusion:

In this paper, I presented the state of the art of wireless sensor networks; their architecture, routing protocols for WSNs, their applications. Also, in this paper, we introduced Also, in this paper; a brief review of the application based on wireless sensor networks is given. Also I introduced the difference between ad hoc networks and wsn. Finally, our directions and recommendations for wireless sensor network management are suggested.

References:

Safari magazine Google.com Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal, Wireless sensor network

survey, Elsevier Computer Networks 52 (2008) 2292–2330 Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam, and Erdal Cayirci, A

Survey on Sensor Networks, IEEE Communications Magazine, August 2002 Slideshare.com ->wireless sensor networks Wiki pedia Abrach, H., S. Bhatti, J. Carlson, H. Dai, J. Rose, A. Sheth, B. Shucker, J. Deng

and R. Han.MANTIS: System support for multimodal networks of in-situ sensors. In: 2nd ACM International Workshop on Wireless SensorNetworks and Applications, September, San Diego, USA, pp: 50-59. DOI: 10.1145/941350.941358.

References download:[1] AdiWirelessOS.pdf

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22[2] Summary of all os.pdf[3] Challenges in sensor networks[4] Disadvantages of wsn[5] Wsn vs. adhoc network

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