Advances in technology has provided the availability of small and low-cost sensor nodes with capability of sensing various types of physical and environmental conditions, data processing, and wireless communication. Variety of sensing capabilities results in profusion of application areas. However, the characteristics of Wireless Sensor Networks (WSN) require more effective methods for data forwarding and processing.
The purpose of this report to provide general knowledge of WSNs, application opportunities, and proposed routing for WSNs. Since there are too many routing algorithms for data forwarding problem in WSNs, only some of them will be presented in details. However, a full comparison of all methods will be given. What is Wireless Sensor Network
A wireless sensor network (WSN) is a wireless network consisting of distributed self-organized autonomous devices using sensors to cooperatively monitor physical or environmental conditions, such as vibration, motion, temperature, sound etc.
Depending on usage purpose there may be additional components such as localization unit, energy producer, position changer etc network security
. In the figure below, general architecture of WSN node and a real example is represented.
Figure 1: WSN Node acrhitecture and a real example.
Note.Haroun, I.,Lambadaris, I., Hafez, R. (September, 2005). Building Wireless Sensor Networks. Retrieved March 26, 2007 from the World Wide Web:
WSN nodes generally have small sizes up to the size of a coin. However, the sizes of WSN nodes may be furtherly decreased with future advances in micro-electro-mechanical systems (MEMS). Due to low bandwidth and low energy sources, transmission range of nodes is restricted with about approximately 30 meters. Thus, dense deployment of nodes is required for more reliable data transmission. The processing capacity of WSN nodes is also low both because of data processed by WSN nodes are too small and energy is limited.
In contrast to multi-threaded/multi-process general-purpose operating systems, WSN nodes use less complex operating systems and event-driven programming models. In contrast to modern operating systems, which consist of millions of lines of code,WSN operating systems codes consists of just a few thousands of lines. Some examples of WSN node operating systems are:
Also it should be considered that, since WSN node hardware is similar to embedded systems, it is possible to use some embedded operating systems such as eCos, uC/OS for sensor networks.
There are many commercially available sensor types to monitor variety of conditions including: Temperature Humidity Movement Lightning condition Pressure Soil makeup Noise levels Presence or absence of certain kinds of objects Mechanical stress levels on attached objects The current characteristics such as speed, direction and size of an object
As a result of availability of different kinds of sensors, there are various the applicationsof WSNs. A general categorization of WSN applications may include military applications, environmental applications, health applications and other commercial applications.
Dense deployment of disposable and low-cost sensor nodes makes WSN concept beneficial for battle fields. Some military applications of WSNs are:
Monitoring friendly forces, equipment and ammunition.
Exploration of opposing forces and terrain
Battle damage assessment
Nuclear, biological and chemical attack detection
Although there are some other techniques to monitor environmental conditions, random distribution and self organization of WSNs make them suitable for environmental monitoring. Some applications include:
Biocomplexity mapping of environment
Detection of natural disasters, such as fire, flood and eartquake detection
Tiny sizes and light-weight structure of WSN nodes provides many functionality in health applications, including:
Telemonitoring of human physiological data
Tracking and monitoring doctors and patients
In addition to all of above, there are many commercial applications of WSNs including
Home automation for smart home environments
Environmental control in buildings
Detecting and monitoring burglary/ thieving
Vehicle tracking and detection
Managing inventory control
Sharing information between physically separated hosts/ sources requires both physical connections between these hosts in terms of cables, links, etc. and a common language, called protocol, to make these hosts understand each other. Networking concept is built on variations of this principle. As in other networks, in WSNs we also need some routing techniques / protocols between nodes to provide connectivity among them in order to gather desired data. Although WSNs have some similarities with traditional networks, currently available routing protocols can not be directly applied to WSNs because of some characteristics of WSNs listed below:
low processing capacity
difficult operations conditions
limited energy source
huge population in WSNs
Non-predetermined position of sensor nodes
Design of routing protocols in WSNs is influenced by many challenging factors to be addressed. Some of them are:
Data reporting method
Quality of service
Figure 2: Routing protocols in WSNs.
Note. J. N. AL-Karaki, A. E. Kamal, -Routing Techniques in Wireless Sensor Networks: A Survey-, IEEE Wireless Communications, Volume 11, Issue 6, Dec. 2004 Page(s):6 - 28
As illustrated in figure 2, almost all routing methods can be classified into three categories depending on networks structure:
Furthermore, these protocols can be classified into subgroups listed below, depending on protocol operation.
Coherent based routing
Proactive routing protocols: All routes are computed before they are used.
Reactive routing protocols: Routes are computed as they are needed.
Hybrid routing protocols: uses both proactive and reactive routing protocols.
Cooperative routing protocols: Nodes send data to a central node where more processing power and route information is available.
Although in some special cases sensor nodes have mobilizers to change the position, most of the sensor nodes are static, i.e. remains in same position, therefore it is preferable to have table-driven routing protocols rather than reactive protocols.
In flat networks, each node typically plays the same role and sensor nodes collaborate together to perform the sensing task. Due to the large number of such nodes, it is not feasible to assign a global identifier to each node. This consideration has led to data centric routing, where the Base Station (BS) sends queries to certain regions and waits for data from the sensors located in the selected regions. Two main types of algorithms in flat routing are flooding, where each node forwards data to all its neighbor so to much redundant data occurs, and data-centric routing where there is no global identifiers for nodes, instead data is identified using attribute based naming.
This protocol uses the idea of distributing only the data that other nodes do not have, assuming the nodes in close proximity have similar data. Thus nodes avoid sending redundant data. Protocol starts when SPIN node gathers new data. Node broadcasts an ADV message containing metadata of newly obtained data. Any neighbor interested in that data sends a REQ message. After that the actual DATA is sent to neighbor node. Operation of SPIN network is illustrated in figure 2.
Figure 3: The SPIN protocol.
Note.Wendi Heinzelman, Joanna Kulik, and Hari Balakrishnan, Adaptive Protocols for Information Dissemination in Wireless Sensor Networks, Proc. 5th ACM/IEEE Mobicom Conference, Seattle, WA, August 1999.
Important advantage of SPIN protocol is that each node only knows its single-hop neighbors therefore topological changes in network localized, i.e. does not affect whole network. On the other hand, SPIN protocol does not guarantee delivery of data because intermediate nodes between source and destination nodes may not be interested in advertised data, therefore such data may not be forwarded to destination.
In spite of SPIN, where availability of data is advertised, in directed diffusion the BS broadcasts interest which describes a task required to be done by the network. Up on receiving the interest, each sensor node then stores the interest entry in its cache and sets up a gradient toward itself to the nodes from which it receives the interest. When a node has data for broadcasted interest, it sends data through the interest's gradient choosing only best paths to avoid further flooding. The steps of directed diffusion process are illustrated in Figure 4.
Figure 4 : Example of Directed Diffusion. (a) Propagate interest, (b) set up gradient and (c) send data.
I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. Wireless sensor networks: a survey. Computer Networks, 38(4):393-422, April 2002.
In MCFA each node records the estimated least cost from itself to Base Station. Initially at each node, the least cost is set to infinity ( ). The BS broadcasts a message with the cost set zero. Whenever a node receives the broadcast message, compares the cost of message with its estimated least cost. If the estimated cost on the message plus the cost of current link is less than what the node has, the estimate on the message and the estimate recorded by the node is updated and then message is broadcasted to neighbors, otherwise the broadcast message is discarded. The figure 5 illustrates steps of this process.
Figure 5: Minimum Cost Forwarding Algorithm
a) each node set its least cost to BS as
b) BS broadcast a message with least cost set to zero
c) if cost of message+link cost = local cost, discart message
Important disadvantage of MCFA is that, the nodes that are far away from the base station may get more broadcasts than those close to the BS. A solution to this problem is to use a backoff algorithm to constrain nodes from sending broadcasts until a * lc time elapsed from the time when message is updated, where a denotes a predefined constant and lc is the link cost of received message.
The paradigm in GBR is calculation of a parameter, called height of the node, which is the minimum path between node and Base Station (BS) in terms of the number of hops between them. The difference between a node's height and the height of its neighbor is called gradient of the link between them. While forwarding data, nodes choose the links which have largest gradient.
Energy Based Scheme: if the available energy of the node decreases below of a certain level, the node increases its height to prevent other nodes sending data to it.
Although this type of routing methods originally proposed in wired networks with their special advantages related to scalability and efficient communication, they also provide energy-efficient routing in WSNs. Some techniques that belong to this family are:
Power-Efficient Gathering in Sensor Information Systems
Threshold-Sensitive Energy Efficient Protocols
Small Minimum energy communication network ( MECN )
Hierarchical power-aware routing
Two-Tier Data Dissemination
In this type of protocols sensor nodes are addressed depending on their locations. network security
Relative coordinates of neighboring nodes is obtained either by exchanging information between neighbor nodes or by directly communicating with a Global Positioning System (GPS). Some techniques that belong to this family are:
Geographic Adaptive Fidelity
Geographic and Energy Aware Routing (GEAR)
MFR, DIR, and GEDIR
The Greedy Other Adaptive Face Routing (GOAFR)
In this report I have tried to explain main concepts of WSN, its features, applications, and finally some proposed routing protocols.I have mentioned that flexible and low-cost structures of WSNs make them applicable for various types of projects. The current situation of WSN can be considered under three different aspects
2) Network engineering perspective: although there are lots of proposed routing methods for WSNs, still new methods are need and currently existing ones need to be improved.
J. N. AL-Karaki, A. E. Kamal, -Routing Techniques in Wireless Sensor Networks: A Survey-, IEEE Wireless Communications, Volume 11, Issue 6, Dec. 2004 Page(s):6 - 28
Wendi Heinzelman, Joanna Kulik, and Hari Balakrishnan, -Adaptive Protocols for Information Dissemination in Wireless Sensor Networks-, Proc. 5th ACM/IEEE Mobicom Conference, Seattle, WA, August 1999.
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