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Wireless Sensor Networks pt 1: Introduction
By: Eliana Stavrou
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    2005-06-08

    Table of Contents:
  • Wireless Sensor Networks pt 1: Introduction
  • Sensor Node Features
  • Sensor Research Challenges

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    Wireless Sensor Networks pt 1: Introduction


    (Page 1 of 3 )

    Wireless sensor networks are a trend of the past few years, and they involve deploying a large number of small nodes. The nodes then sense environmental changes and report them to other nodes over a flexible network architecture. Sensor nodes are great for deployment in hostile environments or over large geographical areas. This article will introduce basic concepts and architecture of sensor networks to familiarize you with their issues.

    Usage of sensor networks

    Sensor networks have been useful in a variety of domains. The primary domains at which sensor are deployed follow:

    • Environmental observation. Sensor networks can be used to monitor environmental changes. An example could be water pollution detection in a lake that is located near a factory that uses chemical substances. Sensor nodes could be randomly deployed in unknown and hostile areas and relay the exact origin of a pollutant to a centralized authority to take appropriate measures to limit the spreading of pollution. Other examples include forest fire detection, air pollution and rainfall observation in agriculture.
    • Military monitoring. Military uses sensor networks for battlefield surveillance; sensors could monitor vehicular traffic, track the position of the enemy or even safeguard the equipment of the side deploying sensors.
    • Building monitoring. Sensors can also be used in large buildings or factories monitoring climate changes. Thermostats and temperature sensor nodes are deployed all over the building’s area. In addition, sensors could be used to monitor vibration that could damage the structure of a building.
    • Healthcare. Sensors can be used in biomedical applications to improve the quality of the provided care. Sensors are implanted in the human body to monitor medical problems like cancer and help patients maintain their health.

    Network model

    A wireless sensor network consists of hundreds or thousands of low cost nodes which could either have a fixed location or randomly deployed to monitor the environment. Due to their small size, they have a number of limitations, an issue that I will discuss later. Sensors usually communicate with each other using a multi hop approach. The flowing of data ends at special nodes called base stations (sometimes they are also referred to as sinks). A base station links the sensor network to another network (like a gateway) to disseminate the data sensed for further processing. Base stations have enhanced capabilities over simple sensor nodes since they must do complex data processing; this justifies the fact that bases stations have workstation/laptop class processors, and of course enough memory, energy, storage and computational power to perform their tasks well. Usually, the communication between base stations is initiated over high bandwidth links.

    Keep in mind that one of the biggest problems of sensor networks is power consumption, which is greatly affected by the communication between nodes. To solve this issue, aggregation points are introduced to the network. This reduces the total number of messages exchanged between nodes and saves some energy. Usually, aggregation points are regular nodes that receive data from neighboring nodes, perform some kind of processing, and then forward the filtered data to the next hop. Similar to aggregation points is clustering. Sensor nodes are organized into clusters, each cluster having a “cluster head” as the leader. The communication within a cluster must travel through the cluster head, which then is forwarded to a neighboring cluster head until it reaches its destination, the base station. Another method for saving energy is setting the nodes to go idle (into sleep mode) if they are not needed and wake up when required. Of course, the challenge is to find a pattern at which energy consumption is made evenly for all the nodes in the network.

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