Wireless Sensor Networks (WSN)

Introduction

The emerging field of wireless sensor networks combines sensing, computation, and communication into a single tiny device. Through advanced mesh networking protocols, these devices form a sea of connectivity that extends the reach of cyberspace out into the physical world. Here the mesh networking connectivity will seek out and exploit any possible communication path by hopping data from node to node in search of its destination.

The power of wireless sensor networks lies in the ability to deploy large numbers of tiny nodes that assemble and configure themselves. Usage scenarios for these devices range from real-time tracking, to monitoring of environmental conditions, to ubiquitous computing environments, to monitoring the health of structures or equipment, to controlling actuators that extend control from cyberspace into the physical world. The most straightforward application of wireless sensor network technology is to monitor remote environments for low frequency data trends. In addition to drastically reducing the installation costs, wireless sensor networks are the ability to dynamically adapt to changing environments. Adaptation mechanisms can respond to changes in network topologies or can cause the network to shift between drastically different modes of operation.

Current wireless systems only scratch the surface of possibilities emerging from the integration of low-power communication, sensing, energy storage, and computation. Wireless sensor networks use small, low-cost embedded devices for a wide range of applications and do not rely on any pre-existing infrastructure. Unlike traditional wireless devices, wireless sensor nodes do not need to communicate directly with the nearest high-power control tower or base station, but only with their local peers. Peer-to-peer networking protocols provide a mesh-like interconnection of Wireless sensor motes. The flexible mesh architectures evident that the dynamically adaptation to support introduction of new nodes or expand to cover a larger geographic region. Additionally, the system can automatically adapt to compensate for node failures. When nodes are added, the interconnection of a wireless sensor network grows and become stronger. This can be grown up to covering of limit less area.

Hundreds of nodes scattered throughout a field assemble together, establish a routing topology, and transmit data back to a collection point or the coordinator point. The application demands for robust, scalable, low-cost and easy to deploy networks are perfectly met by a wireless sensor network. If one of the nodes should fail, a new topology would be selected and the overall network would continue to deliver data. If more nodes are placed in the field, they only create more potential routing opportunities.

The concept of wireless sensor networks is based on a simple equation:
Sensing + CPU + Radio = Thousands of potential applications [12]
Each individual node must be designed to provide the set of primitives necessary to synthesize the interconnected web that will emerge as they are deployed, while meeting strict requirements of size, cost and power consumption

1. Sensor Network Application Classes
We believe that the majority of wireless sensor network deployments come under one these classes. In general, complete application scenarios contain aspects of all three categories.

1.1 Environmental Data Collection
An environmental data collection application is one where a person wants to collect several sensor readings from a set of points in an environment over a period of time in order to detect trends and interdependencies. He would want to collect data from hundreds of points spread throughout the area and he would be interested in collecting data over several months or years in order to look for long-term and seasonal trends. For the data to be meaningful it would have to be collected at regular intervals and the nodes would remain at known locations.

At the network level, the environmental data collection application is characterized by having a large number of nodes continually sensing and transmitting data back to a set of base stations that store the data using traditional methods. These networks generally require very low data rates and extremely long lifetimes.

Environmental data collection applications typically use tree-based routing topologies where each routing tree is rooted at high-capability nodes that sink data. Data is periodically transmitted from child node to parent node up the tree-structure until it reaches the sink. With tree-based data collection each node is responsible for forwarding the data of all its descendants. Once the network is configured, each node periodically samples its sensors and transmits its data up the routing tree and back to the base station.

The typical environment parameters being monitored, such as temperature, light intensity, and humidity, does not change quickly enough to require higher reporting rates. In addition to large sample intervals, environmental monitoring applications do not have strict latency requirements. Data samples can be delayed inside the network for moderate periods of time without significantly affecting application performance. In general the data is collected for future analysis, not for real-time operation.

The most important characteristics of the environmental monitoring requirements are long lifetime, precise synchronization, low data rates and relatively static topologies. Additionally it is not essential that the data be transmitted in real-time back to the central collection point. The data transmissions can be delayed inside the network as necessary in order to improve network efficiency.

1.2 Security Monitoring
Security monitoring networks are composed of nodes that are placed at fixed locations throughout an environment that continually monitor one or more sensors to detect an anomaly. A key difference between security monitoring and environmental monitoring is that security networks are not actually collecting any data. This has a significant impact on the optimal network architecture. Each node has to frequently check the status of its sensors but it only has to transmit a data report when there is a security violation. Additionally, it is essential that it is confirmed that each node is still present and functioning.

For security monitoring applications, the network must be configured so that nodes are responsible for confirming the status of each other. One approach is to have each node be assigned to peer that will report if a node is not functioning. In security network the optimal configuration would be to have a linear topology that forms a Hamiltonian cycle of the network. The power consumption of each node is only proportional to the number of children it has. A majority of the energy consumption in a security network is spent on meeting the strict latency requirements associated with the signaling the alarm when a security violation occurs.

Once detected, a security violation must be communicated to the base station immediately. The latency of the data communication across the network to the base station has a critical impact on application performance. Users demand that alarm situations be reported within seconds of detection. In security networks, a vast majority of the energy will be spend on confirming the functionality of neighboring nodes and in being prepared to instantly forward alarm announcements. Actual data transmission will consume a small fraction of the network energy.

1.3 Node Tracking Scenarios
There are many situations where one would like to track the location of valuable assets or personnel. Current inventory control systems attempt to track objects by recording the last checkpoint that an object passed through. However, with these systems it is not possible to determine the current location of an object.

With wireless sensor networks, objects can be tracked by simply tagging them with a small sensor node. The sensor node will be tracked as it moves through a field of sensor nodes that are deployed in the environment at known locations. Instead of sensing environmental data, these nodes will be deployed to sense the RF messages of the nodes attached to various objects. The nodes can be used as active tags that announce the presence of a device. A database can be used to record the location of tracked objects relative to the set of nodes at known locations.

Unlike sensing or security networks, node tracking applications will continually have topology changes as nodes move through the network. While the connectivity between the nodes at fixed locations will remain relatively stable, the connectivity to mobile nodes will be continually changing. Additionally the set of nodes being tracked will continually change as objects enter and leave the system. It is essential that the network be able to efficiently detect the presence of new nodes that enter the network.

2. An Example Implementation of a WSN, In-door Temperature Controlling System
A hot or cold work environment can lead to physical discomfort and disrupt work operations. Working in a hot office environment may cause fatigue, headaches and/or stuffiness. A cold office environment may cause a decrease in sensitivity and dexterity of the fingers. Indoor thermal conditions are influenced by air temperature, thermal radiation, air speed (drafts), metabolic rate (sitting versus physical activity), clothing and relative humidity. The recommended living room temperature in tropical countries is in between 20° to 28°. It is also applicable to the office environment also.

Monitoring the environment conditions in a computer room or data center is critical to ensuring uptime and system reliability. Operating expensive IT computer equipment for extended periods of time at high temperatures greatly reduces reliability, longevity of components and will likely cause unplanned downtime. Maintaining an ambient temperature range of 68° to 75°F (20° to 24°C) is optimal for system reliability. This temperature range provides a safe buffer for equipment to operate in the event of air conditioning [13].

Wireless Sensor Network Based Indoor Temperature Controlling System is hybrid module of above mentioned three sensor network application classes. So it is an environmental data collection system. Again it is a kind of security monitoring system and also it’s a sensor node tracking system.

This is some kind of a canonical environmental data collection application which is one coordinator wants to collect several sensor readings from a set of points in an environment over a period of time in order to detect trends and interdependencies. Here we need to adjust the environment temperature in to a precise level. For an example the room temperature of a living room sometime should be not so hotter and also not so cooler. Indoor environment temperature collection is needed to decide the average temperature of the area. For the data to be meaningful it would have to be collected at regular intervals and the nodes would remain at known locations. Then only the control station knows the exact temperature of every corner of the area.

At the network level, the entire indoor environment is consist of a large number of nodes continually sensing and transmitting data back to a set of base stations that collect the temperature data and calculate the temperature values for all the end stations. Then at the end stations for an example we are having a decentralized air conditioner controlling system with number of air conditioning machine here and there inside the our desired area. So those machines get the controlling message to adjust the air conditioner temperature to the calculated value. These networks generally require very low data rates and extremely long lifetimes. In typical usage scenario, the nodes will be evenly distributed over the indoor environment. This distance between adjacent nodes will be minimal yet the distance across the entire network will be significant.

The key difference between security monitoring and environmental monitoring is that security networks are not actually collecting any data. When it comes to indoor temperature controlling system as a security monitoring systems, we can remove all the traditional wired fire detections systems and those can be replaced by the wireless fire detection system. Here when we have a pre established wireless sensor network based indoor temperature controlling system, nothing specially needed to be done and that system itself can be used as a fire detection and fire alarming system. Since the monitoring networks are composed of nodes that are placed at fixed locations throughout the indoor environment that continually monitor more sensors to detect the temperatures, wireless sensor system has the basic requirements needed for fire detection.

Node tracking scenarios comes in to play when it is needed to track any locations of the mesh network which has been configured for the indoor temperature controlling system. For a fire detection system it is needed to locate the exact location of fire. For an example if any person needs to control the temperature of his/her area according to his/her desire. There should be a mechanism to allow that person to manually control the air conditioner and other locations should be under control of the established system. Then also it is needed to have the node tracking capability within the system and then only we can allow the system to manually remove the mote from auto controlling mode. Motes can be simply tracked by configuring an ID for each and every node separately. Then all the nodes can be identified and tracked by the ID.

The routing strategy can then be used to route data to a central collection points. That’s the coordinator node of the indoor temperature controlling system. In this application, it is not essential that the nodes develop the optimal routing strategies on their own. Instead, it may be possible to calculate the optimal routing topology of the network and then communicate the necessary information to the nodes as required. This is possible because the physical topology of the network is relatively constant. Here for this application we can use tree based routing topologies. Temperature values captured at end stations is periodically transmitted through routing nodes to parent node of the tree-structure until it reaches the sink node. For many scenarios, the interval between these transmissions can be on the order of minutes. Because the rapid changes of the temperature level can’t be expected within less than one minute, it can be vary up to two three minutes also. When it comes to the fire detection system the nodes must be configured so that nodes are responsible for confirming the status of each other. Otherwise some intruder can light a cigarette and keep it near the temperature sensor. If the nodes doesn’t have the knowledge of node’s status of the nearest, this scenario can be alarmed and warned as a fire.
In contrast, with a security network the optimal configuration would be to have a linear topology that forms a Hamiltonian cycle of the network.

3. Further Modifications of Indoor Temperature Controlling System
3.1 Fire Detection with Smoke Sensors
Fire detection with smoke sensors (using wireless sensor networking technology) come under the application class of security monitoring using wireless sensor networking. Thermal sensor of nodes of the indoor temperature controlling system should be replaced with the smoke detecting sensors. Then the network topology should also be optimized by having linear topology rather than having hierarchical network topology. One of the major fact in this system is majority of the energy consumption is spent on meeting the strict latency requirements associated with the signaling the alarm when a smoke detection is occurs. The latency of the data communication across the network to the base station has a critical impact on application performance and it should be optimized by the routing protocol. This means that network nodes must be able to respond quickly to requests from their neighbors to forward data to the base station. In the indoor temperature controlling system, reducing the energy consumption for availability of long lasting purposes is the matter. But in smoke detection system reducing the latency of an alarm transmission is significantly more important than reducing the energy cost of the transmissions. Here the routing nodes must monitor the network more frequently than the indoor temperature controlling system.

3.2 Intruder Detection with IR Sensors at Door/ Window openings
Wireless sensor network based intruder detection with IR sensors at door/ Window openings and perimeters is also comes under application class of security monitoring. Here thermal sensors of each node should be replaced by the IR sensors. This IR sensor should be capable of detecting the IR raise emitted by the humans. All the other network topology related matters are modified as mention under the system modifications to the fire detection with smoke sensor. As a consequence of this special network architecture, from the application point of view, a position in the nodes is really under the surveillance of the WSN if and only if this position is within the sensing range of at least one of the sensor nodes connected to the coordinator (base station). When this comes to the intruder detection at perimeter level, the sensor node placement is a really big task which should comes under special surveillance. The system should function during specified time period of the day. For example intruder detection with IR sensor at door/window most probably works during the night time. But intruder detection at the perimeter level should works all the time.

3.3 Location Detection of Equipments
Location detection of equipments comes under the category of node tracking system using wireless sensor networks. So the indoor temperature controlling system can also be modified as a location detection system. Then this is not limited to the indoor environment. Here the nodes should be modified by removing the thermal sensor part and modifying the routing algorithm from data collection scenario to node tracking scenario.
With wireless sensor networks, each moving objects can be tracked by simply tagging them with a small sensor node. Then the exact location can be noted without having any difficulty. The Moving object which has been tagged with a sensor node will be tracked as it moves through a field of sensor nodes that are deployed in the environment at known locations. Instead of sensing temperature variations, these nodes will be deployed to sense the RF messages of the nodes attached to various moving objects. With this system, it becomes possible to detect where an object is currently, not simply where it was last scanned.