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WISENET-Wireless Sensor Network (Download Seminar Report)
#1

[attachment=15521]
CHAPTER 1
INTRODUCTION

A wireless sensor network is a distributed collection of a large number of sensor nodes, which are deployed either inside or very close to the phenomenon. The position of these sensor nodes need not be pre-determined and this allows the random deployment in various applications. Other factor which comes into the focus is that sensor network protocols and algorithms must incorporate self organizing capabilities. Wireless sensor networks are collections of distributed nodes which are capable of operating with minimal user attendance and resource constrained. Sensor nodes work in cooperative and distributed manner and usually embedded in physical environment and report all sensed data to central base station known as sink. Essential thing for this operation is that where information is sensed in sensor network.
Cooperative effort of all sensor nodes is a unique feature of wireless sensor networks. Wireless ad hoc networking techniques are required for the realization of these sensor network applications. Protocols and algorithms, proposed for wireless ad-hoc networks are not well suited for wireless sensor networks due to the unique features and application requirements.
Wireless sensor networks are being used in various challenging applications such as climatic monitoring, earthquake detection, tactical surveillance etc. Numerous sensor nodes are deployed to report and monitor distributed event occurrences. In future, millions of sensors will be deployed to sense the events; so sensor nodes have to manage this vast amount of data.
CHAPTER 2
WSN operation and its model

A wireless sensor network of the type investigated here refers to a group of sensors, or nodes that are linked by a wireless medium to perform distributed sensing tasks. Connections between nodes may be formed using such media as infrared devices or radios. Wireless sensor networks will be used for such tasks as surveillance, widespread environmental sampling, security and health monitoring. They can be used in virtually any environment, even those where wired connections are not possible, where the terrain is inhospitable, or where physical placement is difficult.
2.1. Goals of operation
1. The main goal in conventional wireless networks is providing high quality of service and high bandwidth efficiency when mobility exists.
2. For a sensor network we are interested in prolonging the lifetime of the network.
3. We are willing to give up performance in other aspects of the operation such as QoS and bandwidth utilization.
4. Each node depends on small and low capacity batteries as energy sources, and cannot expect replacement when operating in hostile or remote regions.
5. For networks with a fixed infrastructure, loss of connectivity is a statistically rare event and independent of energy usage. On the other hand, in mobile networks, topological changes are mostly attributed to the mobility of the nodes, not energy depletions caused by the execution of various networking protocols.
Therefore, in order to raise system performance, mobility management and failure recovery assumes more importance than energy conservation. For ad hoc sensor networks energy depletion is the primary factor in connectivity degradation and length of operational lifetime.
So overall performance becomes highly dependent on the energy efficiency of the algorithm.
2.2. Characteristics
The main characteristics of a WSN include :
1. Power consumption constrains for nodes using batteries or energy harvesting
2. Ability to cope with node failures
3. Mobility of nodes
4. Dynamic network topology
5. Communication failures
6. Heterogeneity of nodes
7. Scalability to large scale of deployment
8. Ability to withstand harsh environmental condition
9. Easy to use
10. Unattended operation.
2.3. Operation of WSN
A sensor network must be able to operate under very dynamic conditions. Protocols must be able to enable network operation during start-up, steady state and failure.
These are required because sensor network must operate unattended, in most cases. Once the nodes have booted up and network is formed, most of the nodes will be able to sustain a steady state of operation. Bulk of nodes will be formed into a multi-hop network, nodes establish routes by which information is passed to one or more sink nodes. A sink-node may be capable of connecting sensor network to existing long-haul communication infrastructure. Sink may also be a mobile node acting as an information sink, or any other entity that is required to extract information from sensor network.
When a co-operative function is required to extract information about a specific target, a local network is built to facilitate necessary signalling and data transfer tasks. They adapt quickly and efficiently to the appearance of target and nature of signal processing techniques required
2.3.1. Energy Conserving Techniques
Energy consumption occurs in three domains: sensing, data processing, and communications.
In this case communication is major consumer of energy. It is possible to make tradeoffs between data processing and wireless communication. Sensor node will do more local processing, as opposed to exchanging raw data over the air. In the same vein the protocols responsible for ORM must reduce their messaging overhead as much as possible. This leads to the need for highly localized and distributed algorithms for data processing and networking.
There are a number of strategies that can be used to reduce the average supply current of the radio, including:
1. Reduce the amount of data transmitted through data compression and reduction.
2. Lower the transceiver duty cycle and frequency of data transmissions.
3. Reduce the frame overhead.
4. Implement strict power management mechanisms (power-down and sleep modes).
5. Implement an event-driven transmission strategy; only transmit data when a sensor event occurs.
Power reduction strategies for the sensor itself include:
1. Turn power on to sensor only when sampling
2. Turn power on to signal conditioning only when sampling sensor.
3. Only sample sensor when an event occurs.
Lower sensor sample rate to the minimum required by the application.
2.3.2. Channel Access Schemes
Contention based channel access schemes are clearly not suitable for sensor networks due to their requirement for radio transceiver to monitor channel at all times. It is expensive proposition for low radio ranges of interest for sensor networks, where transmission and reception have almost same energy cost. So we would like to turn-off radios when no information is to be sent or received.
i) Self-organizing Medium Access Control for Sensor networks (SMACS)
It is a distributed protocol which enables a collection of nodes to discover their neighbours and establish transmission/reception schedules for communicating with them without the need for any local or global master node.
To achieve this ease of formation, we have combined the neighbor discovery phase with channel assignment phase in the SMACS protocol. We assign a channel to a page link immediately after the existence of the page link is discovered. This way links begin to form concurrently throughout the network. By the time all nodes hear all their neighbors they will have formed a connected network. In a connected network, there exists at least one multi-hop path between any two distinct nodes.
Since only partial information about radio connectivity in the vicinity of a node is used to assign time intervals to links, there exists a potential for time collisions with slots assigned to adjacent links whose existence is not known at the time of channel assignment. To reduce the likelihood of collisions, we require each page link to operate on a different frequency. This frequency band is chosen at random from a large pool of possible choices when the links are formed. figure for non-synchronous scheduled communication. After a page link is established, a node knows when to turn on its transceiver ahead of time to communicate with another node. It will turn off when no communications are scheduled. This scheduled mode of communication enables energy savings for the node. As the page link assignment was accomplished quickly, without requiring accumulation of global connectivity information, or even connectivity information that reaches farther than one hop away, the overall effect will be significant energy savings.
2.3.3. List of Startup messages
The following messages are exchanged between nodes when they are searching for new neighbours:
TYPE1: short invitation containing node's id and number of its attached neighbours. The node which sends it is the inviter during the search transaction.
TYPE2: response to TYPE1. The node that sends it, will be an invitee. There may be more than one invitee for each inviter. This message gives the inviter and invitee's addresses, and invitee's attached state.
TYPE3: response to TYPE2. Indicates which invitee was chosen. It contains the following additional information depending on the node's attached state:
i) Inviter not attached: none.
ii) Invitee, inviter attached: inviter's schedule and frame epoch.
ii) Invitee not attached, inviter attached: proposed channel for the link, calculated by inviter.
TYPE4: response to TYPE3. Message contents are as follows:
i) Invitee not attached, inviter not attached: channel determined by the invitee.
ii) Invitee not attached, inviter attached: none.
ii) Invitee attached, inviter not attached: channel determined by the invitee.
iv) Invitee attached, inviter attached: channel determined from own and inviter's schedule information.
2.3.4. Network Constraints
As the primary limitation is that of the battery power on the stationary nodes, the communication channels between the mobile and stationary sensors must be established with as few messages transmitted by the stationary sensors as possible. This can be accomplished by allowing the mobile node to determine when to invite the stationary node as a connection, as well as when to drop a connection.
The network is assumed to consist of primarily stationary nodes, with few mobile nodes, all of which are randomly distributed. Such an assumption leads to the notion that only a select few stationary sensors will be within the vicinity of a mobile sensor at any given time. Giving the ability to form connections to the stationary nodes would result in the constant specialized signalling with the intent of inviting mobile nodes to join the network. To avoid the unnecessary use of power associated with lost messages, the mobile nodes assume full control of the connection process. Furthermore, the overhead associated with acknowledgements can be eliminated. This is possible as the proximity between sensors almost surely ensures message reception.
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#2
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This article is presented by:
JOEL CHRISTOPHER JORDAN
B.S., University of Illinois at Urbana-Champaign, 2003
DESIGN AND IMPLEMENTATION OF A STOCHASTIC
WIRELESS SENSOR NETWORK


INTRODUCTION
Wireless sensor networks have generated much research interest in recent years as advances in electronics technology have made them feasible. In general, such a network consists of many nodes scattered over an area to provide distributed sensing and data processing [1]. These networks can enable unattended monitoring of physical quantities over large areas on a scale that would be prohibitively expensive to accomplish with humans. Many uses have been suggested for wireless sensor networks, including habitat [2] and medical monitoring [3]. Many groups have designed sensor nodes. These include Berkeley s Mica motes [4] and PicoRadio projects [5], MIT s Amps [6], and Rice s GNOMES [7], as well as many others. All of these sensors have similar goals, such as small physical size, low power consumption, and rich sensing abilities. In addition, the TinyOS project [8] provides a framework for designing flexible distributed applications for data collection and processing across a sensor network. Many sensor network applications require the collection of data over long periods of time. Sensor nodes are generally powered with batteries, putting a limit on how small the node can be made for a given lifetime. Unfortunately, it is unlikely that battery capacities will increase dramatically in the near future. Historically, battery charge density has increased by a mere 2% per year over the last 50 years [9]. As an example, a CR2032 lithium coin cell, about the size of a quarter, would provide an average of only 75 W if used completely over a year. As an alternative to batteries, sensor nodes can scavenge energy from their environment. Ambient light, mechanical vibrations, or even acoustic sources could provide power to operate a sensor. Research suggests that up to 100 W/cm3 can be obtained from vibrational sources [10]. A thin-film solar cell may provide 5 mW/cm2 of power

in bright sunlight, but only about 15 W/cm2 at desk level in office lighting. Unlike batteries, these ambient sources are often unreliable. A solar-powered node could no longer operate if a power outage turned off the lights in a building. Sensor nodes, then, must operate with extremely low power dissipation. However, consider that a typical commercial radio transceiver requires 10 mW of power in receive mode and 35 mW while transmitting . Recent research has produced a transceiver design which needs only 1 mW in its receive mode and 25 mW while transmitting . Even this is more power than a small sensor node can produce. A solution to this problem is low-duty-cycle operation, where sensors spend a large percentage of the time in a low-power sleep mode. Because the power source is often unreliable, the duty cycle will be unreliable, varying with the amount of power available. Others have constructed self-powered sensor nodes with low-duty-cycle operation . However, existing routing algorithms have problems when operating on such hardware. Some, such as GEAR, include power reserves in the route selection heuristic so that routes prefer nodes with more power available. Unfortunately, it requires nodes to constantly listen for transmissions from neighbors, so low-duty-cycle operation is not possible. Other algorithms, such as LEACH , rely on time division multiple access (TDMA) schemes to acheive low duty cycle operation. In this type of algorithm, a master node assigns communication time slots to slave nodes, which only turn on their radios during these time slots. Because self-powered nodes may have unreliable power sources, however, they cannot be guaranteed to wake up as scheduled. To deal with these problems, stochastic sensor networks have been proposed . In such a network, nodes store power while in an inactive mode, then become active until the stored energy is depleted, at which point they return to the inactive state. This process is unsynchronized between the sensor nodes, thus forming a stochastic sensor network. Also, no routing is used. Instead, data is propagated to its destination using much simpler stochastic flooding. Such a network can be made reliable under certain assumptions about the active node density . Furthermore, high-level protocols can be layered onto the network to enable rich applications . While simulations have verified that these networks should work, no real-world testing has taken place. If this theory can be demonstrated in real nodes, it would have great advantages for enabling simple, robust networks of self-powered sensors. Such testing requires a wireless sensor node with rich power management features that no existing architectures offer. Therefore, a new sensor architecture has been designed with extremely low power consumption in mind. This sensor uses solar cells to collect energy and store it in a large reservoir capacitor. While in the inactive state, the sensor can check its stored power levels to determine whether to enter the active mode or to continue storing energy.
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#3
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#7
[attachment=6283]
WISENET-Wireless Sensor Network (Download Seminar Report)

Communication Power
Consumption
How to communicate when nodes sleep
most of the time?
Design MAC to reduce wasted power due
to:
Idle listening
Overemitting
Overhearing
Collisions

Power Comparison
CSMA limited at low traffic
Receiver never turned off
T-MAC
Choose duty cycle
Drops packets at low duty cycles, so get either
low power in low traffic or high throughput
WiseNET is ultralow-power for low traffic,
efficient for high traffic.
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