25-02-2013, 02:10 PM
Wireless Sensor Networks
Wireless Sensor.pdf (Size: 423.09 KB / Downloads: 68)
Introduction
A wireless sensor network is a collection of nodes organized into a cooperative network [10]. Each node
consists of processing capability (one or more microcontrollers, CPUs or DSP chips), may contain multiple
types of memory (program, data and flash memories), have a RF transceiver (usually with a single omni-
directional antenna), have a power source (e.g., batteries and solar cells), and accommodate various sensors
and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc
fashion. Systems of 1000s or even 10,000 nodes are anticipated. Such systems can revolutionize the way we
live and work.
Currently, wireless sensor networks are beginning to be deployed at an accelerated pace. It is not
unreasonable to expect that in 10-15 years that the world will be covered with wireless sensor networks with
access to them via the Internet. This can be considered as the Internet becoming a physical network. This
new technology is exciting with unlimited potential for numerous application areas including environmental,
medical, military, transportation, entertainment, crisis management, homeland defense, and smart spaces.
Since a wireless sensor network is a distributed real-time system a natural question is how many solutions
from distributed and real-time systems can be used in these new systems? Unfortunately, very little prior
MAC
work can be applied and new solutions are necessary in all areas of the system. The main reason is that
the set of assumptions underlying previous work has changed dramatically. Most past distributed systems
research has assumed that the systems are wired, have unlimited power, are not real-time, have user interfaces
such as screens and mice, have a fixed set of resources, treat each node in the system as very important and
are location independent. In contrast, for wireless sensor networks, the systems are wireless, have scarce
power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources,
aggregate behavior is important and location is critical. Many wireless sensor networks also utilize minimal
capacity devices which places a further strain on the ability to use past solutions.
This Chapter presents an overview of some of the key areas and research in wireless sensor networks.
In presenting this work, we use examples of recent work to portray the state of art and show how these
solutions differ from solutions found in other distributed systems. In particular, we discuss the MAC layer
(section 2), routing (section 3), node localization (section 4), clock synchronization (section 5), and power
management (section 6). We also present a brief discussion of two current systems (section 7) in order to
convey overall capabilities of this technology. We conclude in section 8.
Routing
Multihop routing is a critical service required for WSN. Because of this, there has been a large amount of
work on this topic. Internet and MANET routing techniques do not perform well in WSN. Internet routing
assumes highly reliable wired connections so packet errors are rare; this is not true in WSN. Many MANET
routing solutions depend on symmetric links (i.e., if node A can reliably reach node B, then B can reach A)
between neighbors; this is too often not true for WSN. These differences have necessitated the invention and
deployment of new solutions.
ForWSN, which are often deployed in an ad hoc fashion, routing typically begins with neighbor discovery.
Nodes send rounds of messages (packets) and build local neighbor tables. These tables include the minimum
information of each neighbor’s ID and location. This means that nodes must know their geographic location
prior to neighbor discovery. Other typical information in these tables include nodes’ remaining energy, delay
via that node, and an estimate of link quality.
Node Localization
Node localization is the problem of determining the geographical location of each node in the system.
Localization is one of the most fundamental and difficult problems that must be solved for WSN. Localization
is a function of many parameters and requirements potentially making it very complex. For example, issues
to consider include: the cost of extra localization hardware, do beacons (nodes which know their locations)
exist and if so, how many and what are their communication ranges, what degree of location accuracy is
required, is the system indoors/outdoors, is there line of sight among the nodes, is it a 2D or 3D localization
problem, what is the energy budget (number of messages), how long should it take to localize, are clocks
synchronized, does the system reside in hostile or friendly territory, what error assumptions are being made,
and is the system subject to security attacks?
For some combination of requirements and issues the problem is easily solved. If cost and form factor are
not major concerns and accuracy of a few meters is acceptable, then for outdoor systems, equipping each
node with GPS is a simple answer. If the system is manually deployed one node at a time, then a simple
GPS node carried with the deployer can localize each node, in turn, via a solution called Walking GPS [27].
While simple, this solution is elegant and avoids any manual keying in the location for each node.
Most other solutions for localization in WSN are either range-based or range- free. Range-based schemes
use various techniques to first determine distances between node (range) and then compute location using
geometric principles. To determine distances, extra hardware is usually employed, e.g., hardware to detect
the time difference of arrival of sound and radio waves. This difference can then be converted to a distance
measurement.
Clock Synchronization
The clocks of each node in aWSN should read the same time within epsilon and remain that way. Since clocks
drift over time, they must be periodically re- synchronized and in some instances when very high accuracy
is required it is even important for nodes to account for clock drift between synchronization periods.
Clock synchronization is important for many reasons. When an event occurs in a WSN it is often
necessary to know where and when it occurred. Clocks are also used for many system and application tasks.
For example, sleep/wake-up schedules, some localization algorithms, and sensor fusion are some of the
services that often depend on clocks being synchronized. Application tasks such as tracking and computing
velocity are also dependent on synchronized clocks.
The NTP protocol [21] used to synchronize clocks or the Internet is too heavyweight for WSN. Placing
GPS on every node is too costly. Representative clock synchronization protocols that have been developed
for WSN are: RBS [3], TPSN [4] and FTSP [19].
In RBS a reference time message is broadcast to neighbors. Receivers record the time when the message
is received. Nodes exchange their recorded times and adjust their clocks to synchronize. This protocol suffers
no transmitter side non-determinism since timestamps are only on the receiver side. Accuracies are around
30 microseconds for 1 hop. This work did not address multi-hop systems, but could be extended.
Wireless Sensor.pdf (Size: 423.09 KB / Downloads: 68)
Introduction
A wireless sensor network is a collection of nodes organized into a cooperative network [10]. Each node
consists of processing capability (one or more microcontrollers, CPUs or DSP chips), may contain multiple
types of memory (program, data and flash memories), have a RF transceiver (usually with a single omni-
directional antenna), have a power source (e.g., batteries and solar cells), and accommodate various sensors
and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc
fashion. Systems of 1000s or even 10,000 nodes are anticipated. Such systems can revolutionize the way we
live and work.
Currently, wireless sensor networks are beginning to be deployed at an accelerated pace. It is not
unreasonable to expect that in 10-15 years that the world will be covered with wireless sensor networks with
access to them via the Internet. This can be considered as the Internet becoming a physical network. This
new technology is exciting with unlimited potential for numerous application areas including environmental,
medical, military, transportation, entertainment, crisis management, homeland defense, and smart spaces.
Since a wireless sensor network is a distributed real-time system a natural question is how many solutions
from distributed and real-time systems can be used in these new systems? Unfortunately, very little prior
MAC
work can be applied and new solutions are necessary in all areas of the system. The main reason is that
the set of assumptions underlying previous work has changed dramatically. Most past distributed systems
research has assumed that the systems are wired, have unlimited power, are not real-time, have user interfaces
such as screens and mice, have a fixed set of resources, treat each node in the system as very important and
are location independent. In contrast, for wireless sensor networks, the systems are wireless, have scarce
power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources,
aggregate behavior is important and location is critical. Many wireless sensor networks also utilize minimal
capacity devices which places a further strain on the ability to use past solutions.
This Chapter presents an overview of some of the key areas and research in wireless sensor networks.
In presenting this work, we use examples of recent work to portray the state of art and show how these
solutions differ from solutions found in other distributed systems. In particular, we discuss the MAC layer
(section 2), routing (section 3), node localization (section 4), clock synchronization (section 5), and power
management (section 6). We also present a brief discussion of two current systems (section 7) in order to
convey overall capabilities of this technology. We conclude in section 8.
Routing
Multihop routing is a critical service required for WSN. Because of this, there has been a large amount of
work on this topic. Internet and MANET routing techniques do not perform well in WSN. Internet routing
assumes highly reliable wired connections so packet errors are rare; this is not true in WSN. Many MANET
routing solutions depend on symmetric links (i.e., if node A can reliably reach node B, then B can reach A)
between neighbors; this is too often not true for WSN. These differences have necessitated the invention and
deployment of new solutions.
ForWSN, which are often deployed in an ad hoc fashion, routing typically begins with neighbor discovery.
Nodes send rounds of messages (packets) and build local neighbor tables. These tables include the minimum
information of each neighbor’s ID and location. This means that nodes must know their geographic location
prior to neighbor discovery. Other typical information in these tables include nodes’ remaining energy, delay
via that node, and an estimate of link quality.
Node Localization
Node localization is the problem of determining the geographical location of each node in the system.
Localization is one of the most fundamental and difficult problems that must be solved for WSN. Localization
is a function of many parameters and requirements potentially making it very complex. For example, issues
to consider include: the cost of extra localization hardware, do beacons (nodes which know their locations)
exist and if so, how many and what are their communication ranges, what degree of location accuracy is
required, is the system indoors/outdoors, is there line of sight among the nodes, is it a 2D or 3D localization
problem, what is the energy budget (number of messages), how long should it take to localize, are clocks
synchronized, does the system reside in hostile or friendly territory, what error assumptions are being made,
and is the system subject to security attacks?
For some combination of requirements and issues the problem is easily solved. If cost and form factor are
not major concerns and accuracy of a few meters is acceptable, then for outdoor systems, equipping each
node with GPS is a simple answer. If the system is manually deployed one node at a time, then a simple
GPS node carried with the deployer can localize each node, in turn, via a solution called Walking GPS [27].
While simple, this solution is elegant and avoids any manual keying in the location for each node.
Most other solutions for localization in WSN are either range-based or range- free. Range-based schemes
use various techniques to first determine distances between node (range) and then compute location using
geometric principles. To determine distances, extra hardware is usually employed, e.g., hardware to detect
the time difference of arrival of sound and radio waves. This difference can then be converted to a distance
measurement.
Clock Synchronization
The clocks of each node in aWSN should read the same time within epsilon and remain that way. Since clocks
drift over time, they must be periodically re- synchronized and in some instances when very high accuracy
is required it is even important for nodes to account for clock drift between synchronization periods.
Clock synchronization is important for many reasons. When an event occurs in a WSN it is often
necessary to know where and when it occurred. Clocks are also used for many system and application tasks.
For example, sleep/wake-up schedules, some localization algorithms, and sensor fusion are some of the
services that often depend on clocks being synchronized. Application tasks such as tracking and computing
velocity are also dependent on synchronized clocks.
The NTP protocol [21] used to synchronize clocks or the Internet is too heavyweight for WSN. Placing
GPS on every node is too costly. Representative clock synchronization protocols that have been developed
for WSN are: RBS [3], TPSN [4] and FTSP [19].
In RBS a reference time message is broadcast to neighbors. Receivers record the time when the message
is received. Nodes exchange their recorded times and adjust their clocks to synchronize. This protocol suffers
no transmitter side non-determinism since timestamps are only on the receiver side. Accuracies are around
30 microseconds for 1 hop. This work did not address multi-hop systems, but could be extended.