There are a lot
of challenges placed by the deployment of sensor networks which are a superset
of those found in wireless ad hoc networks. Sensor nodes communicate over
wireless, lossy lines with no infrastructure. An additional challenge is
related to the limited, 6 Wireless Sensor Networks – Technology and Protocols
usually non-renewable energy supply of the sensor nodes. In order to maximize
the lifetime of the network, the protocols need to be designed from the
beginning with the objective of efficient management of the energy resources
(Akyildiz et al., 2002). Wireless Sensor Network Design issues are mentioned in
(Akkaya et al., 2005), (Akyildizet al., 2002), (SensorSim; Tossim, Younis et
al., 2004), (Pan et al., 2003) and different possible platforms for simulation
and testing of routing protocols for WSNs are discussed in ( NS-2, Zeng et
al.,1998, SensorSim, Tossiim ). Let us now discuss the individual design issues
in greater detail.
Fault Tolerance: Sensor nodes are
vulnerable and frequently deployed in dangerous environment. Nodes can fail due
to hardware problems or physical damage or by exhausting their energy supply.
We expect the node failures to be much higher than the one normally considered
in wired or infrastructure-based wireless networks. The protocols deployed in a
sensor network should be able to detect these failures as soon as possible and
be robust enough to handle a relatively large number of failures while maintaining
the overall functionality of the network. This is especially relevant to the
routing protocol design, which has to ensure that alternate paths are available
for rerouting of the packets. Different deployment environments pose different
fault tolerance requirements.
Scalability: Sensor networks vary in
scale from several nodes to potentially several hundred thousand. In addition,
the deployment density is also variable. For collecting high-resolution data,
the node density might reach the level where a node has several thousand
neighbours in their transmission range. The protocols deployed in sensor
networks need to be scalable to these levels and be able to maintain adequate
performance.
Production Costs: Because many
deployment models consider the sensor nodes to be disposable devices, sensor
networks can compete with traditional information gathering approaches only if
the individual sensor nodes can be produced very cheaply. The target price
envisioned for a sensor node should ideally be less than $1.
Hardware Constraints: At minimum, every
sensor node needs to have a sensing unit, a processing unit, a transmission
unit, and a power supply. Optionally, the nodes may have several built-in
sensors or additional devices such as a localization system to enable
location-aware routing. However, every additional functionality comes with
additional cost and increases the power consumption and physical size of the
node. Thus, additional functionality needs to be always balanced against cost
and low-power requirements.
Sensor Network Topology: Although WSNs
have evolved in many aspects, they continue to be networks with constrained
resources in terms of energy, computing power, memory, and communications
capabilities. Of these constraints, energy consumption is of paramount
importance, which is demonstrated by the large number of algorithms,
techniques, and protocols that have been developed to save energy, and thereby
extend the lifetime of the network. Topology Maintenance is one of the most
important issues researched to reduce energy consumption in wireless sensor
networks.
Transmission Media: The communication
between the nodes is normally implemented using radio communication over the
popular ISM bands. However, some sensor networks use optical or infrared
communication, with the latter having the advantage of being robust and
virtually interference free.
Power Consumption: As we have already
seen, many of the challenges of sensor networks
revolve around the limited power
resources. The size of the nodes limits the size of the
battery. The software and hardware
design needs to carefully consider the issues of efficient
energy use. For instance, data
compression might reduce the amount of energy used for
radio transmission, but uses additional
energy for computation and/or filtering. The energy
policy also depends on the application;
in some applications, it might be acceptable to turn
off a subset of nodes in order to
conserve energy while other applications require all nodes
operating simultaneously.
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