Wireless Sensor Networks (WSNs): Imran Khan
WSNs provide distributed sensing of physical phenomena with the objective to monitor and eventually control a remote environment.
How do WSNs Work?
Typically, WSN nodes are randomly deployed (to help decrease the cost of deployment) in the field of interest with a relatively dense deployment. The nodes then self-organize to determine the network topology; afterwards, sensor readings from the nodes are routed to the base station using short multihop communication. During this multihop communication, redundant readings from neighboring nodes are aggregated to reduce the number of transmissions in the network.
Factors Driving WSNs Development
Automated sensing, embedded computing, and wireless networking have been around for a relatively long time. However, only recently have computation, communications, and sensing been integrated inexpensively, at a low cost and large scale, which have resulted in significant initiatives by the academic and commercial communities.
WSN versus Traditional Sensor Networks
Traditional sensor networks use a few expensive sensors to cover a large area, which limits the sensing resolution, restricts the deployment to areas with power and communication infrastructure, and require carefully engineered communication topology. These centralized, long range sensor systems fail in complex, cluttered environments with short line-of-sight thus many interesting phenomena can not be sensed from a far distance. Whereas, the distributed sensing approach to WSNs provides better coverage with higher sensing resolution and better fault tolerance and robustness.
WSN versus Ad Hoc Networks
Although both Ad Hoc Networks and WSNs rely on infrastructureless communication, there are significant differences between them. For instance, for WSNs: the number of nodes is usually several orders of magnitude more; nodes are densely developed; nodes are prone to failure; topology changes frequently; nodes normally use broadcast communication not point-to-point communication; nodes are limited significantly in power, communication, and memory; nodes do not normally have global identification because of large overhead and large number of nodes; and WSNs are deployed for specific sensing applications.
The two main challenges facing WSNs are energy limitations and dynamic topology. Since nodes have limited energy and are deployed usually in remote environments, the cost of manual energy replenishment is not practical. As well, since nodes are deployed in unattended environments, when nodes fail (e.g. energy is exhausted, over heat, blow away, RF interference, or malicious sabotage), the WSN needs the ability to self-configure and be adaptive. These two main challenges introduce several specific design challenges: autonomous network discovery, service establishment, data routing and aggregation, query processing, and system organization. TinyManager (IIC WSN Project)
TinyManager is an adaptive integrated management framework to autonomously design and operate heterogeneous WSNs. It is a new evolutionary optimization algorithm to find optimum solutions to complex problems, which is inspired by principles and techniques from Management.
This research investigates implementation and design issues for a heterogeneous network for structural monitoring. The proposed application uses wireless sensors and the controller area network (CAN) to provide energy efficient monitoring. The contributions include: implementation of the PIC18f4680 platform in TinyOS, creating a message protocol over CAN, and developing a sensor board.
International Conference on Communication Networks and Services Research (CNSR) May, 2007