Wireless Sensor Networks

Projects:

• Sensor network routing algorithms for realistic battery models with Mr. Bahman Eksiri. (pdf file)- in the Proccedings of Workshop on Information Fusion and Dissemination in Wireless Sensor Networks, July 14, at Budapest, Hungary.

  [ABSTRACT] Sensor networks are made of nodes that have a processor, memory, wireless transceivers, sensor(s) and a onboard battery. Sensor networks are expected to revolutionize information gathering, processing and dissemination in many diverse environments.The most important factor in the design of sensor network protocols is the conservation of battery capacity.  Surprisingly, almost all existing work uses unrealistic battery models. These models assume that a battery is a ``bucket'' filled with a number of units of energy and that each packet removes a fixed number of units. Real batteries are much more complex, dynamic systems that have several different phenomena existing simultaneously. The objective of this paper is to demonstrate that algorithms designed using more complex battery models perform better in real networks.

  In this paper, we model arguably the most important non-ideal property of real batteries, viz., the charge recovery effect -- battery capacity actually increases when it is allowed to rest for some time. We develop a simple model for the charge recovery effect, and then propose a routing algorithm based on it. Our algorithm makes use of two simple, intuitive objectives: each battery should be allowed to rest between uses if possible, so that its capacity regenerates, and  that the communication load between two nodes should be distributed over multiple paths between them. While it would be nice to balance the communication load between multiple paths, generating  edge or node disjoint paths is a computationally hard problem. We address this problem by generating multiple paths using existing algorithms for braided multipaths. This can be done efficiently and produces paths that are mostly disjoint. We compare (using simulation) our algorithm with the well known Directed Diffusion algorithm which uses a single path for all packets. Our experiments show that our algorithm significantly outperforms Directed Diffusion for our battery model.
  

• Simple randomized MAC protocols that conserve battery power.  
  RMAC: a randomized adaptive medium access control algorithm for sensor networks (pdf file)- in the Proccedings of Second International Workshop on Sensor and Actor Network Protocols and Applications August 22, 2004 Boston, Massachusetts, USA
[ABSTRACT]: It is believed that in the near future, there will be a large-scale deployment of wireless sensor networks for sensing, collecting and transferring information about the environments the sensors are placed in. Due to their peculiar characteristics and goals, sensor networks differ sharply from traditional wired and wireless networks, and so many problems have to be solved afresh for such networks. In this paper, we study the medium access control problem and focus on a class of Time-Division-Multiple-Access (TDMA) protocols called demand assignment protocols.We propose a simple, adaptive algorithm RMAC for heterogeneous wireless sensor networks. RMAC improves on existing demand assignment algorithms like RMAV [Jeong et al], DQRUMA [Karol et al] and the protocol proposed in Aboelaze et al  in several ways. First, it uses Maximum-Likelihood Estimation to reduce packet delays and uses a simple prediction scheme to adapt to changing traffic patterns. Second, in most demand assignment algorithms, a transmitted packet reserves a timeslot for the next packet in the same message. Thus, when multi-packet messages are being transmitted, a new message may have have to wait for a long time before it can be transmitted; i.e., the algorithms are unfair to new sessions. Our algorithm provides a parameter that controls this fairness property of the algorithm. We present simulation results to compare the performance of our algorithm  with RMAV,  DQRUMA and the protocol proposed in Aboelaze et al.

• Design and hardware implementation of a simple sensor network. 

Although I have worked on the design, I need students interested in working with hardware to go through with this project. Please contact me if this sounds exciting to you!

Resources (for York students):

• This course page at UMass has a wealth of information on Sensor Networks.
• See also the following paper on Sensor Network Applications.
• A bibliography on this topic.
• Here is another bibliography on this topic.
• Here is another bibliography on this topic.

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