Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

Browse

Filters

2005 - 20062

Settings

Author: search.filters.author.Shayman, MarkSubject: search.filters.subject.Sensor-Actuator Networks

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Lifetime Maximizing Adaptive Traffic Distribution and Power Control in Wireless Sensor Networks
    (2006) Sun, Fangting; Shayman, Mark; Shayman, Mark; ISR
    In this paper we study how to maximize the lifetime of randomly deployed wireless sensor networks by applying adaptive traffic distribution and power control. We model this problem as a linear program by abstracting the network into multiple layers. First we focus on the scenario where transmission energy consumption plays the dominant role in overall energy consumption. After ignoring the processing energy consumption, we observe that: in order to maximally extend the lifetime, each node should split its traffic into two portions, and send one portion directly to the sink, and the other one to its neighbor in the next inner layer. Next we consider the effect of incorporating the processing energy consumption. In this case, we have similar observation: for each packet to be sent, the sender should either transmit it using the transmission range with the highest energy efficiency per bit per meter, or transmit it directly to the sink. Besides studying the upper bound of maximum achievable lifetime extension, we discuss some practical issues, such as how to handle the signal interference caused by adaptive power control. Finally, we propose a fully distributed algorithm to adaptively split traffic and adjust transmission power for randomly deployed wireless sensor networks. We also provide extensive simulation results which demonstrat that the network lifetime can be dramatically extended by applying the proposed approach in various scenarios.
  • Thumbnail Image
    Item
    Design Optimization of Multi-Sink Sensor Networks by Analogy to Electrostatic Theory
    (2005) Kalantari, Mehdi; Shayman, Mark; Shayman, Mark; ISR
    In this work we introduce a new mathematical tool for optimization of routes, and topology design in wireless sensor networks. We introduce a vector field formulation that models communication in the network, and routing is performed in the direction of this vector field at every location of the network. The magnitude of the vector field at every location represents the density of amount of data that is being transited through that location. We define the total communication cost in the network as the integral of a quadratic form of the vector field over the network area. Our mathematical machinery is based on partial differential equations analogous to the Maxwell equations in electrostatic theory. We use our vector field model to solve the optimization problem for the case in which there are multiple destinations (sinks) in the network. In order to optimally determine the destination for each sensor, we partition the network into areas, each corresponding to one of the destinations. We define a vector field, which is conservative, and hence it can be written as the gradient of a scalar function (also known as a potential function). Then we show that in the optimal assignment of the communication load of the network to the destinations, the value of that potential function should be equal at the locations of all the destinations. Also, we show that such an optimal partitioning of the network load among the destination is unique, and we give iterations to find the optimal solution.