|Toward Energy-efficient Communication in Wireless Sensor Networks|
Wireless Sensor and Actor NetworksA typical wireless sensor network performs only one action: sensing the environment. Our requirement for intelligent interaction with the environment has led to the emergence of Wireless Sensor and Actor Networks (WSANs), where a group of sensors, actors and a central coordination entity (sink) linked by wireless medium perform distributed sensing and acting tasks.
In order to provide tight coupling between sensing and acting, an effective coordination mechanism is required among sensors and actors. In this context, we identify the problem of out-of-order execution of queries and commands due to a lack of coordination between sensors and actors, called hazards. We identify four types of hazards in this project. We also identify and enumerate the associated challenges in addressing hazards. In this context, we discuss the basic design needed to address this problem efficiently. We propose a distributed and fully localized approach that addresses the problem and the associated challenges based on the design. Through analytical studies and simulations we study the performance of the proposed solution and two basic strategies, and show that the proposed solution is efficient for a variety of network conditions.
In WSANs, it is important that the actors act only to the appropriate level when the event occurs in order to perform the desired action on the evironment. In this context, we identify the problem of mutual exclusion, which is the need to act only once for any particular location and command. We define three flavors for mutual exclusion and show with an example application, the undesirable consequences of not providing mutual exclusion. We also identify and enumerate the different variants of the mutual exclusion problem for different application requirements.
Efficient Sensor CommunicationWireless sensor networks (WSNs) are typically characterized by a limited energy supply at sensor nodes. Hence, energy efficiency is an important issue in the system design and operation of WSNs. In this project, we propose a novel communication paradigm that enables energy-efficient information delivery in wireless sensor networks. Compared with traditional communication strategies, the proposed scheme explores a new dimension - time, to deliver information efficiently. We identify a key drawback of this novel strategy: energy - throughput trade-off, and explore optimization mechanisms that can alleviate the trade-off. We then investigate several challenges that need to be overcome, primarily at the medium access control layer of the network protocol stack, in order to realize the new strategy effectively.
Framework for Distributed data FusionSimple in-network data aggregation (or fusion) techniques for sensor networks have been the focus of several recent research efforts, but they are insufficient to support advanced fusion applications. We extend these techniques to future sensor networks and ask two related questions:
We have developed an architectural framework, DFuse, for answering these two questions. It consists of a data fusion API and a distributed algorithm for energy-aware role assignment. The fusion API enables an application to be specified as a coarse-grained dataflow graph, and eases application development and deployment. The role assignment algorithm maps the graph onto the network, and optimally adapts the mapping at run-time using role migration. Work on DFuse is ongoing.
System Support for Cross-Layering in Heterogeneous Sensor StackWireless Sensor Networks are deployed in demanding environments, where application requirements as well as network conditions may change dynamically. Thus the protocol architecture in each node of the sensor network has to be able to adapt to these changing conditions. Sensor Stack project investigates the software architecture of the protocol stack for such futuristic sensor networks and application scenarios. Such an architecture will address key issues such as (a) structured cross layer information sharing among the layers of the architecture to foster agile adaptation of the network modules to changing conditions; (b) information sharing among neighbor nodes to improve network lifetime, and (c) application-specific innetwork computations as part of the layered architecture to reduce the penalties for such processing and improve the latency at the application level. Specifically, this research will make the following contributions.
Last modified 13 April 2006 at 12:17 pm by c-68-39-178-211.hsd1.nj.comcast.net
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