Reliable Bulk Data Dissemination in Sensor Networks

dc.contributor.authorHuang, Leijun
dc.creatorHuang, Leijun
dc.date.accessioned2007-12-18T19:10:49Z
dc.date.available2007-12-18T19:10:49Z
dc.date.issued2007-12-18T19:10:49Z
dc.description.abstractA wireless sensor network consists of a large number of resource-constrained sensor nodes that are self-organized into a multi-hop network and cooperate on a single task. In many situations, sensor networks need to run for a long time once deployed. When the environment changes during their lifetime, updating the code image or application data at the node for a new task becomes necessary, thus making data dissemination a critical issue where a large data object needs to be reliably propagated to all of the nodes in a network. While most of the current sensor nodes are equipped with a multiple-channel radio, the existing data dissemination approaches such as Deluge [1] do not take advantage of multiple channels. Moreover, these approaches mostly focus on the object delivery latency, while energy efficiency is also very important due to the resource constraints of the sensor nodes. This dissertation proposes three novel protocols for reliable bulk data dissemination, named McTorrent, CORD and McCORD, that focus on both object delivery latency and energy efficiency. These protocols use multiple channels, or a core-based two-phase approach, or both techniques to reduce object delivery latency and energy consumption at each node. The results from experiments on both indoor and outdoor testbeds and extensive simulations in various scenarios show that these protocols significantly reduce the latency and/or energy consumption, compared to the existing approaches.
dc.identifier.urihttps://hdl.handle.net/1920/2942
dc.language.isoen_US
dc.subjectSensor networks
dc.subjectReliable bulk data dissemination
dc.subjectEnergy efficiency
dc.subjectLow latency
dc.titleReliable Bulk Data Dissemination in Sensor Networks
dc.typeDissertation
thesis.degree.disciplineComputer Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy in Computer Science

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