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dc.contributor.advisorShihada, Basem
dc.contributor.authorDaghistani, Anas H.
dc.date.accessioned2013-05-18T05:51:56Z
dc.date.available2013-05-18T05:51:56Z
dc.date.issued2013-05-15
dc.identifier.doi10.25781/KAUST-V5V83
dc.identifier.urihttp://hdl.handle.net/10754/292319
dc.description.abstractPower management is an active area of research in wireless sensor networks (WSNs). Efficient power management is necessary because WSNs are battery-operated devices that can be deployed in mission-critical applications. From the communications perspective, one main approach to reduce energy is to maximize throughput so the data can be transmitted in a short amount of time. Frame fragmentation techniques aim to achieve higher throughput by reducing retransmissions. Using experiments on a WSN testbed, we show that frame fragmentation helps to reduce energy consumption. We then study and compare recent frame fragmentation schemes to find the most energy-efficient scheme. Our main contribution is to propose a new frame fragmentation scheme that is optimized to be energy efficient, which is originated from the chosen frame fragmentation scheme. This new energy-efficient frame fragmentation protocol is called (Green-Frag). Green-Frag uses an algorithm that gives sensor nodes the ability to transmit data with optimal transmit power and optimal frame structure based on environmental conditions. Green-Frag takes into consideration the channel conditions, interference patterns and level, as well as the distance between sender and receiver. The thesis discusses various design and implementation considerations for Green-Frag. Also, it shows empirical results of comparing Green-Frag with other frame fragmentation protocols in terms of energy efficiency. Green-Frag performance results shows that it is capable of choosing the best transmit according to the channel conditions. Subsequently, Green-Frag achieves the least energy consumption in all environmental conditions.
dc.language.isoen
dc.subjectenergy-efficient
dc.subjectframe fragmentation
dc.subjectwireless sensor network
dc.subjectpower adaptive
dc.titleGreen-Frag: Energy-Efficient Frame Fragmentation Scheme for Wireless Sensor Networks
dc.typeThesis
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
thesis.degree.grantorKing Abdullah University of Science and Technology
dc.contributor.committeememberAlouini, Mohamed-Slim
dc.contributor.committeememberMoshkov, Mikhail
thesis.degree.disciplineComputer Science
thesis.degree.nameMaster of Science
refterms.dateFOA2018-06-13T09:45:52Z


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