Fuzzy Logic and Image Compression Based Energy Efficient Application Layer Algorithm for Wireless Multimedia Sensor Networks

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dc.authoridOZCELIK, Ibrahim/0000-0001-9985-5268
dc.authorwosidOZCELIK, Ibrahim/AAA-3304-2020
dc.contributor.authorSenturk, Arafat
dc.contributor.authorKara, Resul
dc.contributor.authorOzcelik, Ibrahim
dc.date.accessioned2021-12-01T18:48:06Z
dc.date.available2021-12-01T18:48:06Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.description.abstractWireless Sensor Networks (WSN) are the networks that can realize data processing and computation skills of sensor nodes over the wireless channel and they have several communication devices. Wireless Multimedia Sensor Networks (WMSN) are the networks composed of low-cost sensor nodes that transmit real-time multimedia data like voice, image, and video to each other and to sink. WMSN needs more energy and bandwidth than WSN since they transmit a larger amount of data. The size of the data transmitted by the sensor nodes to each other or the sink becomes an important factor in their energy consumption. Energy consumption is a fundamental issue for WMSN. Other issues that affect the progress of WMSN are limited bandwidth and memory constraints. In these networks, for which the node battery lives are important sources, the limited sources must be effectively used by decreasing the transmitted data amount by removing the redundant data after proper processing of the environmental data. A new algorithm is developed to minimize the energy consumption during image data transmission between sensor nodes on WMSN, and so, make the nodes use their most important source, battery life ef-fectively in this study. This algorithm is named as Energy-aware Application Layer Algorithm based on Image Compression (EALAIC). This algorithm makes use of the top three image compression algorithms for WMSN and decides instantly to which one is the most efficient based on three parameters: the distance between the nodes, total node number, and data transmission frequency. In this way, the sensor node battery lives are used efficiently. The performance analysis of the developed algorithm is also done via Network Simulator - 2 (NS - 2) and it is compared by the existing algorithms in terms of energy rate (consumed energy/total energy) and PSNR (Peak Signal to Noise Ratio).en_US
dc.identifier.doi10.2298/CSIS191124008S
dc.identifier.endpage536en_US
dc.identifier.issn1820-0214
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85088506916en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage509en_US
dc.identifier.urihttps://doi.org/10.2298/CSIS191124008S
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10458
dc.identifier.volume17en_US
dc.identifier.wosWOS:000552257400009en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherComsis Consortiumen_US
dc.relation.ispartofComputer Science And Information Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectEnergy efficiencyen_US
dc.subjectFuzzy logicen_US
dc.subjectImage compressionen_US
dc.subjectWireless multimedia sensor networksen_US
dc.subjectRouting Protocolen_US
dc.subjectQosen_US
dc.subjectAwareen_US
dc.subjectTransmissionen_US
dc.titleFuzzy Logic and Image Compression Based Energy Efficient Application Layer Algorithm for Wireless Multimedia Sensor Networksen_US
dc.typeArticleen_US

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