Sensor scheduling for improved performance of target tracking using wireless sensor networks / Ahmed Gomaa Marie Mohamed ; Supervised Amin Mohamed Nassar , Hany Mohamed Elsayed
Material type: TextLanguage: English Publication details: Cairo : Ahmed Gomaa Marie Mohamed , 2015Description: 86 P. : plans ; 30cmOther title:- جدولة المستشعرات لتحسين أداء تتبع الأهداف باستخدام شبكات الاستشعار اللاسلكية [Added title page title]
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Item type | Current library | Home library | Call number | Copy number | Status | Date due | Barcode | |
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.08.M.Sc.2015.Ah.S (Browse shelf(Opens below)) | Not for loan | 01010110067343000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.08.M.Sc.2015.Ah.S (Browse shelf(Opens below)) | 67343.CD | Not for loan | 01020110067343000 |
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Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics and Communication
Wireless ad-hoc sensor networks have recently emerged as an important research topic. Accurate tracking of targets is a vital application of WSN in military as well as civil applications. In many tracking applications, one of the main issues for system design is that of sensor selection and scheduling, which aims to improve tracking accuracy and conserve resources by selecting the sensor that best contributes to the state estimate at any given time. This thesis focuses on developing sensor scheduling schemes for target tracking. Thesis objectives are to save energy while preserving accuracy and real time performance, and to achieve network lifetime elongation in target tracking. Two methods are proposed to enhance the performance. First method uses the k- means clustering algorithm and adaptive sensor scheduling. The second proposed method improves network lifetime by taking the sensor remaining energy into consideration. The use of K-means clustering method in sensor scheduling is meeting the required tracking accuracy without energy consumption degradation. In addition, the proposed scheme has the better real time performance compared to previously used methods. By taking the sensor remaining energy into account in sensor scheduling, accurate tracking is achieved with significant improvement in network lifetime
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