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DEVELOPMENT OF A MODIFIED REAL-TIME FAULT-TOLERANT TASK ALLOCATION SCHEME FOR WIRELESS SENSOR NETWORKS


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📄 Pages: 84       🧠 Words: 10841       📚 Chapters: 5 🗂️️ For: PROJECT

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ABSTRACT
This research aimed at the development of a modified real-time fault-tolerant task allocation scheme (mRFTAS) for wireless sensor networks (WSNs), using active replication backup techniques. In WSNs, the sensor nodes are at risk of failure and malicious attacks (selective forwarding) and this can have a profoundly negative effect on real-time WSNs. The real-time fault-tolerant task allocation scheme (RFTAS) was developed to address these issues, however, it has the problem of processing time delay. This is attributed to the characteristic of the passive backup copy technique adopted for the RFTAS in which the backup copy is only activated when the primary copy has failed. The delay in the activation of the backup copies of the primary tasks in tasks allocation execution processes as a result of a failure of sensor nodes or the primary tasks, will cause disastrous consequences if the systems are safety-critical, e.g. aircraft, nuclear power plant, forest fire detection, battlefield monitoring. The mRFTAS was therefore developed using the active replication backup technique where both the primary and backup copies of tasks are executed concurrently. The performance of the mRFTAS and RFTAS was compared using total execution time of the task, energy consumption, reliability cost and network lifetime. A graphical user interface (GUI) based system for simulation of sensor nodes in WSNs using RFTAS and mRFTAS called the task allocation scheme simulator (TASS) was developed in order to carry out the performance evaluation. The performance of mRFTAS showed an improvement over RFTAS in terms of minimizing task execution time (28.65%) and reliability cost (7.29%) while maximizing network lifetime (22.26%) but with a trade-off in energy consumption (-17.32%).

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📄 Pages: 84       🧠 Words: 10841       📚 Chapters: 5 🗂️️ For: PROJECT

👁️‍🗨️️️ Views: 254      

⬇️ Download (Complete Report) Now!

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