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Computer Science Project Topics and Materials for Final Year Students

If you are a Computer Science final year students and looking for research idea for your final year project, we have good list of computer science project topics and materials you can choose from to save you time. These topics were selected from Samphina Academy (samphina.com.ng) which is the No1 platform for Academic Research in Nigeria. Below are some selected Computer Science Project Topics and Materials for Final Year

A cooperation federated forwarder selection technique for maximizing n by Rajeev Tiwari, Premkumar Chithaluru et al

Wireless Sensor Network (WSN) fulfills the requirements to solve real-life applications due to their unattended nature. But, the main constraint faced by researchers is the energy available with sensor nodes. The network should have a longer lifetime to offer better data aggregation. So there is a need to prolong the life of sensor nodes and thus WSN. It is necessary to design energy-efficient operational schemes. One of the most suitable approaches to enhance energy efficiency is the clustering scheme, which enhances the performance parameters of WSN. Thus Adaptive Ranking based Energy-efficient Opportunistic routing (AREOR) is an opportunistic scheme that creates dynamic clusters and offers a longer lifetime to the network due to its heuristic. This scheme is modified based on the cooperation of nodes termed Cooperation Federated-AREOR (CF-AREOR), further enhancing the network’s performance parameters. This protocol is implemented using a network simulator, and its performance is a

Ph D awardee - Star of Mysore

Ph D awardee - Star of Mysore
starofmysore.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from starofmysore.com Daily Mail and Mail on Sunday newspapers.

Global IoT Wireless Sensor Market Report 2023: Sector is

A novel approach based on bio-inspired efficient clustering algorithm by Lokesh Lohar, Navneet Kumar Agrawal et al

In large-scale heterogeneous wireless sensor networks (WSNs), clustering is particularly significant for lowering sensor nodes (SNs) energy consumption and creating algorithm more energy efficient. The selection of cluster heads (CHs) is a crucial task in the clustering method. In this paper, optimised K-means clustering algorithm and optimised K-means based modified intelligent CH selection based on BFOA for large-scale network (lar-OK-MICHB) is hybridised for CH selection process. Here, we utilised the extended capabilities of OK-MICHB algorithm for large-scale network. Furthermore, in many applications where energy is a primary constraint, such as military surveillance and natural disaster prediction, the stability region is also a significant factor, with a longer network lifespan being a primary requirement. In the proposed approach, only the CH selection is made after every round in place of cluster and CH change as done in conventional hierarchical algorithm. The simulation resu

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