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Chellapraba, B.
- Improved Energy Efficient Clustering In Manets Using Metaheuristic Optimization
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Authors
Affiliations
1 Department of Computer Science and Engineering, SNS College of Engineering, IN
2 Department of Information Technology, Karpagam Institute of Technology, IN
3 Department of Computer Science and Engineering, St. Joseph Institute of Technology, IN
1 Department of Computer Science and Engineering, SNS College of Engineering, IN
2 Department of Information Technology, Karpagam Institute of Technology, IN
3 Department of Computer Science and Engineering, St. Joseph Institute of Technology, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 1 (2022), Pagination: 2616-2620Abstract
A mobile ad hoc network (MANET) is a wireless network created by a radio terminal built into a mesh topology. Each node is deflected with respect to the other nodes. The Temporary networks can self-heal and automatically redirect back around a lost node. There is an MANET networks require different network layout protocols, such as remote hierarchical remote vector navigation, associative-based navigation, ad-assigning remote vector navigation, and dynamic source navigation. An improved meta-heuristic optimization algorithm is proposed in this paper. It works in conjunction with an autonomous mobile network to increase its power and efficiency. It can transmit large amounts of data using less power and its bandwidth speed increases as its data transfer speed increases. This will improve the amount of service generated there and the users can satisfy the provided services.Keywords
MANET, Mesh Topology, Autonomous Mobile Network, Energy EfficiencyReferences
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- Elimination of Data Modification in Sensor Nodes of WSN Using Deep Learning Model
Abstract Views :73 |
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Authors
Affiliations
1 Department of Information Technology, Karpagam Institute of Technology, IN
2 Department of Computer Science & Engineering, SNS College of Technology, IN
3 Department of Computer Science and Engineering, St. Joseph’s Institute of Technology, IN
1 Department of Information Technology, Karpagam Institute of Technology, IN
2 Department of Computer Science & Engineering, SNS College of Technology, IN
3 Department of Computer Science and Engineering, St. Joseph’s Institute of Technology, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 2 (2022), Pagination: 2712-2717Abstract
This study focuses on removing the possibility of malicious data manipulation in wireless sensor networks (WSN) by utilising a deep learning method. When training deep neural networks, datasets that have been the subject of an attack that alters the data are used as the building blocks. This is done in preparation for putting the networks to the test in the real world. We find out through simulation with a 70:30 cross-validation across a 10-fold sample size that the proposed technique is superior to the current state of the art in terms of the packet delivery rate, latency and throughput.Keywords
Deep Learning Model, Data Modification, WSN, ThroughputReferences
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