Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
Browse
2 results
Search Results
Item Parallelized K-Means clustering algorithm for self aware mobile Ad-hoc networks(2011) Thomas, L.; Manjappa, K.; Annappa, B.; Guddeti, G.R.M.Providing Quality of Service (QoS) in Mobile Ad-hoc Network (MANET) in terms of bandwidth, delay, jitter, throughput etc., is critical and challenging issue because of node mobility and the shared medium. The work in this paper predicts the best effective cluster while taking QoS parameters into account. The proposed work uses K-Means clustering algorithm for automatically discovering clusters from large data repositories. Further, iterative K-Means clustering algorithm is parallelized using Map-Reduce technique in order to improve the computational efficiency and thereby predicting the best effective cluster. Hence, parallel K-Means algorithm is explored for finding the best effective cluster containing the hops which lies in the best cluster with the best throughput in self aware MANET. Copyright © 2011 ACM.Item Decentralised Authentication Protocol for Devices & Users to Access Private Network Services Using Blockchain(IEEE Computer Society, 2023) Praneeth, P.; Tanguturu, R.; Aenugutala, S.P.; Cunha, T.B.D.; Manjappa, K.With recent advancements in the Internet of things, challenges to secure devices and data related to devices have increased. Adversaries using different threats manage to clone/hack/tamper devices by hacking credentials stored in centralised databases. In this work, a decentralised approach using blockchain is proposed to check the authenticity of the device/user trying to access the services of the service provider network. The proposed method uses public and private blockchain networks and Physical Unclonable Function (PUF) to authenticate the device/user and to store their credentials. The decentralised application runs on Hyperledger Fabric, an open-source platform for building blockchain networks. The proposed protocol is tested and implemented in the physical testbed containing Raspberry Pi and Arduino Mega's. © 2023 FRUCT.
