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Vasanthi, V.
- Fractional Gaussian Firefly Algorithm and Darwinian Chicken Swarm Optimization for IoT Multipath Fault-Tolerant Routing
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Authors
Affiliations
1 Computer Science Department, Rathinam College of Arts and Science, Bharathiar University, Coimbatore, IN
2 Department of Information Technology, Sri Krishna Adithya College of Arts and Science, Bharathiar University, Coimbatore, IN
1 Computer Science Department, Rathinam College of Arts and Science, Bharathiar University, Coimbatore, IN
2 Department of Information Technology, Sri Krishna Adithya College of Arts and Science, Bharathiar University, Coimbatore, IN
Source
International Journal of Computer Networks and Applications, Vol 7, No 6 (2020), Pagination: 167-177Abstract
Wireless Sensor Networks (WSN) based Internet-of- Things (IoT) systems offer high efficient data transmission with enhanced Quality of Service (QoS). A multi-constraint based energy-efficient and fault-tolerant routing algorithm using Fractional Gaussian Firefly Algorithm (FGFA) and Darwinian Chicken Swarm Optimization (DCSO) are presented for performing optimal multipath communication. FGFA is an improved Firefly Algorithm in which the fractional theory and Gaussian function are incorporated to improve the convergence speed with higher efficiency. Likewise, the DCSO is an improved model of CSO based on the survival theory of Darwin to decrease the computation time and improve the convergence by eliminating the local optimal challenges. Initially, the network is clustered and the cluster heads (CH) are chosen optimally by FGFA based on the objective function with multiple QoS constraints. Then the best routing paths are chosen by DCSO through similar objective function with inter-cluster and intracluster delay additionally included. The optimal paths are sorted in a hierarchical order from which multiple paths are utilized for data communication. The FGFA+DCSO routing protocol is assessed in NS-2 simulator and the outcomes shown the proficiency of the suggested approach with 6.3% reduced delay, 6% improved throughput, 26.7% minimized energy, 11% increased lifetime, 20% higher PSNR, and hop count reduced by 1.Keywords
Internet-of-Things, Wireless Sensor Networks, Fault Tolerance, Energy Constraint Problem, Fractional Gaussian Firefly Algorithm, Darwinian Chicken Swarm Optimization.Full Text
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- Analysis of Online Intrusion Detection Models to Incorporate Secured Digital Cash Transaction in Mobile Smart Systems
Abstract Views :51 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science, Periyar Arts College, IN
2 Department of Computer Science, Dharmapuram Gnanambigai Government Arts College for Women, IN
3 PG Department of Computer Application, St. Joseph’s College of Arts and Science, Cuddalore, IN
1 Department of Computer Science, Periyar Arts College, IN
2 Department of Computer Science, Dharmapuram Gnanambigai Government Arts College for Women, IN
3 PG Department of Computer Application, St. Joseph’s College of Arts and Science, Cuddalore, IN
Source
ICTACT Journal on Communication Technology, Vol 14, No 4 (2023), Pagination: 3063-3070Abstract
The major Objective of this research paper is to design the Mobile Smart Device Digi Cash Intrusion Detection Framework (MSDDID) for assessing Intrusion Detection (ID) techniques and evaluating ID parameters that has to be rectified for enhancing the security of Digital Cash Transactions in Mobile Smart devices. The Research examined the Intrusion Detection dataset with 41 predictive features and 1 class feature for evaluating prediction in its novel form. The Framework was examined in WEKA with RapidMiner for analysis. The Results of classifiers Decision Table (98.7%), Random Forest Tree (99.79%), AdaBoost (94.37%), CART Model (99.61%), LazyIBK (99.44%), Naïve Bayesian (89.66%) signified that Smart devices security in Digi cash transactions could be predicted with refinement of data during transaction as deployed in this research work. The cluster analysis again conformed that num_root, su_attempted and num_compromised were the three parameters predominantly used for intrusions in the network and has to be addressed in the model.Keywords
Intrusion Detection System, Network Security, Intrusion Detection Parameters, Digital Cash Transactions, Mobile Smart Systems.
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