Tamilselvi P

@cauverycollege.ac.in

Assistant Professor, Department of Information Technology
Cauvery College for Women (Autonomous)

Tamilselvi P


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https://researchid.co/tamilselvi

RESEARCH INTERESTS

Ad hoc network, Social Network
5

Scopus Publications

Scopus Publications

  • ADAPTIVE Q-LEARNING-BASED ROUTING WITH CONTEXT-AWARE METRICS FOR ROBUST MANET ROUTING (AQLR)
    P Tamilselvi, S Suguna Devi, M Thangam, P Muthulakshmi
    International Journal of Computer Networks and Communications, 2025
    Mobile Ad Hoc Networks encounter persistent challenges due to dynamic topologies, limited resources and high routing load. As these problems continue, the network’s overall performance declines as the network scales. To address these challenges Adaptive Q-Learning-Based Routing with Context-Aware Metrics for Robust MANET Routing (AQLR), a routing protocol that uses context-aware data and reinforcement learning to choose the best route for connected mobile devices. AQLR considers four essential routing metrics such as Coverage Factor, RSSI-Based Link Stability, Energy Weighting and Broadcast Delay. AQLR uses Q-learning agent at each node to enable adaptive learning of optimal next-hop decisions based on past history. Composite Routing Metric (CRM) helps to obtain smart decision in the absence of prior learning. Simulation performed with OMNeT++ across varying node densities from 50 to500 the simulation results shows that AQLR outperforms recent machine learning-based routing protocols including QLAR, RL-DWA, and DRL-MANET. Specifically, AQLR achieves up to 95.8% packet delivery ratio, reduces average end-to-end delay by 25–35%, lowers routing overhead by 20–30%, and improves network lifetime by over 15% in dense scenarios. These results affirm the effectiveness of combining reinforcement learning with context-aware metric computation for scalable and energy-efficient MANET routing.
  • Bootstrap Aggregated Mutual Dependency Ensemble Clustering and Learning Agent Based Approach to Eliminate Stale Routes in MANET
    P. Tamilselvi,, T. N. Ravi
    International Journal of Electrical and Electronic Engineering and Telecommunications, 2021
    Mobile Ad hoc networks deploy the network with the support of self-organizing and self-configuring mobile nodes. Due to the lack of centralization, the topological structure of the network fluctuates frequently. Preserving stable link communication to obtain reliable data transmission is the key challenge in the dynamic wireless network environment. This stimulates discrepancy on discovered route paths. To address this issue a novel approach called bootstrap aggregated mutual dependency ensemble clustering and learning agent based approach to eliminate stale routes in MANET (BAMDEC-LABA) is introduced. This algorithm is used to identify the stable link based on the metrics such as residual energy, receiving signal strength, less hop count and node behavior. Maximum dependency with less hop count route paths are classified by employing bootstrap aggregation method. Learning agent examines the node behavior and identifies the selfish and corruptive nodes using node cooperativeness and trust value. The occurrence of the link failure due to the malicious nodes intimated to all the nodes with the distribution of route error packet. The inconsistent route path is eliminated from the cache to preserve the link failure. The performance of the proposed approach is evaluated with different performance metrics such as routing overhead, packet delivery ratio, packet drop rate, and delay. When compared to state-of-the-art approaches, the proposed BAMDEC-LABA technique on an average minimizes the routing overhead by 26%, improves the packet delivery ratio by 18%, packet drop rate is considerably reduced by 68% and delay is found to be minimized by 27%. The proposed method outperforms when compared to state-of-the-art approaches.
  • Hybridization of Brownboost and Random Forest Tree with Gradient Free Optimization for Route Selection
    P. Tamilselvi, T.N. Ravi
    International Journal of Computing, 2021
    MANETs are self-organizing network architectures of mobile nodes. Due to node mobility, wireless network topologies dynamically various over time. A novel link stability estimation technique called Hybridization of Brownboost Cluster and Random Forest Decision Tree with Optimized Route Selection (HBCRFDT-GORS) technique is introduced for increasing the reliable data delivery by eliminating the stale routes in MANET. Brown Boost technique is applied to find the route paths having the smaller number of hop counts to perform the data transmission. After that, the status of the mobile nodes in the selected route paths is determined based on the residual energy and signal strength. Then, a random forest decision tree is applied to correctly identify the stale routes by finding the link failure due to the selfish node and the corruptive node along the route path. Then the broken link is removed from the route path. After eliminating the stale route from the path, the HBCRFDT-GORS technique finds the alternative optimal route through the gradient free optimization. The proposed HBCRFDT-GORS technique performs stale route elimination and improves reliable data delivery from source to destination. Simulation is conducted on different performance metrics such as routing overhead, packet delivery ratio, packet drop rate, and delay with respect to the number of data packets. The Network simulation results indicate that the HBCRFDT-GORS technique is improving the data delivery and and minimizing the delay as well as reducing the packet losses when compared to the baseline approaches.
  • Reweighted Gaussian correlative boost clustering for stale route elimination in manet
    International Journal of Advanced Science and Technology, 2019
  • Routing algorithm to eliminate stale routes (RAESR) in mobile ad hoc networks
    P. Tamilselvi, Dr.T.N. Ravi
    International Journal of Innovative Technology and Exploring Engineering, 2019
    Mobile Ad-hoc Network (MANET) is a collection of self sustaining mobile nodes which are connected through many wi-fi links to form a temporary communication for sharing information between the users. Mobile nodes behave as a host as well as router. As nodes in MANET posse’s mobility in traits frequently leads to irregular link between the nodes. Link failure directs a significant routing overhead during high mobility and also maintaining all the information associated with nodes and routing paths are considered as an extra overhead on the table. In order to overcome these issues, the routing algorithm to eliminate stare routed in routing cache. The neighbor degree centrality table is introduced to recognize the valuable nodes, using the valuable nodes the routes are discovered and link failure information are disseminated across the network wide. The results and findings show that the elimination of stale routes leads to significant reduction in routing overhead which in turn reduces the route error propagation delay