Revathi Sundarasekar

1.4k total citations
9 papers, 808 citations indexed

About

Revathi Sundarasekar is a scholar working on Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Revathi Sundarasekar has authored 9 papers receiving a total of 808 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Networks and Communications, 2 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Revathi Sundarasekar's work include IoT and Edge/Fog Computing (4 papers), Cloud Computing and Resource Management (2 papers) and Traffic Prediction and Management Techniques (2 papers). Revathi Sundarasekar is often cited by papers focused on IoT and Edge/Fog Computing (4 papers), Cloud Computing and Resource Management (2 papers) and Traffic Prediction and Management Techniques (2 papers). Revathi Sundarasekar collaborates with scholars based in India, Lebanon and Malaysia. Revathi Sundarasekar's co-authors include Gunasekaran Manogaran, Priyan Malarvizhi Kumar, R. Varatharajan, Seifedine Kadry, Naveen Chilamkurti, P. Mohamed Shakeel, S. Baskar, BalaAnand Muthu, R. Dinesh Jackson Samuel and Suyel Namasudra and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Revathi Sundarasekar

8 papers receiving 755 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Revathi Sundarasekar India	8	245	217	206	138	103	9	808
Sujatha Krishnamoorthy China	15	171 0.7×	224 1.0×	127 0.6×	154 1.1×	112 1.1×	60	971
Luca Spalazzi Italy	14	193 0.8×	195 0.9×	153 0.7×	75 0.5×	54 0.5×	95	784
Maitreyee Dutta India	17	342 1.4×	220 1.0×	202 1.0×	161 1.2×	129 1.3×	102	1.3k
Senthil Kumar Jagatheesaperumal United States	15	213 0.9×	191 0.9×	152 0.7×	93 0.7×	72 0.7×	68	889
Ruiyun Yu China	17	208 0.8×	292 1.3×	135 0.7×	122 0.9×	212 2.1×	68	1.0k
Anand Paul South Korea	19	226 0.9×	310 1.4×	220 1.1×	279 2.0×	240 2.3×	73	1.2k
Ashit Kumar Dutta Saudi Arabia	15	159 0.6×	302 1.4×	124 0.6×	180 1.3×	166 1.6×	159	1.1k
Dankan Gowda India	21	399 1.6×	193 0.9×	307 1.5×	78 0.6×	186 1.8×	137	1.3k
Shadi Atalla United Arab Emirates	18	194 0.8×	245 1.1×	113 0.5×	155 1.1×	220 2.1×	114	1.1k
Aji Gautama Putrada Indonesia	14	132 0.5×	164 0.8×	123 0.6×	131 0.9×	181 1.8×	156	787

Countries citing papers authored by Revathi Sundarasekar

Since Specialization

Citations

This map shows the geographic impact of Revathi Sundarasekar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Revathi Sundarasekar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Revathi Sundarasekar more than expected).

Fields of papers citing papers by Revathi Sundarasekar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Revathi Sundarasekar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Revathi Sundarasekar. The network helps show where Revathi Sundarasekar may publish in the future.

Co-authorship network of co-authors of Revathi Sundarasekar

This figure shows the co-authorship network connecting the top 25 collaborators of Revathi Sundarasekar. A scholar is included among the top collaborators of Revathi Sundarasekar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Revathi Sundarasekar. Revathi Sundarasekar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Sundarasekar, Revathi, et al.. (2025). Innovative Analogous Storage Framework for IoT using Social Computing and Data Partitioning. 22–28.

Manogaran, Gunasekaran, P. Mohamed Shakeel, S. Baskar, et al.. (2020). FDM: Fuzzy-Optimized Data Management Technique for Improving Big Data Analytics. IEEE Transactions on Fuzzy Systems. 29(1). 177–185. 54 indexed citations

Namasudra, Suyel, et al.. (2020). Towards DNA based data security in the cloud computing environment. Computer Communications. 151. 539–547. 104 indexed citations

Manogaran, Gunasekaran, Mamoun Alazab, Vijayalakshmi Saravanan, et al.. (2020). Machine Learning Assisted Information Management Scheme in Service Concentrated IoT. IEEE Transactions on Industrial Informatics. 17(4). 2871–2879. 40 indexed citations

Manogaran, Gunasekaran, P. Mohamed Shakeel, Hassan Fouad, et al.. (2019). Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System. Sensors. 19(13). 3030–3030. 134 indexed citations

Sundarasekar, Revathi, P. Mohamed Shakeel, S. Baskar, et al.. (2019). Adaptive Energy Aware Quality of Service for Reliable Data Transfer in Under Water Acoustic Sensor Networks. IEEE Access. 7. 80093–80103. 46 indexed citations

Muthu, BalaAnand, C. B. Sivaparthipan, Revathi Sundarasekar, et al.. (2019). Detection of flood disaster system based on IoT, big data and convolutional deep neural network. Computer Communications. 150. 150–157. 141 indexed citations

Kumar, Priyan Malarvizhi, Usha Devi Gandhi, Gunasekaran Manogaran, et al.. (2018). Ant colony optimization algorithm with Internet of Vehicles for intelligent traffic control system. Computer Networks. 144. 154–162. 113 indexed citations

Varatharajan, R., Gunasekaran Manogaran, Priyan Malarvizhi Kumar, & Revathi Sundarasekar. (2017). Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm. Cluster Computing. 21(1). 681–690. 176 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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