D. Manivannan

2.5k total citations
79 papers, 1.6k citations indexed

About

D. Manivannan is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, D. Manivannan has authored 79 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Computer Networks and Communications, 30 papers in Electrical and Electronic Engineering and 18 papers in Artificial Intelligence. Recurrent topics in D. Manivannan's work include Distributed systems and fault tolerance (23 papers), Opportunistic and Delay-Tolerant Networks (22 papers) and Vehicular Ad Hoc Networks (VANETs) (22 papers). D. Manivannan is often cited by papers focused on Distributed systems and fault tolerance (23 papers), Opportunistic and Delay-Tolerant Networks (22 papers) and Vehicular Ad Hoc Networks (VANETs) (22 papers). D. Manivannan collaborates with scholars based in United States, India and Jordan. D. Manivannan's co-authors include Qiangfeng Jiang, Mukesh Singhal, Shafika Showkat Moni, Sherali Zeadally, M. Singhal, A. B. Siddique, Kiho Lim, Yi Luo, Robert H. B. Netzer and Jiang Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Information Sciences.

In The Last Decade

D. Manivannan

74 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
D. Manivannan United States	21	1.4k	691	347	271	152	79	1.6k
Zhiping Jia China	18	1.1k 0.8×	485 0.7×	318 0.9×	315 1.2×	272 1.8×	154	1.6k
Michael Menth Germany	19	1.6k 1.2×	875 1.3×	193 0.6×	125 0.5×	121 0.8×	191	1.8k
Guy Pujolle France	20	1.1k 0.8×	631 0.9×	207 0.6×	281 1.0×	42 0.3×	108	1.4k
David Hung-Chang Du United States	18	1.1k 0.8×	675 1.0×	148 0.4×	183 0.7×	186 1.2×	96	1.4k
Dennis K. Nilsson Sweden	15	382 0.3×	495 0.7×	349 1.0×	214 0.8×	131 0.9×	40	964
Turgay Korkmaz United States	20	1.3k 0.9×	702 1.0×	144 0.4×	122 0.5×	76 0.5×	79	1.5k
Seung Yeob Nam South Korea	19	898 0.6×	723 1.0×	235 0.7×	399 1.5×	35 0.2×	66	1.3k
Po‐Ching Lin Taiwan	16	910 0.7×	385 0.6×	609 1.8×	222 0.8×	132 0.9×	73	1.3k
Ten‐Hwang Lai United States	23	1.4k 1.0×	660 1.0×	225 0.6×	110 0.4×	163 1.1×	58	1.7k
Xuanxia Yao China	15	654 0.5×	297 0.4×	456 1.3×	446 1.6×	42 0.3×	40	1.1k

Countries citing papers authored by D. Manivannan

Since Specialization

Citations

This map shows the geographic impact of D. Manivannan'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 D. Manivannan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Manivannan more than expected).

Fields of papers citing papers by D. Manivannan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Manivannan. 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 D. Manivannan. The network helps show where D. Manivannan may publish in the future.

Co-authorship network of co-authors of D. Manivannan

This figure shows the co-authorship network connecting the top 25 collaborators of D. Manivannan. A scholar is included among the top collaborators of D. Manivannan 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 D. Manivannan. D. Manivannan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Manivannan, D., et al.. (2024). Machine Learning Powered Health Advisory and Web Solutions. 1–5. 1 indexed citations

Siddique, A. B., et al.. (2023). A deep learning approach for intrusion detection in Internet of Things using focal loss function. Internet of Things. 22. 100699–100699. 86 indexed citations

Salameh, Haythem Bany, et al.. (2022). An On-Board Hardware Implementation of AODV Routing Protocol in VANET: Design and Experimental Evaluation. 1–6. 2 indexed citations

Manivannan, D., et al.. (2022). A Secure and Improved Safety Message Collection with Increased Privacy-Preserving Algorithm for VANETs. 21. 1–8. 1 indexed citations

Nalini, M., et al.. (2022). A Standardised Neighbourhood Interface through Massive Parallel Computing for Mining Digital Data. 6(1). 7–14.

Moni, Shafika Showkat & D. Manivannan. (2022). CREASE: Certificateless and REused-pseudonym based Authentication Scheme for Enabling security and privacy in VANETs. Internet of Things. 20. 100605–100605. 13 indexed citations

Moni, Shafika Showkat & D. Manivannan. (2020). Privacy-preserving and Authentication in VANETs. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING. 11(2). 1 indexed citations

Manivannan, D., et al.. (2020). A Secure Source Routing Protocol for Mobile Ad Hoc Networks. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING. 11(3). 212–234.

Manivannan, D., et al.. (2019). Classification, Challenges and Critical Comparison of Proposed Solutions for Vehicular Clouds. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING. 10(1). 5 indexed citations

10.

Manivannan, D., et al.. (2016). A Classification and Characterization of Security Threats in Cloud Computing. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING. 7(1). 1–17. 37 indexed citations

11.

Manivannan, D., et al.. (2014). A Survey of Routing Protocols for Wireless Sensor Networks. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING. 5(2). 139–166. 4 indexed citations

12.

Wu, Jiang & D. Manivannan. (2009). An enhanced model-based checkpointing protocol for preventing useless checkpoints. International Journal of Parallel Emergent and Distributed Systems. 24(5). 383–406. 4 indexed citations

13.

Manivannan, D., et al.. (2008). Delay-Tolerant Routing Protocols for Vehicular Ad Hoc Networks: A Critical Comparison and Classification.. International Conference on Wireless Networks. 149–154. 3 indexed citations

14.

Manivannan, D.. (2008). Checkpointing and rollback recovery in distributed systems: existing solutions, open issues and proposed solutions. International Conference on Systems. 569–574. 1 indexed citations

15.

Wu, Jiang, D. Manivannan, & Bhavani Thuraisingham. (2008). Transaction-Consistent Global Checkpoints in a Distributed Database System. Lecture notes in computer science. 2170(1). 327–334. 1 indexed citations

16.

Luo, Yi & D. Manivannan. (2008). FINE: A Fully Informed aNd Efficient communication-induced checkpointing protocol for distributed systems. Journal of Parallel and Distributed Computing. 69(2). 153–167. 17 indexed citations

17.

Wu, Jiang, Yi Luo, & D. Manivannan. (2007). An enhanced model-based checkpointing protocol. 332–337. 3 indexed citations

18.

Manivannan, D., et al.. (2004). Distributed Self-Healing Bluetooth Scatternet Formation.. International Conference on Wireless Networks. 325–334. 8 indexed citations

19.

Manivannan, D.. (2004). Determining Consistent Global Checkpoints of a Distributed Computation. IEICE Transactions on Information and Systems. 87(1). 164–174. 1 indexed citations

20.

Manivannan, D., et al.. (2003). A Fault-Tolerant Channel Allocation Algorithm for Cellular Networks with Mobile Base Stations.. International Conference on Wireless Networks. 146–153. 5 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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