Anand Nayyar

15.6k citations
312 papers · 7.7k indexed · 2 hit papers · h-index 46

Anand Nayyar

289 papers receiving 7.2k citations

Hit Papers

Machine Learning from Theory to Algorithms: An Overview4322017202620202023100200300400

Peers

Anand Nayyar
Comparison fields: 5 of 198
  • Computer Networks and Communications 2.2k
  • Information Systems 1.5k
  • Health Informatics 72
  • Artificial Intelligence 1.6k
  • Computer Vision and Pattern Recognition 1000
Replace Gunasekaran Manogaran with:
Gunasekaran Manogaran United States
Xiaokang Zhou Japan
Juan M. Corchado Spain
Thar Baker United Kingdom
N. Z. Jhanjhi Malaysia
Mehedi Masud Saudi Arabia
Sandeep K. Sood India
Md. Jalil Piran South Korea
Zhikui Chen China
Huansheng Ning China
Anand Nayyar relative to Gunasekaran Manogaran United States Gunasekaran Manogaran's profile →
Citations per field
00.5×5.3×
Gunasekaran Manogaran · 1×
Citations per year

Countries citing papers authored by Anand Nayyar

Since Specialization
Citations

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

Fields of papers citing papers by Anand Nayyar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Anand Nayyar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Anand Nayyar Line = papers co-authored together Anand Nayyar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20244
3 20245
4 202415
5 20236
6 20238
7 20233
8 202316
9 20230
10 202212
11 202212
12 202123
13 202143
14 202167
15 20206
16 20201
17 202095
18 202037
19 20182
20
Simulation and Performance Comparison of Ant Colony Optimization (ACO) Routing Protocol with AODV, DSDV, DSR Routing Protocols of Wireless Sensor Networks using NS-2 Simulator
201710

About Anand Nayyar

Anand Nayyar is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence, having authored 312 papers that have together received 7.7k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (40 papers), Energy Efficient Wireless Sensor Networks (31 papers), Energy Harvesting in Wireless Networks (21 papers), Mobile Ad Hoc Networks (19 papers), Network Security and Intrusion Detection (18 papers), IoT-based Smart Home Systems (16 papers), Blockchain Technology Applications and Security (15 papers) and Opportunistic and Delay-Tolerant Networks (15 papers). The work is most often cited by research in Computer Networks and Communications (2.2k citations), Information Systems (1.5k citations) and Health Informatics (72 citations). Anand Nayyar has collaborated with scholars based in Vietnam, India and Saudi Arabia. Frequent co-authors include Akshi Kumar, Vikram Puri, Jafar A. Alzubi, Rajeshwar Singh, Arun Solanki, Basit Qureshi, Rajalakshmi Krishnamurthi, Adarsh Kumar, Linesh Raja and Sudeep Tanwar. Their work appears in journals such as Multimedia Tools and Applications, IEEE Access, Computers, materials & continua/Computers, materials & continua (Print), Sensors and Optik.

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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2026