Dr. Ashish kumar Luhach
Also known as: Ashish Kr. Luhach
Papua New Guinea University of Technology, Banasthali Vidyapith Faculty of Mathematics and Computing
Research areas: Computer Science · Computer Networks and Communications · IoT and Edge/Fog Computing · Energy Efficient Wireless Sensor Networks · Metaheuristic Optimization Algorithms Research
0000-0001-8759-0290
About
Dr. Ashish Kumar Luhach received PhD degree in department of computer science from Banasthali University. Dr. Luhach is working at The PNG University of Technology, Papua New Guinea. He has extensive teaching and research experience. His areas of research are Real time and Fault tolerant Cyber Physical systems, Service Oriented Architectures, Wireless Sensor Networks and Bio-inspired Computing. Dr. Luhach has published more 80 research paper in reputed journals and conferences, which are indexed in various international databases. He is also Guest Editor/Editorial board members of various reputed journals. He is member of IEEE, CSI, ACM, IAENG and IACSIT.
Employment
- 2019 - Present
Education
-
Banasthali Vidyapith Faculty of Mathematics and Computing Ph.D? - 2015
Projects & Funding
Projects & funding information is unavailable.
Publications (109)
- Analysis of Challenges of IoT Adoption for Smart City Application Save
- An Investigation into the Practical Use of Internet of Things Technology in Smart City Applications Save
- Analysis of Microgrids with Diverse Distributed Energy Resources Using Genetic Algorithm Save
- Dynamic Load Frequency Control of Microgrids with Diverse Distributed Energy Resources Save
- EFLSM:- An Intelligent Resource Manager for Fog Layer Service Management in Smart Cities Save
- Machine Learning Approach to Predicting Reliability in Healthcare Using Knowledge Engineering Save
- Syndrome Detection Unleashed: Computer Vision Applications in Neurogenetic Diagnoses Save
- A Residual Resource Fitness-Based Genetic Algorithm for a Fog-Level Virtual Machine Placement for Green Smart City Services Save
- An Energy Efficient Evolutionary Approach for Smart City-Based IoT Applications Save
- DRFS: Detecting Risk Factor of Stroke Disease from Social Media Using Machine Learning Techniques Save
- Epidemic Prediction using Machine Learning and Deep Learning Models on COVID-19 Data Save
- Seed: secure and energy efficient data-collection method for IoT network Save
- A Quasistraight Line Routing Protocol for Square Grid-Based Wireless Sensor Networks Save
- A lightweight device-level Public Key Infrastructure with DRAM based Physical Unclonable Function (PUF) for secure cyber physical systems Save
- A neuro evolutionary scheme for improved IoT energy efficiency in smart cities Save
- A virtual execution platform for OpenFlow controller using NFV Save
- Demand-Supply-Based Economic Model for Resource Provisioning in Industrial IoT Traffic Save
- Electronic User Authentication Key for Access to HMI/SCADA via Unsecured Internet Networks Save
- Enhanced method of ANN based model for detection of DDoS attacks on multimedia internet of things Save
- NCCLA: new caledonian crow learning algorithm based cluster head selection for Internet of Things in smart cities Save