2 citations · 4 across the 8 of their papers we have counts for
9 papers
Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach
Wang Wumian, Sajal Saha, Anwar Haque +1
Traffic routing is vital for the proper functioning of the Internet. As users and network traffic increase, researchers try to develop adaptive and intelligent routing algorithms t…
Overcoming Data Limitations in Internet Traffic Forecasting: LSTM Models with Transfer Learning and Wavelet Augmentation
Sajal Saha, Anwar Haque, Greg Sidebottom
Effective internet traffic prediction in smaller ISP networks is challenged by limited data availability. This paper explores this issue using transfer learning and data augmentati…
ConvLSTMTransNet: A Hybrid Deep Learning Approach for Internet Traffic Telemetry
Sajal Saha, Saikat Das, Glaucio H. S. Carvalho
In this paper, we present a novel hybrid deep learning model, named ConvLSTMTransNet, designed for time series prediction, with a specific application to internet traffic telemetry…
An Adaptive End-to-End IoT Security Framework Using Explainable AI and LLMs
Sudipto Baral, Sajal Saha, Anwar Haque
The exponential growth of the Internet of Things (IoT) has significantly increased the complexity and volume of cybersecurity threats, necessitating the development of advanced, sc…
DEK-Forecaster: A Novel Deep Learning Model Integrated with EMD-KNN for Traffic Prediction
Sajal Saha, Sudipto Baral, Anwar Haque
Internet traffic volume estimation has a significant impact on the business policies of the ISP (Internet Service Provider) industry and business successions. Forecasting the inter…
Transfer Learning Based Efficient Traffic Prediction with Limited Training Data
Sajal Saha, Anwar Haque, Greg Sidebottom
Efficient prediction of internet traffic is an essential part of Self Organizing Network (SON) for ensuring proactive management. There are many existing solutions for internet tra…
Wavelet-Based Hybrid Machine Learning Model for Out-of-distribution Internet Traffic Prediction
Sajal Saha, Anwar Haque, Greg Sidebottom
Efficient prediction of internet traffic is essential for ensuring proactive management of computer networks. Nowadays, machine learning approaches show promising performance in mo…
Deep Sequence Modeling for Anomalous ISP Traffic Prediction
Sajal Saha, Anwar Haque, Greg Sidebottom
Internet traffic in the real world is susceptible to various external and internal factors which may abruptly change the normal traffic flow. Those unexpected changes are considere…
An Empirical Study on Internet Traffic Prediction Using Statistical Rolling Model
Sajal Saha, Anwar Haque, Greg Sidebottom
Real-world IP network traffic is susceptible to external and internal factors such as new internet service integration, traffic migration, internet application, etc. Due to these f…