A new approach for energy and delay trade-off intra-clustering routing in WSNs. - Amin Shahraki; Marjan Kuchaki Rafsanjani; Arsham Borumand Saeid (Comput. Math. Appl., 2011)

QARIMA: A new approach to prediction in queue theory. - Marjan Kuchaki Rafsanjani; Atieh Rezaei; Amin Shahraki; Arsham Borumand Saeid (Appl. Math. Comput., 2014)

Last significant trend change detection method for offline poisson distribution datasets. - Amin Shahraki; Hamed Taherzadeh; Øystein Haugen (ISNCC, 2017)

Hierarchical distributed management clustering protocol for wireless sensor networks. - Amin Shahraki; Marjan Kuchaki Rafsanjani; Arsham Borumand Saeid (Telecommun. Syst., 2017)

Social ethics in Internet of Things: An outline and review. - Amin Shahraki; Øystein Haugen (ICPS, 2018)

A Review on the effects of IoT and Smart Cities Technologies on Urbanism. - Amin Shahraki; Delaram Khojasteh Kaffash; Øystein Haugen (SEEDA-CECNSM, 2018)

An Outlier Detection Method to Improve Gathered Datasets for Network Behavior Analysis in IoT. - Amin Shahraki; Øystein Haugen (J. Commun., 2019)

A distributed Front-end Edge node assessment model by using Fuzzy and a learning-to-rank method-machine learning. - Marius Geitle; Amin Shahraki (IEEE DataPort, 2019)

A distributed Front-end Edge node assessment model by using Fuzzy and a learning-to-rank method. - Amin Shahraki (IEEE DataPort, 2019)

A distributed Fog node assessment model by using Fuzzy rules learned by XGBoost. - Amin Shahraki; Marius Geitle (IEEE DataPort, 2019)

Clustering objectives in wireless sensor networks: A survey and research direction analysis. - Amin Shahraki; Amir Taherkordi; Øystein Haugen; Frank Eliassen (Comput. Networks, 2020)

Boosting algorithms for network intrusion detection: A comparative evaluation of Real AdaBoost, Gentle AdaBoost and Modest AdaBoost. - Amin Shahraki; Mahmoud Abbasi; Øystein Haugen (Eng. Appl. Artif. Intell., 2020)

A comparative node evaluation model for highly heterogeneous massive-scale Internet of Things-Mist networks. - Amin Shahraki; Marius Geitle; Øystein Haugen (Trans. Emerg. Telecommun. Technol., 2020)

Internet Traffic Classification Using an Ensemble of Deep Convolutional Neural Networks. - Amin Shahraki; Mahmoud Abbasi; Amir Taherkordi; Mohammed Kaosar (FlexNets@SIGCOMM, 2021)

Synchronization Techniques in "Device to Device- and Vehicle to Vehicle-Enabled" Cellular Networks: A survey. - Mahmoud Abbasi; Amin Shahraki; Hamid R. Barzegar; Claus Pahl (Comput. Electr. Eng., 2021)

TONTA: Trend-based Online Network Traffic Analysis in ad-hoc IoT networks. - Amin Shahraki; Amir Taherkordi; Øystein Haugen (Comput. Networks, 2021)

Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A Survey. - Mahmoud Abbasi; Amin Shahraki; Amir Taherkordi (Comput. Commun., 2021)

A Comprehensive Survey on 6G Networks: Applications, Core Services, Enabling Technologies, and Future Challenges. - Amin Shahraki; Mahmoud Abbasi; Md. Jalil Piran; Mingzhe Chen; Shuguang Cui (CoRR, 2021)

Active Learning for Network Traffic Classification: A Technical Survey. - Amin Shahraki; Mahmoud Abbasi; Amir Taherkordi; Anca Delia Jurcut (CoRR, 2021)

Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey. - Mahmoud Abbasi; Amin Shahraki; Md. Jalil Piran; Amir Taherkordi (Eng. Appl. Artif. Intell., 2021)

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms. - Amin Shahraki; Amir Taherkordi; Øystein Haugen; Frank Eliassen (IEEE Trans. Netw. Serv. Manag., 2021)

FLITC: A Novel Federated Learning-Based Method for IoT Traffic Classification. - Mahmoud Abbasi; Amir Taherkordi; Amin Shahraki (SMARTCOMP, 2022)

A comparative study on online machine learning techniques for network traffic streams analysis. - Amin Shahraki; Mahmoud Abbasi; Amir Taherkordi; Anca Delia Jurcut (Comput. Networks, 2022)

From statistical- to machine learning-based network traffic prediction. - Iraj Lohrasbinasab; Amin Shahraki; Amir Taherkordi; Anca Delia Jurcut (Trans. Emerg. Telecommun. Technol., 2022)

Active Learning for Network Traffic Classification: A Technical Study. - Amin Shahraki; Mahmoud Abbasi; Amir Taherkordi; Anca Delia Jurcut (IEEE Trans. Cogn. Commun. Netw., 2022)

DCServCG: A data-centric service code generation using deep learning. - Zakieh Alizadehsani; Hadi Ghaemi; Amin Shahraki; Alfonso González-Briones; Juan M. Corchado (Eng. Appl. Artif. Intell., 2023)

When machine learning meets Network Management and Orchestration in Edge-based networking paradigms. - Amin Shahraki; Torsten Ohlenforst; Felix Kreyß (J. Netw. Comput. Appl., 2023)

Industrial data monetization: A blockchain-based industrial IoT data trading system. - Mahmoud Abbasi; Javier Prieto 001; Amin Shahraki; Juan M. Corchado (Internet Things, 2023)

Automated Testing and Virtual Commissioning of Automation Networks. - Dirk Schulz 002; Amin Shahraki (CAMAD, 2024)

AMbit: An Efficient Pruning Technique in Federated Learning for Edge Computing Systems. - Emad Hammami; Peiyuan Guan; Amir Taherkordi; Amin Shahraki; Dapeng Lan (ICFEC, 2024)

Transformers in source code generation: A comprehensive survey. - Hadi Ghaemi; Zakieh Alizadehsani; Amin Shahraki; Juan M. Corchado (J. Syst. Archit., 2024)

How Low Can You Go? Revisiting (S)NTP Time Synchronization for Industrial Networks. - Steffen Lindner; Amin Shahraki; Dirk Schulz 002 (WFCS, 2025)

Class Imbalance in Network Traffic Classification: An Adaptive Weight Ensemble-of-Ensemble Learning Method. - Mahmoud Abbasi; Sebastián López Flórez; Amin Shahraki; Amir Taherkordi; Javier Prieto 001; Juan M. Corchado (IEEE Access, 2025)

A new approach on self-adaptive trust management for social Internet of Things. - Elham Moeinaddini; Eslam Nazemi; Amin Shahraki (Comput. Networks, 2025)