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Mohsen Nickray
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2020 – today
- 2024
- [j15]Atousa Daghayeghi, Mohsen Nickray:
Decentralized computation offloading via multi-agent deep reinforcement learning for NOMA-assisted mobile edge computing with energy harvesting devices. J. Syst. Archit. 151: 103139 (2024) - [j14]Atousa Daghayeghi, Mohsen Nickray:
Delay-Aware and Energy-Efficient Task Scheduling Using Strength Pareto Evolutionary Algorithm II in Fog-Cloud Computing Paradigm. Wirel. Pers. Commun. 138(1): 409-457 (2024) - 2023
- [j13]Entesar Hosseini, Mohsen Nickray, Shamsollah Ghanbari:
Energy-efficient scheduling based on task prioritization in mobile fog computing. Computing 105(1): 187-215 (2023) - 2022
- [j12]Entesar Hosseini, Mohsen Nickray, Shamsollah Ghanbari:
Optimized task scheduling for cost-latency trade-off in mobile fog computing using fuzzy analytical hierarchy process. Comput. Networks 206: 108752 (2022) - 2021
- [j11]Ahmad Sharif, Mohsen Nickray, Ali Shahidinejad:
Energy-efficient fault-tolerant scheduling in a fog-based smart monitoring application. Int. J. Ad Hoc Ubiquitous Comput. 36(1): 32-49 (2021) - [j10]Mahboobe Rezaei, Hamed Noori, Mohsen Mohammadkhani Razlighi, Mohsen Nickray:
ReFOCUS+: Multi-Layers Real-Time Intelligent Route Guidance System With Congestion Detection and Avoidance. IEEE Trans. Intell. Transp. Syst. 22(1): 50-63 (2021) - 2020
- [j9]Pegah Gazori, Dadmehr Rahbari, Mohsen Nickray:
Saving time and cost on the scheduling of fog-based IoT applications using deep reinforcement learning approach. Future Gener. Comput. Syst. 110: 1098-1115 (2020) - [j8]Ahmad Sharif, Mohsen Nickray, Ali Shahidinejad:
Fault-tolerant with load balancing scheduling in a fog-based IoT application. IET Commun. 14(16): 2646-2657 (2020) - [j7]Ali Mohsenzadeh, Mohsen Nickray, Amir Jalaly Bidgoly, Yaghoub Farjami:
A new task scheduling mechanism in grid computing using trust model. Multiagent Grid Syst. 16(2): 135-152 (2020) - [j6]Dadmehr Rahbari, Mohsen Nickray:
Task offloading in mobile fog computing by classification and regression tree. Peer-to-Peer Netw. Appl. 13(1): 104-122 (2020)
2010 – 2019
- 2019
- [j5]Gholamreza Heydari, Dadmehr Rahbari, Mohsen Nickray:
Energy saving scheduling in a fog-based IoT application by Bayesian taskclassification approach. Turkish J. Electr. Eng. Comput. Sci. 27(6): 4167-4187 (2019) - [j4]Mohammad Moein Fazeli, Yaghoub Farjami, Mohsen Nickray:
An ensemble optimisation approach to service composition in cloud manufacturing. Int. J. Comput. Integr. Manuf. 32(1): 83-91 (2019) - 2018
- [j3]Elham Mirzavand Borujeni, Dadmehr Rahbari, Mohsen Nickray:
Fog-based energy-efficient routing protocol for wireless sensor networks. J. Supercomput. 74(12): 6831-6858 (2018) - 2017
- [c6]Sabihe Kabirzadeh, Dadmehr Rahbari, Mohsen Nickray:
A hyper heuristic algorithm for scheduling of fog networks. FRUCT 2017: 148-155 - [c5]Dadmehr Rahbari, Mohsen Nickray:
Scheduling of fog networks with optimized knapsack by symbiotic organisms search. FRUCT 2017: 278-283 - 2015
- [j2]Mohsen Nickray, Ali Afzali-Kusha, Riku Jäntti:
Simultaneous power control and power management algorithm with sector-shaped topology for wireless sensor networks. EURASIP J. Wirel. Commun. Netw. 2015: 118 (2015) - 2012
- [j1]Mohsen Nickray, Ali Afzali-Kusha, Riku Jäntti:
MEA: an energy efficient algorithm for dense sector-based wireless sensor networks. EURASIP J. Wirel. Commun. Netw. 2012: 85 (2012) - [c4]Vahid Naghshin, Behrouz Maham, Walid Saad, Mohsen Nickray:
Lifetime maximization in cluster-based outage-restricted wireless sensor networks. SPAWC 2012: 369-373 - 2010
- [c3]Mohsen Nickray, Ali Afzali-Kusha:
ATC - An Asymmetric Topology Control Algorithm for Heterogeneous Wireless Sensor Networks. WINSYS 2010: 75-81
2000 – 2009
- 2006
- [c2]Masood Deh-Yadegari, Mohsen Nickray, Ali Afzali-Kusha, Zainalabedin Navabi:
A New Protocol Stack Model for Network on Chip. ISVLSI 2006: 440-441 - 2005
- [c1]Mohsen Nickray, Masoud Dehyadegari, Ali Afzali-Kusha:
Power and delay optimization for network on chip. ECCTD 2005: 273-276
Coauthor Index
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last updated on 2024-10-02 21:41 CEST by the dblp team
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