M
Mehdi Bennis
Researcher at University of Oulu
Publications - 642
Citations - 37644
Mehdi Bennis is an academic researcher from University of Oulu. The author has contributed to research in topics: Computer science & Wireless network. The author has an hindex of 68, co-authored 569 publications receiving 25361 citations. Previous affiliations of Mehdi Bennis include Kyung Hee University & Nokia Networks.
Papers
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Journal ArticleDOI
Fronthaul-Aware Software-Defined Wireless Networks: Resource Allocation and User Scheduling
TL;DR: In this paper, a two-timescale fronthaul-aware SDN control mechanism is proposed in which the controller maximizes the time-averaged network throughput by enforcing a coarse correlated equilibrium in the long timescale.
Proceedings ArticleDOI
An Oblivious Game-Theoretic Approach for Wireless Scheduling in V2V Communications
TL;DR: The decision making process at each service request is transformed into a single-agent Markov decision process, for which an on-line auction based learning scheme is proposed, in terms of per-service request average utility.
Posted Content
Remote UAV Online Path Planning via Neural Network Based Opportunistic Control
TL;DR: Simulations corroborate the effectiveness of oHJB in reducing the UAV’s travel time and energy by utilizing the trade-off between uploading delays and control robustness in poor channel conditions.
Posted Content
Dynamic Clustering and User Association in Wireless Small Cell Networks with Social Considerations
TL;DR: In this paper, a novel social network-aware user association in wireless small cell networks with underlaid device-to-device (D2D) communication is investigated, which exploits social strategic relationships between user equipments (UEs) and their physical proximity to optimize the overall network performance.
Proceedings ArticleDOI
Maximum Allowable Transfer Interval Aware Scheduling for Wireless Remote Monitoring
TL;DR: This paper tackles the problem of remote monitoring in which a number of sensor nodes are transmitting time sensitive measurements to a remote monitoring site and uses the Lyapunov stochastic optimization framework to solve the relaxed problem.