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Alagan Anpalagan
Researcher at Ryerson University
Publications - 489
Citations - 9573
Alagan Anpalagan is an academic researcher from Ryerson University. The author has contributed to research in topics: Cognitive radio & Wireless network. The author has an hindex of 41, co-authored 463 publications receiving 7375 citations. Previous affiliations of Alagan Anpalagan include Seneca College & University of Toronto.
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Efficient Energy Management for the Internet of Things in Smart Cities
TL;DR: A unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities and the energy harvesting in smart cities is provided, which is a promising solution for extending the lifetime of low-power devices and its related challenges.
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Opportunistic Spectrum Access in Cognitive Radio Networks: Global Optimization Using Local Interaction Games
TL;DR: It is shown that with the proposed games, global optimization is achieved with local information, specifically, the local altruistic game maximized the network throughput and the local congestion game minimizes the network collision level.
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Radio Resource Allocation Algorithms for the Downlink of Multiuser OFDM Communication Systems
TL;DR: No matter which optimization method is used, in both classes, the overall performance is improved with the increase in the number of users, due to multiuser diversity.
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Opportunistic Spectrum Access in Unknown Dynamic Environment: A Game-Theoretic Stochastic Learning Solution
TL;DR: This work proposes a stochastic learning automata (SLA) based channel selection algorithm, with which the secondary users learn from their individual action-reward history and adjust their behaviors towards a NE point, and investigates the achievable performance of the game in terms of system throughput and fairness.
Journal ArticleDOI
Optimization classification, algorithms and tools for renewable energy: A review
Muhammad Iqbal,Muhammad Azam,Muhammad Naeem,Muhammad Naeem,Ahmed Shaharyar Khwaja,Alagan Anpalagan +5 more
TL;DR: This paper presents a review of different optimization methods for deployment and operation of renewable energy sources based generating units, and presents different types of linear and non-linear optimization algorithms used in renewableEnergy sources.