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Timeout policy is an industry standard for dynamic power management (DPM), and thus is easy and safe to implement in many power-managed systems. The optimisation of timeout policy suffered from the lack of effective analytical model and fell in heuristic previously. This study presents an adaptive optimisation method for timeout DPM policy. First, a semi-Markov control processes model is introduced...
A class of resource location service for distributed VoD system, which combines one-hop k-random walk and global centralized indexing service, is studied. First, in order to minimizing the cost of communication and guaranteeing the response time performance, a Markov model is proposed to describe the queue phenomenon, admission control and the process of location. In this model, control is related...
Semi-Markov control problems with unknown kernel are considered, a reinforcement learning based online adaptive optimization algorithm is proposed. First an event-driven stochastic switching model is introduced to formulate the semi-Markov control problems. Then by utilizing the features of event-driven policy an optimization algorithm that combines policy gradient estimation and stochastic approximation...
Motivated by optimization of network communication systems, this paper presents an event-driven semi-Markov switching state-space control process with hierarchical dynamic architectures. First, the semi-Markov kernel of the switching control process is constructed, and the sensitivity formula for performance derivatives under average criterion is derived. Then, an online optimization algorithm that...
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