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Reinforcement learning algorithms are a powerful machine learning technique. However, much of the work on these algorithms has been developed with regard to discrete nite-state Markovian problems, which is too restrictive for many real-world environments. Therefore, it is desirable to extend these methods to high dimensional continuous state-spaces, which(More)
— Hybrid Cloud offers small business customers the flexibility of a cloud-based solution with the security of a locally housed server. The customer's data is stored on the New Hybrid Cloud Server, and the New Hybrid Cloud Server is located at the customer's site, but is managed remotely. A style of computing where massively scalable (and elastic) IT-related(More)
In this paper, we propose an adaptive contention-based MAC scheduling scheme called Multi-channel Contention-based TDMA (MC/TDMA) for Multichannel wireless networks which provides proportional service differentiation while achieving high resource utilization. The MC/TDMA scheme adaptively schedules the traffic over multiple non-overlapping channels by(More)
In this paper, we propose multi-channel time division multiple access (MC/TDMA) scheme which provides proportional service differentiation while achieving high throughput in a multichannel wireless network. Proportional service differentiation is achieved by scheduling traffic over multiple non- overlapping channels using the modified open-shop scheduling(More)
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