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Wireless cognitive radio (CR) is a newly emerging paradigm that attempts to opportunistically transmit in licensed frequencies , without affecting the pre-assigned users of these bands. To enable this functionality, such a radio must predict its operational parameters, such as transmit power and spectrum. These tasks, collectively called spectrum management(More)
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving large-scale instances of classic multi-agent problems. We apply our techniques to the predator-prey pursuit problem. We first demonstrate that Kanerva Coding applied within a reinforcement learner(More)
The combination of hardware acceleration and flexibility make FPGAs important to image processing applications. There is also a need for efficient, flexible hardware/software codesign environments that can balance the benefits and costs of using FPGAs. Image processing applications often consist of a pipeline of components where each component applies a(More)
—Cloud computing nowadays becomes quite popular among a community of cloud users by offering a variety of resources. However, burstiness in user demands often dramatically degrades the application performance. In order to satisfy peak user demands and meet Service Level Agreement (SLA), efficient resource allocation schemes are highly demanded in the cloud.(More)
—Wireless mesh networks, composed of interconnected clusters of mesh router (MR) and multiple associated mesh clients (MCs), may use cognitive radio equipped transceivers, allowing them to choose licensed frequencies for high bandwidth communication. However, the protection of the licensed users in these bands is a key constraint. In this paper, we propose(More)
The LFW algorithm We consider the total weighted completion time scheduling problem for parallel identical machines and precedence constraints , Plprecl c w;C;. We describe a family of natural scheduling algorithms that optimally solve the single machine problem, and show that they can be used to achieve good $srform&ce for the multiple-machine problem.(More)
<italic>Since there is generally insufficient instruction level parallelism within a single basic block, higher performance is achieved by speculatively scheduling operations in superblocks. This is difficult in general because each branch competes for the processor's limited resources. Previous work manages the performance tradeoffs that exist between(More)