Abstract-Channel assignment was extensively researched for multi-radio wireless mesh networks, but still challenging when comes to implementation. In this paper we propose a semi-dynamic and distributed channel assignment called SICA based on the game theory formulation. To the best of our knowledge this is the first game formulation of channel assignment which takes the co-channel interference into account. SICA is an interference aware, distributed channel assignment which preserving the network connectivity without relaying on any common channel nor central node for coordination between mesh routers. SICA applies an on-line learner algorithm which assumes that nodes doesn't have perfect information. We have implemented SICA and compared against another interference-aware channel assignment proposed in the literature called Urban-X. Simulation results show that SICA outperforms Urban-X, even using less radio interfaces per node.

Channel assignment has been extensively researched for multi-radio wireless mesh networks, but it is still very challenging when it comes to its implementation. In this paper we propose a semi-dynamic and distributed channel assignment mechanism called SICA (Semidynamic Interference aware Channel Assignment) based on game theory formulation. SICA is an interference aware, distributed channel assignment which preserves the network connectivity without relying on a common channel nor central node for coordination between mesh routers. SICA applies a real time learner algorithm which assumes that nodes do not have perfect information about the network topology. To the best of our knowledge this is the first game formulation of channel assignment which takes the co-channel interference into account. We have simulated SICA and compared against other channel assignment mechanisms proposed in the literature. Simulation results show that SICA outperforms other mechanisms.

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In today's computer architectures, many scientific applications are considered to be memory bound. The memory wall, i.e. the large disparity between a processor's speed and the required time to access off-chip memory, is a yet-to-be-solved problem that can greatly reduce performance and make us underutilise the processors capabilities. Many different approaches have been proposed to tackle this problem, such as the addition of a large cache hierarchy, multithreading or speculative data prefetching. Most of these approaches rely on the prediction of the application's future behaviour, something that should not be necessary as this information is known by the programmer and is located in the application itself. Instead of designing hardware that attempts to guess the future, the goal should be to provide the programmer with the hardware support required to decide when the data is transferred and where is it transferred to. With this goal in mind, we introduce the Data Transfer Engine, a runtime-assisted, software prefetcher that exploits the information provided by the programmer in order to place data in the cache hierarchy close to the processor that will make use of it. The DTE can not only significantly reduce stall time due to cache misses but, more importantly, it allows us to design new computer architectures that are able to tolerate very high memory latencies.

In this paper, we address the channel assignment problem in a multi-radio mesh network that involves assigning channels to radio interfaces for eliminating the effect of wireless interference. Due to the insufficient number of frequency channels and available radios per node, interference is still present which limits the available bandwidth on wireless links and eventually decreases the achievable throughput. In this paper, we investigate the effect of considering the diverse delivery probability of the wireless links on the channel assignment solutions. We show that it is possible to classify the wireless links and omit some of them to benefit from a more diverse-channel solution. We propose a new channel assignment mechanism aiming to minimize the interference over high performance links. Finally, a performance study is carried out to assess the effectiveness of our proposed algorithm. Evaluations show that the multi-channel network obtained from our proposed algorithm achieves significant improvement in terms of reducing the interference and increasing the network capacity.