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Real-time systems have to complete the execution of a task within the predetermined time while ensuring that the execution results are logically correct. Such systems require scheduling methods that can adequately distribute the given tasks to a processor. Scheduling methods that all tasks can be executed within a predetermined deadline are called an optimal scheduling. In this paper, we propose a...
Context data is important information for the behaviors of the applications in a pervasive space. To effectively restore huge amount of data, tree-liked layered storage architecture are proposed, where the leaf nodes collect the data from the sensing devices located in its domain. However, the sensing devices may be moving among different domains. In order to integrate the data from the same device,...
A new parallel programming framework for DNA sequence alignment in homogeneous multi-core processor architectures is proposed. Contrasting with traditional coarse-grained parallel approaches, that divide the considered database in several smaller subsets of complete sequences to be aligned with the query sequence, the presented methodology is based on a slicing procedure of both the query and the...
In public display systems determine what to present and when is a central feature. Although several adaptive scheduling alternatives have been explored, which introduce sensibility of the display to some type of external variable, they are still very dependent on the user in their behavior, content specific in their nature and very rigid in their adaptation to their social environment, not providing...
Location and manipulation of complex data is a difficult, challenging task in nowadays extremely complex IT systems and on the Internet, overwhelmed with a huge amount of information that develops and grows rapidly. In this paper, we propose a self-organizing approach that combines purely decentralized unstructured P2P with space based computing in order to locate effectively and filter (retrieve)...
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