8,519 research outputs found

    Combining link and content-based information in a Bayesian inference model for entity search

    No full text
    An architectural model of a Bayesian inference network to support entity search in semantic knowledge bases is presented. The model supports the explicit combination of primitive data type and object-level semantics under a single computational framework. A flexible query model is supported capable to reason with the availability of simple semantics in querie

    Run-time resource allocation for embedded Multiprocessor System-on-Chip using tree-based design space exploration

    Get PDF
    The dynamic nature of application workloads in modern MPSoC-based embedded systems is growing. To cope with the dynamism of application workloads at run time and to improve the efficiency of the underlying system architecture, this paper presents a novel run-time resource allocation algorithm for multimedia applications with the objective of minimizing energy consumption for predefined deadlines. This algorithm is based on a novel tree-based design space exploration (DSE) method, which is performed in two phases: design-time and run-time. During design time, application clustering is combined with the tree-based DSE, and after that, feature extraction and application classification is performed during run-time based on well-known machine learning techniques. We evaluated our algorithm using a heterogeneous MPSoC system with several applications that have different communication and computation behaviors. Our experimental results revealed that during runtime, more than 91% of the applications were classified correctly by our proposed algorithm to select the best resources for allocation. Therefore the results clearly confirm that our algorithm is effective

    Workflow Scheduling Techniques and Algorithms in IaaS Cloud: A Survey

    Get PDF
    In the modern era, workflows are adopted as a powerful and attractive paradigm for expressing/solving a variety of applications like scientific, data intensive computing, and big data applications such as MapReduce and Hadoop. These complex applications are described using high-level representations in workflow methods. With the emerging model of cloud computing technology, scheduling in the cloud becomes the important research topic. Consequently, workflow scheduling problem has been studied extensively over the past few years, from homogeneous clusters, grids to the most recent paradigm, cloud computing. The challenges that need to be addressed lies in task-resource mapping, QoS requirements, resource provisioning, performance fluctuation, failure handling, resource scheduling, and data storage. This work focuses on the complete study of the resource provisioning and scheduling algorithms in cloud environment focusing on Infrastructure as a service (IaaS). We provided a comprehensive understanding of existing scheduling techniques and provided an insight into research challenges that will be a possible future direction to the researchers
    • …
    corecore