Publication

Abstract : Parallel Programming (PP) used to be an area is confined to scientific and cloud computing applications. However, with the proliferation of multicore processors, parallel programming has definitely become a mainstream of concern. To satisfy the requirement, one can leverage multi-core architectures to parallelize traffic monitoring so as to progress information processing capabilities over traditional uni-processor architectures. In this paper an effective scheduling framework for multi-core processors that strike a balance between control over the system and an effective network traffic control mechanism for high-performance computing is proposed. In the proposed Cache Fair Thread Scheduling (CFTS), information supplied by the user to guide threads scheduling and also, where necessary, gives the programmer fine control over thread placement. For this wait-free data structure are applied in lieu of conventional lock-based methods for accessing internal scheduler structure, alleviating to some extent serialization and hence the degree of contention. Cloud computing has recently received considerable attention, as a promising approach for delivering network traffic services by improving the utilization of data centre resources. The primary goal of scheduling framework is to improve application throughput and overall system utilization in cloud applications. The resultant aim of the framework is to improve fairness so that each thread continues to make good forward progress. The experimental results show that the parallel CFTS-WF could not only increase the processing rate, but also keep a well performance on stability which is important for cloud computing. This makes, it an effective network traffic control mechanism for cloud computing.