When metadata is distributed across many metadata servers in a distributed file system with a locality-preserving metadata distribution unit like a directory, simply increasing the number of metadata servers does not give high-aggregate performance for the metadata operation such as file creation. This paper proposes an effective and consistent method for processing metadata operations, at low ...

intraorganizational units play a critical role in km processes of acquiring, creating, exchanging, and utilizing knowledge assets. while much attention has been directed to effective knowledge strategies forsupporting organizational km processes, there is a lack of insightful research on knowledge strategy and its implementation at the work-unit level. this study examines two types of work unit...

irrigular land use, land degradation and increasing yield per surface area unit supplicate to be inevitable optimal land utilization.so land evaluation, planning and management to be necessary to achieve a sustainabledevelopment.following this trend, microleis (mediterranean land evaluation information system)has evolved towards an agro-ecological decision support system.the goal of this study ...

MapReduce and other Data-Intensive Scalable Computing paradigms have emerged as the most popular solution for processing massive data sets, a crucial task in surviving the “Data Deluge”. Recent works have shown that maintaining data locality is paramount to achieve high performance in such paradigms. To this end, suitable task assignment algorithms are needed. Current solutions use round-robin ...

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...

Demands for flexible processing have moved generalpurpose processing into the data path of networks. Processor schedulers have a great impact on the performance of these real-time systems. We present measurements that show that the workload of a network processor is highly regular and predictable. Processing time predictions, based on these measurements, can be used in scheduling together with ...

As the foundation for MapReduce processing, Hadoop is one of the fundamental technologies in big data analytics. Hadoop breaks up large data into data blocks, replicates them, and stores them in a distributed storage system. Data blocks can be placed in a machine where the data will be processed (data local), in a machine in the same rack (rack-local), or in a machine in a different rack (off-r...

The H.264/AVC standard provides high compression efficiency at the cost of increased computational complexity. As a consequence, dedicated hardware circuits are typically required for its most computationally intensive parts, such as the transform coding block that must support multiple transform operations: the 4× 4 forward and inverse integer DCT and the 4×4 and 2×2 Hadamard transforms. In th...

A recurrent problem posed by parallel processing architectures is that of communication latency. In this work, the latency problem is presented with special emphasis given to RISC based multiprocessors. An interprocessor communication model for parallel programs based on locality is presented. This model enables the programmer to manipulate locality at the language level and to take advantage o...