SUMMARYData Grids are an emerging technology for managing large amounts of distributed data. This technology is highly anticipated by scientific communities, such as in the area of astronomy and high-energy physics, because their experiments generate massive amounts of data which need to be shared and analysed. Since it is not feasible to test different usages on real testbeds, it is easier to use simulations as a means of studying complex scenarios. This paper presents our work on incorporating data Grids features as an extension to GridSim, a computational Grid simulator. The extension provides essential building blocks for simulating various data Grids scenarios. Moreover, it is designed to be easily extended. This approach makes it easy to try various strategies and to add functionalities to suit the needs of other communities. This paper also gives a detailed description of the design and usage examples demonstrating the versatility of this tool.

Hardware multithreading is becoming a generally applied technique in the next generation of microprocessors. Several multithreaded processors are announced by industry or already into production in the areas of high-performance microprocessors, media, and network processors.A multithreaded processor is able to pursue two or more threads of control in parallel within the processor pipeline. The contexts of two or more threads of control are often stored in separate on-chip register sets. Unused instruction slots, which arise from latencies during the pipelined execution of single-threaded programs by a contemporary microprocessor, are filled by instructions of other threads within a multithreaded processor. The execution units are multiplexed between the thread contexts that are loaded in the register sets.Underutilization of a superscalar processor due to missing instruction-level parallelism can be overcome by simultaneous multithreading, where a processor can issue multiple instructions from multiple threads each cycle. Simultaneous multithreaded processors combine the multithreading technique with a wide-issue superscalar processor to utilize a larger part of the issue bandwidth by issuing instructions from different threads simultaneously.Explicit multithreaded processors are multithreaded processors that apply processes or operating system threads in their hardware thread slots. These processors optimize the throughput of multiprogramming workloads rather than single-thread performance. We distinguish these processors from implicit multithreaded processors that utilize thread-level speculation by speculatively executing compiler- or machine-generated threads of control that are part of a single sequential program.This survey paper explains and classifies the explicit multithreading techniques in research and in commercial microprocessors.

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We present a polynomial time heuristic algorithm for the minimum dominating set problem. The algorithm can readily be used for solving the minimum α -all-neighbor dominating set problem and the minimum set cover problem. We apply the algorithm in heuristic solving the minimum k-center problem in polynomial time. Using a standard set of 40 test problems we experimentally show that our k-center algorithm performs much better than other well-known heuristics and is competitive with the best known (non-polynomial time) algorithms for solving the k-center problem in terms of average quality and deviation of the results as well as the execution time.