582 research outputs found

    Optimal Memoryless Encoding for Low Power Off-Chip Data Buses

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    Off-chip buses account for a significant portion of the total system power consumed in embedded systems. Bus encoding schemes have been proposed to minimize power dissipation, but none has been demonstrated to be optimal with respect to any measure. In this paper, we give the first provably optimal and explicit (polynomial-time constructible) families of memoryless codes for minimizing bit transitions in off-chip buses. Our results imply that having access to a clock does not make a memoryless encoding scheme that minimizes bit transitions more powerful.Comment: Proceedings of the 2006 IEEE/ACM international Conference on Computer-Aided Design (San Jose, California, November 05 - 09, 2006). ICCAD '06. ACM, New York, NY, 369-37

    Locating one pairwise interaction: Three recursive constructions

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    In a complex component-based system, choices (levels) for components (factors) may interact to cause faults in the system behaviour. When faults may be caused by interactions among few factors at specific levels, covering arrays provide a combinatorial test suite for discovering the presence of faults. While well studied, covering arrays do not enable one to determine the specific levels of factors causing the faults; locating arrays ensure that the results from test suite execution suffice to determine the precise levels and factors causing faults, when the number of such causes is small. Constructions for locating arrays are at present limited to heuristic computational methods and quite specific direct constructions. In this paper three recursive constructions are developed for locating arrays to locate one pairwise interaction causing a fault

    Screening interacting factors in a wireless network testbed using locating arrays

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    Wireless systems exhibit a wide range of configurable parameters (factors), each with a number of values (levels), that may influence performance. Exhaustively analyzing all factor interactions is typically not feasible in experimental systems due to the large design space. We propose a method for determining which factors play a significant role in wireless network performance with multiple performance metrics (response variables). Such screening can be used to reduce the set of factors in subsequent experimental testing, whether for modelling or optimization. Our method accounts for pairwise interactions between the factors when deciding significance, because interactions play a significant role in real-world systems. We utilize locating arrays to design the experiment because they guarantee that each pairwise interaction impacts a distinct set of tests. We formulate the analysis as a problem in compressive sensing that we solve using a variation of orthogonal matching pursuit, together with statistical methods to determine which factors are significant. We evaluate the method using data collected from the w-iLab.t Zwijnaarde wireless network testbed and construct a new experiment based on the first analysis to validate the results. We find that the analysis exhibits robustness to noise and to missing data

    The chromatic index of cyclic Steiner 2-designs

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    The number of colours needed to colour the blocks of a cyclic Steiner 2-design S(2,k,v) is at most v

    Locating and Detecting Arrays for Interaction Faults

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    The identification of interaction faults in component-based systems has focused on indicating the presence of faults, rather than their location and magnitude. While this is a valuable step in screening a system for interaction faults prior to its release, it provides little information to assist in the correction of such faults. Consequently tests to reveal the location of interaction faults are of interest. The problem of nonadaptive location of interaction faults is formalized under the hypothesis that the system contains (at most) some number d of faults, each involving (at most) some number t of interacting factors. Restrictions on the number and size of the putative faults lead to numerous variants of the basic problem. The relationships between this class of problems and interaction testing using covering arrays to indicate the presence of faults, designed experiments to measure and model faults, and combinatorial group testing to locate faults in a more general testing scenario, are all examined. While each has some definite similarities with the fault location problems for component-based systems, each has some striking differences as well. In this paper, we formulate the combinatorial problems for locating and detecting arrays to undertake interaction fault location. Necessary conditions for existence are established, and using a close connection to covering arrays, asymptotic bounds on the size of minimal locating and detecting arrays are established. A final version of this paper appears in J Comb Optim (2008) 15: 17-48
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