17 research outputs found

    Metric-locating-dominating sets of graphs for constructing related subsets of vertices

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    © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/A dominating set S of a graph is a metric-locating-dominating set if each vertex of the graph is uniquely distinguished by its distances from the elements of S , and the minimum cardinality of such a set is called the metric-location-domination number. In this paper, we undertake a study that, in general graphs and specific families, relates metric-locating-dominating sets to other special sets: resolving sets, dominating sets, locating-dominating sets and doubly resolving sets. We first characterize the extremal trees of the bounds that naturally involve metric-location-domination number, metric dimension and domination number. Then, we prove that there is no polynomial upper bound on the location-domination number in terms of the metric-location-domination number, thus extending a result of Henning and Oellermann. Finally, we show different methods to transform metric-locating-dominating sets into locating-dominating sets and doubly resolving sets. Our methods produce new bounds on the minimum cardinalities of all those sets, some of them concerning parameters that have not been related so farPeer ReviewedPostprint (author's final draft

    LIPIcs, Volume 258, SoCG 2023, Complete Volume

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    LIPIcs, Volume 258, SoCG 2023, Complete Volum

    LIPIcs, Volume 244, ESA 2022, Complete Volume

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    LIPIcs, Volume 244, ESA 2022, Complete Volum

    Fault Tolerant Task Mapping in Many-Core Systems

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    The advent of many-core systems, a network on chip containing hundreds or thousands of homogeneous processors cores, present new challenges in managing the cores effectively in response to processing demands, hardware faults and the need for heat management. Continually diminishing feature size of devices increase the probability of fabrication de- fects and the variability of performance of individual transistors. In many-core systems this can result in the failure of individual processing cores, routing nodes or communication links, which require the use of fault tolerant mechanisms. Diminishing feature size also increases the power density of devices, giving rise to the concept of dark silicon where only a portion of the functionality available on a chip can be active at any one time. Core fault tolerance and management of dark silicon can both be achieved by allocating a percentage of cores to be idle at any one time. Idle cores can be used as dark silicon to evenly distribute heat generated by processing cores and can also be used as spare cores to implement fault tolerance. Both of these can be achieved by the dynamic allocation of processes to tasks in response to changes to the status of hardware resources and the demands placed on the system, which in turn requires real time task mapping. This research proposes the use of a continuous fault/recovery cycle to implement graceful degradation and amelioration to provide real-time fault tolerance. Objective measures for core fault tolerance, link fault tolerance, network power and excess traffic have been developed for use by a multi-objective evolutionary algorithm that uses knowledge of the processing demands and hardware status to identify optimal task mappings. The fault/recovery cycle is shown to be effective in maintaining a high level of performance of a many-core array when presented with a series of hardware faults

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    27th Annual European Symposium on Algorithms: ESA 2019, September 9-11, 2019, Munich/Garching, Germany

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