26,093 research outputs found

    Exploiting non-constant safe memory in resilient algorithms and data structures

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    We extend the Faulty RAM model by Finocchi and Italiano (2008) by adding a safe memory of arbitrary size SS, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the safe memory. Let ÎŽ\delta and α\alpha denote, respectively, the maximum amount of faults which can happen during the execution of an algorithm and the actual number of occurred faults, with α≀Ύ\alpha \leq \delta. We propose a resilient algorithm for sorting nn entries which requires O(nlog⁥n+α(ÎŽ/S+log⁥S))O\left(n\log n+\alpha (\delta/S + \log S)\right) time and uses Θ(S)\Theta(S) safe memory words. Our algorithm outperforms previous resilient sorting algorithms which do not exploit the available safe memory and require O(nlog⁥n+αΎ)O\left(n\log n+ \alpha\delta\right) time. Finally, we exploit our sorting algorithm for deriving a resilient priority queue. Our implementation uses Θ(S)\Theta(S) safe memory words and Θ(n)\Theta(n) faulty memory words for storing nn keys, and requires O(log⁥n+ÎŽ/S)O\left(\log n + \delta/S\right) amortized time for each insert and deletemin operation. Our resilient priority queue improves the O(log⁥n+ÎŽ)O\left(\log n + \delta\right) amortized time required by the state of the art.Comment: To appear in Theoretical Computer Science, 201

    On the Error Resilience of Ordered Binary Decision Diagrams

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    Ordered Binary Decision Diagrams (OBDDs) are a data structure that is used in an increasing number of fields of Computer Science (e.g., logic synthesis, program verification, data mining, bioinformatics, and data protection) for representing and manipulating discrete structures and Boolean functions. The purpose of this paper is to study the error resilience of OBDDs and to design a resilient version of this data structure, i.e., a self-repairing OBDD. In particular, we describe some strategies that make reduced ordered OBDDs resilient to errors in the indexes, that are associated to the input variables, or in the pointers (i.e., OBDD edges) of the nodes. These strategies exploit the inherent redundancy of the data structure, as well as the redundancy introduced by its efficient implementations. The solutions we propose allow the exact restoring of the original OBDD and are suitable to be applied to classical software packages for the manipulation of OBDDs currently in use. Another result of the paper is the definition of a new canonical OBDD model, called {\em Index-resilient Reduced OBDD}, which guarantees that a node with a faulty index has a reconstruction cost O(k)O(k), where kk is the number of nodes with corrupted index

    Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

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    © 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

    Bridging topological and functional information in protein interaction networks by short loops profiling

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    Protein-protein interaction networks (PPINs) have been employed to identify potential novel interconnections between proteins as well as crucial cellular functions. In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins. We compared 30 PPINs with corresponding randomised null models and examined the occurrence of common biological functions in loops extracted from a cross-validated high-confidence dataset of 622 human protein complexes. We demonstrate that loops are an intrinsic feature of PPINs and that specific cell functions are predominantly performed by loops of different lengths. Topologically, we find that loops are strongly related to the accuracy of PPINs and define a core of interactions with high resilience. The identification of this core and the analysis of loop composition are promising tools to assess PPIN quality and to uncover possible biases from experimental detection methods. More than 96% of loops share at least one biological function, with enrichment of cellular functions related to mRNA metabolic processing and the cell cycle. Our analyses suggest that these motifs can be used in the design of targeted experiments for functional phenotype detection.This research was supported by the Biotechnology and Biological Sciences Research Council (BB/H018409/1 to AP, ACCC and FF, and BB/J016284/1 to NSBT) and by the Leukaemia & Lymphoma Research (to NSBT and FF). SSC is funded by a Leukaemia & Lymphoma Research Gordon Piller PhD Studentship

    A Conflict-Resilient Lock-Free Calendar Queue for Scalable Share-Everything PDES Platforms

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    Emerging share-everything Parallel Discrete Event Simulation (PDES) platforms rely on worker threads fully sharing the workload of events to be processed. These platforms require efficient event pool data structures enabling high concurrency of extraction/insertion operations. Non-blocking event pool algorithms are raising as promising solutions for this problem. However, the classical non-blocking paradigm leads concurrent conflicting operations, acting on a same portion of the event pool data structure, to abort and then retry. In this article we present a conflict-resilient non-blocking calendar queue that enables conflicting dequeue operations, concurrently attempting to extract the minimum element, to survive, thus improving the level of scalability of accesses to the hot portion of the data structure---namely the bucket to which the current locality of the events to be processed is bound. We have integrated our solution within an open source share-everything PDES platform and report the results of an experimental analysis of the proposed concurrent data structure compared to some literature solutions

    Bloom Filters in Adversarial Environments

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    Many efficient data structures use randomness, allowing them to improve upon deterministic ones. Usually, their efficiency and correctness are analyzed using probabilistic tools under the assumption that the inputs and queries are independent of the internal randomness of the data structure. In this work, we consider data structures in a more robust model, which we call the adversarial model. Roughly speaking, this model allows an adversary to choose inputs and queries adaptively according to previous responses. Specifically, we consider a data structure known as "Bloom filter" and prove a tight connection between Bloom filters in this model and cryptography. A Bloom filter represents a set SS of elements approximately, by using fewer bits than a precise representation. The price for succinctness is allowing some errors: for any x∈Sx \in S it should always answer `Yes', and for any x∉Sx \notin S it should answer `Yes' only with small probability. In the adversarial model, we consider both efficient adversaries (that run in polynomial time) and computationally unbounded adversaries that are only bounded in the number of queries they can make. For computationally bounded adversaries, we show that non-trivial (memory-wise) Bloom filters exist if and only if one-way functions exist. For unbounded adversaries we show that there exists a Bloom filter for sets of size nn and error Δ\varepsilon, that is secure against tt queries and uses only O(nlog⁥1Δ+t)O(n \log{\frac{1}{\varepsilon}}+t) bits of memory. In comparison, nlog⁥1Δn\log{\frac{1}{\varepsilon}} is the best possible under a non-adaptive adversary

    Actors vs Shared Memory: two models at work on Big Data application frameworks

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    This work aims at analyzing how two different concurrency models, namely the shared memory model and the actor model, can influence the development of applications that manage huge masses of data, distinctive of Big Data applications. The paper compares the two models by analyzing a couple of concrete projects based on the MapReduce and Bulk Synchronous Parallel algorithmic schemes. Both projects are doubly implemented on two concrete platforms: Akka Cluster and Managed X10. The result is both a conceptual comparison of models in the Big Data Analytics scenario, and an experimental analysis based on concrete executions on a cluster platform

    Open-Source Telemedicine Platform for Wireless Medical Video Communication

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    An m-health system for real-time wireless communication of medical video based on open-source software is presented. The objective is to deliver a low-cost telemedicine platform which will allow for reliable remote diagnosis m-health applications such as emergency incidents, mass population screening, and medical education purposes. The performance of the proposed system is demonstrated using five atherosclerotic plaque ultrasound videos. The videos are encoded at the clinically acquired resolution, in addition to lower, QCIF, and CIF resolutions, at different bitrates, and four different encoding structures. Commercially available wireless local area network (WLAN) and 3.5G high-speed packet access (HSPA) wireless channels are used to validate the developed platform. Objective video quality assessment is based on PSNR ratings, following calibration using the variable frame delay (VFD) algorithm that removes temporal mismatch between original and received videos. Clinical evaluation is based on atherosclerotic plaque ultrasound video assessment protocol. Experimental results show that adequate diagnostic quality wireless medical video communications are realized using the designed telemedicine platform. HSPA cellular networks provide for ultrasound video transmission at the acquired resolution, while VFD algorithm utilization bridges objective and subjective ratings
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