A Hybrid Neuro–Wavelet Predictor for QoS Control and Stability

Napoli, Christian; Pappalardo, Giuseppe; Tramontana, Emiliano

doi:10.1007/978-3-319-03524-6_45

Cited by 22 publications

(17 citation statements)

References 30 publications

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“…The properties of this network (Napoli et al, 2013) starting from an input at a time step τ n , to predict how rare fragments will be at a time step τ n+r . In this way, the RNN acts like a functional…”

Section: Proposed Multiscale Neural Predictormentioning

confidence: 99%

A mathematical model for file fragment diffusion and a neural predictor to manage priority queues over BitTorrent

Napoli

Pappalardo

Tramontana

2016

International Journal of Applied Mathematics and Computer Science

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BitTorrent splits the files that are shared on a P2P network into fragments and then spreads these by giving the highest priority to the rarest fragment. We propose a mathematical model that takes into account several factors such as the peer distance, communication delays, and file fragment availability in a future period also by using a neural network module designed to model the behaviour of the peers. The ensemble comprising the proposed mathematical model and a neural network provides a solution for choosing the file fragments that have to be spread first, in order to ensure their continuous availability, taking into account that some peers will disconnect.

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Section: Proposed Multiscale Neural Predictormentioning

confidence: 99%

A mathematical model for file fragment diffusion and a neural predictor to manage priority queues over BitTorrent

Napoli

Pappalardo

Tramontana

2016

International Journal of Applied Mathematics and Computer Science

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“…They are either used alone, as in the case of the Agile system [96], or in conjunction with ANN in a recent work by Napoli et al [97].…”

Section: Elastic Scaling In Dtm Systemsmentioning

confidence: 99%

Self-tuning in Distributed Transactional Memory

Couceiro

Didona

Rodrı́gues

et al. 2015

Transactional Memory. Foundations, Algorithms, Tools, and Applications

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Many different mechanisms have been developed to implement Distributed Transactional Memory (DTM). Unfortunately, there is no "one-size-fits-all" design that offers the desirable performance across all possible workloads and scales. In fact, the performance of these mechanisms is affected by a number of intertwined factors that make it hard, or even impossible, to statically configure a DTM platform for optimal performance. These observations have motivated the emergence of self-tuning schemes for automatically adapting the algorithms and parameters used by the main building blocks of DTM systems. This chapter surveys existing research in the area of autonomic DTM design, with a focus on the approaches aimed at answering the following two fundamental questions: how many resources (number of nodes, etc.) should a DTM platform be provisioned with, and which protocols should be used to ensure data consistency.

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“…where D( X) and it's derivatives are evaluated at image points and T is offset from these points (for details see [45] Match to sub pixel maximum location, 7: Eliminate edge points, 8: end for 9: Construct keys using interpolated value.…”

Section: B Sift -Classic Attemptmentioning

confidence: 99%

“…Some aspects of positioning computing network models by the use of EC are presented in [4], [5], [6] and [7], [8] or [9]. In [10], [11] and [12], [13] applications of EC methods in dynamic systems positioning and simulation is presented.…”

Section: Introductionmentioning

confidence: 99%

Simplified firefly algorithm for 2D image key-points search

Napoli

Pappalardo

Tramontana

et al. 2014

2014 IEEE Symposium on Computational Intelligence for Human-Like Intelligence (CIHLI)

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Abstract-In order to identify an object, human eyes firstly search the field of view for points or areas which have particular properties. These properties are used to recognise an image or an object. Then this process could be taken as a model to develop computer algorithms for images identification. This paper proposes the idea of applying the simplified firefly algorithm to search for key-areas in 2D images. For a set of input test images the proposed version of firefly algorithm has been examined. Research results are presented and discussed to show the efficiency of this evolutionary computation method.

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A Hybrid Neuro–Wavelet Predictor for QoS Control and Stability

Cited by 22 publications

References 30 publications

A mathematical model for file fragment diffusion and a neural predictor to manage priority queues over BitTorrent

A mathematical model for file fragment diffusion and a neural predictor to manage priority queues over BitTorrent

Self-tuning in Distributed Transactional Memory

Simplified firefly algorithm for 2D image key-points search

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