Edge computing pushes cloud capabilities to the edge of the network, closer to the users, to address stringent Quality-of-Service requirements and ensure more efficient bandwidth usage. Function-as-a-Service appears t...
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ISBN:
(纸本)9781665435383
Edge computing pushes cloud capabilities to the edge of the network, closer to the users, to address stringent Quality-of-Service requirements and ensure more efficient bandwidth usage. Function-as-a-Service appears to be the most natural service model solution to enhance Edge computing applications' deployment and responsiveness. Unfortunately, the conventional FaaS model does not fit well in distributed and heterogeneous edge environments, where traffic demands arrive to (and are served by) edge nodes that may get overloaded under certain traffic conditions or where the access points of the network might frequently change, as for mobile applications. this short paper tries to fill this gap by proposing DFaaS, a novel decentralized FaaS-based architecture designed to autonomously balance the traffic load across edge nodes belonging to federated Edge computing ecosystems. DFaaS implementation relies on an overlay peer-to-peer network and a distributed control plane that takes decisions on load redistribution. Although preliminary, results confirm the feasibility of the approach, showing that the system can transparently redistribute the load across edge nodes when they become overloaded.
In the time of increasing crime Face recognition is very significant with regards to computer vision, security, monitoring, reconnaissance, pattern checking, neural network, real-time video processing, etc. Face is no...
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the proceedings contain 53 papers. the special focus in this conference is on Computer recognition Systems. the topics include: recognition of fuzzy or incompletely described objects;multi-aspect assessment and classi...
ISBN:
(纸本)9783319591612
the proceedings contain 53 papers. the special focus in this conference is on Computer recognition Systems. the topics include: recognition of fuzzy or incompletely described objects;multi-aspect assessment and classification of porous materials designed for tissue engineering;enhancing English-Japanese translation using syntactic patternrecognition methods;travel time prediction for trams in Warsaw;diagnostic rule extraction using the dempster-shafer theory extended for fuzzy focal elements;gait recognition using motion trajectory analysis;determining of an estimate of the equivalence relation on the basis of pairwise comparisons;semi-automatic segmentation of scattered and distributed objects;a vision-based method for automatic crack detection in railway sleepers;towards privacy-aware keyboards;saliency-based optimization for the histogram of oriented gradients-based detection methods;efficient sketch recognition based on shape features and multidimensional indexing;performance evaluation of selected thermal imaging-based human face detectors;on a new method of dynamic integration of fuzzy linear regression models;ensemble machine learning approach for android malware classification using hybrid features;an ensemble of weak classifiers for patternrecognition in motion capture clouds of points;portable dynamic malware analysis with an improved scalability and automatisation;projection-based person identification;an algorithm for selective preprocessing of multi-class imbalanced data;the method of person verification by use of finger knuckle images;recent advances in image pre-processing methods for palmprint biometrics;some properties of consensus based classification;knowledge based active partition approach for heart ventricle recognition;raster maps search using text queries and reasoning.
the proceedings contain 51 papers. the topics discussed include: sparker: optimizing spark for heterogeneous clusters;phase annotated learning for apache spark: workload recognition and characterization;Yodea: workloa...
ISBN:
(纸本)9781538678992
the proceedings contain 51 papers. the topics discussed include: sparker: optimizing spark for heterogeneous clusters;phase annotated learning for apache spark: workload recognition and characterization;Yodea: workload pattern assessment tool for cloud migration;cost-time performance of scaling applications on the cloud;investigating and modeling performance scalability for distributed graph analytics;scalability and locality awareness of remote procedure calls: an experimental study in edge infrastructures;an architectural framework for serverless edge computing: design and emulation tools;using quantile regression for reclaiming unused cloud resources while achieving SLA;and systematic and recomputable comparison of multi-cloud management platforms.
In this paper, we propose a new method based on wavelet transform, statistical features and central moments for both graphics and scene text detection in video images. the method uses wavelet single level decompositio...
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Direct search (DS) methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optim...
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ISBN:
(纸本)0889866104
Direct search (DS) methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One such method is pattern Search (PS) algorithm. this paper presents a new approach to solve the load-flow problem using pattern Search (PS) optimization method. the method is illustrated by various tests on a six-bus system. the time performance and results of PS method are compared withthose reported by genetic algorithm (GA) in the literature. this study has demonstrated that PS is able to provide an exact solution to the problem. the outcome is very encouraging and proves that pattern search (PS) is very applicable and shows reliability, accuracy in solving the power-flow problem.
A wide range of applications, from e-learning to natural disaster management are reliant on video streaming. Video streaming will construct more than 80% of the whole Internet traffic by 2019. Currently, video stream ...
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ISBN:
(纸本)9781450351492
A wide range of applications, from e-learning to natural disaster management are reliant on video streaming. Video streaming will construct more than 80% of the whole Internet traffic by 2019. Currently, video stream providers offer little or no interactive services on their streamed videos. Stream viewers, however, demand a wide variety of interactive services (e.g., dynamic video summarization or dynamic transcoding) on the streams. Taking into account the long tail access pattern to video streams, it is not feasible to preprocess all possible interactions for all video streams. Also, Processing them is also not feasible on energy- and compute-limited viewers' thin-clients. the proposed research provides a cloud-based video streaming engine that enables interactive video streaming. Interactive Video Streaming Engine (IVSE) is generic and video stream providers can customize it by defining their own interactive services, depending on their applications and their viewers' desires. the engine enacts the defined interactive services through on-demand processing of the video streams on potentially heterogeneous cloud services, in a cost-efficient manner, and with respect to stream viewers' QoS demands.
In Pervasive computing research, substantial work has been directed towards radio-based sensing of human movement patterns. this research has, however, mainly been focused on movements of individuals. this paper addre...
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ISBN:
(纸本)9781467302586
In Pervasive computing research, substantial work has been directed towards radio-based sensing of human movement patterns. this research has, however, mainly been focused on movements of individuals. this paper addresses the joint identification of the movement indoors of multiple persons forming a cohesive whole - specifically flocks - with clustering approaches operating on three different feature sets derived from WiFi signals which are comparatively analysed. Automatic detection of flocks has several important applications, including social and psychological sensing and emergency research studies. We use a dataset comprising 16 subjects forming one to four flocks walking in a building on single and multiple floors. For the detection of flocks we achieved an average F-measure accuracy of up to 85 percent. We report on the advantages and drawbacks of the three different types of feature sets considering their suitability for use "in the wild" or in well-defined environments.
the proceedings contain 10 papers presendted at a virtual meeting. the special focus in this conference is on Mobile Wireless Middleware, Operating Systems and Applications. the topics include: Instantaneous Availabil...
ISBN:
(纸本)9783030986704
the proceedings contain 10 papers presendted at a virtual meeting. the special focus in this conference is on Mobile Wireless Middleware, Operating Systems and Applications. the topics include: Instantaneous Availability Analysis of Maintenance Process Based on Semi-Markov Model;Study on Urban Travel Volume During the Outbreak of COVID-19;Safety Helmet Wearing recognition Based on YOLOv5;preface;human Behavior Estimation Using Micro-vibration Sensor Based on Deep Boltzmann Machine;a Survey of Techniques for Constructing Mongolian Domain-Specific Knowledge Graph;a Review of Additive Manufacturing (3D Printing) in Aerospace: Technology, Materials, Applications, and Challenges;Layered-MAC: An Energy-Protected and Efficient Protocol for Wireless Sensor Networks.
作者：
Pletschacher, StefanResearch Lab.
School of Computing Science and Engineering University of Salford Greater Manchester United Kingdom
recognition and encoding of digitized historical documents is still a challenging and difficult task. A major problem is the occurrence of unknown glyphs and symbols which might not even exist in modern alphabets. Cur...
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