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A GPU-based hybrid jDE algorithm applied to the 2D-AB protein structure prediction problem 8

A GPU-based hybrid jDE algorithm applied to the 2D-AB protei...

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8th Brazilian Conference on Intelligent Systems, BRACIS 2019

作者： Boiani, Mateus Dominico, Gabriel Stubs Parpinelli, Rafael Graduate Program in Applied Computing Santa Catarina State University Joinville Santa Catarina Brazil

ISBN: (纸本)9781728142531

Protein Structure Prediction (PSP) problem is an open problem in bioinformatics and, as the problem scales, complexity and processing time increases. In this way, robust methods and massively parallel architectures are required. This paper presents a GPU-based hybrid algorithm, named cuHjDE, to handle the 2D-AB off-lattice PSP problem. The cuHjDE is composed of the jDE algorithm and the Hooke-Jeeves local search algorithm. An important feature present in the cuHjDE algorithm is the use of a crowding mechanism to avoid premature convergence promoting diversification in the search space. The proposed algorithm is compared with four state-of-the-art algorithms in both artificial and real proteins. Also, the impact of using GPU is analyzed. Experimental results point out that the proposed approach is competitive in artificial sequences and achieved new best results for all real sequence proteins. © 2019 IEEE.

关键词： Proteins

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Differential evolution with cluster-based external archive and local search for multimodal optimization 8

Differential evolution with cluster-based external archive a...

引用

8th Brazilian Conference on Intelligent Systems, BRACIS 2019

作者： Dominico, Gabriel Boiani, Mateus Stubs Parpinelli, Rafael Graduate Program in Applied Computing Santa Catarina State University Joinville Santa Catarina Brazil

ISBN: (纸本)9781728142531

One of the main objectives in multimodal optimization is to find multiple optima solutions in a search space. Hence, population-based metaheuristics are suitable for this class of problems but their loss of diversity while converging may become a problem when tracking multiple optima. In this paper, we propose the use of a cluster-based external archive maintenance strategy along with the jDE algorithm, namely NCjDE-HJar. The DBSCAN algorithm is employed to group candidate solutions in an external archive representing multiple peaks that will feed the Hooke-Jeeves local search algorithm. Also, the Michalewicz mutation strategy is applied to refine the solutions found by the jDE algorithm. The proposed approach is compared with five state-of-the-art algorithms in terms of peak ratio and the results obtained show that the proposed modifications favor the finding more multimodal peaks. © 2019 IEEE.

关键词： Evolutionary algorithms

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An IoT Transport Architecture for Passenger Counting: A Real Implementation 17

An IoT Transport Architecture for Passenger Counting: A Real...

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17th IFIP/IEEE International Symposium on Integrated Network Management, IM 2021

作者： Kniess, Janine Rutke, Julio Cezar Castaneda, William Alberto Cruz Santa Catarina State University Graduate Program in Applied Computing Brazil

ISBN: (纸本)9783903176324

A smart urban mobility considers the technological-based development in transport systems, services and their use to improve the movement of people and goods inter or intra-cities. Cities increasingly face problems caused by traffic and need to find solutions to improve mobility and to reduce congestion and pollution. In this paper, we present a Passenger Counting Scheme into buses. Embedded counting algorithms based on Computer Vision are proposed to count passenger arrivals and departures in real time. Experiments in a real scenario expose that the proposed scheme achieved a high percentage of success in passenger count. © 2021 IFIP.

关键词： Smart city

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DCANon: Towards Distributed Certification Authority (CA) with Non-fungible Token (NFT) 37th

DCANon: Towards Distributed Certification Authority (CA) wit...

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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Descio-Trineto, Rafael Pillon, Maurício Koslovski, Guilherme Miers, Charles Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783031290558

Distributed applications rely on Certification Authorities (CAs) entities associated with a few institutions around the world. There are countless trusted institutions on the networks, e.g., universities, governments, banks, making effective use of CAs. Although largely used, the decentralized management of CAs is an administrative challenge. In this context, the joint emergence of digital ledgers and Non-Fungible Tokens (NFTs) compose a new opportunity to effectively decentralize single assets safely. Towards Distributed Certification Authority with Non-Fungible Token (DCANon) is a distributed Certification Authority (CA) built to trusted institutions and supported by Non-Fungible Token (NFT) concepts. DCANon changes the way revocation may be find, permitting that all consortium member crawler the blockchain for revoked certificates, independently from which CA this revocation occurs. A proof-of-concept prototype was implemented with Hyperledger Fabric demonstrating the benefits of DCANon. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Distributed ledger

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DeepScheduling: Grid computing Job Scheduler Based on Deep Reinforcement Learning 34th

DeepScheduling: Grid Computing Job Scheduler Based on Deep R...

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34th International Conference on Advanced Information Networking and Applications, AINA 2020

作者： Casagrande, Lucas C. Koslovski, Guilherme P. Miers, Charles C. Pillon, Maurício A. Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030440404

Grid systems are large-scale platforms which consume a considerable amount of energy. Several efficient resource/power management strategies were proposed by the specialized literature. However, most of the proposed strategies are rule-based policies which do not exploit workload patterns. Deploying the same set of rules on systems using different usage patterns, and platform settings, may lead to a sub-optimized setup. Due to the complex nature of grid systems, tailoring such a system-specific policy is not a straightforward task. In this paper, we explore a Deep Reinforcement Learning (DRL) method to build an adaptive energy-aware scheduling policy. We trained our algorithm using real workload traces from Grid’5000 platform. Our experiments pointed out an energy setup saving up to 7%, as well as average requests waiting time reduction of 27%. Finally, the resuslts clarify the importance of explore the workload to build system-specific policies. © 2020, Springer Nature Switzerland AG.

关键词： Reinforcement learning

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An improved evolutionary hybrid method for cloud provider selection 8

An improved evolutionary hybrid method for cloud provider se...

引用

8th Brazilian Conference on Intelligent Systems, BRACIS 2019

作者： Borges De Moraes, Lucas Fiorese, Adriano Stubs Parpinelli, Rafael Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9781728142531

Cloud computing (CC) popularization unleashed the creation and competition of a large number of new companies providing CC services, the so called Cloud Providers (CPs). Thus, select the smallest CP set with the lowest price that are the most suitable to a given request (customer's needs, such as demanded resources and desired service quality) becomes a hard problem. Nonetheless, robust search methods like metaheuristics ones are used to solve it, for instance Evolutionary Algorithms (EAs). Performance Indicators (PIs) were used to quantify features of each CP used later to select them using a method. This paper proposes an improved hybrid method which uses in sequence: a deterministic, an EA and a local search method to find the most suitable possible CP set in the solution search space. This hybrid method was tested and has the highest assertiveness among all others methods developed to solve this problem, becoming a promising solution to a real application. © 2019 IEEE.

关键词： Benchmarking

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SSL-C4.5: Implementation of a Classification Algorithm for Semi-supervised Learning Based on C4.5 9th

SSL-C4.5: Implementation of a Classification Algorithm for S...

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9th Brazilian Conference on Intelligent Systems, BRACIS 2020

作者： Ortiz-Díaz, Agustín Alejandro Bayer, Flavio Roberto Baldo, Fabiano Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030613792

Classification algorithms have been extensively studied in many of the major scientific investigations in recent decades. Many of these algorithms are designed for supervised learning, which requires labeled instances to achieve effective learning models. However, in many of the real human processes, data labeling is expensive and time-consuming. Because of this, alternative learning paradigms have been proposed to reduce the cost of the labeling process without a significant loss of model performance. This paper presents the Semi-Supervised Learning C4.5 algorithm (SSL-C4.5) designed to work in scenarios where only a small part of the data is labeled. SSL-C4.5 was implemented over the J48 implementation of the C4.5 algorithm available at the WEKA platform. The J48 was modified incorporating a metric for semi-supervised learning. This metric aims at inducing decision tree models able to analyze and extract information from the entire training dataset, including instances of unlabeled data in scenarios where they are the majority. The assessment performed using eight different benchmark datasets showed that the new proposal has achieved promising results compared to the supervised version of C4.5. © 2020, Springer Nature Switzerland AG.

关键词： Decision trees

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SDN4Moodle: An SDN-based Toolset to Enhance QoS of Moodle Platform

SDN4Moodle: An SDN-based Toolset to Enhance QoS of Moodle Pl...

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2018 IEEE Symposium on Computers and Communications, ISCC 2018

作者： Marcondes, Anderson H. Da Silva Miers, Charles C. Pillon, Maurcio A. Koslovski, Guilherme P. Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9781538669501

Network configuration, performance, and congestion impact the Quality of Service (QoS) of Moodle Learning Management System (LMS). Moreover, LMSs composing modules have different QoS demands for each activity. Upon a network, they compete for resources with applications for social media, streaming, chat, cloud file synchronization, games, among others. Eventually, the network congestion can leave the LMS service unavailable for students and professors. Recently, the popularization of Software Defined Networks (SDN) revolutionized the network management. We propose SDN4Moodle, a toolset to increase the QoS of Moodle services. SDN4Moodle was implemented in conformity to Moodle's plugin guidelines, and it is controlled by internal Moodle events. Each action performed by a Moodle's user is dynamically translated into network forwarding rules, and switches configuration. Our experimental results indicates SDN4Moodle, an open-source system, efficiently achieves flows isolation and bandwidth control on shared networks. © 2018 IEEE.

关键词： Quality of service

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Executing distributed applications on SDN-based Data Center: A study with NAS Parallel Benchmark 7

Executing distributed applications on SDN-based Data Center:...

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2016 7th International Conference on the Network of the Future, NOF 2016

作者： Marcondes, Anderson H. S. Diel, Gustavo De Souza, Felipe R. Vieira, Paulo R. Fiorese, Adriano Koslovski, Guilherme P. Graduate Program in Applied Computing Santa Catarina State University Joinville SC Brazil

ISBN: (纸本)9781509046713

Software-Defined Networking (SDN) paradigm has decoupled data and control planes on traditional networks. In this context, a logically-centralized controller, with full knowledge on network resources and traffic loads, executes routing algorithms to identify forwarding paths, while networking resources (switches and routers) just work on packet forwarding. This work contributes by executing and characterizing a well-know distributed application, NAS parallel benchmark, atop an SDN-based data center. A comparison with different flow routing algorithms is presented, highlighting that an application can reduce its runtime when applying a multi-path routing. © 2016 IEEE.

关键词： Benchmarking

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Optimal resource allocation for survivable virtual infrastructures

Optimal resource allocation for survivable virtual infrastru...

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10th International Conference on Design of Reliable Communication Networks, DRCN 2014

作者： De S. Cavalcanti, Gustavo A. Obelheiro, Rafael R. Koslovski, Guilherme Graduate Program in Applied Computing Department of Computer Science Santa Catarina State University Brazil

ISBN: (纸本)9781479940097

Virtual infrastructures (VIs) consolidated the dynamic provisioning of computing and communication resources. A VI is a set of virtual machines interconnected by virtual links and switches/routers. Infrastructure providers (InPs) manage the physical substrates in which virtual resources requested by VIs (such as CPU, disk, memory, bandwidth) are reserved and allocated. Resource allocation is a complex problem that needs to satisfy different goals: users expect to run their applications on survivable VIs, while InPs aim to maximize profits, minimize costs and reduce substrate fragmentation. However, there is a dichotomy between minimizing substrate fragmentation, by co-locating VIs, and maximizing VI survivability, by sparsely allocating resources in order to decrease the impact of substrate failures. In this context, this paper discusses VI survivability and its impact on substrate fragmentation. We propose a mixed integer linear programming model to allocate resources considering the joint coordination of fragmentation and survivability. Experimental results suggest that it is possible to enhance VI survivability without significantly impacting substrate fragmentation. © 2014 IEEE.

关键词： Substrates

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