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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： Robaina, Gabriel Fiorese, Adriano Graduate Program in Applied Computing - PPGCAP Santa Catarina State University - UDESC Joinville Brazil

ISBN: (纸本)9789897586484

The mobile games market has grown in relevancy compared to traditional gaming platforms. The standard architecture for these games requires the processing of game logic and graphics using the device's own hardware. Alternatively, cloud based architectures for remote gaming on smartphones present high game input delay at a high cost for the service provider. This poses a limitation to the variety and complexity of games that target these platforms as well as constraining user QoE. To address that limitation, this work proposes the Gaming On The Edge (GOTE) architecture, that aims to enable complex games to be played on smartphone devices while leveraging edge computing infrastructure into graphics processing and content distribution systems. A GOTE architecture's proof of concept is developed and tested using WebRTC with an RTP streaming pipeline that exploits NVENC for achieving low latency video encoding. Experimental results show that GOTE architecture is a viable alternative to cloud based remote gaming on smartphones at the advantage of lowering latency of video and game input. An open source implementation of the architecture is provided in order to assist further research in this area. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Edge computing

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Experimental analysis of microservices architectures for hosting cloud-based Massive Multiplayer Online Role-Playing Game (MMORPG)

Experimental analysis of microservices architectures for hos...

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IEEE International Conference on Cloud computing Technology and Science (CloudCom)

作者： Marlon H. Schweigert Diego E.G.C. de Oliveira Guilherme P. Koslovski Maurício A. Pillon Charles C. Miers Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Brazil

The popularization increase of MMORPGs demands new technological approaches to supply users’ requirements with a lower cost of computational resources. Designing these architectures, from the network point of view, is relevant and impacts these games’ success. We analyze and identify the computational resources consumed by the architectures Rudy, Salz, and Willson, which are microservices architectures elaborated for MMORPGs. These architectures were analyzed and tested using automated clients on the architectures deployed in our private computational cloud to identify resource bottlenecks. We conclude the performance, from the point of view of response time, is related to better use of CPU, either by data storage microservices or by data processing microservices. In addition, the application of queuing systems or barriers to manage access or minimize the consumption of an internal service proved feasible, directly impacting the flow of data through the architecture.

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Comparing Best and Quota Fragment Picker Protocols applied to Protein Structure Prediction 20th

Comparing Best and Quota Fragment Picker Protocols Applied t...

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20th International Conference on Hybrid Intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Will, Nilcimar Neitzel Parpinelli, Rafael Stubs UDESC Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil

ISBN: (纸本)9783030730499

The use of fragment insertion in the protein structure prediction problem can be considered one of the most successful strategies to add problem-dependent information. The well known Rosetta suite provides two protocols for generating fragment libraries: Best and Quota. The first aims to maximize a given score function, while the second aims add fragment diversity. This paper presents the results with four proteins to verify the impact of using more secondary structure information through the quota protocol when compared to the best protocol. The tests were performed considering the PSIPRED, SPIDER2, and MUFold predictors. Results obtained are compared in terms of RMSD, processing time, and convergence. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Forecasting

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Integrity of Cyber-Physical Discrete Event Systems under covert actuator attacks

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IFAC-PapersOnLine 2024年第1期58卷 198-203页

作者： Samuel Oliveira André B. Leal Marcelo Teixeira Yuri K. Lopes Department of Exact and Technological Sciences Federal University of Amapá (UNIFAP) Macapá/AP Brazil Graduate Program in Electrical Engineering Santa Catarina State University (UDESC) Joinville/SC Brazil Graduate Program in Electrical Engineering Federal University of Technology (UTFPR) Pato Branco/PR Brazil Graduate Program in Applied Computing Santa Catarina State University (UDESC) Joinville/SC Brazil

The connectivity requirements brought by Industry 4.0 pose new challenges for cyber-physical systems (CPS), such as the strengthening of their resilience against cyberattacks. In this paper, we use the discrete event systems (DES) formalism to develop an approach that aims to protect CPS from covert actuator attacks using event permutation maps. In this approach, properly selected controllable events are permuted on the plant's site so that attacks on actuators do not have the impact on the plant as expected by the intruder and unsafe states are avoided. Furthermore, a property termed AE-protectability is presented to characterize the necessary and sufficient conditions for the system to be protected against such attacks through event permutations. The proposed approach is applied to a case study where the Identification of the attack is done without causing damage while maintaining the integrity of the system.

关键词： Cyber-security Supervisory Control Theory Diagnosis

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Joint Cache Placement and Request Routing Optimization in Heterogeneous Cellular Networks

Joint Cache Placement and Request Routing Optimization in He...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Marisangila Alves Guilherme Piĉgas Koslovski Graduate Program in Applied Computing - Santa Catarina State University - UDESC

ISBN: (数字)9781665497923

ISBN: (纸本)9781665497930

The 5G Quality-of-Service (QoS) objectives con-tributed to the Heterogeneous Cellular Network (HCN) evolution, dictating that applications can rely on low-latency and high-bandwidth networks. However, concurrent requests of large amount of multimedia data generate a burden on the backhaul and fronthaul networks due to redundant retransmissions and pose challenges for achieving the QoS objectives. Although mobile network operators can place content closer to the HCN edge to improve the overall QoS indicators, there are still challenges to design a cache policy aware of limited storage capacity, different content popularity, device mobility, and network congestion. This work innovates by introducing a cooperative policy to join caches placement and routing users' requests atop an HCN. By combining networking and cache QoS requirements, the policy balances the fronthaul network load and dynamically maps the caches to HCN resources. We formulated the cache policy through linear programming and in-depth evaluated its performance using extensive simulation scenarios. The results indicate that the proposed network-aware policy decreases the network latency, even when subject to changes in content popularity distribution and total HCN storage capacity.

关键词： Cellular networks Measurement 5G mobile communication Quality of service Routing Linear programming Low latency communication

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Lightweight SPIFFE Verifiable Identity Document (LSVID): A Nested Token Approach for Enhanced Security and Flexibility in SPIFFE

Lightweight SPIFFE Verifiable Identity Document (LSVID): A N...

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IEEE International Conference on Cloud computing Technology and Science (CloudCom)

作者： Henrique Z. Cochak Charles C. Miers Pedro H.B. Correia Marco A. Marques Marcos A. Simplicio Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Brazil Laboratory of Computer Networks and Architecture (LARC) Universidade de Sao Paulo (USP) Brazil

ISBN: (数字)9798331507589

ISBN: (纸本)9798331507596

Service identities are crucial for authentication and access control, ensuring that only authorized services access specific resources. The SPIFFE framework addresses workload identity management and authentication effectively but needs support for solutions (e.g., extensible tokens) that fine-granular authorization mechanisms in distributed scenarios can use. In this context, we present the Lightweight SVID (LSVID), an identity document in JSON format that can be extended and used as a token. As an extensible token, Lightweight SVID (LSVID) enables features such as delegation, attenuation, and traceability, enhancing its flexibility and applicability. Our approach provides efficient handling of token extensions and validations, demonstrated through a proof-of-concept implemented in Go. Baseline results indicate that LSVID critical operations are efficient, with processing times in the microsecond range, offering significant functional advantages over the traditional JWT-SVIDs, one of two key security documents from SPIFFE.

关键词： Computers Authorization Cloud computing Authentication Attenuation

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Multi-Instance Task in Swarm Robotics: Sorting Groups of Robots or Objects into Clusters with Minimalist Controllers

Multi-Instance Task in Swarm Robotics: Sorting Groups of Rob...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Adilson Krischanski Yuri K. Lopes Andre B. Leal Ricardo F. Martins Roberto S.U. Rosso Department of Computer Science Santa Catarina State University (UDESC) Joinville Brazil Graduate Program in Applied Computing (PPGCAP) UDESC Brazil Department of Electrical Engineering Santa Catarina State University (UDESC) Joinville Brazil

Relying only on behaviors that emerge from simple responsive controllers; swarms of robots have been shown capable of autonomously aggregate themselves or objects into clusters without any form of communication. We push these controllers to the limit, requiring robots to sort themselves or objects into different clusters. Based on a responsive controller that maps the current reading of a line-of-sight sensor to a pair of speeds for the robots' differential wheels, we demonstrate how multiple tasks instances can be accomplished by a robotic swarm. Using the dividing rectangles approach and physics simulation, a training step optimizes the parameters of the controller guided by a fitness function. We conducted a series of systematic trials in physics-based simulation and evaluate the performance in terms of dispersion and the ratio of clustered robots/objects. Across 20 trials where 30 robots cluster themselves into 3 groups, an average of 99.83% of them were correctly clustered into their group after 300 s. Across 50 trials where 15 robots cluster 30 objects into 3 groups, an average of 61.20%, 82.87%, and 97.73% of objects were correctly clustered into their group after 600 s, 900 s, and 1800 s, respectively. The object cluster behavior scales well while the aggregation does not, the latter due to the requirement of control tuning based on the number of robots.

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Data classification and reinforcement learning to avoid congestion on SDN-based data centers

Data classification and reinforcement learning to avoid cong...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Gustavo Diel Charles Christian Miers Maurício Aronne Pillon Guilherme Piêgas Koslovski Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Joinville Brazil

ISBN: (纸本)9781665435413

A contemporaneous data center (DC) hosts multiple competitive network data flows from different applications, sharing the intermediate switches capacities. In this context, congestion control and avoidance on Transmission Control Protocol (TCP) are critical tasks to ensure the quality of service for hosted applications. Specifically, Software Defined Networking (SDN) created an opportunity to avoid congestion once the centralized controller can gather ongoing and historical information from all network switches and flows. However, the data gathered is enormous, and fast-computing algorithms are crucial for decision-making. In this sense, this work proposes Reinforcement Learning- and SDN-aided Congestion Avoidance Tool (RSCAT), which uses data classification to determine if the network is congested and actor-critic reinforcement learning to find better TCP parameters. Our experimental analysis shows RSCAT could decrease the Flow Completion Time (FCT) of DCTCP and CUBIC variants in several cases without requiring any software update on DC end-points.

关键词： Data centers Protocols Software algorithms Decision making Reinforcement learning Quality of service Software

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Performance analysis of the Raft consensus algorithm on Hyperledger Fabric and Ethereum on cloud

Performance analysis of the Raft consensus algorithm on Hype...

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IEEE International Conference on Cloud computing Technology and Science (CloudCom)

作者： João H. F. Battisti Vitor E. Batista Guilherme P. Koslovski Maurício A. Pillon Charles C. Miers Marco A. Marques Marcos Simplício Diego Kreutz Graduate Program in Applied Computing (PPGCAP) Santa Catarina State University (UDESC) Brazil Laboratory of Computer Networks and Architecture (LARC) Universidade de São Paulo (USP) Brazil Graduate Program in Software Engineering Federal University of Pampa (Unipampa) Brazil

The use of private or consortium blockchains in organizations’ applications is growing. A relevant aspect of blockchains is the choice of consensus mechanism. This decision delimits which blockchain solutions are suitable for the private scenario. Once the consensus mechanism is chosen, more than one blockchain may be enabled. However, this decision making is not trivial and requires detailed experimental indicators about algorithms and blockchains performance. In this context, we provide a comprehensive performance analysis of the Raft consensus mechanism based on its implementation in Hyperledger Fabric and Ethereum blockchain solutions. We performed our experiments on an OpenStack private cloud using each blockchain developer’s default settings for virtual machines. Our findings show how the implementation of each solution can impact the application’s performance under certain conditions.

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Modelling IF Steels Using Artificial Neural Networks and Automated Machine Learning 20th

Modelling IF Steels Using Artificial Neural Networks and Aut...

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20th International Conference on Hybrid Intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Sgrott, Douglas Macedo Cerqueira, Fabricio Moreira Miranda, Fabiano J. F. Filho, José F. S. Parpinelli, Rafael S. UDESC Graduate Program in Applied Computing Santa Catarina State University JoinvilleSC Brazil Global Research and Development Group ArcelorMittal São Francisco do SulSC Brazil

ISBN: (纸本)9783030730499

The development of steels requires multiples manufacturing steps and involves a high number of variables and non-linear processes. Although there are data-driven models used to predict such steels’ mechanical properties, their design often requires specialized Machine Learning knowledge, hampering the application of such models. In this paper, an Automated Machine Learning (AutoML) framework, namely Auto-Keras, was employed to generate and train a data-driven model on a steel data-set through Neural Architecture Search. This paper proposes predicting the mechanical properties of steels applying Artificial Neural Networks (ANN) as a multivariate regression problem using AutoML. The results show that even with a vast parameter search space, it is possible to generate ANNs with different architectures that provide high performance with free and open-source AutoML. Three ANNs with different activation functions were optimized using Auto-Keras and compared. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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