A. Baranov, P. Telegin, B. Shabanov, D. Lyakhovets
In this paper we investigate the problem of modelling modern supercomputer job management systems (JMS). When modelling the JMS, one of the main issues is the adequacy of the model used in experimental studies. The paper attempts to determine the measure of the JMS model adequacy by comparing the characteristics of two job streams, one of which was acquired from a real supercomputer and the other is obtained from the JMS model. We show that the normalized Euclidean distance between vectors of jobs residence times obtained from the job streams of the real system and the JMS model can serve as a measure of the adequacy of the JMS model. The paper also defines the reference value of the measure of adequacy corresponding to the JMS model with virtual nodes.
{"title":"Measure of Adequacy for the Supercomputer Job Management System Model","authors":"A. Baranov, P. Telegin, B. Shabanov, D. Lyakhovets","doi":"10.15439/2019F186","DOIUrl":"https://doi.org/10.15439/2019F186","url":null,"abstract":"In this paper we investigate the problem of modelling modern supercomputer job management systems (JMS). When modelling the JMS, one of the main issues is the adequacy of the model used in experimental studies. The paper attempts to determine the measure of the JMS model adequacy by comparing the characteristics of two job streams, one of which was acquired from a real supercomputer and the other is obtained from the JMS model. We show that the normalized Euclidean distance between vectors of jobs residence times obtained from the job streams of the real system and the JMS model can serve as a measure of the adequacy of the JMS model. The paper also defines the reference value of the measure of adequacy corresponding to the JMS model with virtual nodes.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124158002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A Travelling Salesman Problem (TSP) is an NP-hard combinatorial problem that is very important for many real-world applications. In this paper, it is shown, that proposed approach solves multi-objective TSP (mTSP) more effectively than other investigated methods, i.e., Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed methods use rank and crowding distance (well-known from NSGA-II), combining those mechanisms in a novel, unique way: competing and co-evolving in the evolution process. The proposed modifications are investigated and verified by the benchmark mTSP instances, and results are compared to other methods.
{"title":"Non-dominated Sorting Tournament Genetic Algorithm for Multi-Objective Travelling Salesman Problem","authors":"P. Myszkowski, Maciej Laszczyk, Kamil Dziadek","doi":"10.15439/2019F192","DOIUrl":"https://doi.org/10.15439/2019F192","url":null,"abstract":"A Travelling Salesman Problem (TSP) is an NP-hard combinatorial problem that is very important for many real-world applications. In this paper, it is shown, that proposed approach solves multi-objective TSP (mTSP) more effectively than other investigated methods, i.e., Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed methods use rank and crowding distance (well-known from NSGA-II), combining those mechanisms in a novel, unique way: competing and co-evolving in the evolution process. The proposed modifications are investigated and verified by the benchmark mTSP instances, and results are compared to other methods.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128179398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Alves da Silva, José Alberto Sousa Torres, Alexandre Pinheiro, Francisco L. de Caldas Filho, Fábio L. L. Mendonça, B. Praciano, Guilherme Oliveira Kfouri, Rafael Timóteo de Sousa Júnior
Drivers’ behavior in traffic is a determining factor for the rate of accidents on roads and highways. This paper presents the design of an intelligent IoT system capable of inferring and warning about road traffic risks and danger zones, based on data obtained from the vehicles and their drivers mobile phones, thus helping to avoid accidents and seeking to preserve the lives of the passengers. The proposed approach is to collect vehicle telemetry data and mobile phone sensors data through an IoT network and then to analyze the driver’s behavior while driving, along with data from the environment. The results of the inference serve to alert drivers about incidents in their trajectory as well as to provide feedback on how they are driving. The proposal is validated using a developed prototype to test its data collection and inference features in a small scale experiment.
{"title":"Inference of driver behavior using correlated IoT data from the vehicle telemetry and the driver mobile phone","authors":"Daniel Alves da Silva, José Alberto Sousa Torres, Alexandre Pinheiro, Francisco L. de Caldas Filho, Fábio L. L. Mendonça, B. Praciano, Guilherme Oliveira Kfouri, Rafael Timóteo de Sousa Júnior","doi":"10.15439/2019F263","DOIUrl":"https://doi.org/10.15439/2019F263","url":null,"abstract":"Drivers’ behavior in traffic is a determining factor for the rate of accidents on roads and highways. This paper presents the design of an intelligent IoT system capable of inferring and warning about road traffic risks and danger zones, based on data obtained from the vehicles and their drivers mobile phones, thus helping to avoid accidents and seeking to preserve the lives of the passengers. The proposed approach is to collect vehicle telemetry data and mobile phone sensors data through an IoT network and then to analyze the driver’s behavior while driving, along with data from the environment. The results of the inference serve to alert drivers about incidents in their trajectory as well as to provide feedback on how they are driving. The proposal is validated using a developed prototype to test its data collection and inference features in a small scale experiment.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134239119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main aim of proposed paper is the design of new software system for modelling and control of discrete-event and hybrid systems using Arduino and similar microcontrollers. In this article we propose a new tool. This new tool is based on Petri nets and it is called PN2ARDUINO. It offers a capability of communication with the microcontroller. Communication with the microcontroller is based on modified Firmata protocol so control algorithm can be implemented on all microcontrollers that support this type of protocol. The developed software tool was successfully verified for control of laboratory systems. It can also be used for education and also for research purposes as it offers a graphical way for designing control algorithm for hybrid and mainly discrete-event systems. Proposed tool can enrich education and practice in the field of cyber-physical systems.
{"title":"PN2ARDUINO - A New Petri Net Software Tool For Control Of Discrete-event And Hybrid Systems Using Arduino Microcontrollers","authors":"Erik Kučera, Oto Haffner, R. Leskovský","doi":"10.15439/2019F20","DOIUrl":"https://doi.org/10.15439/2019F20","url":null,"abstract":"The main aim of proposed paper is the design of new software system for modelling and control of discrete-event and hybrid systems using Arduino and similar microcontrollers. In this article we propose a new tool. This new tool is based on Petri nets and it is called PN2ARDUINO. It offers a capability of communication with the microcontroller. Communication with the microcontroller is based on modified Firmata protocol so control algorithm can be implemented on all microcontrollers that support this type of protocol. The developed software tool was successfully verified for control of laboratory systems. It can also be used for education and also for research purposes as it offers a graphical way for designing control algorithm for hybrid and mainly discrete-event systems. Proposed tool can enrich education and practice in the field of cyber-physical systems.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"41 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133077445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The coverage of a Region of Interest (RoI), that must be satisfied when deploying a Wireless Sensor Network (WSN), depends on several factors related not only to the sensor nodes (SNs) capabilities but also to the RoI topography. This latter has been omitted by most previous deployment approaches, which assume that the RoI is 2D. However, some recent WSNs deployment approaches dropped this unrealistic assumption. This paper surveys the different models adopted by the state-of-the-art deployment approaches. The weaknesses that need to be addressed are identified and some proposals expected to enhance the practicality of these models are discussed.
{"title":"On Coverage of 3D Terrains by Wireless Sensor Networks","authors":"Mostefa Zafer, Mustapha Réda Senouci, M. Aissani","doi":"10.15439/2019F24","DOIUrl":"https://doi.org/10.15439/2019F24","url":null,"abstract":"The coverage of a Region of Interest (RoI), that must be satisfied when deploying a Wireless Sensor Network (WSN), depends on several factors related not only to the sensor nodes (SNs) capabilities but also to the RoI topography. This latter has been omitted by most previous deployment approaches, which assume that the RoI is 2D. However, some recent WSNs deployment approaches dropped this unrealistic assumption. This paper surveys the different models adopted by the state-of-the-art deployment approaches. The weaknesses that need to be addressed are identified and some proposals expected to enhance the practicality of these models are discussed.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133602897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As more and more data are available, training a machine learning model can be extremely intractable, especially for complex models like Support Vector Regression (SVR) training of which requires solving a large quadratic programming optimization problem. Selecting a small data subset that can effectively represent the characteristic features of training data and preserve their distribution is an efficient way to solve this problem. This paper proposes a systematic approach to select the best representative data for SVR training. The distributions of both predictor and response variables are preserved in the selected subset via a 2-layer data clustering strategy. A 2-layer step-wise greedy algorithm is introduced to select best data points for constructing a reduced training set. The proposed method has been applied for predicting deck’s win rates in the Clash Royale Challenge, in which 10 subsets containing hundreds of data examples were selected from 100k for training 10 SVR models to maximize their prediction performance evaluated using R-squared metric. Our final submission having a R2 score of 0.225682 won the 3rd place among over 1200 solutions submitted by 115 teams.
{"title":"Training Subset Selection for Support Vector Regression","authors":"Cenru Liu, Jiahao Cen","doi":"10.15439/2019F363","DOIUrl":"https://doi.org/10.15439/2019F363","url":null,"abstract":"As more and more data are available, training a machine learning model can be extremely intractable, especially for complex models like Support Vector Regression (SVR) training of which requires solving a large quadratic programming optimization problem. Selecting a small data subset that can effectively represent the characteristic features of training data and preserve their distribution is an efficient way to solve this problem. This paper proposes a systematic approach to select the best representative data for SVR training. The distributions of both predictor and response variables are preserved in the selected subset via a 2-layer data clustering strategy. A 2-layer step-wise greedy algorithm is introduced to select best data points for constructing a reduced training set. The proposed method has been applied for predicting deck’s win rates in the Clash Royale Challenge, in which 10 subsets containing hundreds of data examples were selected from 100k for training 10 SVR models to maximize their prediction performance evaluated using R-squared metric. Our final submission having a R2 score of 0.225682 won the 3rd place among over 1200 solutions submitted by 115 teams.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131662118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud availability is a major performance parameter in cloud Service Level Agreements (SLA). Its correct evaluation is essential to SLA enforcement and possible litigation issues. Current methods fail to correctly identify the fault location, since they include the network contribution. We propose a procedure to identify the failures actually due to the cloud itself and provide a correct cloud availability measure. The procedure employs tools that are freely available, i.e. traceroute and whois, and arrives at the availability measure by first identifying the boundaries of the cloud. We evaluate our procedure by testing it on three major cloud providers: Google Cloud, Amazon AWS, and Rackspace. The results show that the procedure arrives at a correct identification in 95% of cases. The cloud availability obtained in the test after correct identification lies between 3 and 4 nines for the three platforms under test.
{"title":"Whose Fault is It? Correctly Attributing Outages in Cloud Services","authors":"M. Naldi, Matteo Adriani","doi":"10.15439/2019F59","DOIUrl":"https://doi.org/10.15439/2019F59","url":null,"abstract":"Cloud availability is a major performance parameter in cloud Service Level Agreements (SLA). Its correct evaluation is essential to SLA enforcement and possible litigation issues. Current methods fail to correctly identify the fault location, since they include the network contribution. We propose a procedure to identify the failures actually due to the cloud itself and provide a correct cloud availability measure. The procedure employs tools that are freely available, i.e. traceroute and whois, and arrives at the availability measure by first identifying the boundaries of the cloud. We evaluate our procedure by testing it on three major cloud providers: Google Cloud, Amazon AWS, and Rackspace. The results show that the procedure arrives at a correct identification in 95% of cases. The cloud availability obtained in the test after correct identification lies between 3 and 4 nines for the three platforms under test.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"1 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116940194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper deals with a possible approach to controlling marine fish stocks using the prey-predator model described by the Lotka-Volterra equations. The control strategy is conceived using the sliding mode control (SMC) approach which, based on the Lyapunov theorem, offers the possibility to track desired functions, thus guaranteeing the stability of the controlled system. This approach can be used for sustainable management of marine fish stocks: through the developed algorithm, the appropriate number of active fishermen and the suitable period for fishing can be determined. Computer simulations validate the proposed approach.
{"title":"Sustainable Management of Marine Fish Stocks by Means of Sliding Mode Control","authors":"Katharina Benz, Claus Rech, Paolo Mercorelli","doi":"10.15439/2019F221","DOIUrl":"https://doi.org/10.15439/2019F221","url":null,"abstract":"This paper deals with a possible approach to controlling marine fish stocks using the prey-predator model described by the Lotka-Volterra equations. The control strategy is conceived using the sliding mode control (SMC) approach which, based on the Lyapunov theorem, offers the possibility to track desired functions, thus guaranteeing the stability of the controlled system. This approach can be used for sustainable management of marine fish stocks: through the developed algorithm, the appropriate number of active fishermen and the suitable period for fishing can be determined. Computer simulations validate the proposed approach.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125825656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Edoardo Fadda, Daniele Manerba, R. Tadei, P. Camurati, G. Cabodi
Electric vehicles are accelerating the world’s transition to sustainable energy. Nevertheless, the lack of a proper charging station infrastructure in many real implementations still represents an obstacle for the spread of such a technology. In this paper, we present a real case application of optimization techniques ques in order to solve the location problem of electric charging stations in the district of Biella, Italy. The plan is composed by several progressive installations and decision makers pursue several objectives that might be in contrast. For this reason, we present an imiovative framework based on the comparison of several ad-hoc Key Performance Indicators for evaluating many different aspects of a location solution.
{"title":"KPIs for Optimal Location of charging stations for Electric Vehicles: the Biella case-study","authors":"Edoardo Fadda, Daniele Manerba, R. Tadei, P. Camurati, G. Cabodi","doi":"10.15439/2019F171","DOIUrl":"https://doi.org/10.15439/2019F171","url":null,"abstract":"Electric vehicles are accelerating the world’s transition to sustainable energy. Nevertheless, the lack of a proper charging station infrastructure in many real implementations still represents an obstacle for the spread of such a technology. In this paper, we present a real case application of optimization techniques ques in order to solve the location problem of electric charging stations in the district of Biella, Italy. The plan is composed by several progressive installations and decision makers pursue several objectives that might be in contrast. For this reason, we present an imiovative framework based on the comparison of several ad-hoc Key Performance Indicators for evaluating many different aspects of a location solution.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128214571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There has been research regarding relationship between human personalities and visiting places using Big Five Factor (BFF). However, other factors such as Social media usage, Hobby, Gender, Age, and Religion and so on are regarded as also major factors which effects the choice of visiting place of a person. Using questionnaire designed by authors, these factors as well as BFF were prepared for this research. The visiting places were collected by a smartphone app called SWARM and classified in 10 categories. In sum, personal data of 34 participants had been collected for several months. To Figure out the relationship between these factors and visiting places, random forest technique of ensemble method was used.
{"title":"Analysis of Relationship between Personal Factors and Visiting Places using Random Forest Technique","authors":"Young Myung Kim, H. Song","doi":"10.15439/2019F318","DOIUrl":"https://doi.org/10.15439/2019F318","url":null,"abstract":"There has been research regarding relationship between human personalities and visiting places using Big Five Factor (BFF). However, other factors such as Social media usage, Hobby, Gender, Age, and Religion and so on are regarded as also major factors which effects the choice of visiting place of a person. Using questionnaire designed by authors, these factors as well as BFF were prepared for this research. The visiting places were collected by a smartphone app called SWARM and classified in 10 categories. In sum, personal data of 34 participants had been collected for several months. To Figure out the relationship between these factors and visiting places, random forest technique of ensemble method was used.","PeriodicalId":168208,"journal":{"name":"2019 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128662433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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