{"title":"Network slicing for 5G networks: A survey and an analysis of future trends","authors":"A. Kaloxylos","doi":"10.1145/3139367.3139392","DOIUrl":"https://doi.org/10.1145/3139367.3139392","url":null,"abstract":"The support of network slicing in 5G networks is one of the hottest research topics. Slicing is considered to be one of the key enablers for multi-tenancy support and multi-service provision. During the past years, network slicing has been thoroughly investigated, but still several issues remain open. This paper provides a comprehensive overview of solutions and discusses the main trends and open issues.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130977105","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}
{"title":"RiSKi: A Framework for Modeling Cyber Threats to Estimate Risk for Data Breach Insurance","authors":"A. Panou, Christoforos Ntantogian, C. Xenakis","doi":"10.1145/3139367.3139426","DOIUrl":"https://doi.org/10.1145/3139367.3139426","url":null,"abstract":"Historically, the financial benefits of cyber security investments have not been calculated with the same financial discipline used to evaluate other material investments. This was mainly due to a lack of readily available data on cyber incidents impacts and systematic methodology to support the efficacy of cyber investments. In this paper we propose an innovative, cyber investment management framework named RiSKi that incorporates detection and continuous monitoring of insiders societal behavior, to the extent permitted by the law, to proactively address implied anomalies and threats and their potential business impact and risks. Moreover, it provides access to published security incidents data to enable businesses to advance their understanding of cybersecurity and awareness of the threats and consequences related to cyber breaches, and, eventually, enable faster recovery from an event. RiSKI armed with the above information, employs a methodology, and develops a supporting scenario-based cyber investment tool, for quantifying the benefits of cybersecurity investments against the many ways that potential cyber risks can affect the operation of a business.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116244913","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}
{"title":"Automated parameter selection of scheduling algorithms using machine learning techniques","authors":"P. Alefragis, Charalampos Sofos","doi":"10.1145/3139367.3139442","DOIUrl":"https://doi.org/10.1145/3139367.3139442","url":null,"abstract":"The work describes the effort to automatically select scheduling algorithms and generate corresponding parameters for new problem instances based on the results obtained for similar problem instances that have been extensively investigated. The effort tries to vastly reduce the development cycle of optimization algorithms as parameter tuning is usually more time consuming that implementing the algorithm or model. We investigated various heuristic methods for hyper-parameter selection and evaluated different machine learning methods. The results are very promising as selecting the top 5% combination of algorithms and parameters manages to consistently achieve results that are in the top 10% of the generated solutions, if full parameter and algorithm execution is performed.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122914160","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}
Olga Tsesmetzoglou, Paris Xyntarianos-Tsiropinas, T. Spyrou
{"title":"SAV-IT: A software tool for interpreting and presenting dynamic Street Art image maps","authors":"Olga Tsesmetzoglou, Paris Xyntarianos-Tsiropinas, T. Spyrou","doi":"10.1145/3139367.3139399","DOIUrl":"https://doi.org/10.1145/3139367.3139399","url":null,"abstract":"The purpose of this paper, is to present \"Street Art Variation - Interpretation Tool\" (a Street Art interventions 1 collection software tool) while unfolding the polymorphic character of its culture. Street Art is a method of expression, which can communicate thoughts, emotions and messages via images and symbols to everyone. The SAV-IT involves and expands the visual communication element of Street Art. The visual interventions can be anatomized with the creation of intense and compelling image maps of interconnected art works. Thus, the system exhibits all the unique ways each artist creates from their own perspective, influenced by the general context they interact with. The SAV-IT offers a well-organized and well-structured environment, based on a relational database. Not only are the interventions fully explained and assorted into categories such as message, technique, style and aesthetic, they are also categorized according to their subordinate characteristics such as size, surface etc. Since the former one share the basic features with which each artist works so as to communicate reflections, they constitute the core parameters of categorization.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126652800","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}
I. Livieris, Stamatis Karlos, V. Tampakas, P. Pintelas
{"title":"A hybrid conjugate gradient method based on the self-scaled memoryless BFGS update","authors":"I. Livieris, Stamatis Karlos, V. Tampakas, P. Pintelas","doi":"10.1145/3139367.3139384","DOIUrl":"https://doi.org/10.1145/3139367.3139384","url":null,"abstract":"In this work, we present a new conjugate gradient method adapting the approach of the hybridization of the conjugate gradient update parameters of DY and HS+ convexly, which is based on a quasi-Newton philosophy. The computation of the hybrization parameter is obtained by minimizing the distance between the hybrid conjugate gradient direction and the self-scaling memoryless BFGS direction. Our numerical experiments indicate that our proposed method is preferable and in general superior to classic conjugate gradient methods in terms of efficiency and robustness.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133194484","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}
{"title":"Automating the generation of hardware accelerators from custom arithmetic functions","authors":"Giannis Petrousov, M. Dasygenis","doi":"10.1145/3139367.3139421","DOIUrl":"https://doi.org/10.1145/3139367.3139421","url":null,"abstract":"Field programmable gate arrays (FPGAs) have become the standard for fast prototyping and evaluation of custom IP cores. However, the creation of complex circuits is a time consuming and error prone task with repeating procedures such as testing and verification. And even though there are several EDA tools which generate intellectual property (IP) blocks for specific purposes, to the best of our knowledge, there are no online tools able to design IP blocks from custom arithmetic functions. In this paper, we introduce our proof of concept (POC) circuit generator which is able to produce custom and verified hardware accelerators, specified in HDL, to speed up arbitrary integer arithmetic functions.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133705826","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}
Antonios T. Makaratzis, C. Filelis-Papadopoulos, K. M. Giannoutakis, G. Gravvanis, D. Tzovaras
{"title":"A comparative study of CPU power consumption models for cloud simulation frameworks","authors":"Antonios T. Makaratzis, C. Filelis-Papadopoulos, K. M. Giannoutakis, G. Gravvanis, D. Tzovaras","doi":"10.1145/3139367.3139409","DOIUrl":"https://doi.org/10.1145/3139367.3139409","url":null,"abstract":"In this paper a comparative study of CPU power models that have been widely used in cloud simulation environments is conducted. Generic CPU power models for the estimation of the energy consumption of CPU servers have been proposed in cloud simulation frameworks, since estimations of the energy consumption of cloud computing infrastructures can be obtained through simulation experimentation. The main characteristic of these models is that they have low computational complexity and can be applied to a wide range of modern CPU servers. A recently proposed CPU power consumption model, based on a third degree polynomial, is examined and evaluated. A comparative study based on available CPU power measurements of CPU servers, obtained from SPEC benchmark, is conducted. Additionally, experimentation on three CPU servers is performed and power measurements are obtained for various workloads in order evaluate the estimations of the different CPU power models.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130782217","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}
I. Chochliouros, S. Ziegler, L. Bolognini, N. Alonistioti, M. Stamatelatos, Panagiotis Kontopoulos, G. Mourikas, V. Vlachos, N. Gligoric, Marita Holst
{"title":"Enabling Crowd-sourcing-based Privacy Risk Assessment in EU: the Privacy Flag Project","authors":"I. Chochliouros, S. Ziegler, L. Bolognini, N. Alonistioti, M. Stamatelatos, Panagiotis Kontopoulos, G. Mourikas, V. Vlachos, N. Gligoric, Marita Holst","doi":"10.1145/3139367.3139417","DOIUrl":"https://doi.org/10.1145/3139367.3139417","url":null,"abstract":"Personal data have become merchandisable asset encouraging stakeholders to collect and trade them without end-user's awareness and acceptance. Although EU is adapting the legal framework, the extent of applications most of which are developed from outside the EU jurisdiction, strongly limit the possibility to effectively impose a privacy-protection framework globally. The Privacy Flag project researches and combines the potential of crowdsourcing, ICT technologies and legal expertise for enabling citizens monitoring and controlling their privacy1.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116511197","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}
{"title":"Personalized Learning Pathways using semantic web rules","authors":"Omiros Iatrellis, A. Kameas, P. Fitsilis","doi":"10.1145/3139367.3139404","DOIUrl":"https://doi.org/10.1145/3139367.3139404","url":null,"abstract":"Information technology has the potential to greatly improve the quality of services offered by educational institutions. Personalized learning requires adaptive learning schemes since the student status and conditions inside an institution constantly change. In this paper, we present the EDUC8 (EDUCATE) system, which aims at providing a new approach concerning real-time personalization and adaptation of learning business processes. The EDUC8 system consists of a learning process execution engine supported by a semantic framework, which is based on an ontology enclosing the knowledge and the information and provides decisions and recommendations for the next steps of the learning process. Moreover, the results of the rule-set execution may create new objects that will be stored in the ontology as new knowledge1.","PeriodicalId":436862,"journal":{"name":"Proceedings of the 21st Pan-Hellenic Conference on Informatics","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115964563","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}