Panagiotis Leliopoulos
University of Piraeus, Digital Systems (DS), Graduate Student
- Panagiotis Leliopoulos is holding a Bachelor Degree on Electronic Engineering and three Master Degrees (M.Sc.): On IC... morePanagiotis Leliopoulos is holding a Bachelor Degree on Electronic Engineering and three Master Degrees (M.Sc.): On ICT with direction on the Network-Oriented Information Systems and Cloud Computing from the University of Piraeus, on Business Analytics from the Athens University of Economics and Business and on Data Science from the National Centre for Scientific Research "Demokritos", and the University of the Peloponnese.Hence, he has experience on the Hadoop framework and Map-Reduce processes and he is developing Map-Reduce Skyline Algorithms for Research. Furthermore, he has published articles on e-Commerce, about “The Evolution of Business to Consumer (B2C) E-Commerce” (posted in dblp), and on Education, about “The Use of Big Data in Education” in international conferences and journals. At the end, he has work experience as Consultant and Technical Project Manager on ICT applications, in the Public and Private sector and Telecommunication Companies.edit
Research Interests:
In this Master Thesis we study the performance of a computer cluster, based on the developing on a skyline algorithm. Furthermore the particular algorithm is implemented so as to run parallel in distributed systems, with the method of... more
In this Master Thesis we study the performance of a computer cluster, based on the developing on a skyline algorithm. Furthermore the particular algorithm is implemented so as to run parallel in distributed systems, with the method of MapReduce. Specifically, the experimental part of the work consists of a computer cluster from one to four nodes. Also we compared the timing to three different dataset of 2000 points. Hence, we are counting separately the time performance of each dataset from one up to four nodes respectively. The development of the application is based on the method of MapReduce, and implemented on the R language. The basic architecture is essentially three basic functions such as the random number generator, the classification of items in ascending order by column, and finally the calculation of the skyline points. Finally our application has been tested locally on a computer by using Virtual Machines, which are based on the Cloudera platform. Furthermore our cluster is able to run on Cloud Computing platform.
Research Interests: Distributed Computing, Clusters & Networks, R programming language, Hadoop, Map Reduce, and 10 moreParallel & Distributed Computing, Big Data, Skyline, Big Data Analytics, MapReduce and Hadoop, Skyline queries, Adaptive MapReduce In Hadoop, Hadoop Developer, HDFS (Hadoop Distributed File System), and Big Data and Hadoop
This paper is a study on the use of Big Data in Education. Analyzed how the Big Data and Open Data technology can actually involve to education. Furthermore how big mounts of unused data can benefit and improve education. Providing some... more
This paper is a study on the use of Big Data in Education. Analyzed how the Big Data and Open Data technology can actually involve to education. Furthermore how big mounts of unused data can benefit and improve education. Providing some new tools and methods bypassing the traditional difficulties and open a new way of education.
Research Interests:
This paper is a review on Business to Consumer (B2C) electronic commerce (e-commerce) and it studies its evolution over the last decade. The Internet characteristics that affect B2C are the Internet growth, which at first includes the... more
This paper is a review on Business to Consumer (B2C) electronic commerce (e-commerce) and it studies its evolution over the last decade. The Internet characteristics that affect B2C are the Internet growth, which at first includes the number of Internet users and secondly, the infrastructure, which is basically the quality and speed of the lines. Moreover, the way the Internet growth has affected the B2C e-commerce growth over the last ten years is studied in three major countries-areas. The USA because it is an Internet developed country with vast e-commerce sales, China because it is a rapidly developing Internet country with a large number of users and fast e-commerce activity growth in the last decade and finally, the European Union, because of its diversity in Internet and e-commerce growth. This paper focuses on the aforementioned three geographic areas and extracts its conclusions from the observations of B2C behavior growth in these areas.
Research Interests:
This paper is a study on the use of Big Data in Education. Analyzed how the Big Data and Open Data technology can actually involve to education. Furthermore how big mounts of unused data can benefit and improve education. Providing some... more
This paper is a study on the use of Big Data in Education. Analyzed how the Big Data and Open Data technology can actually involve to education. Furthermore how big mounts of unused data can benefit and improve education. Providing some new tools and methods bypassing the traditional difficulties and open a new way of education.
Research Interests:
Η χρήση των ΤΠΕ έχει εφαρμογή στις περισσότερες δραστηριότητες του σύγχρονου πολιτισμού. Σε αυτό το πλαίσιο δεν θα μπορούσε να εξαιρεθεί η εκπαίδευση, μιας που οι ανάγκες της αναφορικά με την αξιοποίηση των νέων τεχνολογιών έχουν αυξηθεί... more
Η χρήση των ΤΠΕ έχει εφαρμογή στις περισσότερες δραστηριότητες του σύγχρονου πολιτισμού. Σε αυτό το πλαίσιο δεν θα μπορούσε να εξαιρεθεί η εκπαίδευση, μιας που οι ανάγκες της αναφορικά με την αξιοποίηση των νέων τεχνολογιών έχουν αυξηθεί τα τελευταία χρόνια. Ειδικότερα, η στροφή στην χρήση των ΤΠΕ στην εκπαίδευση έχει συχνά«κατευθύνει» την εκπαίδευση, σε προσανατολισμένες στον μαθητή (student-centered) προσεγγίσεις. Μέσα από την παρούσα εργασία, θα επιχειρήσουμε μια συνοπτική περιγραφή του εργαλείου «Microsoft Expression Blend», αναφερόμενοι στις δυνατότητές του, σχετικά με τη δημιουργία διαδραστικών εφαρμογών. Οι εφαρμογές αυτές, μπορούν να υλοποιηθούν στα πλαίσια εργαστηριακών μαθημάτων προπτυχιακού επιπέδου της Ανώτατης Τεχνολογικής Εκπαίδευσης και να προσφέρουν εκπαιδευτικά οφέλη στους φοιτητές αυτούς. Επιπλέον, θα αναφερθούμε στα πλεονεκτήματα του συγκεκριμένου εργαλείου, σχετικά με την χρήση του αντικειμενοστραφούς προγραμματισμού(object oriented programming). Η σημασία της αξ...
In this Master Thesis we study the performance of a computer cluster, based on the developing on a skyline algorithm. Furthermore the particular algorithm is implemented so as to run parallel in distributed systems, with the method of... more
In this Master Thesis we study the performance of a computer cluster, based on the developing on a skyline algorithm. Furthermore the particular algorithm is implemented so as to run parallel in distributed systems, with the method of MapReduce.
Specifically, the experimental part of the work consists of a computer cluster from one to four nodes. Also we compared the timing to three different dataset of 2000 points. Hence, we are counting separately the time performance of each dataset from one up to four nodes respectively.
The development of the application is based on the method of MapReduce, and implemented on the R language. The basic architecture is essentially three basic functions such as the random number generator, the classification of items in ascending order by column, and finally the calculation of the skyline points.
Finally our application has been tested locally on a computer by using Virtual Machines, which are based on the Cloudera platform. Furthermore our cluster is able to run on Cloud Computing platform.
Specifically, the experimental part of the work consists of a computer cluster from one to four nodes. Also we compared the timing to three different dataset of 2000 points. Hence, we are counting separately the time performance of each dataset from one up to four nodes respectively.
The development of the application is based on the method of MapReduce, and implemented on the R language. The basic architecture is essentially three basic functions such as the random number generator, the classification of items in ascending order by column, and finally the calculation of the skyline points.
Finally our application has been tested locally on a computer by using Virtual Machines, which are based on the Cloudera platform. Furthermore our cluster is able to run on Cloud Computing platform.