Damianos Diasakos
Short CV: Damianos Diasakos was born in 2002 in Kalamata, Greece. In 2020, he began his studies as an undergraduate student in the Department of Computer Engineering and Informatics Department at the University of Patras. Some of his interests in the field of computer science are Mobile Telecommunication Networks, Machine Learning and Databases. He holds a certificate of Proficiency in English, obtained through the Michigan Language Assessment in 2018. He has been a member of the LDST team since 2023.
Conferences
Bouras, Christos; Diasakos, Damianos; Gkamas, Apostolos; Kokkinos, Vasileios; Pouyioutas, Philippos; Prodromos, Nikolaos
Simulation – based Beamforming Optimization in Moving Drones Conference
15th IFIP Wireless and Mobile Computing (IFIP WMNC), November 11 – 12, 2024, Venice, Italy, pp 1-6 (to appear) , 2024.
Abstract | Links | BibTeX | Tags:
@conference{nokeyc,
title = {Simulation – based Beamforming Optimization in Moving Drones},
author = {Christos Bouras and Damianos Diasakos and Apostolos Gkamas and Vasileios Kokkinos and Philippos Pouyioutas and Nikolaos Prodromos},
url = { https://telematics.upatras.gr/wp-content/uploads/2024/10/WMNC2024_cameraready_final.pdf},
year = {2024},
date = {2024-11-12},
urldate = {2024-11-12},
booktitle = {15th IFIP Wireless and Mobile Computing (IFIP WMNC), November 11 – 12, 2024, Venice, Italy, pp 1-6 (to appear)
},
pages = {1 - 6},
abstract = {The integration of drone technology with 5G networks presents novel opportunities for enhancing wireless communication systems. This paper explores the application of beamforming optimization techniques in dynamic environments, specifically focusing on moving drones in a simulated environment based on the DeepMIMO O1 scenario. By leveraging the unique properties of the O1 drone setup of DeepMIMO simulation environment, which simulates realistic urban mobility patterns at millimeter-wave (mmWave) frequencies, we propose a novel beamforming algorithm designed to optimize the signal quality and stability in highly mobile aerial networks. Key performance metrics used in this study include Signal-to-Noise Ratio (SNR), battery consumption, and power consumption of both the drones and the base station. Our findings indicate that the adaptive beamforming algorithm not only enhances the SNR and reduces power consumption but also optimizes battery usage compared
to conventional beamforming methods. This study enhances the understanding of mmWave beamforming dynamics in aerial scenarios but also lays the groundwork for future advancements
in drone-based communication networks.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The integration of drone technology with 5G networks presents novel opportunities for enhancing wireless communication systems. This paper explores the application of beamforming optimization techniques in dynamic environments, specifically focusing on moving drones in a simulated environment based on the DeepMIMO O1 scenario. By leveraging the unique properties of the O1 drone setup of DeepMIMO simulation environment, which simulates realistic urban mobility patterns at millimeter-wave (mmWave) frequencies, we propose a novel beamforming algorithm designed to optimize the signal quality and stability in highly mobile aerial networks. Key performance metrics used in this study include Signal-to-Noise Ratio (SNR), battery consumption, and power consumption of both the drones and the base station. Our findings indicate that the adaptive beamforming algorithm not only enhances the SNR and reduces power consumption but also optimizes battery usage compared
to conventional beamforming methods. This study enhances the understanding of mmWave beamforming dynamics in aerial scenarios but also lays the groundwork for future advancements
in drone-based communication networks.
to conventional beamforming methods. This study enhances the understanding of mmWave beamforming dynamics in aerial scenarios but also lays the groundwork for future advancements
in drone-based communication networks.
Prodromos, Nikolaos; Diasakos, Damianos; Kokkinos, Vasileios; Gkamas, Apostolos; Pouyioutas, Philippos; Bouras, Christos
Optimizing Network Slices: A Comparative Analysis of Allocation Algorithms for 5G Environments Conference
2024 International Conference on Future Communications and Networks (FCN 2024), November 18 - 22, 2024, Valetta, Malta (to appear), no. 1- 6, 2024.
@conference{nokeyb,
title = {Optimizing Network Slices: A Comparative Analysis of Allocation Algorithms for 5G Environments},
author = {Nikolaos Prodromos and Damianos Diasakos and Vasileios Kokkinos and Apostolos Gkamas and Philippos Pouyioutas and Christos Bouras},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/10/FCN2024_camera_ready.pdf},
year = {2024},
date = {2024-09-30},
urldate = {2024-09-30},
booktitle = {2024 International Conference on Future Communications and Networks (FCN 2024), November 18 - 22, 2024, Valetta, Malta (to appear)},
number = {1- 6},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Prodromos, Nikolaos; Diasakos, Damianos; Kokkinos, Vasileios; Gkamas, Apostolos; Bouras, Christos; Pouyioutas, Philippos
Dynamic Bandwidth Allocation in MIMO 5G Networks Conference
The 20th International Wireless Communications & Mobile Computing Conference (IWCMC 2024), May 27 – 31, 2024, Ayia Napa, Cyprus, 2024.
Abstract | Links | BibTeX | Tags:
@conference{4662,
title = {Dynamic Bandwidth Allocation in MIMO 5G Networks},
author = {Nikolaos Prodromos and Damianos Diasakos and Vasileios Kokkinos and Apostolos Gkamas and Christos Bouras and Philippos Pouyioutas},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/06/IWCMC2024_CR.pdf},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {The 20th International Wireless Communications & Mobile Computing Conference (IWCMC 2024), May 27 – 31, 2024, Ayia Napa, Cyprus},
pages = {97 - 102},
abstract = {The advent of 5G technology has ushered in a new era of wireless communication, characterized by its promise of high data rates, low latency, and enhanced connectivity. In this context, Multiple-Input Multiple-Output (MIMO) systems have emerged as a key enabler, leveraging advanced antenna arrays to simultaneously serve multiple users with increased spectral efficiency. This paper investigates the dynamic resource allocation problem in a MIMO 5G environment, where each user possesses distinct bandwidth requirements. The focus is on optimizing user allocation while considering the limited bandwidth and user capacity of base stations. By harnessing the
power of deep learning techniques, the proposed solution aims to efficiently manage the allocation of users to base station antennas, thereby maximizing overall network performance while accommodating heterogeneous user demands.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
The advent of 5G technology has ushered in a new era of wireless communication, characterized by its promise of high data rates, low latency, and enhanced connectivity. In this context, Multiple-Input Multiple-Output (MIMO) systems have emerged as a key enabler, leveraging advanced antenna arrays to simultaneously serve multiple users with increased spectral efficiency. This paper investigates the dynamic resource allocation problem in a MIMO 5G environment, where each user possesses distinct bandwidth requirements. The focus is on optimizing user allocation while considering the limited bandwidth and user capacity of base stations. By harnessing the
power of deep learning techniques, the proposed solution aims to efficiently manage the allocation of users to base station antennas, thereby maximizing overall network performance while accommodating heterogeneous user demands.
power of deep learning techniques, the proposed solution aims to efficiently manage the allocation of users to base station antennas, thereby maximizing overall network performance while accommodating heterogeneous user demands.
Bouras, Christos; Diasakos, Damianos; Katsigiannis, Chrysostomos; Kokkinos, Vasileios; Gkamas, Apostolos; Karacapilidis, Nikos; Charalabidis, Yannis; Lachana, Zoi; Alexopoulos, Charalampos; Papadopoulos, Theodoros; Karamanolis, Georgios; Psalidas, Michail
A Chatbot Generator for Improved Digital Governance Conference
20th European Mediterranean & Middle Eastern Conference on Information Systems (EMCIS 2023), December 11 – 12, 2023, Dubai, UAE, pp. 123-134, 2023.
Abstract | Links | BibTeX | Tags:
@conference{4657,
title = {A Chatbot Generator for Improved Digital Governance},
author = {Christos Bouras and Damianos Diasakos and Chrysostomos Katsigiannis and Vasileios Kokkinos and Apostolos Gkamas and Nikos Karacapilidis and Yannis Charalabidis and Zoi Lachana and Charalampos Alexopoulos and Theodoros Papadopoulos and Georgios Karamanolis and Michail Psalidas},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/06/A-Chatbot-Generator-for-Improved-Digital_.pdf},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {20th European Mediterranean & Middle Eastern Conference on Information Systems (EMCIS 2023), December 11 – 12, 2023, Dubai, UAE, pp. 123-134},
pages = {123-134},
abstract = {Chatbots, the pioneering conversational artificial intelligence (AI) agents, have experienced remarkable growth and integration in various domains. In modern societies, chatbots have emerged as transformative digital entities, revolutionizing the way humans interact with technology. These conversational AI agents have transcended their initial applications to become integral parts of various industries and daily life. One of the most prominent roles of chatbots is in customer service, where they offer round-the-clock assistance, swift issue resolution, and personalized interactions.By handling routine queries and tasks, chatbots free up human agents to focus on complex and specialized issues, thus optimizing overall efficiency and customer satisfaction. To this end, this paper aims to present and describe the architecture of a novel chatbot generator with improved functionality in terms of quality of communication with end users and level of provided services, with a specialized infrastructure understanding the Greek language. The chatbot generator was developed in the framework of a research project and will be pilot tested by two end-users, the National Bank of Greece (NBG) and the General Secretariat for Information Systems & Digital Governance (GSIS-DG).},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Chatbots, the pioneering conversational artificial intelligence (AI) agents, have experienced remarkable growth and integration in various domains. In modern societies, chatbots have emerged as transformative digital entities, revolutionizing the way humans interact with technology. These conversational AI agents have transcended their initial applications to become integral parts of various industries and daily life. One of the most prominent roles of chatbots is in customer service, where they offer round-the-clock assistance, swift issue resolution, and personalized interactions.By handling routine queries and tasks, chatbots free up human agents to focus on complex and specialized issues, thus optimizing overall efficiency and customer satisfaction. To this end, this paper aims to present and describe the architecture of a novel chatbot generator with improved functionality in terms of quality of communication with end users and level of provided services, with a specialized infrastructure understanding the Greek language. The chatbot generator was developed in the framework of a research project and will be pilot tested by two end-users, the National Bank of Greece (NBG) and the General Secretariat for Information Systems & Digital Governance (GSIS-DG).
Bouras, Christos; Diasakos, Damianos; Apostolopoulos, A; Kokkinos, Vasileios; Pouyioutas, Philippos; Prpdromos, Nikolaos
Evaluation of User Allocation Techniques in Massive MIMO 5G Networks Conference
The 10th International Conference on wireless Networks and Mobile Communications (WINCOM 2023), October 26 – 28, 2023, Istanbul, Turkey, pp. 1-6, 2023.
Abstract | Links | BibTeX | Tags:
@conference{4654,
title = {Evaluation of User Allocation Techniques in Massive MIMO 5G Networks},
author = {Christos Bouras and Damianos Diasakos and A Apostolopoulos and Vasileios Kokkinos and Philippos Pouyioutas and Nikolaos Prpdromos},
url = {https://telematics.upatras.gr/evaluation-of-user-allocation-techniques-in-massive-mimo-5g-networks/},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {The 10th International Conference on wireless Networks and Mobile Communications (WINCOM 2023), October 26 – 28, 2023, Istanbul, Turkey, pp. 1-6},
pages = {1 - 6},
abstract = {Massive MIMO (Multiple Input Multiple Output) is a fundamental technique for improving the efficiency of 5G wireless networks. At the base station, it calls for the use of numerous antennas—usually in the dozens or even hundreds. In addition to better coverage and less interference, this enables a large increase in the amount of data that can be delivered and received simultaneously. By enabling more precise signal transmission and reception, Massive MIMO can also result in significant energy savings. The use of optimization techniques can further improve the performance of 5G networks. The aim of this paper is to investigate a signal quality optimization technique for MIMO in which users are allocated to antennas according to different algorithms. For our research, the DeepMIMO simulator produced a dataset that sets up all necessary parameters. In our study, we examine different techniques for user allocation in 5G MIMO Networks. We conclude that transforming the problem of user allocation to a linear assignment problem in order to find the most efficient connection between the users and the base stations is one of the best ways to optimize user allocation.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Massive MIMO (Multiple Input Multiple Output) is a fundamental technique for improving the efficiency of 5G wireless networks. At the base station, it calls for the use of numerous antennas—usually in the dozens or even hundreds. In addition to better coverage and less interference, this enables a large increase in the amount of data that can be delivered and received simultaneously. By enabling more precise signal transmission and reception, Massive MIMO can also result in significant energy savings. The use of optimization techniques can further improve the performance of 5G networks. The aim of this paper is to investigate a signal quality optimization technique for MIMO in which users are allocated to antennas according to different algorithms. For our research, the DeepMIMO simulator produced a dataset that sets up all necessary parameters. In our study, we examine different techniques for user allocation in 5G MIMO Networks. We conclude that transforming the problem of user allocation to a linear assignment problem in order to find the most efficient connection between the users and the base stations is one of the best ways to optimize user allocation.
Bouras, Christos; Diasakos, Damianos; Katsigiannis, Chrysostomos; Kokkinos, Vasileios; Gkamas, Apostolos; Karacapilidis, Nikos; Charalabidis, Yannis; Lachana, Zoi; Alexopoulos, Charalampos; Papadopoulos, Theodoros; Karamanolis, Georgios; Psalidas, Michail
On the Development of a Novel Chatbot Generator Architecture: Design and Assessment Issues Conference
8th IEEE International Conference on Mathematics and Computers in Sciences (MCSI 2023), October 14 - 16, 2023, Athens, Greece, pp. 83-88, 2023.
Abstract | Links | BibTeX | Tags:
@conference{4655,
title = {On the Development of a Novel Chatbot Generator Architecture: Design and Assessment Issues},
author = {Christos Bouras and Damianos Diasakos and Chrysostomos Katsigiannis and Vasileios Kokkinos and Apostolos Gkamas and Nikos Karacapilidis and Yannis Charalabidis and Zoi Lachana and Charalampos Alexopoulos and Theodoros Papadopoulos and Georgios Karamanolis and Michail Psalidas},
url = {https://telematics.upatras.gr/wp-content/uploads/2024/06/MCSI2023_Bouras-2.pdf},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {8th IEEE International Conference on Mathematics and Computers in Sciences (MCSI 2023), October 14 - 16, 2023, Athens, Greece, pp. 83-88},
pages = {83 - 88 },
abstract = {Chatbots are witnessing remarkable growth in various fields. In modern society, chatbots have evolved into innovative digital entities that have revolutionized the way people interact with technology. These conversational AI agents have gone beyond their initial uses to become an integral part of various industries. One of the most important roles of chatbots is customer service, providing 24/7 support, quick problem resolution, and personalized interactions. Chatbots free up human agents by handling routine queries and tasks, allowing them to focus on complex and specific issues, optimizing the overall efficiency and customer satisfaction. To this end, this paper aims to present the architecture of a novel chatbot generator with improved functionality in terms of quality of communication with end users and level of provided services. In addition, the paper presents the results of two pilot chatbots assessment by users with experience in artificial intelligence and chatbot technology.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Chatbots are witnessing remarkable growth in various fields. In modern society, chatbots have evolved into innovative digital entities that have revolutionized the way people interact with technology. These conversational AI agents have gone beyond their initial uses to become an integral part of various industries. One of the most important roles of chatbots is customer service, providing 24/7 support, quick problem resolution, and personalized interactions. Chatbots free up human agents by handling routine queries and tasks, allowing them to focus on complex and specific issues, optimizing the overall efficiency and customer satisfaction. To this end, this paper aims to present the architecture of a novel chatbot generator with improved functionality in terms of quality of communication with end users and level of provided services. In addition, the paper presents the results of two pilot chatbots assessment by users with experience in artificial intelligence and chatbot technology.