2021
D. Pliatsios; A.A. Boulogeorgos; T. Lagkas; V. Argyriou; I. Moscholios; P. Sarigiannidis
Semi-Grant-Free Non-Orthogonal Multiple Access for Tactile Internet of Things Conference
2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) (IEEE PIMRC 2021), 2021.
Abstract | BibTeX | Tags: Grant-Free, Internet of things, Non-orthogonal multiple access | Links:
@conference{D2021,
title = {Semi-Grant-Free Non-Orthogonal Multiple Access for Tactile Internet of Things},
author = {D. Pliatsios and A.A. Boulogeorgos and T. Lagkas and V. Argyriou and I. Moscholios and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/352551145_Semi-Grant-Free_Non-Orthogonal_Multiple_Access_for_Tactile_Internet_of_Things},
doi = {10.1109/PIMRC50174.2021.9569640},
year = {2021},
date = {2021-09-12},
booktitle = {2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) (IEEE PIMRC 2021)},
abstract = {Ultra-low latency connections for a massive number of devices are one of the main requirements of the nextgeneration tactile Internet-of-Things (TIoT). Grant-free nonorthogonal multiple access (GF-NOMA) is a novel paradigm that leverages the advantages of grant-free access and non-orthogonal transmissions, to deliver ultra-low latency connectivity. In this work, we present a joint channel assignment and power allocation solution for semi-GF-NOMA systems, which provides access to both grant-based (GB) and grant-free (GF) devices, maximizes the network throughput, and is capable of ensuring each device's throughput requirements. In this direction, we provide the mathematical formulation of the aforementioned problem. After explaining that it is not convex, we propose a solution strategy based on the Lagrange multipliers and subgradient method. To evaluate the performance of our solution, we carry out system-level Monte Carlo simulations. The simulation results indicate that the proposed solution can optimize the total system throughput and achieve a high association rate, while taking into account the minimum throughput requirements of both GB and GF devices.},
keywords = {Grant-Free, Internet of things, Non-orthogonal multiple access},
pubstate = {published},
tppubtype = {conference}
}
Ultra-low latency connections for a massive number of devices are one of the main requirements of the nextgeneration tactile Internet-of-Things (TIoT). Grant-free nonorthogonal multiple access (GF-NOMA) is a novel paradigm that leverages the advantages of grant-free access and non-orthogonal transmissions, to deliver ultra-low latency connectivity. In this work, we present a joint channel assignment and power allocation solution for semi-GF-NOMA systems, which provides access to both grant-based (GB) and grant-free (GF) devices, maximizes the network throughput, and is capable of ensuring each device's throughput requirements. In this direction, we provide the mathematical formulation of the aforementioned problem. After explaining that it is not convex, we propose a solution strategy based on the Lagrange multipliers and subgradient method. To evaluate the performance of our solution, we carry out system-level Monte Carlo simulations. The simulation results indicate that the proposed solution can optimize the total system throughput and achieve a high association rate, while taking into account the minimum throughput requirements of both GB and GF devices.
I.A. Chousainov; I. Moscholios; P. Sarigiannidis; M. Logothetis
Multiservice Loss Models for Cloud Radio Access Networks Journal Article
In: IEEE Access, 2021.
Abstract | BibTeX | Tags: call blocking, Cloud-radio access, convolution, poisson process | Links:
@article{Chousainov2021,
title = {Multiservice Loss Models for Cloud Radio Access Networks},
author = {I.A. Chousainov and I. Moscholios and P. Sarigiannidis and M. Logothetis},
url = {https://www.researchgate.net/publication/353991171_Multiservice_Loss_Models_for_Cloud_Radio_Access_Networks},
doi = {10.1109/ACCESS.2021.3105946},
year = {2021},
date = {2021-08-18},
journal = {IEEE Access},
abstract = {In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units which form a common pool of computational resource units. Depending on their capacity, the RRHs may form one or more clusters. Each RRH accommodates multiservice traffic, i.e., calls from different service-classes with different radio and computational resource requirements. Arriving calls follow a Poisson process and simultaneously require radio and computational resource units in order to be accepted in the serving RRH. If their resource requirements cannot be met then calls are blocked and lost. Otherwise, calls remain in the serving RRH for a generally distributed service time. Assuming the single-cluster C-RAN, we model it as a multiservice loss system, prove that a product form solution exists for the steady-state probabilities and determine call blocking probabilities via an efficient convolution algorithm whose accuracy is validated via simulation. Furthermore, we generalize the previous multiservice loss model by considering the more complex multi-cluster case where RRHs of the same capacity are grouped in different clusters.},
keywords = {call blocking, Cloud-radio access, convolution, poisson process},
pubstate = {published},
tppubtype = {article}
}
In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units which form a common pool of computational resource units. Depending on their capacity, the RRHs may form one or more clusters. Each RRH accommodates multiservice traffic, i.e., calls from different service-classes with different radio and computational resource requirements. Arriving calls follow a Poisson process and simultaneously require radio and computational resource units in order to be accepted in the serving RRH. If their resource requirements cannot be met then calls are blocked and lost. Otherwise, calls remain in the serving RRH for a generally distributed service time. Assuming the single-cluster C-RAN, we model it as a multiservice loss system, prove that a product form solution exists for the steady-state probabilities and determine call blocking probabilities via an efficient convolution algorithm whose accuracy is validated via simulation. Furthermore, we generalize the previous multiservice loss model by considering the more complex multi-cluster case where RRHs of the same capacity are grouped in different clusters.
I. Siniosoglou; V. Argyriou; S. Bibi; T. Lagkas; P. Sarigiannidis
Unsupervised Ethical Equity Evaluation of Adversarial Federated Networks Conference
The 16th International Conference on Availability, Reliability and Security, 2021.
Abstract | BibTeX | Tags: adverserial federated networks, machine learning, security | Links:
@conference{Siniosoglou2021c,
title = {Unsupervised Ethical Equity Evaluation of Adversarial Federated Networks},
author = {I. Siniosoglou and V. Argyriou and S. Bibi and T. Lagkas and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/353936098_Unsupervised_Ethical_Equity_Evaluation_of_Adversarial_Federated_Networks},
doi = {10.1145/3465481.3470478},
year = {2021},
date = {2021-08-17},
booktitle = {The 16th International Conference on Availability, Reliability and Security},
pages = {1-6},
abstract = {While the technology of Deep Learning (DL) is a powerful tool when properly trained for image analysis and classification applications, some factors for its optimization rely solely on the training data and their environment. In an effort to tackle the problem of knowledge bias created during the training process of a Deep Neural Network (DNN) and specifically Adversarial Networks for image augmentation, this work presents an entirely unsupervised methodology for discovering the unfairness level of Deep Learning (DL) models and in extend, its wrongly accumulated or biased classes. Fdi, the proposed evaluation metric for quantizing the level of unfairness of a model is introduced, along with the method of weighting the model’s knowledge and producing its weakest aspects in a data-agnostic way.},
keywords = {adverserial federated networks, machine learning, security},
pubstate = {published},
tppubtype = {conference}
}
While the technology of Deep Learning (DL) is a powerful tool when properly trained for image analysis and classification applications, some factors for its optimization rely solely on the training data and their environment. In an effort to tackle the problem of knowledge bias created during the training process of a Deep Neural Network (DNN) and specifically Adversarial Networks for image augmentation, this work presents an entirely unsupervised methodology for discovering the unfairness level of Deep Learning (DL) models and in extend, its wrongly accumulated or biased classes. Fdi, the proposed evaluation metric for quantizing the level of unfairness of a model is introduced, along with the method of weighting the model’s knowledge and producing its weakest aspects in a data-agnostic way.
P. Diamantoulakis; P. Bouzinis; P. Sarigiannidis; Z. Ding; G. Karagiannidis
Optimal Design and Orchestration of Mobile Edge Computing with Energy Awareness Journal Article
In: IEEE Transactions on Sustainable Computing , vol. 1, no. 1, 2021.
Abstract | BibTeX | Tags: energy consumption, mobile edge computing, multiple access, task offloading | Links:
@article{Diamantoulakis2021,
title = {Optimal Design and Orchestration of Mobile Edge Computing with Energy Awareness},
author = {P. Diamantoulakis and P. Bouzinis and P. Sarigiannidis and Z. Ding and G. Karagiannidis},
url = {https://www.researchgate.net/publication/352908814_Optimal_Design_and_Orchestration_of_Mobile_Edge_Computing_with_Energy_Awareness},
doi = {10.1109/TSUSC.2021.3103476},
year = {2021},
date = {2021-08-13},
journal = {IEEE Transactions on Sustainable Computing },
volume = {1},
number = {1},
abstract = {In this work, we propose the use of an advanced multiple access technique and its joint design with adaptive task offloading, in order to reduce delay and energy consumption. More specifically, the use of generalized hybrid orthogonal/non-orthogonal multiple access (OMA/NOMA) for MEC is introduced, which is theoretically superior to other alternatives from the existing literature. In more detail, the proposed scheme is based on the joint utilization of dynamic user scheduling among OMA/NOMA phases and variable decoding order during the successive interference cancellation in NOMA phase. Also, the systems orchestration is optimized for both full and partial task offloading. Specifically, in full offloading scenario, the user scheduling, time allocation, and power control are jointly optimized. Regarding partial offloading, the computational resources, i.e., the clock speed of the local processors and the number of offloaded bits, are jointly optimized with the communication resources, taking into account the constraint of the energy that is consumed for both local processing and task offloading, which is particularly challenging due to the non-convex nature of the corresponding optimization problem. All optimization problems are efficiently solved by either using closed-form solutions that provide useful insights or low-complexity algorithms.},
keywords = {energy consumption, mobile edge computing, multiple access, task offloading},
pubstate = {published},
tppubtype = {article}
}
In this work, we propose the use of an advanced multiple access technique and its joint design with adaptive task offloading, in order to reduce delay and energy consumption. More specifically, the use of generalized hybrid orthogonal/non-orthogonal multiple access (OMA/NOMA) for MEC is introduced, which is theoretically superior to other alternatives from the existing literature. In more detail, the proposed scheme is based on the joint utilization of dynamic user scheduling among OMA/NOMA phases and variable decoding order during the successive interference cancellation in NOMA phase. Also, the systems orchestration is optimized for both full and partial task offloading. Specifically, in full offloading scenario, the user scheduling, time allocation, and power control are jointly optimized. Regarding partial offloading, the computational resources, i.e., the clock speed of the local processors and the number of offloaded bits, are jointly optimized with the communication resources, taking into account the constraint of the energy that is consumed for both local processing and task offloading, which is particularly challenging due to the non-convex nature of the corresponding optimization problem. All optimization problems are efficiently solved by either using closed-form solutions that provide useful insights or low-complexity algorithms.
V. Moysiadis; T. Lagkas; V. Argyriou; A. Sarigiannidis; I. Moscholios; P. Sarigiannidis
Extending ADR mechanism for LoRa enabled mobile end-devices Journal Article
In: Simulation Modelling Practice and Theory, vol. 102388, 2021.
Abstract | BibTeX | Tags: adaptive data rate, energy consumption, LoRa, LoRaWAN, mobile devices | Links:
@article{Moysiadis2021b,
title = {Extending ADR mechanism for LoRa enabled mobile end-devices},
author = {V. Moysiadis and T. Lagkas and V. Argyriou and A. Sarigiannidis and I. Moscholios and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/353860976_Extending_ADR_mechanism_for_LoRa_enabled_mobile_end-devices},
doi = {10.1016/j.simpat.2021.102388},
year = {2021},
date = {2021-08-08},
journal = {Simulation Modelling Practice and Theory},
volume = {102388},
abstract = {A considerable percentage of Internet of Things end-devices are characterised by mobility, a feature that adds extra complexity to protocols used in Wireless Sensor Networks. LoRa is one of the newly introduced wireless sensor protocols, capable of delivering messages in long distances and consuming low energy, features that make it proper for low cost devices. Although LoRa was introduced as a technology for stationary devices, it can also be used for mobile devices of low speed. In this paper, we introduce an enhancement to Adaptive Data Rate (ADR) mechanism to enable mobile LoRa, by improving the connection reliability of mobile end-devices, while keeping energy consumption at low levels. Firstly, we propose the Linear Regression - ADR (LR-ADR) mechanism for the Network Server side to smooth the Signal to Noise Ratio (SNR) estimates per gateway and predict the SNR of the next transmission. Secondly, we propose the Linear Regression + ADR (LR+ADR) mechanism, an adaptive method for the end-device side to regain the connectivity faster with the Network Server. We conducted simulation modelling to evaluate the performance of our implementation while we compared our results with four alternative solutions ADR, ADR+, EMA-ADR, G-ADR. The results prove that our first approach (LR-ADR) performs better than the best competitor, and our second approach (LR+ADR) brings an additional improvement in terms of Packet Delivery Ratio (PDR), while they retain the Energy Consumption per Packet Delivered (ECPD) at low levels. In particular, in a scenario that mimics real world conditions, LR+ADR presents an increase of up to 520% for PDR compared to the original ADR and an improvement of up to 38% compared to the best competitor (G-ADR). Moreover, it reduces ECPD up to 74% compared to the original ADR, while keeping it at the same level with the best competitor (G-ADR).},
keywords = {adaptive data rate, energy consumption, LoRa, LoRaWAN, mobile devices},
pubstate = {published},
tppubtype = {article}
}
A considerable percentage of Internet of Things end-devices are characterised by mobility, a feature that adds extra complexity to protocols used in Wireless Sensor Networks. LoRa is one of the newly introduced wireless sensor protocols, capable of delivering messages in long distances and consuming low energy, features that make it proper for low cost devices. Although LoRa was introduced as a technology for stationary devices, it can also be used for mobile devices of low speed. In this paper, we introduce an enhancement to Adaptive Data Rate (ADR) mechanism to enable mobile LoRa, by improving the connection reliability of mobile end-devices, while keeping energy consumption at low levels. Firstly, we propose the Linear Regression - ADR (LR-ADR) mechanism for the Network Server side to smooth the Signal to Noise Ratio (SNR) estimates per gateway and predict the SNR of the next transmission. Secondly, we propose the Linear Regression + ADR (LR+ADR) mechanism, an adaptive method for the end-device side to regain the connectivity faster with the Network Server. We conducted simulation modelling to evaluate the performance of our implementation while we compared our results with four alternative solutions ADR, ADR+, EMA-ADR, G-ADR. The results prove that our first approach (LR-ADR) performs better than the best competitor, and our second approach (LR+ADR) brings an additional improvement in terms of Packet Delivery Ratio (PDR), while they retain the Energy Consumption per Packet Delivered (ECPD) at low levels. In particular, in a scenario that mimics real world conditions, LR+ADR presents an increase of up to 520% for PDR compared to the original ADR and an improvement of up to 38% compared to the best competitor (G-ADR). Moreover, it reduces ECPD up to 74% compared to the original ADR, while keeping it at the same level with the best competitor (G-ADR).
T. Sachinidis; A. A. Boulogeorgos; P. Sarigiannidis
Dual-hop Blockchain Radio Access Networks for Advanced Coverage Expansion Conference
10th International Conference on Modern Circuits and Systems Technologies (MOCAST 2021), 2021.
Abstract | BibTeX | Tags: Blockchain, Coverage, Radio Access Network | Links:
@conference{Sachinidis2021,
title = {Dual-hop Blockchain Radio Access Networks for Advanced Coverage Expansion},
author = {T. Sachinidis and A. A. Boulogeorgos and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/351437505_Dual-hop_Blockchain_Radio_Access_Networks_for_Advanced_Coverage_Expansion},
doi = {10.1109/MOCAST52088.2021.9493339},
year = {2021},
date = {2021-07-27},
booktitle = {10th International Conference on Modern Circuits and Systems Technologies (MOCAST 2021)},
abstract = {Dynamic dual-hop relaying network topologies that enable access to end-users through intermediate individual and commercial, static as well as moving, infrastructures are expected to become fundamental pillars of the sixth-generation wireless systems. Their main requirement is to ensure end-users information privacy. Motivated by this, the current contribution focuses on introducing a dual-hop blockchain radio access network (DH-BRAN) topology for dynamic coverage expansion. To analyze the performance of this topology, we present the theoretical framework that captures its characteristics. Building upon it, the DH-BRAN performance, in terms of latency and waiting probability, is quantified. Our results reveal that DR-BRAN can be employed in several realistic use-cases and that there exists a trade-off between latency and security.},
keywords = {Blockchain, Coverage, Radio Access Network},
pubstate = {published},
tppubtype = {conference}
}
Dynamic dual-hop relaying network topologies that enable access to end-users through intermediate individual and commercial, static as well as moving, infrastructures are expected to become fundamental pillars of the sixth-generation wireless systems. Their main requirement is to ensure end-users information privacy. Motivated by this, the current contribution focuses on introducing a dual-hop blockchain radio access network (DH-BRAN) topology for dynamic coverage expansion. To analyze the performance of this topology, we present the theoretical framework that captures its characteristics. Building upon it, the DH-BRAN performance, in terms of latency and waiting probability, is quantified. Our results reveal that DR-BRAN can be employed in several realistic use-cases and that there exists a trade-off between latency and security.
D. Pliatsios; P. Sarigiannidis; G. Fragulis; A. Tsiakalos; D. Margounakis
A Dynamic Recommendation-based Trust Scheme for the Smart Grid Conference
3rd International Workshop on Cyber-Security Threats, Trust and Privacy management in Software-defined and Virtualized Infrastructures (SecSoft 2021), 2021.
Abstract | BibTeX | Tags: cyberattacks, security, Smart Grid, smart meters, trust management | Links:
@conference{Pliatsios2021,
title = {A Dynamic Recommendation-based Trust Scheme for the Smart Grid},
author = {D. Pliatsios and P. Sarigiannidis and G. Fragulis and A. Tsiakalos and D. Margounakis},
url = {https://www.researchgate.net/publication/353484865_A_Dynamic_Recommendation-based_Trust_Scheme_for_the_Smart_Grid},
doi = {10.1109/NetSoft51509.2021.9492542 +Date: 26 July 2021},
year = {2021},
date = {2021-07-26},
booktitle = {3rd International Workshop on Cyber-Security Threats, Trust and Privacy management in Software-defined and Virtualized Infrastructures (SecSoft 2021)},
abstract = {The integration of the internet of things (IoT) concept into the traditional electricity grid introduces several critical vulnerabilities. Intrusion detection systems (IDSs) can be effective countermeasures against cyberattacks, however, they require considerable computational and storage resources. As IoT-enabled metering devices have limited resources, IDSs cannot efficiently ensure security. To this end, trust evaluation schemes have emerged as promising solutions toward protecting resource-constrained metering devices. In this work, we proposed a trust evaluation scheme for the smart grid, that is based on direct trust evaluation and recommendation. The proposed hierarchical scheme is able to evaluate the trustiness of each metering device without requiring any significant modifications to the already deployed infrastructure. Additionally, the proposed scheme features is dynamic, meaning that it is robust against nonadversarial events that negatively impact the device’s trustiness. To validate the performance of the proposed scheme, we carry out network-level simulations and investigate how the various network parameters impact the trust evaluation performance.},
keywords = {cyberattacks, security, Smart Grid, smart meters, trust management},
pubstate = {published},
tppubtype = {conference}
}
The integration of the internet of things (IoT) concept into the traditional electricity grid introduces several critical vulnerabilities. Intrusion detection systems (IDSs) can be effective countermeasures against cyberattacks, however, they require considerable computational and storage resources. As IoT-enabled metering devices have limited resources, IDSs cannot efficiently ensure security. To this end, trust evaluation schemes have emerged as promising solutions toward protecting resource-constrained metering devices. In this work, we proposed a trust evaluation scheme for the smart grid, that is based on direct trust evaluation and recommendation. The proposed hierarchical scheme is able to evaluate the trustiness of each metering device without requiring any significant modifications to the already deployed infrastructure. Additionally, the proposed scheme features is dynamic, meaning that it is robust against nonadversarial events that negatively impact the device’s trustiness. To validate the performance of the proposed scheme, we carry out network-level simulations and investigate how the various network parameters impact the trust evaluation performance.
L. Lazaridis; M. Papatsimouli; K. Kollias; P. Sarigiannidis; G. Fragulis
Hitboxes: A Survey About Collision Detection in Video Games Conference
Lecture Notes in Computer Science, vol. 12789, Springer, Cham. , 2021.
Abstract | BibTeX | Tags: collision detection, hitboxes, k-DOP | Links:
@conference{Lazaridis2021,
title = {Hitboxes: A Survey About Collision Detection in Video Games},
author = {L. Lazaridis and M. Papatsimouli and K. Kollias and P. Sarigiannidis and G. Fragulis},
url = {https://www.researchgate.net/publication/352958813_Hitboxes_A_Survey_About_Collision_Detection_in_Video_Games},
doi = {doi.org/10.1007/978-3-030-77277-2_24},
year = {2021},
date = {2021-07-24},
booktitle = {Lecture Notes in Computer Science},
volume = {12789},
publisher = {Springer, Cham. },
abstract = { Over the past decades, video games have become a mainstream form of entertainment and are increasingly used for other purposes such as education or health. This paper surveys recent research and practice in Collision detection in computer gaming that is the detection when two or more objects collide with each other and it plays a crucial role in almost every game as the majority of them are about one thing hitting another. Ground for your feet; a sword and a warrior’s body; a golf ball and a golf club. Hence we have a lot of hitboxes, an invisible geometry around objects that inform them when a collision takes place. There are several methods which solve this kind of problems but what is proven so far from the research is that computers are unexpectedly bad at dealing with collisions. As a result, it is sensible different games take dissimilar approaches on how the way hitboxes work. In this paper we will be focused on Bounding Volumes Hierarchy (BVH) class analyzing three basic methods: OBB, AABB and k-DOP along with some improvements that have been done throughout the years and how these are applied in modern video games.},
keywords = {collision detection, hitboxes, k-DOP},
pubstate = {published},
tppubtype = {conference}
}
Over the past decades, video games have become a mainstream form of entertainment and are increasingly used for other purposes such as education or health. This paper surveys recent research and practice in Collision detection in computer gaming that is the detection when two or more objects collide with each other and it plays a crucial role in almost every game as the majority of them are about one thing hitting another. Ground for your feet; a sword and a warrior’s body; a golf ball and a golf club. Hence we have a lot of hitboxes, an invisible geometry around objects that inform them when a collision takes place. There are several methods which solve this kind of problems but what is proven so far from the research is that computers are unexpectedly bad at dealing with collisions. As a result, it is sensible different games take dissimilar approaches on how the way hitboxes work. In this paper we will be focused on Bounding Volumes Hierarchy (BVH) class analyzing three basic methods: OBB, AABB and k-DOP along with some improvements that have been done throughout the years and how these are applied in modern video games.
T. Lagkas; D. Klonidis; P. Sarigiannidis; I. Tomkos
Optimized Joint Allocation of Radio, Optical, and MEC Resources for the 5G and Beyond Fronthaul Journal Article
In: IEEE Transactions on Network and Service Management, 2021.
Abstract | BibTeX | Tags: 5G and beyond, energy efficiency, joint resource allocation, Learning automata, MEC, New Radio, NFV | Links:
@article{Lagkas2021,
title = {Optimized Joint Allocation of Radio, Optical, and MEC Resources for the 5G and Beyond Fronthaul},
author = {T. Lagkas and D. Klonidis and P. Sarigiannidis and I. Tomkos},
url = {https://www.researchgate.net/publication/353062079_Optimized_Joint_Allocation_of_Radio_Optical_and_MEC_Resources_for_the_5G_and_Beyond_Fronthaul},
doi = {10.1109/TNSM.2021.3094789},
year = {2021},
date = {2021-07-06},
journal = {IEEE Transactions on Network and Service Management},
abstract = {In 5G and beyond telecommunication infrastructures a crucial challenge in achieving the strict Key Performance Indicators (KPIs) regarding capacity, latency, and guaranteed quality of service, is the efficient handling of the fronthaul bottleneck. This part of the next generation networks is expected to comprise the New Radio (NR) access and the Next Generation Passive Optical Network (NGPON) domains. Latest developments load the fronthaul with computing tasks as well (e.g., for AI-based processes) in the context of Mobile Edge Computing (MEC). Towards efficient management of all resource types, this paper proposes a joint allocation scheme with three optimization phases for radio, optical, and MEC resources. This scheme, which has been developed in the context of the blueSPACE 5G Infrastructure Public Private Partnership (5G PPP) project, exploits cutting-edge technologies, such as radio beamforming, spatial-spectral granularity in optical networks, and Network Function Virtualization (NFV), to provide dynamic, adaptive, and energy efficient allocation of resources. The devised model is mathematically described and the overall solution is evaluated in a realistic simulation scenario, demonstrating its effectiveness.},
keywords = {5G and beyond, energy efficiency, joint resource allocation, Learning automata, MEC, New Radio, NFV},
pubstate = {published},
tppubtype = {article}
}
In 5G and beyond telecommunication infrastructures a crucial challenge in achieving the strict Key Performance Indicators (KPIs) regarding capacity, latency, and guaranteed quality of service, is the efficient handling of the fronthaul bottleneck. This part of the next generation networks is expected to comprise the New Radio (NR) access and the Next Generation Passive Optical Network (NGPON) domains. Latest developments load the fronthaul with computing tasks as well (e.g., for AI-based processes) in the context of Mobile Edge Computing (MEC). Towards efficient management of all resource types, this paper proposes a joint allocation scheme with three optimization phases for radio, optical, and MEC resources. This scheme, which has been developed in the context of the blueSPACE 5G Infrastructure Public Private Partnership (5G PPP) project, exploits cutting-edge technologies, such as radio beamforming, spatial-spectral granularity in optical networks, and Network Function Virtualization (NFV), to provide dynamic, adaptive, and energy efficient allocation of resources. The devised model is mathematically described and the overall solution is evaluated in a realistic simulation scenario, demonstrating its effectiveness.
I. Siniosoglou; P. Sarigiannidis; S. Yannis; A. Khadka; G. Efstathopoulos; T. Lagkas
Synthetic Traffic Signs Dataset for Traffic Sign Detection & Recognition In Distributed Smart Systems Conference
2021.
BibTeX | Tags: | Links:
@conference{inproceedings,
title = {Synthetic Traffic Signs Dataset for Traffic Sign Detection & Recognition In Distributed Smart Systems},
author = { I. Siniosoglou and P. Sarigiannidis and S. Yannis and A. Khadka and G. Efstathopoulos and T. Lagkas},
url = {https://www.researchgate.net/publication/356351910_Synthetic_Traffic_Signs_Dataset_for_Traffic_Sign_Detection_Recognition_In_Distributed_Smart_Systems},
doi = {10.1109/DCOSS52077.2021.00056},
year = {2021},
date = {2021-07-01},
pages = {302-308},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Address
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Contact Information
tel: +30 2461 056527
Email: ithaca@uowm.gr
