Συνέδρια

@conference{Kallitsis2023209,

title = {A Joint Wireless Data-Power Exchange Approach for Distributed Energy Harvesting Networks},

author = {G. Kallitsis and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187794022&doi=10.1109%2fCSCN60443.2023.10453207&partnerID=40&md5=013d00ec2a1c7681d6502d149b99035d},

doi = {10.1109/CSCN60443.2023.10453207},

isbn = {9798350395389},

year  = {2023},

date = {2023-01-01},

journal = {2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023},

pages = {209-215},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This work addresses the problem of efficient joint wireless data-energy transfer in distributed networks. We consider devices capable of exchanging data and energy wirelessly, aiming at optimal data/energy transfer scheduling. Wireless Power Transfer resembles energy-harvesting but it bears its own peculiarities. We formulate mathematically the evolution of the data queue and battery state of each node according to a back-pressure inspired approach, and define an optimization problem aiming at better energy balancing. We employ a dual Lagrange multiplier solution, and through simulation and analysis, we identify the critical parameters determining the behavior of the system. This is a cornerstone work towards developing a more generic framework within the conceived 6G architecture, and here we demonstrate its theoretical and practical potentials. © 2023 IEEE.},

note = {cited By 0; Conference of 2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023 ; Conference Date: 6 November 2023 Through 8 November 2023; Conference Code:197830},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kourouthanassis2023,

title = {Platform Architecture and Functionality for Efficient and Intelligent Logistics},

author = {P. Kourouthanassis and C. Bardaki and A. Sourvinos and V. Karyotis and P. Mylonas},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174950955&doi=10.1109%2fSMAP59435.2023.10255183&partnerID=40&md5=62b36f77637e60fe562c2d390d065332},

doi = {10.1109/SMAP59435.2023.10255183},

isbn = {9798350327717},

year  = {2023},

date = {2023-01-01},

journal = {2023 18th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2023},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper describes the layered architecture and functionality of an intelligent logistics platform for logistics companies to centrally coordinate their transportation operations. It offers real-Time tracking, tracing, and reporting capabilities to logistics stakeholders, as well as dynamic scheduling and routing of deliveries forming shipments and routes with optimized resources allocation and costs. The optimization of shipments scheduling and routing is performed drawing on the backpressure technique, which, to the best of our knowledge, has never been applied to optimize supply chain transport operations. The algorithm combines a variety of factors that affect transportation operations (such as the capacity and current inventory of each node in the transportation network and the fleet characteristics) and proposes dynamically shipments and optimal paths for the company fleet and couriers for last-mile delivery. © 2023 IEEE.},

note = {cited By 0; Conference of 18th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2023 ; Conference Date: 25 September 2023 Through 26 September 2023; Conference Code:192944},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Nikopoulou2023,

title = {Digital Technology Implementation in the Hospitality Industry and Hotel Star Rating: Does It Matter? Evidence from Greece},

author = {M. Nikopoulou and P. Chasapi and P. Kourouthanassis and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182023425&doi=10.1109%2fIISA59645.2023.10345942&partnerID=40&md5=080f7b2ba59074f7f5a471bb386cb269},

doi = {10.1109/IISA59645.2023.10345942},

year  = {2023},

date = {2023-01-01},

journal = {14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023},

volume = {15},

number = {3},

note = {cited By 1},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Nikopoulou2023c,

title = {Digital Technology Implementation in the Hospitality Industry and Hotel Star Rating: Does It Matter? Evidence from Greece},

author = {M. Nikopoulou and P. Chasapi and P. Kourouthanassis and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182023425&doi=10.1109%2fIISA59645.2023.10345942&partnerID=40&md5=080f7b2ba59074f7f5a471bb386cb269},

doi = {10.1109/IISA59645.2023.10345942},

year  = {2023},

date = {2023-01-01},

journal = {14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023},

note = {cited By 1},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kakkavas202258,

title = {Realistic Field Trial Evaluation of a Tele-operated Support Service for Remote Driving over 5G},

author = {G. Kakkavas and M. Diamanti and K. Nseboah Nyarko and M. Gabriel and V. Karyotis and K. Mosner and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150026185&doi=10.1109%2fCSCN57023.2022.10051034&partnerID=40&md5=59fc87d2140bee67e8a0dff69646d92d},

doi = {10.1109/CSCN57023.2022.10051034},

isbn = {9781665476218},

year  = {2022},

date = {2022-01-01},

journal = {2022 IEEE Conference on Standards for Communications and Networking, CSCN 2022},

pages = {58-63},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In this paper, we focus on the development and realistic field trial evaluation of a Tele-operated Support (TeSo) service for remote driving over 5G mobile communications. The presented prototype was created within the context of the transport vertical of the "5G HEalth, AquacultuRe and Transport (5G-HEART)"5G PPP Phase 3 project and was meti culously tested and evaluated in several realistic test cases over a commercial 5G Non-Standalone (NSA) deployment. A vehicle equipped with appropriate sensors and actuators was actively controlled from a distance of 36 km, exchanging sensor data and video streams in the uplink and vehicle-control commands in the downlink with the remote operations center. This work is among the first experimentally-driven quantitative analyses of such an application with a real pilot using an actual vehicle. Our objective was to validate the feasibility of the proposed TeSo service by evaluating relevant performance metrics, such as latency, jitter, throughput, and loss rate. Moreover, our extensive testing aimed to identify salient features and emerging challenges from the prototype, which can aid in a two-fold manner: first, paving the way for the eventual commercialization of the service, and second, guiding standardization effort for a relevant emerging market in the near future. © 2022 IEEE.},

note = {cited By 1; Conference of 2022 IEEE Conference on Standards for Communications and Networking, CSCN 2022 ; Conference Date: 28 November 2022 Through 30 November 2022; Conference Code:186982},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Karyotis2022,

title = {A Framework for a Holistic Information System for Small-Medium Logistics Enterprises},

author = {V. Karyotis and E. Stai and P. Kourouthanasis and P. Mylonas},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143080514&doi=10.1109%2fSMAP56125.2022.9941923&partnerID=40&md5=4336f1e08c3b52f517432d35bb184469},

doi = {10.1109/SMAP56125.2022.9941923},

isbn = {9781665487276},

year  = {2022},

date = {2022-01-01},

journal = {2022 17th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2022},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Logistic or freight networks have gained considerable interest lately, calling for intelligent methods in order to deal with the increasing load requirements while maintaining sustainable costs. In this work, we focus on addressing the needs of small-medium freight companies so that they can cope with the emerging challenges in the post-COVID era. More specifically, we initially identify the requirements and the architecture of a candidate holistic information system that such a company would need to ensure optimal deliveries and efficiency of its operation. Then we focus on the scheduling-routing component of the proposed information system framework. We review the proposed solutions and propose a novel one based on the concept of backpressure joint scheduling-routing inspired from telecommunication networks. We believe that this approach can seamlessly and efficiently provide the means for small-scale companies, and larger ones as well, to optimize their operations and improve their offered quality of service. © 2022 IEEE.},

note = {cited By 1; Conference of 17th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2022 ; Conference Date: 3 November 2022 Through 4 November 2022; Conference Code:184277},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Vitoropoulou2022375,

title = {On the Fair Energy Sharing in Networks with Wireless Charging-capable Devices},

author = {M. Vitoropoulou and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142721925&doi=10.1109%2fWiMob55322.2022.9941704&partnerID=40&md5=455b20e124f40d5cbe8d019cc7744863},

doi = {10.1109/WiMob55322.2022.9941704},

issn = {21619646},

year  = {2022},

date = {2022-01-01},

journal = {International Conference on Wireless and Mobile Computing, Networking and Communications},

volume = {2022-October},

pages = {375-380},

publisher = {IEEE Computer Society},

abstract = {The emerging technology of Wireless Power Trans-fer (WPT) has enabled mobile devices to replenish their batteries and increase their lifetime by exchanging energy with other devices in vicinity. In this paper, we study the problem of peer-to-peer WPT in a network of battery-constrained devices for which we aim to provide a fair energy allocation via mutual exchanges. In this respect, devices of lowest battery level remain functional for longer time, while respecting and satisfying a given set of wireless charging constraints. By taking into consideration the skewed energy availability in the network, as well as the loss induced by wireless energy transfer, we formulate and analyze three energy allocation schemes based on the concepts of lexicographic optimization and algorithmic graph theory, which, under different optimization criteria, aim to extend network lifetime. The performance of the proposed schemes is evaluated and compared in terms of energy efficiency and balancing quality through modeling and simulation over synthetic networks. © 2022 IEEE.},

note = {cited By 0; Conference of 18th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2022 ; Conference Date: 10 October 2022 Through 12 October 2022; Conference Code:184410},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kakkavas2022280,

title = {Teleoperated Support for Remote Driving over 5G Mobile Communications},

author = {G. Kakkavas and K. N. Nyarko and C. Lahoud and D. Kuhnert and P. Kuffner and M. Gabriel and S. Ehsanfar and M. Diamanti and V. Karyotis and K. Mobner and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142211184&doi=10.1109%2fMeditCom55741.2022.9928745&partnerID=40&md5=3e3e5e2f323069f97498c9b24937265b},

doi = {10.1109/MeditCom55741.2022.9928745},

isbn = {9781665498258},

year  = {2022},

date = {2022-01-01},

journal = {2022 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2022},

pages = {280-285},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {The fifth-generation (5G) mobile communications promise far more capabilities than competing technologies and are expected to enable a wide range of vertical use cases. Among them, remote driving has attracted much interest from both academia and the industry, either as a stepping stone on the road to fully autonomous driving or as its complement constituting a fallback/backup service. This paper presents the design, development, and evaluation of a teleoperated support (TeSo) service over 5G mobile communications, realized within the framework of the '5G HEalth, AquacultuRe and Transport (5G-HEART)' EU project. We present an end-to-end service architecture and a complete implementation, accompanied by validation trials and performance measurements in a real pilot over a commercial 5G network deployment with an actual vehicle that has been extended to support a variety of experimentation options. With this work, we demonstrate the feasibility of the proposed TeSo service, and we quantify various performance metrics of interest, such as latency, jitter, throughput, and loss rate for longer-term reference use. © 2022 IEEE.},

note = {cited By 4; Conference of 2nd IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2022 ; Conference Date: 5 September 2022 Through 8 September 2022; Conference Code:183951},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Nikiforos2022,

title = {Machine Learning on Wikipedia Text for the Automatic Identification of Vocational Domains of Significance for Displaced Communities},

author = {M. N. Nikiforos and K. Deliveri and K. L. Kermanidis and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143056941&doi=10.1109%2fSMAP56125.2022.9941803&partnerID=40&md5=23c418b4cd3150c5a08fc65dcb5177b6},

doi = {10.1109/SMAP56125.2022.9941803},

year  = {2022},

date = {2022-01-01},

journal = {2022 17th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2022},

note = {cited By 1},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kakkavas2021,

title = {Future Network Traffic Matrix Synthesis and Estimation Based on Deep Generative Models},

author = {G. Kakkavas and M. Kalntis and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114962425&doi=10.1109%2fICCCN52240.2021.9522222&partnerID=40&md5=b55537afb9ced698d9c0012a1d046d67},

doi = {10.1109/ICCCN52240.2021.9522222},

issn = {10952055},

year  = {2021},

date = {2021-01-01},

journal = {Proceedings - International Conference on Computer Communications and Networks, ICCCN},

volume = {2021-July},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Traffic matrices (TMs) contain information that is essential for network management, traffic engineering, and anomaly detection. However, constructing a TM through direct traffic measurements has a high administrative and computational cost. A more feasible approach is to estimate the TM from the easily obtainable link load measurements. In this paper, we address the issue of traffic matrix estimation (TME) from link loads using a deep generative model - namely, a variational autoencoder (VAE) - to solve the respective ill-posed inverse problem. In particular, we train the VAE with historical data (previously observed TMs) and we leverage the trained decoder to transform TME into a minimization problem in the latent space, which in turn can be solved by employing a gradient-based optimizer. Furthermore, the trained decoder can be used for traffic matrix synthesis, i.e., for generating synthetic TM examples that have 'similar' properties to the samples of the training set. Finally, we explore the incremental optimization of the sequence of objectives constructed from the sequence of decoders that we obtain at different stages of the VAE training. The performance of the proposed methods is evaluated using a publicly available dataset of actual traffic matrices recorded in a real backbone network. © 2021 IEEE.},

note = {cited By 9; Conference of 30th International Conference on Computer Communications and Networks, ICCCN 2021 ; Conference Date: 19 July 2021 Through 22 July 2021; Conference Code:171515},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Kakkavas2021466,

title = {Demo Proposal: Tele-Operated Support over 4G/5G Mobile Communications},

author = {G. Kakkavas and M. Diamanti and M. Gabriel and C. Lahoud and P. Akula and V. Karyotis and K. Mosner and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124480634&doi=10.1109%2fMeditCom49071.2021.9647643&partnerID=40&md5=23eca4195ba809f048a4b486e8c8fa8f},

doi = {10.1109/MeditCom49071.2021.9647643},

isbn = {9781665445054},

year  = {2021},

date = {2021-01-01},

journal = {2021 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2021},

pages = {466-467},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This demonstration presents the design and implementation of a remote driving (tele-operated) support service over mobile communications with an actual vehicle, in the framework of the 5G-HEART project. Also, it evaluates the performance of existing cellular technologies, which is essential for better understanding and planning remote driving through 5G. © 2021 IEEE.},

note = {cited By 3; Conference of 2021 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2021 ; Conference Date: 7 September 2021 Through 10 September 2021; Conference Code:175865},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Spatharakis2021464,

title = {Industrial Robotics Experimentation over Federated Next Generation Internet Testbeds},

author = {D. Spatharakis and M. Avgeris and G. Kakkavas and K. Papadakis-Vlachopapadopoulos and I. Dimolitsas and D. Dechouniotis and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124454326&doi=10.1109%2fMeditCom49071.2021.9647524&partnerID=40&md5=8da4aa260a74d925bc45c3a505c0ef64},

doi = {10.1109/MeditCom49071.2021.9647524},

isbn = {9781665445054},

year  = {2021},

date = {2021-01-01},

journal = {2021 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2021},

pages = {464-465},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Modern Industry 4.0 applications require the interplay between industrial equipment, robots, and network infrastructure. This article demonstrates the experimental capabilities of the NETMODE testbed, part of the MESON project, on Industry 4.0 and remote driving scenarios. © 2021 IEEE.},

note = {cited By 0; Conference of 2021 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2021 ; Conference Date: 7 September 2021 Through 10 September 2021; Conference Code:175865},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Krommyda2021678,

title = {Visualizing and exploring big datasets based on semantic community detection},

author = {M. Krommyda and K. Tsitseklis and V. Kantere and V. Karyotis and S. Papavassiliou},

editor = {Zeinalipour D. Velegrakis Y. Velegrakis Y.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113712934&doi=10.5441%2f002%2fedbt.2021.82&partnerID=40&md5=ad58b2f6a115ba3527775b9d93438610},

doi = {10.5441/002/edbt.2021.82},

issn = {23672005},

year  = {2021},

date = {2021-01-01},

journal = {Advances in Database Technology - EDBT},

volume = {2021-March},

pages = {678-681},

publisher = {OpenProceedings.org},

abstract = {The extended use of the RDF model has made available many datasets from heterogeneous sources that are of interest to a wide audience. Their exploration, however, is a highly demanding task requiring extensive training and knowledge of the SPARQL language. In this demo, we present an innovative system, which supports the exploration of large RDF datasets without requiring any knowledge about the RDF or SPARQL. The system is based on a novel algorithm that detects semantically similar communities capitalizing on hyperbolic network embedding and a weighted similarity metric. The detected communities are visualized in a user-friendly way and presented to the user through a two level abstraction interface with a toolbox of exploration functionalities. © 2021 Copyright held by the owner/author(s).},

note = {cited By 0; Conference of Advances in Database Technology - 24th International Conference on Extending Database Technology, EDBT 2021 ; Conference Date: 23 March 2021 Through 26 March 2021; Conference Code:171234},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Nikiforos2020,

title = {Enhancing Collaborative Filtering Recommendations for Web-based Learning Platforms with Genetic Algorithms},

author = {M. N. Nikiforos and M. Malakopoulou and A. Stylidou and A. -G. Alvanou and V. Karyotis and P. Kourouthanassis},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097598439&doi=10.1109%2fSMAP49528.2020.9248472&partnerID=40&md5=e8ab00020bbab229e12e04a952b494b2},

doi = {10.1109/SMAP49528.2020.9248472},

isbn = {9781728159195},

year  = {2020},

date = {2020-01-01},

journal = {SMAP 2020 - 15th International Workshop on Semantic and Social Media Adaptation and Personalization},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Web-based learning platforms are now offering a considerable amount of training options, exhibiting great variability, similar to the one encountered by a potential customer in electronic shops. To mitigate this, efficient and effective recommendations engines are needed, capable of satisfying the specific needs of each user, while achieving the best possible promotion of available onlinetraining. This paper discusses the design of a potential generic architecture for online education recommender systems, specifically targeted for promoting online courses and web-based learning material. From an algorithmic perspective, the system relies on item-based and user-based collaborativefiltering approaches. It extends this approach with a genetic algorithm, thus increasing its potential impact. Overall, the paper paves the ground for the specification of generic principles governing the design of personalized online education platforms as well as identifying metrics for evaluating their performance. © 2020 IEEE.},

note = {cited By 3; Conference of 15th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2020 ; Conference Date: 29 October 2020 Through 30 October 2020; Conference Code:164932},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Tsitseklis2019185,

title = {A Realistic Evaluation of MRF-based Resource Allocation for SDR Cognitive Radio Networks},

author = {K. Tsitseklis and G. Kakkavas and V. Karyotis and S. Papavassiliou},

editor = {Oteafy S. Tan H.-P. Andersson K.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080939926&doi=10.1109%2fLCN44214.2019.8990725&partnerID=40&md5=5ece1109bea717561dba60bfdc872500},

doi = {10.1109/LCN44214.2019.8990725},

isbn = {9781728110288},

year  = {2019},

date = {2019-01-01},

journal = {Proceedings - Conference on Local Computer Networks, LCN},

volume = {2019-October},

pages = {185-192},

publisher = {IEEE Computer Society},

abstract = {In this paper, we focus on the development and realistic evaluation of a resource allocation approach for cognitive radios implemented with Software Defined Radio (SDR) technology over two testbeds of the ORCA federation. Our cross-layer approach is based on a Markov Random Field (MRF) framework realizing a distributed computation among the secondary nodes of cognitive radios. This is the first implementation and real experimental evaluation of such a mechanism. New SDR functions for implementing various cognitive radio functionalities, such as spectrum sensing, distributed node synchronization, etc., were developed in GNU Radio from scratch. We demonstrated the feasibility of the MRF-based resource allocation approach and quantified various performance metrics of interest, such as allocation fairness and collision percentage. Through this development, several design principles of broader interest for SDR emerged (e.g., for spectrum sensing and collision detection design), while salient features of our framework requiring further research and development were discovered (e.g., need for parallel implementation). © 2019 IEEE.},

note = {cited By 0; Conference of 44th Annual IEEE Conference on Local Computer Networks, LCN 2019 ; Conference Date: 14 October 2019 Through 17 October 2019; Conference Code:157724},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Tsanikidis2018135,

title = {On the Energy-Efficient Coverage of Network Regions with Convex Opaque Obstacles},

author = {C. Tsanikidis and M. Vitoropoulou and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060539317&doi=10.1109%2fPIMRC.2018.8580878&partnerID=40&md5=d3a99b40001d185764422a49efa7cf7e},

doi = {10.1109/PIMRC.2018.8580878},

isbn = {9781538660096},

year  = {2018},

date = {2018-01-01},

journal = {IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC},

volume = {2018-September},

pages = {135-141},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In this paper we propose a topology control based approach for addressing the coverage problem in a planar region containing convex opaque obstacles. Such environments represent typical cases of realistic wireless sensor networks and Internet-of-Things deployments. Assuming the devices have the capability to modify their sensing ranges, our goal is to maximize the area covered by randomly dispersed sensors, while reducing their sensing energy consumption as much as possible despite the presence of convex obstacles. To address the former, we introduce a relevant framework capitalizing on the notion of the visibility polygon and propose two algorithms, a centralized (and a randomized version thereof) and a distributed one, which aim to maximize the ratio of covered area to consumed energy, while ensuring a minimum coverage percentage. Through analysis and simulation we demonstrate that the proposed schemes achieve energy efficient coverage, outperforming the plain assignment of maximum sensing range across the network. © 2018 IEEE.},

note = {cited By 0; Conference of 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2018 ; Conference Date: 9 September 2018 Through 12 September 2018; Conference Code:143803},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Karyotis2018266,

title = {Enhancing Community Detection for Big Sensor Data Clustering via Hyperbolic Network Embedding},

author = {V. Karyotis and K. Tsitseklis and K. Sotiropoulos and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056458909&doi=10.1109%2fPERCOMW.2018.8480134&partnerID=40&md5=082f7ba01a225e8ccef49047803f02bd},

doi = {10.1109/PERCOMW.2018.8480134},

isbn = {9781538632277},

year  = {2018},

date = {2018-01-01},

journal = {2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018},

pages = {266-271},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In this paper we present a novel big data clustering approach for measurements obtained from pervasive sensor networks. To address the potential very large scale of such datasets, we map the problem of data clustering to a community detection one. Datasets are cast in the form of graphs, representing the relations among individual observations and data clustering is mapped to node clustering (community detection) in the data graph. We propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, making it possible to compute more efficiently the hyperbolic edge-betweenness centrality (HEBC) needed in the modified GN algorithm. This allows for more efficient clustering of the nodes of the data graph without significantly sacrificing accuracy. We demonstrate the efficacy of our approach with artificial network and data topologies, and real benchmark datasets. The proposed methodology can be used for efficient clustering of datasets obtained from massive pervasive smart city/building sensor networks, such as the FIESTA-IoT platform, and exploited in various applications such as lower-cost sensing. © 2018 IEEE.},

note = {cited By 1; Conference of 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 ; Conference Date: 19 March 2018 Through 23 March 2018; Conference Code:140607},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Papadis2017973,

title = {A path-based recommendations approach for online systems via hyperbolic network embedding},

author = {N. Papadis and E. Stai and V. Karyotis},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030552382&doi=10.1109%2fISCC.2017.8024652&partnerID=40&md5=e493e583b0401de9bed050de76373b57},

doi = {10.1109/ISCC.2017.8024652},

issn = {15301346},

year  = {2017},

date = {2017-01-01},

journal = {Proceedings - IEEE Symposium on Computers and Communications},

pages = {973-980},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In this paper we introduce and demonstrate new recommendation algorithms for large-scale online systems, such as e-shops and cloud services. The proposed algorithms are based on the combination of network embedding in hyperbolic space with greedy routing, exploiting properties of hyperbolic metric spaces. Contrary to the existing recommender systems that rank products in order to propose the highest ranked ones to the users, our proposed recommender system creates a progressive path of recommendations towards a final (known or inferred) target product using greedy routing over networks embedded in hyperbolic space. Thus, it prepares the user by intermediate recommendations for maximizing the chances that he/she accepts the recommendation of the target product(s). This casts the problem of locating a suitable recommendation as a path problem, where leveraging on the efficiency of greedy routing in graphs embedded in hyperbolic spaces and exploiting special network structure, if any, pays dividends. Two variants of our recommendation approach are provided, namely Hyperbolic Recommendation-Known Destination (HRKD), Hyperbolic Recommendation-Unknown Destination (HRUD), when the target product is known or unknown, respectively. We demonstrate how the proposed approach can be used for producing efficient recommendations in online systems, along with studying the impact of the several parameters involved in its performance via proper emulation of user activity over suitably defined graphs. © 2017 IEEE.},

note = {cited By 2; Conference of 2017 IEEE Symposium on Computers and Communications, ISCC 2017 ; Conference Date: 3 July 2017 Through 7 July 2017; Conference Code:130537},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Pateli2017,

title = {Configurations explaining the impact of social media on innovation performance},

author = {A. G. Pateli and P. Mikalef},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091076659&partnerID=40&md5=3415a12331f2ce24b3f3fa68185bce37},

year  = {2017},

date = {2017-01-01},

journal = {Proceedings ot the 21st Pacific Asia Conference on Information Systems: ''Societal Transformation Through IS/IT'', PACIS 2017},

note = {cited By 3},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{VanDeWetering20171468,

title = {A strategic alignment model for it flexibility and dynamic capabilities: Toward an assessment tool},

author = {R. Van De Wetering and P. Mikalef and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057570366&partnerID=40&md5=3c9cdcf7a7e9f46d28ff69f252d8bc09},

year  = {2017},

date = {2017-01-01},

journal = {Proceedings of the 25th European Conference on Information Systems, ECIS 2017},

pages = {1468-1485},

note = {cited By 30},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{Mikalef2017,

title = {Social media for open innovation: A study of adoption determinants},

author = {P. Mikalef and A. G. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047238599&partnerID=40&md5=86597c7a1b19d0789b48e084d163cadc},

year  = {2017},

date = {2017-01-01},

journal = {Proceedings ot the 21st Pacific Asia Conference on Information Systems: ''Societal Transformation Through IS/IT'', PACIS 2017},

note = {cited By 6},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{VanDeWetering2017,

title = {Managing firms’ innovation capabilities through strategically aligning combinative IT and dynamic capabilities},

author = {R. Van De Wetering and P. Mikalef and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029444120&partnerID=40&md5=be3cd9c137eccf659a0bc8b7b90ef2b2},

year  = {2017},

date = {2017-01-01},

journal = {AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation},

volume = {2017-August},

note = {cited By 12},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}