2021 |
A. Griva; A.D. Boursianis; S. Wan; P. Sarigiannidis; G. Karagiannidis; S.K. Goudos , "Performance Evaluation of LoRa Networks in an Open Field Cultivation Scenario", 2021. Conference Περίληψη | BibTeX | Ετικέτες: Data Extraction Rate, Internet of Things (IoT), Long Range (LoRa), Network Energy Consumption, Smart Agriculture | Σύνδεσμοι: @conference{Griva2021, title = {Performance Evaluation of LoRa Networks in an Open Field Cultivation Scenario}, author = { A. Griva and A.D. Boursianis and S. Wan and P. Sarigiannidis and G. Karagiannidis and S.K. Goudos}, url = {https://www.researchgate.net/publication/353498225_Performance_Evaluation_of_LoRa_Networks_in_an_Open_Field_Cultivation_Scenario}, doi = {10.1109/MOCAST52088.2021.9493416}, year = {2021}, date = {2021-01-01}, journal = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021}, abstract = {The employment of Internet of Things (IoT) technology in agriculture could be beneficial in managing the cultivation production in a highly-customizable way. LoRa (Long Range) is one of the most important technologies in cultivation fields mainly thanks to its ability to provide long-range transmission and low power consumption. In this paper, we evaluate the performance of LoRa networks in an open field cultivation scenario via simulations using FLoRa, an open-source framework in OMNeT++. The number of nodes, the number of gateways, the antenna gain, and the size of the deployment area have a considerable impact on both the data extraction rate and the energy consumption of a LoRa network. Our results show that the optimization of the parameters that affect the performance of a LoRa network could transform traditional agriculture into a new perspective of smart cultivation. Finally, we evaluate the impact of the density and the geometric characteristics of three types of crop (tomatoes, grapes, apples) on the number of intersections that were caused by the insertion of physical objects-obstacles in a LoRa network. © 2021 IEEE.}, keywords = {Data Extraction Rate, Internet of Things (IoT), Long Range (LoRa), Network Energy Consumption, Smart Agriculture}, pubstate = {published}, tppubtype = {conference} } The employment of Internet of Things (IoT) technology in agriculture could be beneficial in managing the cultivation production in a highly-customizable way. LoRa (Long Range) is one of the most important technologies in cultivation fields mainly thanks to its ability to provide long-range transmission and low power consumption. In this paper, we evaluate the performance of LoRa networks in an open field cultivation scenario via simulations using FLoRa, an open-source framework in OMNeT++. The number of nodes, the number of gateways, the antenna gain, and the size of the deployment area have a considerable impact on both the data extraction rate and the energy consumption of a LoRa network. Our results show that the optimization of the parameters that affect the performance of a LoRa network could transform traditional agriculture into a new perspective of smart cultivation. Finally, we evaluate the impact of the density and the geometric characteristics of three types of crop (tomatoes, grapes, apples) on the number of intersections that were caused by the insertion of physical objects-obstacles in a LoRa network. © 2021 IEEE. |
2020 |
A. Protopsaltis; P. Sarigiannidis; D. Margounakis; A. Lytos , "Data Visualization in Internet of Things: Tools, Methodologies, and Challenges", Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES '20 Association for Computing Machinery, Virtual Event, Ireland, 2020, ISBN: 9781450388337. Conference Περίληψη | BibTeX | Ετικέτες: Anomaly Detection, Μεγάλα Δεδομένα και Ευφυείς Εφαρμογές στο Διαδίκτυο των Πραγμάτων, Data visualization, Internet of Things (IoT) | Σύνδεσμοι: @conference{Protopsaltis2020, title = {Data Visualization in Internet of Things: Tools, Methodologies, and Challenges}, author = { A. Protopsaltis and P. Sarigiannidis and D. Margounakis and A. Lytos}, url = {https://www.researchgate.net/publication/343935293_Data_Visualization_in_Internet_of_Things_Tools_Methodologies_and_Challenges}, doi = {10.1145/3407023.3409228}, isbn = {9781450388337}, year = {2020}, date = {2020-01-01}, booktitle = {Proceedings of the 15th International Conference on Availability, Reliability and Security}, publisher = {Association for Computing Machinery}, address = {Virtual Event, Ireland}, series = {ARES '20}, abstract = {As the Internet of Things (IoT) grows rapidly, huge amounts of wireless sensor networks emerged monitoring a wide range of infrastructure, in various domains such as healthcare, energy, transportation, smart city, building automation, agriculture, and industry producing continuously streamlines of data. Big Data technologies play a significant role within IoT processes, as visual analytics tools, generating valuable knowledge in real-time in order to support critical decision making. This paper provides a comprehensive survey of visualization methods, tools, and techniques for the IoT. We position data visualization inside the visual analytics process by reviewing the visual analytics pipeline. We provide a study of various chart types available for data visualization and analyze rules for employing each one of them, taking into account the special conditions of the particular use case. We further examine some of the most promising visualization tools. Since each IoT domain is isolated in terms of Big Data approaches, we investigate visualization issues in each domain. Additionally, we review visualization methods oriented to anomaly detection. Finally, we provide an overview of the major challenges in IoT visualizations.}, keywords = {Anomaly Detection, Big Data, Data visualization, Internet of Things (IoT)}, pubstate = {published}, tppubtype = {conference} } As the Internet of Things (IoT) grows rapidly, huge amounts of wireless sensor networks emerged monitoring a wide range of infrastructure, in various domains such as healthcare, energy, transportation, smart city, building automation, agriculture, and industry producing continuously streamlines of data. Big Data technologies play a significant role within IoT processes, as visual analytics tools, generating valuable knowledge in real-time in order to support critical decision making. This paper provides a comprehensive survey of visualization methods, tools, and techniques for the IoT. We position data visualization inside the visual analytics process by reviewing the visual analytics pipeline. We provide a study of various chart types available for data visualization and analyze rules for employing each one of them, taking into account the special conditions of the particular use case. We further examine some of the most promising visualization tools. Since each IoT domain is isolated in terms of Big Data approaches, we investigate visualization issues in each domain. Additionally, we review visualization methods oriented to anomaly detection. Finally, we provide an overview of the major challenges in IoT visualizations. |
2019 |
D. Pliatsios; P. Sarigiannidis , "Power allocation in downlink non-orthogonal multiple access IoT-enabled Systems: A particle swarm optimization approach", 2019. Conference Περίληψη | BibTeX | Ετικέτες: Internet of Things (IoT), Non Orthogonal Multiple Access (NOMA), Particle Swarm Optimization (PSO) | Σύνδεσμοι: @conference{Pliatsios2019416, title = {Power allocation in downlink non-orthogonal multiple access IoT-enabled Systems: A particle swarm optimization approach}, author = { D. Pliatsios and P. Sarigiannidis}, url = {https://www.researchgate.net/publication/335366103_Power_Allocation_in_Downlink_Non-orthogonal_Multiple_Access_IoT-enabled_Systems_A_Particle_Swarm_Optimization_Approach}, doi = {10.1109/DCOSS.2019.00085}, year = {2019}, date = {2019-01-01}, journal = {Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019}, pages = {416-422}, abstract = {The exponential proliferation of the Internet of Things (IoT) concept renders it an integral part of the emerging 5th Generation (5G) of mobile networks. In order to address the requirement of massive IoT-type connections, the spectrum has to be better utilized. Non-Orthogonal Multiple Access (NOMA) is a promising technique that can effectively improve the spectrum efficiency. In this paper, we consider the power allocation problem of a downlink Single Input Single Output (SISO) NOMA system. We aim to maximize the total system throughput, while maintaining a good level of fairness among the users. The system available bandwidth is divided into a number of subbands, and each subband is assigned to two users. The combination of the assigned users is based on the performance of each one, in terms of throughput. Two methods are reported for allocating power to each subband. In the first method, the maximum transmission power is equally divided to all bands, whereas, in the second, we use the Particle Swarm Optimization (PSO) algorithm to allocate the power to each band aiming to maximize the total system throughput. The power allocated to each band is further divided into the two multiplexed users. A series of extensive simulations and comparisons were employed to evaluate our proposed power allocation methods. The results indicate that our methods provide a significant improvement over the compared ones, both in terms of achieved system throughput and fairness among the users. © 2019 IEEE.}, keywords = {Internet of Things (IoT), Non Orthogonal Multiple Access (NOMA), Particle Swarm Optimization (PSO)}, pubstate = {published}, tppubtype = {conference} } The exponential proliferation of the Internet of Things (IoT) concept renders it an integral part of the emerging 5th Generation (5G) of mobile networks. In order to address the requirement of massive IoT-type connections, the spectrum has to be better utilized. Non-Orthogonal Multiple Access (NOMA) is a promising technique that can effectively improve the spectrum efficiency. In this paper, we consider the power allocation problem of a downlink Single Input Single Output (SISO) NOMA system. We aim to maximize the total system throughput, while maintaining a good level of fairness among the users. The system available bandwidth is divided into a number of subbands, and each subband is assigned to two users. The combination of the assigned users is based on the performance of each one, in terms of throughput. Two methods are reported for allocating power to each subband. In the first method, the maximum transmission power is equally divided to all bands, whereas, in the second, we use the Particle Swarm Optimization (PSO) algorithm to allocate the power to each band aiming to maximize the total system throughput. The power allocated to each band is further divided into the two multiplexed users. A series of extensive simulations and comparisons were employed to evaluate our proposed power allocation methods. The results indicate that our methods provide a significant improvement over the compared ones, both in terms of achieved system throughput and fairness among the users. © 2019 IEEE. |
2018 |
P. Bellavista; C. Giannelli; T. Lagkas; P. Sarigiannidis , "Quality management of surveillance multimedia streams via federated SDN controllers in Fiwi-iot integrated deployment environments", IEEE Access, 6 , pp. 21324-21341, 2018. Journal Article Περίληψη | BibTeX | Ετικέτες: federated SDN controllers, Fiber wireless (FiWi), Internet of Things (IoT), quality management, software defined networking (SDN) | Σύνδεσμοι: @article{Bellavista201821324, title = {Quality management of surveillance multimedia streams via federated SDN controllers in Fiwi-iot integrated deployment environments}, author = { P. Bellavista and C. Giannelli and T. Lagkas and P. Sarigiannidis}, url = {https://www.researchgate.net/publication/324249418_Quality_Management_of_Surveillance_Multimedia_Streams_via_Federated_SDN_Controllers_in_FiWi-IoT_Integrated_Deployment_Environments}, doi = {10.1109/ACCESS.2018.2822401}, year = {2018}, date = {2018-01-01}, journal = {IEEE Access}, volume = {6}, pages = {21324-21341}, abstract = {Traditionally, hybrid optical-wireless networks (Fiber-Wireless - FiWi domain) and last-mile Internet of Things edge networks (Edge IoT domain) have been considered independently, with no synergic management solutions. On the one hand, FiWi has primarily focused on high-bandwidth and low-latency access to cellular-equipped nodes. On the other hand, Edge IoT has mainly aimed at effective dispatching of sensor/actuator data among (possibly opportunistic) nodes, by using direct peer-to-peer and base station (BS)-assisted Internet communications. The paper originally proposes a model and an architecture that loosely federate FiWi and Edge IoT domains based on the interaction of FiWi and Edge IoT software defined networking controllers: The primary idea is that our federated controllers can seldom exchange monitoring data and control hints the one with the other, thus mutually enhancing their capability of end-to-end quality-aware packet management. To show the applicability and the effectiveness of the approach, our original proposal is applied to the notable example of multimedia stream provisioning from surveillance cameras deployed in the Edge IoT domain to both an infrastructure-side server and spontaneously interconnected mobile smartphones, our solution is able to tune the BS behavior of the FiWi domain and to reroute/prioritize traffic in the Edge IoT domain, with the final goal to reduce latency. In addition, the reported application case shows the capability of our solution of joint and coordinated exploitation of resources in FiWi and Edge IoT domains, with performance results that highlight its benefits in terms of efficiency and responsiveness. © 2013 IEEE.}, keywords = {federated SDN controllers, Fiber wireless (FiWi), Internet of Things (IoT), quality management, software defined networking (SDN)}, pubstate = {published}, tppubtype = {article} } Traditionally, hybrid optical-wireless networks (Fiber-Wireless - FiWi domain) and last-mile Internet of Things edge networks (Edge IoT domain) have been considered independently, with no synergic management solutions. On the one hand, FiWi has primarily focused on high-bandwidth and low-latency access to cellular-equipped nodes. On the other hand, Edge IoT has mainly aimed at effective dispatching of sensor/actuator data among (possibly opportunistic) nodes, by using direct peer-to-peer and base station (BS)-assisted Internet communications. The paper originally proposes a model and an architecture that loosely federate FiWi and Edge IoT domains based on the interaction of FiWi and Edge IoT software defined networking controllers: The primary idea is that our federated controllers can seldom exchange monitoring data and control hints the one with the other, thus mutually enhancing their capability of end-to-end quality-aware packet management. To show the applicability and the effectiveness of the approach, our original proposal is applied to the notable example of multimedia stream provisioning from surveillance cameras deployed in the Edge IoT domain to both an infrastructure-side server and spontaneously interconnected mobile smartphones, our solution is able to tune the BS behavior of the FiWi domain and to reroute/prioritize traffic in the Edge IoT domain, with the final goal to reduce latency. In addition, the reported application case shows the capability of our solution of joint and coordinated exploitation of resources in FiWi and Edge IoT domains, with performance results that highlight its benefits in terms of efficiency and responsiveness. © 2013 IEEE. |
2017 |
P. Sarigiannidis; E. Karapistoli; A.A. Economides , "Modeling the Internet of Things under Attack: A G-network Approach", IEEE Internet of Things Journal, 4 (6), pp. 1964-1977, 2017. Journal Article Περίληψη | BibTeX | Ετικέτες: G-networks, Internet of Things (IoT), Modeling, queuing theory, security | Σύνδεσμοι: @article{Sarigiannidis20171964, title = {Modeling the Internet of Things under Attack: A G-network Approach}, author = { P. Sarigiannidis and E. Karapistoli and A.A. Economides}, url = {https://www.researchgate.net/publication/317867935_Modelling_the_Internet_of_Things_Under_Attack_A_G-network_Approach?_sg=nQGxFUwlDGkq6bJAkluGr9ICZ80minya34gpJdFzE990HU4AFYuPRV760oFW4FmaMbAYtNSeFztuzGo}, doi = {10.1109/JIOT.2017.2719623}, year = {2017}, date = {2017-01-01}, journal = {IEEE Internet of Things Journal}, volume = {4}, number = {6}, pages = {1964-1977}, abstract = {This paper introduces a novel, analytic framework for modeling security attacks in Internet of Things (IoT) infrastructures. The devised model is quite generic, and as such, it could flexibly be adapted to various IoT architectures. Its flexibility lies in the underlying theory, it is based on a dynamic G-network, where the positive arrivals denote the data streams that originated from the various data collection networks (e.g., sensor networks), while the negative arrivals denote the securit attacks that result in data losses (e.g., jamming attacks). In addition, we take into account the intensity of an attack by considering both light and heavy attacks. The light attack implies simple losses of traffic data, while the heavy attack causes massive data loss. The introduced model is solved subject to the arrival and departure rates in terms of: 1) average number of data packets in the application domain and 2) attack impact (loss rate). A comprehensive verification discussion accompanied by numerous numerical results verify the accuracy of the proposed model. Moreover, the assessment of the presented model highlights notable operation characteristics of the underlying IoT system under light and heavy attacks. © 2017 IEEE.}, keywords = {G-networks, Internet of Things (IoT), Modeling, queuing theory, security}, pubstate = {published}, tppubtype = {article} } This paper introduces a novel, analytic framework for modeling security attacks in Internet of Things (IoT) infrastructures. The devised model is quite generic, and as such, it could flexibly be adapted to various IoT architectures. Its flexibility lies in the underlying theory, it is based on a dynamic G-network, where the positive arrivals denote the data streams that originated from the various data collection networks (e.g., sensor networks), while the negative arrivals denote the securit attacks that result in data losses (e.g., jamming attacks). In addition, we take into account the intensity of an attack by considering both light and heavy attacks. The light attack implies simple losses of traffic data, while the heavy attack causes massive data loss. The introduced model is solved subject to the arrival and departure rates in terms of: 1) average number of data packets in the application domain and 2) attack impact (loss rate). A comprehensive verification discussion accompanied by numerous numerical results verify the accuracy of the proposed model. Moreover, the assessment of the presented model highlights notable operation characteristics of the underlying IoT system under light and heavy attacks. © 2017 IEEE. |
Διεύθυνση
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Πληροφορίες Επικοινωνίας
tel: +30 2461 056527
Email: ithaca@uowm.gr