Impact of drone route geometry on information collection in wireless sensor networks

The recent technological evolution of drones along with the constantly growing maturity of its commercialization, has led to the emergence of novel drone-based applications within the field of wireless sensor networks for information collection purposes. In such settings, especially when deployed in outdoor environments with limited external control, energy consumption and robustness are challenging problems for the system’s operation. In the present paper, a drone-assisted wireless sensor network is studied, the aim being to coordinate the routing of information (among the ground nodes and its propagation to the drone), investigating several drone trajectories or route shapes and examining their impact on information collection (the aim being to minimize transmissions and consequently, energy consumption). The main contribution lies on the proposed algorithms that coordinate the communication between (terrestrial) sensor nodes and the drone that may follow different route shapes. It is shown through simulations using soft random geometric graphs that the number of transmitted messages for each drone route shape depends on the rotational symmetry around the center of each shape. An interesting result is that the higher the order of symmetry, the lower the number of transmitted messages for data collection. Contrary, for those cases that the order of symmetry is the same, even for different route shapes, similar number of messages is transmitted. In addition to the simulation results, an experimental demonstration, using spatial data from grit bin locations, further validates the proposed solution under real-world conditions, demonstrating the applicability of the proposed approach.publishedVersio

Polynuclear ampyrone based 3d coordination clusters

The use of the monoanionic Schiff base ligand (E)-4-(2-hydroxybenzylideneamino)-2,3-dimethyl-1-phenyl-1,2-dihydropyrazol-5-one in transition (Co, Ni and Cu) coordination chemistry yields mono-, tetra- and pentanuclear Coordination Clusters with different structural motifs. An organic transformation occurs in the ligand in the Cu compound for which theoretical studies are presented. Solution studies, topological issues and magnetic studies are discussed. The present results demonstrate the richness of the coordination chemistry of this monoprotic organic ligand, which promotes the formation of high-nuclearity CC

Shedding light on the use of Cu(II)-salen complexes in the A3 coupling reaction

One Cu(II) complex, {Cu(II)L} (1S), has been synthesised, in two high yielding steps under ambient conditions, and characterised by single-crystal X-Ray diffraction (SXRD), IR, UV Vis, Circular Dichroism (CD), Elemental analysis, Thermogravimetric analysis (TGA) and Electron Spray Ionization Mass Spectroscopy (ESI-MS). This air-stable compound enables the generation, at room temperature and open-air, of twenty propargylamines, nine new, from secondary amines, aliphatic aldehydes and alkynes with a broad scope with yields up to 99%. Catalyst loadings can be as low as 1 mol%, while the recovered material retains its structural integrity and can be used up to 5 times without loss of its activity. Control experiments, SXRD, 2 cyclic voltammetry and theoretical studies shed light on the mechanism revealing that the key to success is the use of phenoxido salen based ligands. These ligands orchestrate topological control permitting alkyne binding with concomitant activation of the C–H bond and simultaneously acting as template temporarily accommodating the abstracted acetylenic proton, and continuous generating, via in-situ formed radicals and Single Electron Transfer (SET) mechanism, of a transient Cu(I) active site to facilitate this transformation. The scope and limitations of this protocol are discussed and presented

An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting

Internet of Things (IoT) appliances, especially those realized through wireless sensor networks (WSNs), have been a dominant subject for heavy research in the environmental and agricultural sectors. To address the ever-increasing demands for real-time monitoring and sufficiently handle the growing volumes of raw data, the cloud/fog computing paradigm is deemed a highly promising solution. This paper presents a WSN-based IoT system that seamlessly integrates all aforementioned technologies, having at its core the cloud/fog hybrid network architecture. The system was intensively validated using a demo prototype in the Ionian University facilities, focusing on response time, an important metric of future smart applications. Further, the developed prototype is able to autonomously adjust its sensing behavior based on the criticality of the prevailing environmental conditions, regarding one of the most notable climate hazards, wildfires. Extensive experimentation verified its efficiency and reported on its alertness and highly conforming characteristics considering the use-case scenario of Corfu Island’s 2019 fire risk severity. In all presented cases, it is shown that through fog leveraging it is feasible to contrive significant delay reduction, with high precision and throughput, whilst controlling the energy consumption levels. Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler’s burning index scoring

Βελτιστοποίηση χρήσης δικτυακών πόρων σε περιβάλλοντα υπολογιστικού νέφους

Recent technological advances in cloudification and virtualization already support numerous applications and wide deployment of network devices, e.g., Internet of Things (IoT), and Wireless Sensor Networks (WSNs), that are envisioned to reach the extreme number of 28 billion devices by the end of 2021. The expected increment in human-type and machine-type communications introduce a wide variety of communication characteristics with different requirements regarding data rate, latency, mobility, and reliability. In such environments, to compensate for the huge demands in resources and the growing volumes of data, numerous data centers, and devices deployed around the world work in unison to efficiently accommodate service provisioning. Nevertheless, as the number of users and cloud services increases, key optimization problems emerge and become a priority for cloud service providers who focus on scalability and service availability problems in order to minimize the overall operational cost and eventually increase their profit revenues and public acceptance. In this context, the problems of discovering the number and location of virtual machines that instantiate a cloud service, as well as finding efficient ways for user assignment and dynamic resource allocation, become exceedingly complex problems (NP-hard), since their solutions are affected by a large number of criteria, parameters, and constraints. When also considering the high inherent dynamicity and frequent fluctuations in network traffic and conditions, it becomes abundantly clear that classical or strictly centralized approaches, requiring global knowledge of the topology conditions, fail to capture the needs for timely scalability and adaptability. Thus, the need for procuring new feasible and low-complexity solutions for service location, resource allocation, and data handling arises, even if these come at the expense of unguaranteed optimal solutions. The present thesis dissertation studies the preceding problems through a different prism, taking advantage of the benefits offered by distributed computing. As such, it is divided into two major focal points of interest. The first explores location-allocation issues in Cloud Gaming, the latter being an ideal representative of highly dynamic cloud computing environments that can be straightforwardly generalized to capture other cloud application domains. Contrary to general approaches, the focus is on the fog/edge layer, for which five decentralized policies, relying solely on local network information, are derived and analyzed for efficient, elastic, and scalable admission control, user assignment, server allocation, resource optimization, and service placement. Regarding the second focal point, issues affiliating to data handling optimization in the IoT are studied, with emphasis on data measurement synchronization and drone-based information collection. Finally, two complete systems, that incorporate fog computing for resource optimization and adaptation, are presented, on one hand for the case of Smart Cities and on the other hand for the case of Smart Agriculture.Οι πρόσφατες τεχνολογικές εξελίξεις στη νεφοϋπολογιστική και εικονικοποίηση υποστηρίζουν ήδη πολλές σύγχρονες εφαρμογές και πληθώρα συσκευών δικτύου, π.χ. Διαδίκτυο των Πραγμάτων (ΔτΠ) και Ασύρματα Δίκτυα Αισθητήρων (ΑΔΑ), που μάλιστα προβλέπεται ότι θα φτάσουν τον ακραίο αριθμό των 28 δισεκατομμυρίων συσκευών έως το τέλος του 2021. Αυτή η αναμενόμενη αύξηση των επικοινωνιών ανθρώπου και μηχανής εισάγει μια ευρεία ποικιλία χαρακτηριστικών επικοινωνίας με διαφορετικές απαιτήσεις σχετικά με τον ρυθμό μετάδοσης δεδομένων, την καθυστέρηση, την κινητικότητα και την αξιοπιστία. Σε τέτοια περιβάλλοντα, για να επιτευχθεί αντιστάθμιση των τεράστιων απαιτήσεων σε πόρους και του αυξανόμενου όγκου δεδομένων, πολλά κέντρα δεδομένων και συσκευές ανά τον κόσμο λειτουργούν από κοινού για να επιτύχουν αποτελεσματική παροχή υπηρεσιών. Ωστόσο, καθώς ολοένα αυξάνεται ο αριθμός των χρηστών και των υπηρεσιών υπολογιστικού νέφους, προκύπτουν βασικά προβλήματα βελτιστοποίησης, η λύση των οποίων αποτελεί προτεραιότητα για τους παρόχους υπηρεσιών νέφους που εστιάζουν σε προβλήματα κλιμάκωσης και διαθεσιμότητας πόρων, προκειμένου να ελαχιστοποιηθεί το συνολικό λειτουργικό κόστος και τελικά να αυξηθούν η κερδοφορία και η αποδοχή του κοινού. Σε αυτό το πλαίσιο, τα προβλήματα της ανακάλυψης του αριθμού και της θέσης των εικονικών μηχανών, που φιλοξενούν μια υπηρεσία νέφους, καθώς και η εύρεση αποτελεσματικών τρόπων εκχώρησης χρήστη και δυναμικής κατανομής πόρων, εξελίσσονται σε εξαιρετικά πολύπλοκα προβλήματα (NP-hard), αφού οι λύσεις τους επηρεάζονται από μεγάλο αριθμό κριτηρίων, παραμέτρων και περιορισμών. Λαμβάνοντας υπόψιν και την υψηλή εγγενή δυναμικότητα και τις συχνές διακυμάνσεις στην κυκλοφορία και τις συνθήκες του δικτύου, καθίσταται απολύτως σαφές ότι οι κλασικές ή αυστηρά κεντρικοποιημένες προσεγγίσεις, που απαιτούν καθολική γνώση της δικτυακής τοπολογίας, αποτυγχάνουν να καλύψουν τις απαιτήσεις για έγκαιρη επεκτασιμότητα και προσαρμοστικότητα. Έτσι, προκύπτει η ανάγκη για νέες εφικτές και χαμηλής πολυπλοκότητας λύσεις για την τοποθέτηση υπηρεσιών, την κατανομή πόρων, και τον χειρισμό δεδομένων, ακόμη και αν αυτές έρχονται σε βάρος μη εγγυημένων βέλτιστων λύσεων. Η παρούσα διατριβή μελετά τα προηγούμενα προβλήματα μέσω ενός διαφορετικού πρίσματος, αξιοποιώντας τα οφέλη που προσφέρει ο κατανεμημένος υπολογισμός. Ως εκ τούτου, χωρίζεται σε δύο κύριους άξονες ενδιαφέροντος. Ο πρώτος διερευνά ζητήματα τοποθεσίας υπηρεσιών και κατανομής πόρων σε συστήματα Cloud Gaming, με τα τελευταία να θεωρούνται ιδανικοί εκπρόσωποι άκρως δυναμικών περιβαλλόντων υπολογιστικού νέφους, και που μπορούν εύκολα να γενικευτούν για άλλους τομείς εφαρμογών νέφους. Σε αντίθεση με προηγούμενες ερευνητικές προσεγγίσεις, η παρούσα διατριβή εστιάζει στο επίπεδο της υπολογιστικής ομίχλης, για το οποίο προτείνονται και αναλύονται πέντε κατανεμημένες πολιτικές, που βασίζονται αποκλειστικά σε τοπική δικτυακή πληροφορία, για την επίτευξη αποδοτικής, ελαστικής, και κλιμακώσιμης εκχώρησης χρηστών, ελέγχου εισδοχής, ανάθεσης εξυπηρετητών, βελτιστοποίησης χρήσης πόρων, και τοποθέτησης υπηρεσιών. Όσον αφορά τον δεύτερο άξονα εστίασης, μελετώνται θέματα που σχετίζονται με τη βελτιστοποίηση του χειρισμού δεδομένων στο ΔτΠ, με έμφαση να δίνεται στον συγχρονισμό μετρήσεων και στην συλλογή πληροφορίας από δρόνο. Τέλος, παρουσιάζονται δύο ολοκληρωμένα συστήματα, τα οποία ενσωματώνουν υπολογιστική ομίχλης για βελτιστοποίηση και αυτόματη προσαρμογή της παροχής πόρων, αφενός για την περίπτωση των Έξυπνων Πόλεων και αφετέρου για την περίπτωση της Έξυπνης Γεωργίας

A Low-Cost Vehicular Traffic Monitoring System Using Fog Computing

With the rapid increase of vehicles in use worldwide, the need for efficient traffic monitoring systems has arisen. This work proposes a low-cost vehicular traffic monitoring system using IoT devices and fog computing. The system is based on a three-tiered architecture which is composed of (i) the mobile tracking system that records the positions of the vehicles using GPS technologies; (ii) the information gathering system which gathers all the data collected by the mobile tracking system; and (iii) the fog devices that process the data collected and extract the information needed. The system is tested in the town of Corfu during a period of increased tourism when the traffic is considered to be relatively dense. The mobile tracking system devices are placed on taxis and with the help of professional taxi drivers the accuracy of the data collected is evaluated. The system is able to record the movement of the vehicles accurately using its own independent data. The results can be remotely accessed by utilizing fog and cloud computing infrastructure established to process the data and upload it on a server. The system is used to give a better understanding of the speed variance in the center of the town during different dates and hours. In conclusion the system presented in this study can be utilized to monitor the traffic and provide vital information about its behavior in relation to time

Impact of drone route geometry on information collection in wireless sensor networks

The recent technological evolution of drones along with the constantly growing maturity of its commercialization, has led to the emergence of novel drone-based applications within the field of wireless sensor networks for information collection purposes. In such settings, especially when deployed in outdoor environments with limited external control, energy consumption and robustness are challenging problems for the system’s operation. In the present paper, a drone-assisted wireless sensor network is studied, the aim being to coordinate the routing of information (among the ground nodes and its propagation to the drone), investigating several drone trajectories or route shapes and examining their impact on information collection (the aim being to minimize transmissions and consequently, energy consumption). The main contribution lies on the proposed algorithms that coordinate the communication between (terrestrial) sensor nodes and the drone that may follow different route shapes. It is shown through simulations using soft random geometric graphs that the number of transmitted messages for each drone route shape depends on the rotational symmetry around the center of each shape. An interesting result is that the higher the order of symmetry, the lower the number of transmitted messages for data collection. Contrary, for those cases that the order of symmetry is the same, even for different route shapes, similar number of messages is transmitted. In addition to the simulation results, an experimental demonstration, using spatial data from grit bin locations, further validates the proposed solution under real-world conditions, demonstrating the applicability of the proposed approach