@article {4519, title = {A Comparative Study of Machine Learning Models for Spreading Factor Selection in LoRa Networks}, journal = {Journal of Wireless Networks and Broadband Technologies (IJWNBT), IGI Global}, volume = {10}, year = {2021}, pages = {100-121}, abstract = {Low Power Wide Area Networks (LPWAN) technologies offer reasonably priced connectivity to a large number of low-power devices spread over great geographical ranges. Long Range (LoRa) is a LPWAN technology that empowers energy-efficient communication. In LoRaWAN networks collisions are strongly correlated with Spreading Factor (SF) assignment of end-nodes which affects network performance. In this work, SF assignment using Machine Learning models in simulation environment is presented. This work examines three approaches for the selection of the SF during LoRa transmissions a) random SF assignment b) Adaptive Data Rate (ADR) and c) SF selection through Machine Learning (ML). The main target is to study and determine the most efficient approach as well as to investigate the benefits of using ML techniques in the context of LoRa networks. In this research a library that enables the communication between ML libraries and OMNeT++ simulator was created. The performance of the approaches is evaluated for different scenarios, using the delivery ratio and energy consumption metrics.}, author = {Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris and Nikolaos Papachristos} } @article {4576, title = {Performance Evaluation of Monitoring IoT Systems using LoRaWan}, journal = {Telecommunication Systems, Springer Verlang}, year = {2021}, abstract = {The proliferation of smart devices, or even better, IoT devices, has led to the widespread development of applications that take advantage of these devices. Of particular interest is the precise localization of such a device. However, these use cases become extremely difficult when connectivity to end-devices is required even in areas where the signal is too low or different technologies co-exist for the transmission of the data. In this research work, we study LoRaWan and Wi-Fi as two possible candidates for data transmission. We are particularly focused on the study of the above technologies in terms of performance as well as application development that can be used as rescue monitoring systems. For this reason, we start by describing LoRa as an ideal low power and long-distance communication protocol on the IoT devices compared to the Wi-Fi network. We perform various simulations in terms of time on air transmission, bit error rate by changing important metrics to study the behavior of the whole mechanism. Based on our simulations, the main findings highlight that the contribution of a Spreading Factor (SF) and bandwidth (BW) optimizations can be applied to real hardware for real Search and Rescue (SAR) cases giving improved results in case of coverage and battery extension applications. As a continuation of our research, we developed a monitor application that collects and visualizes data from end-nodes (wearables). These data are processed gateway and network server to The Things Network (TTN) for further analysis. The proposed solution can be used in different rescue monitor scenarios such as identifying and find individuals of vulnerable groups or those belonging to group of people with a high probability of being lost. The purpose of the above solution is to overcome monitor problems on SAR cases, compare with WiFi and suggest a module supporting both technologies in order to be used in real experiments.}, author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos} } @conference {4504, title = {Real - Time Geolocation Approach through LoRa on Internet of Things}, booktitle = {The 35th International Conference on Information Networking (ICOIN 2021), January 13 - 16, 2021, Jesu Island}, year = {2021}, month = {January 13 - 16,}, pages = {186-191}, abstract = {Internet of Things (IoT) and wireless technologies like LoRa brought more opportunities for application development in a plethora of different fields. One of these is location estimation of real-time objects and people. In this study, we focus on monitoring user{\textquoteright}s location through a wearable IoT device with LoRa connectivity. The paper presents the development and integration of an loT ecosystem (Hardware and Software) which can be used in Search and Rescue (SAR) use cases. The proposed IoT ecosystem is evaluated and deployed inreal-scenarios with established gateways. After that we compare the existed location-estimation methods in terms of attenuation problem, cost and operation as well to conclude to the most suitable solution that can be integrated in LoRaWAN environments. Finally, the conclusions of this work and improvements for possible future activity are described.}, author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos} } @conference {4507, title = {Spreading Factor Analysis for LoRa networks: A supervised learning approach}, booktitle = {9th World Conference on Information Systems and Technologies (WorldCIST{\textquoteright}21), March 30 - 31 and 1-2 April 1 - 2, 2021, Azores, Portugal}, year = {2021}, abstract = {Today, the Internet of Things (IoT) has been introduced in our lives, giving a variety of solutions and applications. The critical requirements for de-vices connected to the IoT are long battery life, long coverage, and low de-ployment cost. Some applications require the transmission of data over long distances, thus Low Power Wide Area Networks (LPWAN) have emerged, with LoRa being one of the most popular players of the market. In order, to improve energy consumption and connectivity problems, machine learning can be used in LoRa networks. In this paper, we intend to improve the energy consumption of end nodes by using machine learning models. For this reason, we present a comparison of classification algorithms, specifically, the k-NN, the Na{\"\i}ve Bayes, and Support Vector Machines (SVM), for the Spreading Factor (SF) as-signment in LoRa networks. The simulation results indicate that, both energy efficiency and reliability in IoT communications could be significantly im-proved using the proposed learning approach. These promising results, which are achieved using lightweight learning, make our solution favorable in many low-cost low-power IoT applications.}, author = {Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris and Nikolaos Papachristos} } @conference {4531, title = {Spreading Factor Selection Mechanism for Transmission over LoRa Networks}, booktitle = {28th International Conference on Telecommunications (ICT 2021), June 1 - 3, 2021, London, UK }, year = {2021}, pages = {344-353}, abstract = {This paper presents a mechanism for Spreading Factor (SF) prediction in LoRa networks for more optimized data transmissions. The proposed mechanism is based on Machine Learning (ML) algorithms and assigns the node{\textquoteright}s SF value based on prior transmission data. This paper examines three different approaches for the selection of the SF during LoRa transmissions a) Random SF assignment b) Adaptive Data Rate (ADR) and c) ML based SF selection. The main target is to study and determine the most efficient approach, as well as to investigate the exploitation of ML techniques in the context of LoRa networks. We created a simple library based on ML libraries, such as Scikit Learn that can be used with the FLoRa an OMNeT++ based LoRa simulator. With the use of this library, it is possible to predict the node{\textquoteright}s SF using ML techniques. Two classification algorithms were tested, the k Nearest Neighbors (k-NN) and Na{\"\i}ve Bayes classifier. Finally, we compared the ML mechanisms with two variants of the ADR mechanism. The approaches performance is evaluated for different scenarios, using the delivery ratio and energy consumption metrics.}, author = {Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris and Nikolaos Papachristos} } @article {4487, title = {Geolocation analysis for SAR systems using LoRaWAN}, journal = {International Journal of Communication Systems, Wiley InterScience}, year = {2020}, abstract = {Low Power Wide Area Network (LPWAN) technologies aiming to provide power-efficient solutions to the field of Internet of Things (IoT). Over the last years we have seen a significant development within the area of IoT applications. For many applications, the problem of localization (i.e. determine the physical location of nodes) is critical. An area study of such use case is also the rescue monitor systems. In this study, we start by describing a solution designed for the Long Range Wide Area Network (LoRaWAN) to localize position of IoT modules such as wearables used from vulnerable groups. Through performance study of the behavior of a LoRaWAN channel and using trilateration and RSSI information, the localization of an IoT wearable can be acquired within a small range. Routing people in need is one of the use cases the above mechanism could be integrated so as to be able to be tracked by familiar people. After that, we evaluate the usage of mathematical model of multilateration algorithms using Time Difference of Arrival (TDoA) as a solution for positioning over LoRaWAN. The research is carried out using simulations in Python by configuring the constant positions of the Gateways inside an outdoor area. The proposed algorithms can be integrated in application for tracking people at any time and especially routing people from vulnerable groups. Through multilateration and algorithm{\textquoteright}s prediction, we can have an accuracy of 40-60m in location positioning, ideal for search and rescue use cases. We finally summarize the above algorithms{\textquoteright} estimation and general behavior in a SAR system.}, author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos} } @conference {4433, title = {IoT Geolocation Performance Using LoRaWAN}, booktitle = {The 34th International Conference on Advanced Information Networking and Applications (AINA - 2020), Caserta, Italy}, year = {2020}, abstract = {Low Power Wide Area Network (LPWAN) technologies aiming to provide power-efficient solutions to the world of IoT. This paper describes a solution based on the Long Range Wide Area Network (LoRaWAN) technology to geolocalise IoT modules such as wearables used from vulnerable groups. Through estimation of the behavior of a LoRaWAN channel and using trilateration and RSSI information, the localization of an IoT wearable can be obtained within a small range. Routing people in need is one of the use cases the above mechanism could be integrated so as to be able to be tracked by familiar people.}, author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos} } @inbook {4496, title = {Search and Rescue System Based on NB-IoT Wearable Device}, booktitle = {Principles and Applications of Narrowband Internet of Things (NBIoT), IGI Global}, year = {2020}, pages = {195-222}, chapter = {9}, abstract = {This chapter presents the design and development of a search and rescue (SAR) system, for the location and provision of aid to people who are missing or in imminent danger, especially those belonging to population groups with a particularly high probability of getting lost. With the use of Low-Power Wide Area Network (LPWAN) technology, such as Narrow Band Internet of Things (NB-IoΤ), authors are able to provide search and rescue solutions for individuals, especially those belonging to groups of people who are more likely to get lost. The central part of the system is a modular {\textquotedblleft}wearable (portable){\textquotedblright} device, while in the framework of the implementation of this system authors have seriously taken into consideration the aspects of energy efficiency in order to provide better battery life.}, author = {Christos Bouras and Apostolos Gkamas and Spyridon Katsampiris and Nikolaos Papachristos} } @conference {4461, title = {Time Difference of Arrival Localization Study for SAR Systems over LoRaWAN}, booktitle = {15th International Conference on Future Networks and Communications (FNC 2020)}, year = {2020}, abstract = {Over the last years we have seen a rapid expansion within the area of Internet of Things (IoT) applications. For many applications{\textquoteright} use cases, such as rescue monitor systems, the problem of localization (i.e. determine the physical location of nodes) is critical. This paper studies and evaluates the usage of mathematical model of multilateration algorithms using Time Difference of Arrival (TDoA) as a solution for positioning over Long Range Wide Area Network (LoRaWAN). The research is carried out using simulations in Python by configuring the constant positions of the Gateways inside an outdoor area. The proposed algorithms can be integrated in application for tracking people at any time and especially routing people from vulnerable groups. Through multilateration and algorithm{\textquoteright}s prediction, we can have an accuracy of 40-60m in location positioning ideal for search and rescue use cases.}, author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos} } @conference {4412, title = {Using LoRa Technology for IoT Monitoring Systems}, booktitle = {10th International Conference on the Network of the Future (NoF 2019), Rome, Italy}, year = {2019}, month = {October 1 - 3}, pages = {134-137}, abstract = {This paper presents technology comparison scenarios for Internet of Things (IoT) concepts on rescue monitoring. The study starts by comparing WiFi \& LoRa as wireless technologies able to be used by smart devices for data transmission. The IoT end-devices used in these concepts have high requirements in battery saving and for this reason the usage of low-power modules is advisable. This paper focus in rescue monitoring and the goal in the current study is the usage of the two wireless technologies used for data transmission from IoT devices: the already known WiFi and the upcoming LoRa technology. During rescue monitoring, important concepts are the identification and individuals{\textquoteright} rescue of particularly vulnerable groups or individuals belonging to population groups with a high probability of being lost. A LoRa based gateway and WiFi Router is used to connect the end-devices used in our scenarios to the Internet. The collected data on server application as captured from installed sensors on the IoT modules can be displayed to authorized users through a web or mobile application. The results through simulation and real time experiments indicate that LoRa could be an ideal candidate for rescue monitoring. This study is a first step in creating a more general ecosystem for rescue concepts including all the hardware and software using the LoRa technology as transmission method.}, author = {Christos Bouras and Apostolos Gkamas and Vasileios Kokkinos and Nikolaos Papachristos} } @article {4405, title = {WiFiMon - A Tool for Wi-Fi Performance Monitoring and Verification}, journal = {International Journal of Wireless Networks and Broadband Technologies (IJWNBT), IGI Global}, volume = {8}, year = {2019}, pages = {1-18}, abstract = {Measuring network quality of a wireless network as experienced by end-users is quite difficult, as there isn{\textquoteright}t a single tool available that can record measurements on all sides of the system. The approach presented in this research work is based on the end-user feedback, giving the opportunity of visualization of network performance in real time. We initially present an overview of the developed tool, called WiFiMon, which has the ability to capture, record measurements and export statistics on the quality of Wi-Fi network as perceived by the end-users. The measurements are initiated by the end-users - without their intervention {\textendash} after they visit a web page or use a mobile application. WiFiMon aims to give a clear understanding of the Wi-Fi network conditions by measuring specific parameters of the network, such as download/upload throughput, and correlate these measurements with raw data from various log files to obtain additional information regarding the performance of specific access points. The results reveal the functionality of the proposed tool and its scalability.}, author = {Kurt Baumann and Christos Bouras and Vasileios Kokkinos and Nikolaos Papachristos and Kostas Stamos} } @article {4259, title = {MCS Selection Exploiting Femtocells Utilization in Multicast Transmissions}, journal = {International Journal of Communication Systems, Wiley InterScience}, volume = {31}, year = {2018}, abstract = {Multicast-Broadcast over Single Frequency Network (MBSFN) technology, as introduced by the Long Term Evolution Advanced (LTE-A) group, is expected to be part of the upcoming cellular systems offering resource efficiency to broadcast services. MBSFN transmission is suitable to serve multicast groups searching the same content. In addition, the fast emerging technology of femtocells networks and their hybrid nature can lead to efficient resource sharing between non-subscribed users when located inside their coverage. The focus of this manuscript is twofold; firstly, we have contacted simulation experiments to compare the MBSFN transmission with the traditional PTP transmission for various femtocell distributions and network topology changes; secondly, a novel multicast transmissions mechanism is proposed from non-subscribed users who exploit femtocells resources for broadcast services, without limiting user{\textquoteright}s data requirements. The simulation results lead to a significant system{\textquoteright}s performance in terms of average throughput, total capacity and energy consumption.}, author = {Christos Bouras and Nikolaos Kanakis and Vasileios Kokkinos and Nikolaos Papachristos and Demosthenes Vouyioukas} } @conference {4324, title = {Performance evaluation of LoraWan physical layer integration on IoT devices}, booktitle = {Global Information Infrastructure and Networking Symposium (GIIS 2018), Thessaloniki, Greece}, year = {2018}, abstract = {Due to the constant motion of wireless devices in the Internet of Things (IoT), infrastructure wireless networks cannot provide connectivity at all times, in comparison with ad hoc networks, which are more easy to use and are based on abstract and continuously altering topologies. LoraWan, as a Long Range Wide Area Network specification recommended by the LoRa Alliance, is a low power and long distance communication protocol suitable for IoT environments and applications to different domains such as healthcare and smart farming. This IoT concept is gaining a rapid growth on the IoT market and is simultaneously improving our living environment. In this paper, we first briefly introduce LoRa as an efficient solution of physical layer integration on the IoT devices. We then conduct a performance evaluation taking into consideration metrics such as bit error rate, time on air transmission based on Signal to Noise Ratio (SNR) and Spreading Factors modifications for different bandwidth values.}, author = {Christos Bouras and Vasileios Kokkinos and Nikolaos Papachristos} } @conference {4192, title = {Extension to Middleware for IoT Devices, with Applications in Smart Cities}, booktitle = {2nd EAI International Conference on ICT Infrastructures and Services for Smart Cities (IISSC 2017), Brindesi, Italy}, year = {2017}, month = {April 20 - 21}, abstract = {

This work proposes extensions toWubby (a device-level software platform for IoT devices, a technology developed by Econais A.E.) to support wireless modules for mobile networks (4G / LTE-A, and also supporting the forthcoming 5G). The proposed extension leverages the use of such modules, as it allows easy programming and existing code re-use. It thus adds a compatibility layer across the di erent modules as it a common set of classes for the wireless modules. The system can be used to support the networking aspects of a variety of IoT applications, including applications for Smart Cities, using a variety of IoT devices. This work suggests such a case focusing on air quality monitoring.

}, author = {Christos Bouras and Vaggelis Kapoulas and Vasileios Kokkinos and Dimitris Leonardos and Costas Pipilas and Nikolaos Papachristos} } @conference {4194, title = {WiFiMon App Measuring Wi-Fi Performance as Experienced by End - Users}, booktitle = {24th International Conference on Telecommunication (ICT 2017)}, year = {2017}, month = {May 3 - 5}, abstract = {

The measurement of quality and efficiency of a wireless Wi-Fi network is particularly difficult, as there is not a single tool that can record measurements from all sides of the system, i.e. from both the access point and the end-user. Existing tools are able to monitor the overall quality of the wireless network; although they cannot determine how end-users experience the quality of Wi-Fi in a particular part of the network at a given time. In this paper we present a novel tool, named WiFiMon, which enables measuring, recording and exporting statistics regarding the quality of a Wi-Fi network as experienced by the end-users. The measurements are triggered by the end-users when they visit WiFiMon-enabled websites and/or run WiFiMon-enabled mobile applications and are recorded without users{\textquoteright} intervention. Main goal of WiFiMon is to give network administrators a better overview on how the endusers experience the conditions of the Wi-Fi network.

}, author = {Kurt Baumann and Christos Bouras and Vasileios Kokkinos and Nikolaos Papachristos and Kostas Stamos} } @conference {4136, title = {Comparison of Point to Point and MBSFN transmissions in Next Generation Mobile Networks}, booktitle = {The 14th ACM International Symposium on Mobility Management and Wireless Access (Mobiwac 2016)}, year = {2016}, month = {November 13 - 17}, pages = {169-172}, abstract = {

Multicast/Broadcast Multicast Service over Single Frequency Network (MBSFN) technology has introduced advanced broadcast capabilities to cellular systems. In Long Term Evolution Advanced (LTE-A) systems, MBSFN transmission accommodates multicast groups in search of the same data. In this paper we compare the traditional Point-to-Point (PTP) communication with the MBSFN services through simulation experiments for various femtocell distributions and network configurations. The comparison takes into account the average throughput, overhead cost, energy consumption and capacity gain, concluding that MBSFN through multicast transmission may guarantee performance improvement even for users in the cell boundaries.

}, author = {Christos Bouras and Nikos Kanakis and Vasileios Kokkinos and Nikolaos Papachristos and Demosthenes Vouyioukas} } @conference {4118, title = {Utilization of Hybrid Access Femtocells During Multicast Transmissions in Mobile Networks}, booktitle = {European Conference on Networks and Communications, Athens, Greece}, year = {2016}, month = {June 27 - 30}, pages = {190-194}, abstract = {

Femtocells enhance indoor coverage of mobile services using the owner{\textquoteright}s broadband connection. They were initially designed to serve a number of subscribed User Equipments within their range. This design however, resulted in underutilization of the femtocells resources, and simultaneously in high interference levels for nearby non-subscribed users. Nowadays, femtocells can support multicast transmissions, while their hybrid operation allows non-subscribed users to use a portion of their resources. In this paper we propose a novel mechanism that is based on the selection of the appropriate Modulation and Coding Scheme. The mechanism allows non-subscribed users to utilize a portion of the femtocells{\textquoteright} resources for multicast transmissions when located inside their coverage, without affecting the owners{\textquoteright} satisfaction. The simulation results show that depending on the portion of the femtocells{\textquoteright} resources allocated to non-subscribed users, the mechanism may significantly increase the average user throughput.

}, author = {Christos Bouras and Nikolaos Kanakis and Vasileios Kokkinos and Nikolaos Papachristos and Demosthenes Vouyioukas} }