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Author

Mehmet Ali Erturk

Bio: Mehmet Ali Erturk is an academic researcher from Istanbul University. The author has contributed to research in topics: Load balancing (computing) & Quality of service. The author has an hindex of 3, co-authored 11 publications receiving 84 citations.

Papers
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Journal ArticleDOI
TL;DR: LoRaWAN technology, the state of art studies in the literature and open opportunities are introduced and theses will provide open opportunities.
Abstract: Internet of Things (IoT) expansion led the market to find alternative communication technologies since existing protocols are insufficient in terms of coverage, energy consumption to fit IoT needs. Low Power Wide Area Networks (LPWAN) emerged as an alternative cost-effective communication technology for the IoT market. LoRaWAN is an open LPWAN standard developed by LoRa Alliance and has key features i.e., low energy consumption, long-range communication, builtin security, GPS-free positioning. In this paper, we will introduce LoRaWAN technology, the state of art studies in the literature and provide open opportunities.

91 citations

Proceedings ArticleDOI
01 Jul 2017
TL;DR: The standard and data frame transmission in LoRaWAN is explored and evaluated with a custom test-bed system for data transmission for health care systems and critical health data in disaster environments.
Abstract: LoRaWAN is a Low Power Wide Area Network (LPWAN) technology which enables low cost and low power IoT device communication even in dense urban areas. LoRa modulation is capable of extracting data from a weak signal in noisy environments. This modulation technique can be useful for the delivery of critical data in the noisy environment. In this study, we investigate LoRaWAN technology in the context of data transmission for health care systems (or critical health data in disaster environments). In the study, we explore the standard and evaluate data frame transmission in LoRaWAN with a custom test-bed system.

37 citations

Journal ArticleDOI
31 Dec 2020
TL;DR: In this paper, the authors examined educational experiences during the 2020 Spring Semester at Istanbul University, which has been regarded as the role model by many other Turkish universities for complying with decisions made by the Council of Higher Education in Turkey (CHE) in parallel with the rapid spread of the global pandemic.
Abstract: This study centers on the distance education applications that have played a leading role in implementing educational activities conducted by higher education institutions in Turkey and around the world during the COVID-19 global pandemic. In this context, the purpose of this study is to examine educational experiences during the 2020 Spring Semester at Istanbul University, which has been regarded as the role model by many other Turkish universities for complying with decisions made by the Council of Higher Education in Turkey (CHE) in parallel with the rapid spread of the global pandemic. In this regard, the distance education processes coordinated by Istanbul University’s Faculty of Open and Distance Education will be scrutinized in all aspects using the outcomes from questionnaires and other certain statistics. The study aims to help present an innovative perspective for the 2020-2021 academic year in light of all the circumstances and developments encountered during the COVID process.

7 citations

Proceedings ArticleDOI
23 Oct 2014
TL;DR: This study presents a framework for modeling, analyzing and designing QoS-aware Load Balancing solutions and shows that the model is effective in capturing network performance and in designing LB solutions that account for traffic priorities and the configuration of QoS parameters.
Abstract: Access Point (AP) selection in WiFi hotspots is driven by stations and it is based on the measured strongest RSSI (Received Signal Strength Indicator) level: any station connects to the AP that provides the higher physical data rate. Although simple and effective in low crowded scenarios with low-medium traffic load, this strategy performs inefficiently when the number of mobile users is high and their distribution among APs is unbalanced, i.e. when network congestion becomes an issue. Load Balancing (LB) solutions aim at solving this problem by enforcing the connection of stations to the AP having either the smallest number of associated stations or the lowest traffic load. However, LB solutions do not account for traffic priorities or, when they consider them, they do not deal with the joint configuration of QoS (Quality of Service) and LB parameters. In this study we present a framework for modeling, analyzing and designing QoS-aware LB solutions. The proposed framework assumes that stations implement the Enhanced Distributed Channel Access (EDCA) mechanism of the IEEE 802.11e standard. Moreover, in order to make the framework concrete, we assume that the QoS goal is the weighted fair allocation of wireless resources. However, the framework is not restricted to this goal and can be easily extended in order to deal with a different cost function. The proposed framework is validated through simulations in a typical indoor LB scenario. The results show that the model is effective in capturing network performance and in designing LB solutions that account for traffic priorities and the configuration of QoS parameters.

5 citations

Journal ArticleDOI
TL;DR: Wireless hotspots, ie, infrastructures composed of several IEEE 802.11 access points, are today the most common solution in providing Internet access to a wide and rapidly changing population of users.
Abstract: Summary Wireless hotspots, ie, infrastructures composed of several IEEE 802.11 access points (APs), are today the most common solution in providing Internet access to a wide and rapidly changing population of users. According to common device implementation, stations establish associations with APs based on the measured strongest Received Signal Strength Indicator level. This usually leads to an uneven distribution of users to APs, increasing the chances of local network congestion. Load balancing (LB) solutions aim at mitigating this problem controlling the distribution of users. The LB algorithms enforce stations to associate with APs that manage a low number of users and/or that have a low traffic load. Usually, LB solutions do not consider traffic priorities or they assume some a priori quality of service (QoS) configuration for users. In this study, we propose a QoS-LB solution based on the cell breathing technique with the goal of balancing the load in IEEE 802.11e Enhanced Distributed Channel Access (EDCA) Hotspots. The proposed algorithm explores the space of possible power/EDCA configurations by using a branch and bound approach that reduces the number of analyzed configurations and, hence, the time required to find the global optimal solution. The algorithm has been analytically defined and its performance evaluated through simulations and tests in a real test bed. The results prove that the proposed solution is effective in solving the optimal QoS-LB configuration problem in WiFi hotspots of average size.

3 citations


Cited by
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Journal ArticleDOI
30 Jun 2018-Sensors
TL;DR: This paper describes an energy consumption model based on LoRa and LoRaWAN, which allows estimating the consumed power of each sensor node element and can be used to compare different Lo RaWAN modes to find the best sensor node design to achieve its energy autonomy.
Abstract: Energy efficiency is the key requirement to maximize sensor node lifetime. Sensor nodes are typically powered by a battery source that has finite lifetime. Most Internet of Thing (IoT) applications require sensor nodes to operate reliably for an extended period of time. To design an autonomous sensor node, it is important to model its energy consumption for different tasks. Each task consumes a power consumption amount for a period of time. To optimize the consumed energy of the sensor node and have long communication range, Low Power Wide Area Network technology is considered. This paper describes an energy consumption model based on LoRa and LoRaWAN, which allows estimating the consumed power of each sensor node element. The definition of the different node units is first introduced. Then, a full energy model for communicating sensors is proposed. This model can be used to compare different LoRaWAN modes to find the best sensor node design to achieve its energy autonomy.

230 citations

Journal ArticleDOI
TL;DR: A ubiquitous healthcare framework, UbeHealth, is proposed that leverages edge computing, deep learning,big data, big data, high-performance computing (HPC), and the Internet of Things (IoT) to address the aforementioned challenges.
Abstract: Smart city advancements are driving massive transformations of healthcare, the largest global industry. The drivers include increasing demands for ubiquitous, preventive, and personalized healthcare, to be provided to the public at reduced risks and costs. Mobile cloud computing could potentially meet the future healthcare demands by enabling anytime, anywhere capture and analyses of patients’ data. However, network latency, bandwidth, and reliability are among the many challenges hindering the realization of next-generation healthcare. This paper proposes a ubiquitous healthcare framework, UbeHealth, that leverages edge computing, deep learning, big data, high-performance computing (HPC), and the Internet of Things (IoT) to address the aforementioned challenges. The framework enables an enhanced network quality of service using its three main components and four layers. Deep learning, big data, and HPC are used to predict network traffic, which in turn are used by the Cloudlet and network layers to optimize data rates, data caching, and routing decisions. Application protocols of the traffic flows are classified, enabling the network layer to meet applications’ communication requirements better and to detect malicious traffic and anomalous data. Clustering is used to identify the different kinds of data originating from the same application protocols. A proof of concept UbeHealth system has been developed based on the framework. A detailed literature review is used to capture the design requirements for the proposed system. The system is described in detail including the algorithmic implementation of the three components and four layers. Three widely used data sets are used to evaluate the UbeHealth system.

146 citations

Journal ArticleDOI
TL;DR: Results from testing across a number of regions indicate that such an Internet of Things medical solution is a robust and simple way to deliver next generation community-based smart diagnostics and disease management to best benefit patients and clinical staff alike.
Abstract: This paper presents an advanced Internet of Things point-of-care bio-fluid analyzer; a LoRa/Bluetooth-enabled electronic reader for biomedical strip-based diagnostics system for personalized monitoring. We undertake test simulations (technology trial without patient subjects) to demonstrate potential of long-range analysis, using a disposable test ‘key’ and companion Android app to form a diagnostic platform suitable for remote point-of-care screening for urinary tract infection (UTI). The 868 MHz LoRaWAN-enabled personalized monitor demonstrated sound potential with UTI test results being correctly diagnosed and transmitted to a remote secure cloud server in every case. Tests ranged over distances of 1.1–6.0 Km with radio path losses from 119–141 dB. All tests conducted were correctly and robustly received at the base station and relayed to the secure server for inspection. The UTI test strips were visually inspected for correct diagnosis based on color change and verified as 100% accurate. Results from testing across a number of regions indicate that such an Internet of Things medical solution is a robust and simple way to deliver next generation community-based smart diagnostics and disease management to best benefit patients and clinical staff alike. This significant step can be applied to any type of home or region, particularly those lacking suitable mobile signals, broadband connections, or even landlines. It brings subscription-free long-range bio-telemetry to healthcare providers and offers savings on regular clinician home visits or frequent clinic visits by the chronically ill. This paper highlights practical hurdles in establishing an Internet of Medical Things network, assisting informed deployment of similar future systems.

109 citations

Journal ArticleDOI
04 Apr 2020-Sensors
TL;DR: A low-cost, modular, and Long-Range Wide-Area Network (LoRaWAN)-based IoT platform, denoted as “LoRa WAN-based Smart Farming Modular IoT Architecture” (Lo RaFarM), and aimed at improving the management of generic farms in a highly customizable way is presented.
Abstract: Presently, the adoption of Internet of Things (IoT)-related technologies in the Smart Farming domain is rapidly emerging. The ultimate goal is to collect, monitor, and effectively employ relevant data for agricultural processes, with the purpose of achieving an optimized and more environmentally sustainable agriculture. In this paper, a low-cost, modular, and Long-Range Wide-Area Network (LoRaWAN)-based IoT platform, denoted as "LoRaWAN-based Smart Farming Modular IoT Architecture" (LoRaFarM), and aimed at improving the management of generic farms in a highly customizable way, is presented. The platform, built around a core middleware, is easily extensible with ad-hoc low-level modules (feeding the middleware with data coming from the sensors deployed in the farm) or high-level modules (providing advanced functionalities to the farmer). The proposed platform has been evaluated in a real farm in Italy, collecting environmental data (air/soil temperature and humidity) related to the growth of farm products (namely grapes and greenhouse vegetables) over a period of three months. A web-based visualization tool for the collected data is also presented, to validate the LoRaFarM architecture.

103 citations

Journal ArticleDOI
05 Sep 2020-Sensors
TL;DR: An overview of LoRaWAN network performance that has been explored and documented in the literature and recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability are provided.
Abstract: Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how the network server must command end nodes pertaining rate adaptation. As a result, numerous ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of service requirements, different metrics, and radio frequency (RF) conditions. This offers a challenge for the reliability and suitability of these schemes. This paper presents a comprehensive review of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of LoRaWAN network performance that has been explored and documented in the literature and then focus on recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability. We then distinguish the approaches used, highlight their strengths and drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps and future directions.

91 citations