scholarly journals Clustering Optimization of LoRa Networks for Perturbed Ultra-Dense IoT Networks

Information ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 76
Author(s):  
Mohammed Saleh Ali Muthanna ◽  
Ping Wang ◽  
Min Wei ◽  
Ahsan Rafiq ◽  
Nteziriza Nkerabahizi Josbert
Keyword(s):  
Distribution Function ◽  
Long Range ◽  
Clustering Algorithms ◽  
Throughput Capacity ◽  
Average Throughput ◽  
Iot Applications ◽  
Maximum Value ◽  
Throughput Model ◽  
Clustering Optimization

Long Range (LoRa) communication is widely adapted in long-range Internet of Things (IoT) applications. LoRa is one of the powerful technologies of Low Power Wide Area Networking (LPWAN) standards designed for IoT applications. Enormous IoT applications lead to massive traffic results, which affect the entire network’s operation by decreasing the quality of service (QoS) and minimizing the throughput and capacity of the LoRa network. To this end, this paper proposes a novel cluster throughput model of the throughput distribution function in a cluster to estimate the expected value of the throughput capacity. This paper develops two main clustering algorithms using dense LoRa-based IoT networks that allow clustering of end devices according to the criterion of maximum served traffic. The algorithms are built based on two-common methods, K-means and FOREL. In contrast to existing methods, the developed method provides the maximum value of served traffic in a cluster. Results reveal that our proposed cluster throughput model obtained a higher average throughput value by using a normal distribution than a uniform distribution.

A comparative analysis of long range and NB-IoT in terms of quality of connectivity

2021 ◽  
Author(s):  
P. Yogendra Prasad ◽  
H. Heera ◽  
N. Padmaja ◽  
Bathala sony
Keyword(s):  
Comparative Analysis ◽  
Long Range

scholarly journals A SELF-ORGANIZING MAP FOR MIXED CONTINUOUS AND CATEGORICAL DATA

2011 ◽  
pp. 24-32 ◽  
Author(s):  
Nicoleta Rogovschi ◽  
Mustapha Lebbah ◽  
Younès Bennani
Keyword(s):  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Mixed Data ◽  
Categorical Variables ◽  
Data Sets ◽  
Self Organizing Map ◽  
Data Set ◽  
Public Data ◽  
Self Organizing

Most traditional clustering algorithms are limited to handle data sets that contain either continuous or categorical variables. However data sets with mixed types of variables are commonly used in data mining field. In this paper we introduce a weighted self-organizing map for clustering, analysis and visualization mixed data (continuous/binary). The learning of weights and prototypes is done in a simultaneous manner assuring an optimized data clustering. More variables has a high weight, more the clustering algorithm will take into account the informations transmitted by these variables. The learning of these topological maps is combined with a weighting process of different variables by computing weights which influence the quality of clustering. We illustrate the power of this method with data sets taken from a public data set repository: a handwritten digit data set, Zoo data set and other three mixed data sets. The results show a good quality of the topological ordering and homogenous clustering.

scholarly journals A Long-range Context-aware Platform Design For Rural Monitoring With IoT In Precision Agriculture

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Deniz TAŞKIN ◽  
Selçuk YAZAR
Keyword(s):  
Long Range ◽  
Precision Agriculture ◽  
Rural Areas ◽  
Smart Cities ◽  
Soil Surface ◽  
Area Network ◽  
Context Aware ◽  
Wide Area Network ◽  
Performance Measurements ◽  
Iot Applications

The Internet of Things (IoT) applications has been developing greatly in recent years to solve communication problems, especially in rural areas. Within the IoT, the context-awareness paradigm, especially in precision agricultural practices, has come to a state of the planning of production time. As smart cities approach, the smart environment approach also increases its place in IoT applications and has dominated research in recent years in literature. In this study, soil and environmental information were collected in 17 km diameter in rural area with developed Long Range (LoRa) based context-aware platform. With the developed sensor and actuator control unit, soil moisture at 5 cm and 30 cm depth and soil surface temperature information were collected and the communication performance was investigated. During the study, the performance measurements of the developed Serial Peripheral Interface (SPI) enabled Long Range Wide Area Network (LoRaWAN) gateway were also performed.

scholarly journals Analisis Perbedaan Peformance dan Quality Of Service (Qos) Antara Eigrp dengan Ospf (Studi Kasus Menggunakan 6 Router Melalui GNS 3 dan Wireshark)

2018 ◽  
Vol 2 (1) ◽  
pp. 10
Author(s):  
Unung Verawardina
Keyword(s):  
Quality Of Service ◽  
Long Range ◽  
Routing Protocol ◽  
Packet Loss ◽  
Routing Protocols ◽  
Data Transfer ◽  
Link State ◽  
Routing Table ◽  
The Difference

In a dynamic routing setting a routing protocol is required to perform the settings to find the shortest and best path. Routing protocols are of two types: vector distance and link state. Use of EIGRP routing that includes long-range vectors and link state OSPF Link link state coverage, peg well to be implemented in complex network because it can adapt well. In this research is the method used for routing and speed of time available EIGRP routing and OSPF routing through simulator GNS3 and wireshark application, then analyze the difference of peformance with speed of routing table and speed of time. While for Quality of Service (QoS) compare network service quality from EIGRP and OSPF routing which include delay, packet loss, and throughput. Based on the results of the research shows the EIGRP routing table is better in the selection path, EIGRP smaller time tansfer data then its data transfer faster than the OSPF. Overall Quality Of Service (Qos) delay, packetloss and throughput on EIGRP and OSPF are well balanced and good.

scholarly journals Maintainability Evaluation of Object-Oriented Software System Using Clustering Techniques

2013 ◽  
Vol 5 (2) ◽  
pp. 136-143 ◽  
Author(s):  
Astha Mehra ◽  
Sanjay Kumar Dubey
Keyword(s):  
Clustering Algorithms ◽  
Daily Basis ◽  
Computer Assisted ◽  
Program Execution ◽  
Huge Data ◽  
Large Databases ◽  
Input Dataset ◽  
Data Objects

In today’s world data is produced every day at a phenomenal rate and we are required to store this ever growing data on almost daily basis. Even though our ability to store this huge data has grown but the problem lies when users expect sophisticated information from this data. This can be achieved by uncovering the hidden information from the raw data, which is the purpose of data mining.  Data mining or knowledge discovery is the computer-assisted process of digging through and analyzing enormous set of data and then extracting the meaning out of it. The raw and unlabeled data present in large databases can be classified initially in an unsupervised manner by making use of cluster analysis. Clustering analysis is the process of finding the groups of objects such that the objects in a group will be similar to one another and dissimilar from the objects in other groups. These groups are known as clusters.  In other words, clustering is the process of organizing the data objects in groups whose members have some similarity among them. Some of the applications of clustering are in marketing -finding group of customers with similar behavior, biology- classification of plants and animals given their features, data analysis, and earthquake study -observe earthquake epicenter to identify dangerous zones, WWW -document classification, etc. The results or outcome and efficiency of clustering process is generally identified though various clustering algorithms. The aim of this research paper is to compare two important clustering algorithms namely centroid based K-means and X-means. The performance of the algorithms is evaluated in different program execution on the same input dataset. The performance of these algorithms is analyzed and compared on the basis of quality of clustering outputs, number of iterations and cut-off factors.

scholarly journals An experimental study on the effects of swirling oxidizer flow and diameter of fuel nozzle on behaviour and light emittance of propane-oxygen non-premixed flame

2017 ◽  
Vol 21 (3) ◽  
pp. 1453-1462 ◽  
Author(s):  
Alireza Javareshkian ◽  
Sadegh Tabejamaat ◽  
Soroush Sarrafan-Sadeghi ◽  
Mohammadreza Baigmohammadi
Keyword(s):  
Reynolds Numbers ◽  
Flame Length ◽  
Nozzle Diameter ◽  
Fuel Flow ◽  
Maximum Value ◽  
Fuel Nozzle ◽  
Flame Shape ◽  
The Stability ◽  
Blue Flame

In this study, the stability and the light emittance of non-premixed propane-oxygen flames have been experimentally evaluated with respect to swirling oxidizer flow and variations in fuel nozzle diameter. Hence, three types of the vanes with the swirl angles of 30?, 45?, and 60? have been chosen for producing the desired swirling flows. The main aims of this study are to determine the flame behaviour, light emittance, and also considering the effect of variation in fuel nozzle diameter on combustion phenomena such as flame length, flame shape, and soot free length parameter. The investigation into the flame phenomenology was comprised of variations of the oxidizer and fuel flow velocities (respective Reynolds numbers) and the fuel nozzle diameter. The results showed that the swirl effect could change the flame luminosity and this way could reduce or increase the maximum value of the flame light emittance in the combustion zone. Therefore, investigation into the flame light emittance can give a good clue for studying the mixing quality of reactants, the flame phenomenology (blue flame or sooty flame, localized extinction), and the combustion intensity in non-premixed flames.

scholarly journals An Investigation of Moroccan Vinegars: Their Physicochemical Properties and Antioxidant and Antibacterial Activities

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Driss Ousaaid ◽  
Hamada Imtara ◽  
Hassan Laaroussi ◽  
Badiaa Lyoussi ◽  
Ilham Elarabi
Keyword(s):  
Physicochemical Properties ◽  
Bioactive Compounds ◽  
Antibacterial Activities ◽  
Storage Conditions ◽  
Production Methods ◽  
Maximum Value ◽  
Processing And Storage ◽  
And Storage ◽  
Excellent Source

Vinegar is a natural product rich in bioactive compounds such as phenols, flavonoids, and organic acids. Several factors affect the quality of vinegars such as apple origin, environmental conditions, production methods, processing, and storage conditions. We investigated the quality of apple vinegars as well as their physicochemical properties and the antioxidant and antibacterial activities of vinegars collected from different areas in Morocco. For physicochemical properties, the outcomes showed the following values: pH (3.18–3.83), electrical conductivity (2.11–2.90), acidity (0.24–5.6), Brix (3.25–6), and density (1.0123–1.0233). The polyphenols content of samples was 68.91 mg AG/100 mL in sample S6 as the minimum value and 147.54 mg AG/100 mL in sample S2 as the maximum value. The best ability to scavenge the DPPH radical was observed in sample S3 (IC50 = 0.45 ± 0.013 µL/mL). Sample S2 showed moderate antibacterial effect against microorganisms tested with MICs ranging from 0.78 µL/mL to 1.125 µL/mL and with a diameter of inhibition ranging from 15.65 mm to 27.65 mm. In addition, a strong correlation was observed between the antibacterial activity of vinegars and physicochemical parameters (pH and total acidity). These outcomes have shown that our vinegar samples are an excellent source of bioactive compounds with potent antioxidant and antibacterial potentials.

Sign in / Sign up

Export Citation Format

Share Document