Growing popularity of Internet demands for the agility as well as the flexibility of computer networks. Traditional networking system is unable to satisfy recent computing needs. Proprietary devices configured manually create an error-prone situation in addition they are incapable to fully utilize the capability of physical network infrastructure. This has resulted in the paradigm shift in the networking industry and it is known as Software defined networking. Advantages such as programmability, task virtualization and easy management of the network can be provided by employing SDN platform, on the other hand POX is defined as a Python based open source OpenFlow SDN Controller mainly used for faster development and prototyping of new network applications basically comes pre-installed with the mininet virtual machine. POX controller can turn dumb OpenFlow devices into hub, switch, load balancer and firewall devices. In this paper Performance metrics such as service Delay, utilized bandwidth, received packets and bytes were measured and recorded using network monitoring tools like iperf and D-ITG in order to analyze the functionality of the POX controller as well as to evaluate the operation performance of POX controller for SDN environment. The results of this research were the recommendation of using POX controller in for rapid development and prototyping of network control systems as well as being the framework for the interaction with Open Flow switches.

Air pollution is conducted to harmful substances like solid particles, gases or liquid droplets. More pollutants CO, SO2, NOx, CO2.This research is proposed the design and implementation of mobile, low cost and accurate air pollution monitoring system using Arduino microcontroller and gas sensor like MQ2, MQ131, MQ135, MQ136, DHT22, measuring materials mentioned above, smoke, Acetone, Alcohol, LPG, Toluene, temperature, humidity and GPS sensor”NEO-6M” that track the location of air pollution data, and display the analysis result on ESRI maps. The system also save the results on SQL server DB. The data is classified using data mining algorithms, presenting the result on a map helps governmental organizations, nature guards, and ecologists to analyze data in real time to simplify the decision making process. The proposed system uses J48 pruning tree classifier generated using cross validation of fold (10) with highest accuracy 100%, while IBK ≈99.67, Naïve bays ≈90.89, and SVM ≈81.4. It’s found that the common air quality for Baghdad (study area) is between (“Good”, “Satisfactory”, and “Moderately”) for 1835 records of air samples during (January and February 2021) time period.

<p>The recommendation system is an intelligent system gives recommendations to users to discover the best interesting items. The purpose of this proposed recommendation system is to develop a system to find the best electrical devices according to weather conditions and user preferences. The proposed solution relies on the characteristics of electrical appliances and their suitability to weather conditions in any city. The proposed solution is the first recommendation system combines devices properties, weather conditions, and user preferences using a new combination of algorithms. The clustering algorithms are the most applicable in the field of recommendation system. The proposed solution relies on a combination of Elbow method, pro­­posed modified K-means and Silhouette algorithm to find the best number of clusters before starting the clustering process. Then calculate the weights for each cluster and compare them with the weather weights to find the required clusters sorted from the near to far according to a computed threshold. The empirical results showed that the proposed solution demonstrated a 94% accuracy to match the characteristics of the recommended devices with the climatic characteristics of the region and user preferences. The accuracy is measured using Silhouette algorithm.</p>

A denial of service (DoS) attack is one of the dangerous threats to networks that Internet resources and services will be less available, as they are easily operated and difficult to detect. As a result, identifying these intrusions is a hot issue in cybersecurity. Intrusion detection systems that use classic machine learning algorithms have a long testing period and high computational complexity. Therefore, it is critical to develop or improve techniques for detecting such an attack as quickly as possible to reduce the impact of the attack. As a result, we evaluate the effectiveness of rapid machine learning methods for model testing and generation in communication networks to identify denial of service attacks. In WEKA tools, the CICIDS2017 dataset is used to train and test multiple machine learning algorithms. The wide learning system and its expansions and the REP tree (REPT), random tree (RT), random forest (RF), decision stump (DS), and J48 were all evaluated. Experiments have shown that J48 takes less testing time and performs better, whereases it is performed by using 4-8 features. An accuracy result of 99.51% and 99.96% was achieved using 4 and 8 features, respectively.

In the last few years, there has been a growing interest in the rise of demand for moving from traditional networks towards software-defined networks, this has raised a lot of challenges. Software-defined networks are continually evolving, which include the need to address issues such as scalability, and packet loss, transmission delay and network congestion. accordingly, researchers introduced the concept of multi-controller architectures, although it will not assist to balance the load between them, it will tackle the network congestion issue through the distribution of load between them. the present study proposes a linear multi-controller architecture to explore the impact of increasing the number of controllers connected in a linear style on network performance. The study was based on the generation of simultaneous multi-flows with different sizes using Distributed Internet Traffic Generator(D-ITG). From the outcomes of our investigation, it is possible to conclude that the performance-enhanced uniformly with the number of controllers while preserving the same number of Open Vswitches. as the number of controllers reached four, The Quad-controller architecture recorded the best results related to improving the reduction of average delay and average jitter to 62% and 64% as well as increasing the throughput, bytes received, average packet rate to 32%, 32% and 31.8%.