Kalu, Constance (2019). Development and Performance Analysis of Bisection Method-Based Optimal Path Length Algorithm for Terrestrial Microwave Link. Review of Computer Engineering Research, 6(1): 1-11. DOI: 10.18488/journal.76.2019.61.1.11
In this paper, Bisection method-based algorithm for the computation of optimal path length of terrestrial microwave link is presented. Also, performance analysis of the algorithm is presented in terms of the convergence cycle of the algorithm. The impact of various link parameters on the convergence cycle of the algorithm is also presented. Mathlab program was used to carry out sample numerical computation for a microwave link having the following parameters: frequency (f) = 12 GHz, transmit power (PT) = 10dBm, transmitter antenna gain (GT) = 35 dBi, receiver antenna gain (GR) = 35 dBi, fade margin (fms) =20dB, receiver sensitivity (PS) = -80dBm, Rain Zone = N, point refractivity gradient (dN1) = -400, link percentage outage (p0) = 0.01% . The results showed that the Bisection algorithm converged at the 17th cycle. It was found from the analysis that the convergence cycle of the algorithm varied linearly with frequency, decreasing with frequency from a value of 17 at frequency of 12 GHz to 15 at a frequency of 45 GHz. On the other hand, the convergence cycle varied nonlinearly with percentage availability of the link. Also, for a given frequency and link percentage availability the convergence cycle increased with increase in rain rate. The result of the research is very essential for microwave link designers to determine the optimal path length for effective link performance under different link configurations and locations.
This study applies Bisection algorithm to determine the optimal path length of line of site wireless communication link. The Bisection method presented in this paper is simpler and easier to be applied in more situations than the Newton Raphson method. Used in Emenyi, et al. .
Classification Ensemble Based Anomaly Detection in Network Traffic
Ramiz M. Alıguliyev , Makrufa Sh. Hajirahimova (2019). Classification Ensemble Based Anomaly Detection in Network Traffic. Review of Computer Engineering Research, 6(1): 12-23. DOI: 10.18488/journal.76.2019.61.12.23
Recently, the expansion of information technologies and the exponential increase of the digital data have deepened more the security and confidentiality issues in computer networks. In the Big Data era information security has become the main direction of scientific research and Big Data analytics is considered being the main tool in the solution of information security issue. Anomaly detection is one of the main issues in data analysis and used widely for detecting network threats. The potential sources of outliers can be noise and errors, events, and malicious attacks on the network. In this work, a short review of network anomaly detection methods is given, is looked at related works. In the article, a more exact and simple multi-classifier model is proposed for anomaly detection in network traffic based on Big Data. Experiments have been performed on the NSL-KDD data set by using the Weka. The offered model has shown decent results in terms of anomaly detection accuracy.
This study proposed multi-classifier model for increasing anomaly detection accuracy in network traffic. The model consists of the J48, LogitBoost, IBk, AdaBoost, RandomTree classifiers. This work performed a comparative analysis of used classifiers and their combination to see which one will give the best result In study classifiers and their combination have been implemented on NSL-KDD open source dataset using WEKA tool. The results show that the ensemble classifiers provide the better result than using these classifiers individually. The computer network traffic analysis with employment of our model can help network engineers and administrators to create a more reliable network, avoid possible discharges and take precautionary measures.
Design of Automated Departmental Lecture Timetable System
A lecture timetable is a tabular list showing the times which a particular lecture is scheduled to hold and the venue in each day of the week. Its content includes the course code for each course, the coded lecture venue, and the time for each lecture. A lecture timetable is designed every semester. In this era of technological advancement, virtually every aspect of human enterprise has been automated (the use of machines especially computers instead of human to accomplish a task). Now students can pay their school fee, register their courses and even check their results on the internet. This is the drive that gave birth to this research work: the design of an automated lecture timetable for the department of mathematical sciences, Kogi State University Anyigba. The project presents the automated design of lecture timetable. The principle of operation is simple and employs the use of computer technology. A program is written in Visual Basic which produces the output in an error free tabular form displaying the courses/venues for each particular lecture schedule.
The paper's primary contribution is the eradication of double scheduling, time clashing, and poor resources’ utilization in timetabling. The implementation employs the use of ICT to reduce the cost and time taken to design a timetable, eliminates the drawback of human error. Every semester, the application only needs an update of courses, and venues.
Identification of Privacy and Security Risks of Internet of Things: An Empirical Investigation
Muhammad Hamza , Muhammad Azeem Akbar , Muhammad Shafiq , Tahir Kamal , Ali Mahmoud Baddour (2019). Identification of Privacy and Security Risks of Internet of Things: An Empirical Investigation. Review of Computer Engineering Research, 6(1): 35-44. DOI: 10.18488/journal.76.2019.61.35.44
The internet of things (IOT) is a phenomenon of connected devices over the internet to ease human life. It is a system where a separate computing device embedded with sensors is connected to other devices or to the cloud through the different infrastructures of the Internet. The implication of the IOT is still challenging in a geographically distributed environment. Particularly, the main challenges are associated with data privacy and security. In this study, we investigate in the report the risks/issue related to IoT data privacy and security from the existing literature for the last two years and provide a review. We identify a total of seven issues related to IoT data privacy and security. The findings revolved that Privacy, Security, confidentiality, and integrity are the most significant issues for IoT in the current era. The findings of this study provide the researchers with a body of knowledge about the critical issues faced by the users and practitioners of IOT across the globe.
In this paper, we conducted the literature review to find out the main challenges that are being faced by challenges related to privacy and security mainly, authentication and access control, confidentiality and integrity IOT devices users and as well as for IOT manufacturer. We highlighted seven, privacy, trust on the device and conducted a questionnaire survey from different organizations and from different research experts and ranked it accordingly.