Enhanced Queue Management Mechanism for Differentiated Services Networks

In the Internet, it is supposed that all connections are treated equally in the network. Due to the limitation of network resources are limited, providing guarantees on performance measures imposes declining new connections if resources are not available. Assigning network resources to connections according to their classes requires differentiating between the connection classes. For this reason, the Differentiated Services (DiffServ) has been proposed. Many of the QoS mechanisms have been developed which allow different services carried by the Internet to co-exist. Many of these mechanisms were both complex and failed to scale to meet the demands of the Internet. MRED is the common mechanism used in DifJServ routers. It suflers from large queue length variation and untimely congestion detection and notification. These consequences cause performance degradation due to high queuing delays and high packet loss. In this project, enhanced version of MRED is developed to improve the performance of Diffserv networks that use TCP as the transport layer protocol. Enhanced MRED includes average packet arrival rate when computing the packet drop probability. Enhanced MRED showed a good pedonnance compared to that of MRED, in term of fast congestion detection and notification. The limitation of the new mechanism is that it works only with responsive connections which play a big role in avoiding and controlling the congestion. The major contribution of this project is to provide an improved queue management mechanism for Diffserv networks that responds to congestion more quickly, delivers congestion notification timers, and controls the queue length directly to congestion which results in minimizing queue length variation. All these would help improve the DlffServ networks performance

Queue Management Performance Evaluation of REM, GRED, and DropTail Algorithms

As the new user applications and Internet traffic are increased rapidly Rapid growth, the need for developing the Internet infrastructure that guarantee good level of quality of service became necessary. Congestion that is caused by uncontrollable amount of traffic remains as a main problem that threats the Quality of Service (QoS) on the Internet. Proactive Queue Management Mechanisms employed in the Internet routers help in improving the performance of responsive applications such as TCP applications. The selection of Active queue management mechanism plays an important role that leads to well network performance and utilization. In this project, we performance evaluation for examining the performance of the some of the known queue management mechanisms, namely DropTail, REM, and RED proposed for IP routers to achieve performance among competing sources. The purpose of this performance examination is to identify the key parameters to improve the fairness and link utilization in TCP/IP networks. In addition, this will help obtaining a better understanding of these mechanisms by identifying and clarifying factors that influence their performance in order to improve TCP/IP networks performance overall

QoS performance analysis of bit rate video streaming in next generation networks using TCP, UDP and a TCP+UDP hybrid

The growth in users streaming videos on the Internet has led to increased demand for improved video quality and reception. In next generation networks (NGNs), such as 3G and 4G LTE, quality of service (QoS) implementation is one of the ways in which good video quality and good video reception can be achieved. QoS mainly involves following an industry-wide set of standard metrics and mechanisms to achieve high-quality network performance in respect of video streaming. Adopting routing and communication protocols is one way QoS is implemented in NGNs. This article describes QoS of bit rate video streaming, and QoS performance analysis of video streaming, in relation to the main network transport protocols, namely transmission control protocol (TCP) and user datagram protocol (UDP). A simulation test bed was set up using OPNET modeller 14.5. In this setup, a network topology was created and duplicated three times, in order to configure two simulation scenarios (each using the distinct protocols), and a third simulation scenario using both protocols in hybrid form. The findings in the simulations indicated that, when a network is configured with both TCP and UDP protocols in video streaming, there is a positive change in the degree of performance in terms of the QoS of videostreaming applications, unlike when the protocols are used independently.CA2016www.wits.ac.za/linkcentre/aji

Effects of Real-World Experiences in Active Learning (R.E.A.L.) Applied in an Information Systems Data Communication and Networking Course

The purpose of this study was to determine if the use of Real-World Experiences in Active Learning (R.E.A.L.) impacted student learning outcomes in an undergraduate information systems (IS) data communication and networking course. A quasi-experimental, quantitative approach was used to investigate whether the R.E.A.L. treatments, used as active learning strategies, significantly impacted student performance, short-term retention, long-term retention, and student engagement. The data collection was completed in one semester. Participants were students enrolled in an IS data communication and networking course during the Fall 2019 semester. The students, enrolled in the two sections of the course, were taught using a crossover design where each student received eight treatments. The researcher of the study served as the instructor for both sections. The research question and four hypotheses were analyzed using repeated measures MANCOVA and multi-level modeling (MLM). After a statistical analysis of the direct effects of the R.E.A.L. treatments on student performance, short term retention, long term retention, and engagement, none of the four hypotheses were fully supported. The results indicated that the R.E.A.L. xiii treatments did not significantly impact the student learning outcomes from the course. Research findings partially supported hypothesis H1 indicating that age, ethnicity, and major have some influence on students’ performance and age may have some influence on short-term retention. Statistically significant results were obtained for the H1a Network treatment (F(1,28) = 6.033, p = 0.021, partial η2 = 0.177), meaning that the mean for the H1a Network treatment (M = 90.842) was significantly different than the lecture mean (M = 75.533). The H1b Handshake treatment (F(1,28) = 15.405, p = .001, partial η2 = 0.355) and the H1c Wireless treatment (F(1,28) = 11.385, p = .002, partial η2 = 0.289) produced results in the reverse direction of what was hypothesized, meaning that the mean for the H1b Handshake treatment (M = 49.800) and the H1c Wireless treatment (M = 86.842) were significantly lower than the lecture means for both hypothesis tests. Research findings partially supported hypothesis H2 indicating that age may have influence on short-term retention. Statistically significant results were obtained for the H2e Network speed treatment (F(1,28) = 5.709, p = 0.024, partial η2 = 0.164) and H2f Network management treatment (F(1,28) = 5.654, p = 0.024, partial η2 = 0.163). However, findings from the MLM post hoc tests of direct, interaction, and indirect effects did show some areas for future work in certain demographics, especially gender and ethnicity. Findings of the study were not shown to be significant however, the post hoc testing revealed areas where future work could be beneficial

Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system

TF2Network : predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information

A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidop-sis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75-92% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response

HoneyDOC: An Efficient Honeypot Architecture Enabling All-Round Design

Honeypots are designed to trap the attacker with the purpose of investigating its malicious behavior. Owing to the increasing variety and sophistication of cyber attacks, how to capture high-quality attack data has become a challenge in the context of honeypot area. All-round honeypots, which mean significant improvement in sensibility, countermeasure and stealth, are necessary to tackle the problem. In this paper, we propose a novel honeypot architecture termed HoneyDOC to support all-round honeypot design and implementation. Our HoneyDOC architecture clearly identifies three essential independent and collaborative modules, Decoy, Captor and Orchestrator. Based on the efficient architecture, a Software-Defined Networking (SDN) enabled honeypot system is designed, which supplies high programmability for technically sustaining the features for capturing high-quality data. A proof-of-concept system is implemented to validate its feasibility and effectiveness. The experimental results show the benefits by using the proposed architecture comparing to the previous honeypot solutions.Comment: Non

Development of a Surgical Assistance System for Guiding Transcatheter Aortic Valve Implantation

Development of image-guided interventional systems is growing up rapidly in the recent years. These new systems become an essential part of the modern minimally invasive surgical procedures, especially for the cardiac surgery. Transcatheter aortic valve implantation (TAVI) is a recently developed surgical technique to treat severe aortic valve stenosis in elderly and high-risk patients. The placement of stented aortic valve prosthesis is crucial and typically performed under live 2D fluoroscopy guidance. To assist the placement of the prosthesis during the surgical procedure, a new fluoroscopy-based TAVI assistance system has been developed. The developed assistance system integrates a 3D geometrical aortic mesh model and anatomical valve landmarks with live 2D fluoroscopic images. The 3D aortic mesh model and landmarks are reconstructed from interventional angiographic and fluoroscopic C-arm CT system, and a target area of valve implantation is automatically estimated using these aortic mesh models. Based on template-based tracking approach, the overlay of visualized 3D aortic mesh model, landmarks and target area of implantation onto fluoroscopic images is updated by approximating the aortic root motion from a pigtail catheter motion without contrast agent. A rigid intensity-based registration method is also used to track continuously the aortic root motion in the presence of contrast agent. Moreover, the aortic valve prosthesis is tracked in fluoroscopic images to guide the surgeon to perform the appropriate placement of prosthesis into the estimated target area of implantation. An interactive graphical user interface for the surgeon is developed to initialize the system algorithms, control the visualization view of the guidance results, and correct manually overlay errors if needed. Retrospective experiments were carried out on several patient datasets from the clinical routine of the TAVI in a hybrid operating room. The maximum displacement errors were small for both the dynamic overlay of aortic mesh models and tracking the prosthesis, and within the clinically accepted ranges. High success rates of the developed assistance system were obtained for all tested patient datasets. The results show that the developed surgical assistance system provides a helpful tool for the surgeon by automatically defining the desired placement position of the prosthesis during the surgical procedure of the TAVI.Die Entwicklung bildgeführter interventioneller Systeme wächst rasant in den letzten Jahren. Diese neuen Systeme werden zunehmend ein wesentlicher Bestandteil der technischen Ausstattung bei modernen minimal-invasiven chirurgischen Eingriffen. Diese Entwicklung gilt besonders für die Herzchirurgie. Transkatheter Aortenklappen-Implantation (TAKI) ist eine neue entwickelte Operationstechnik zur Behandlung der schweren Aortenklappen-Stenose bei alten und Hochrisiko-Patienten. Die Platzierung der Aortenklappenprothese ist entscheidend und wird in der Regel unter live-2D-fluoroskopischen Bildgebung durchgeführt. Zur Unterstützung der Platzierung der Prothese während des chirurgischen Eingriffs wurde in dieser Arbeit ein neues Fluoroskopie-basiertes TAKI Assistenzsystem entwickelt. Das entwickelte Assistenzsystem überlagert eine 3D-Geometrie des Aorten-Netzmodells und anatomischen Landmarken auf live-2D-fluoroskopische Bilder. Das 3D-Aorten-Netzmodell und die Landmarken werden auf Basis der interventionellen Angiographie und Fluoroskopie mittels eines C-Arm-CT-Systems rekonstruiert. Unter Verwendung dieser Aorten-Netzmodelle wird das Zielgebiet der Klappen-Implantation automatisch geschätzt. Mit Hilfe eines auf Template Matching basierenden Tracking-Ansatzes wird die Überlagerung des visualisierten 3D-Aorten-Netzmodells, der berechneten Landmarken und der Zielbereich der Implantation auf fluoroskopischen Bildern korrekt überlagert. Eine kompensation der Aortenwurzelbewegung erfolgt durch Bewegungsverfolgung eines Pigtail-Katheters in Bildsequenzen ohne Kontrastmittel. Eine starrere Intensitätsbasierte Registrierungsmethode wurde verwendet, um kontinuierlich die Aortenwurzelbewegung in Bildsequenzen mit Kontrastmittelgabe zu detektieren. Die Aortenklappenprothese wird in die fluoroskopischen Bilder eingeblendet und dient dem Chirurg als Leitfaden für die richtige Platzierung der realen Prothese. Eine interaktive Benutzerschnittstelle für den Chirurg wurde zur Initialisierung der Systemsalgorithmen, zur Steuerung der Visualisierung und für manuelle Korrektur eventueller Überlagerungsfehler entwickelt. Retrospektive Experimente wurden an mehreren Patienten-Datensätze aus der klinischen Routine der TAKI in einem Hybrid-OP durchgeführt. Hohe Erfolgsraten des entwickelten Assistenzsystems wurden für alle getesteten Patienten-Datensätze erzielt. Die Ergebnisse zeigen, dass das entwickelte chirurgische Assistenzsystem ein hilfreiches Werkzeug für den Chirurg bei der Platzierung Position der Prothese während des chirurgischen Eingriffs der TAKI bietet