The demand for passenger transportation, especially by road, has been increasing due to globalisation, resulting in further delays and traffic congestion. This paper addresses issues to minimise delays and traffic congestion using source and destination information in an urban environment. A journey is defined as the traversal of several road links and junctions. The delays on the links are analysed using M/M/K Markov technique. The delays at a junction are examined using the Zero-Server Markov Chain technique. In order to study multiple junctions, this technique is combined with the Jackson Network model. This combined approach is then used to evaluate the delays at multiple junctions using the Middlesex University VANET Testbed (a real-time vehicular network in London, UK). Initial results indicate that there is more congestion at traffic junctions and hence the Markov Chain analysis will allow better traffic algorithms to reduce congestion at traffic junctions, resulting in reduced journey times as well as less congestion. 

Exploring New Traffic Prediction Models to build an Intelligent Transport System for Smart Cities

The major network design or data distributed problems may be described as constrained optimization problems. Constrained optimization problems include restrictions imposed by the system designers. These limitations are basically due to the system design’s physical limitations or functional requirements of the network system. Constrained optimization is a computationally challenging job whenever the constraints/limitations are nonlinear and nonconvex. Furthermore, nonlinear programming methods can easily deal same optimization problem if somehow the constraints are nonlinear and convex. In this paper, we have addressed a distributed network design problem involving uncertainty that transmits data across a parallel router. This distributed network design problem is a Jackson open-type network design problem that has been formulated based on the M/M/1 queueing system. Because our network design problem is a nonlinear, convex optimization problem, we have employed a well-known Kuhn–Tucker (K-T) optimality algorithm to solve the same. Here, we have used triangular fuzzy numbers to express uncertain traffic rates and data processing rates. Then, by applying 
 
 α
 
 -level interval of fuzzy numbers and their corresponding parametric representation of 
 
 α
 
 -level intervals, the associated network design problem has been transformed to its parametric form and later has been solved. To obtain the optimal data stream rate in terms of interval and to illustrate the applicability of the entire approach, a hypothetical numerical example has been exhibited. Finally, the most important results have been reported.

Optimization of Data Distributed Network System under Uncertainty

The real-time vehicular traffic system is an integral part of the urban vehicular traffic system, which provides effective traffic signal control for a large multifaceted traffic network and is a highly challenging distributed control problem. Coordinating vehicular traffic enables the network model to deliver an efficient service flow. Consider that there are four lanes of vehicular traffic in this situation, allowing parallel vehicle movements to occur without causing an accident. In this instance, the vehicular system’s control parameters are time and vehicle volume. In this work, vehicular traffic flow is examined, and an algorithm to estimate vehicle waiting time in each direction is estimated. The effectiveness of the proposed vehicle traffic signal distribution control system by comparing the experimental results with a real-time vehicular traffic system is verified. This is also illustrated numerically. 

Vehicular Traffic Flow Analysis and Minimize the Vehicle Queue Waiting Time Using Signal Distribution Control Algorithm

The Community Request Queue Management System for Local Government Unit of Cabanatuan City aimed to give solutions to the following struggles of Barangay officials: pen and paper storage management, complicated retrieval of records, and compromised set up due to the COVID-19 pandemic. The system went through the stages of the Software Development Life Cycle, namely: Stage 1 – Requirement Analysis; Stage 2 – System Design; Stage 3 – Development; Stage 4 – Testing; Stage 5 – Deployment; and Stage 6 - Maintenance. The system took ten months to design and develop. Different softwares were used for the development of the user and admin interface using programming languages, which are HTML, Java, and PHP. For the development of the database, MySQL was utilized. It has been strongly agreed by Barangay Officials and users based on the following criteria: functionality, usability, efficiency, portability, reliability, and security. The system gave the barangay officials a modern, convenient, and efficient way of performing their services. It lessened the people coming in and out in the barangay hall, thus resulting in the adherence to the COVID-19 protocols. The Community Request Queue Management System for Local Government Unit of Cabanatuan City provided the Sumacab Sur Citizens an alternative way of submitting inquiries, filing complaints and requesting documents. The Barangay Personnel were able to produce printed requested documents and give their response via e-mail.

/pdf/community-request-queue-management-system-for-local-3omwapif.pdf

Community Request Queue Management System for Local Government Unit of Cabanatuan City

Efficient resource utilization and low response times are critical challenges in storage area network (SAN) systems, especially as data-intensive applications like those driven by the Internet of Things and Artificial Intelligence place increasing demands on reliable, high-performance data storage solutions. Addressing these challenges, this paper contributes by proposing a proactive, utilization-driven traffic redistribution strategy to achieve balanced load distribution across switches, thereby improving the overall SAN performance and alleviating the risk of overload-incurred cascading failures. The proposed approach incorporates a Jackson Queueing Network-based method to evaluate both utilization and response time of individual switches, as well as the overall system response time. Based on a comprehensive case study of a mesh SAN system, two key parameters—the transition probability adjustment step size and the node selection window size—are analyzed for their impact on the effectiveness of the proposed strategy, revealing several valuable insights into fine-tuning traffic redistribution parameters. 

Utilization-Driven Performance Enhancement in Storage Area Networks

Traffic congestion is increasing in over populated urban areas, our traditional traffic management system can no longer solve this problem. However, this problem can be solved by converting our road networks into queueing networks. This paper proposes, the use of an open Jackson Queueing Model which can be equated with our existing road network to calculate the waiting time of vehicles in the network, which can be further processed to put the network into an optimized state. In this model, the waiting time depends on both arrival rate and service rate. Our implementation designates a set of service rates from a range of possible service rates for each road within the network and these designated service rates are used to calculate waiting time. As these various combinations of service rates of different roads produce multiple waiting times, we select the combination set of service rates which has the lowest set of waiting times. This set of service rates is also compared with quadratic optimization problem of the same road network to evaluate implementation’s accuracy.

/pdf/queueing-theory-based-vehicular-traffic-management-system-mo7exrn8x5.pdf

Queueing Theory Based Vehicular Traffic Management System Through Jackson Network Model and Optimization

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Queueing Theory Based Vehicular Traffic Management System Through Jackson Network Model and Optimization