Modeling and analysis of multiservice queuing system for WiMAX network

An analytical queuing model is proposed for the classified services of WiMAX network. Simulation model is also developed that corresponds to the Markovian analytical model using Java modeling tool （JMT）. This is a new and efficient discrete event tool for queuing network modeling and workload analysis. QoS metrics have been evaluated for the multi-rate traffic in multiple scenari- os. Results obtained from simulation are compared for validation and analysis. Outcomes show that the proposed model is more efficient than the conventional method by improving residence time, re- sponse time, increasing system throughput and efficiency at queuing level with a slight degradation in call acceptance factor.

Multiway Relay Based Framework for Network Coding in Multi-Hop WSNs

In today’s information technology(IT)world,the multi-hop wireless sensor networks(MHWSNs)are considered the building block for the Internet of Things(IoT)enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service(QoS)in a stipulated time slot to end-user over the Internet.Smart city(SC)is an example of one such application which can automate a group of civil services like automatic control of traffic lights,weather prediction,surveillance,etc.,in our daily life.These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput,energy efficiency,and end-to-end delay,wherein low latency is considered a challenging issue in next-generation networks(NGN).This paper introduces a single and parallels stable server queuing model with amulti-class of packets and native and coded packet flowto illustrate the simple chain topology and complexmultiway relay(MWR)node with specific neighbor topology.Further,for improving data transmission capacity inMHWSNs,an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node.Finally,the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets.The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results.

Information freshness optimization of multiple status update streams in Internet of things:Generation rate control and service rate reservation

The Internet of things(IoT)has become a key infrastructure providing up-to-date and fresh information for policy analysis and decision-making of upper-layer applications.However,there are limited sensing and communication resources in IoT devices,which significantly affects the timeliness and freshness of the updated status.This work proposes two schemes,namely,the generation rate control and service rate reservation schemes,to improve the overall information freshness of multiple status update streams at the receiver.Specifically,using the recently proposed Age of Information(AoI)as the metric for evaluating information freshness,we characterized the overall information freshness,i.e.,the overall average AoI at the receiver for both schemes,by considering the urgency difference of status update and streams.Both schemes for status updates and streams,respectively,were formulated as two optimization problems.We proved that both problems are convex and the optimal generation and service rates for different streams are found by the standard convex optimization algorithm.Moreover,we proposed both approximate optimal generation and approximate optimal service rate for fast deployment in heavy and light load cases.Numerical results verify the theoretical findings and accuracy of the proposed approximate solutions,guiding the design and deployment of IoT.

Performance Assessment and Configuration Analysis in the Study of SCADA System (Supervisory Control and Data Acquisition)

Queuing models are used to assess the functionality and aesthetics of SCADA systems for supervisory control and data collection.Here,the main emphasis is on how the queuing theory can be used in the system’s design and analysis.The analysis’s findings indicate that by using queuing models,cost-performance ratios close to the ideal might be attained.This article discusses a novel methodology for evaluating the service-oriented survivability of SCADA systems.In order to evaluate the state of service performance and the system’s overall resilience,the framework applies queuing theory to an analytical model.As a result,the SCADA process is translated using the M^(X)/G/1 queuing model,and the queueing theory is used to evaluate this design’s strategy.The supplemental variable technique solves the queuing problem that comes with the subsequent results.The queue size,server idle time,utilization,and probabilistic generating factors of the distinct operating strategies are estimated.Notable examples were examined via numerical analysis using mathematical software.Because it is used frequently and uses a statistical demarcation method,this tactic is completely acceptable.The graphical representation of this perspective offers a thorough analysis of the alleged limits.

Quasi-Negative Binomial: Properties, Parametric Estimation, Regression Model and Application to RNA-SEQ Data

Background: The Poisson and the Negative Binomial distributions are commonly used to model count data. The Poisson is characterized by the equality of mean and variance whereas the Negative Binomial has a variance larger than the mean and therefore both models are appropriate to model over-dispersed count data. Objectives: A new two-parameter probability distribution called the Quasi-Negative Binomial Distribution (QNBD) is being studied in this paper, generalizing the well-known negative binomial distribution. This model turns out to be quite flexible for analyzing count data. Our main objectives are to estimate the parameters of the proposed distribution and to discuss its applicability to genetics data. As an application, we demonstrate that the QNBD regression representation is utilized to model genomics data sets. Results: The new distribution is shown to provide a good fit with respect to the “Akaike Information Criterion”, AIC, considered a measure of model goodness of fit. The proposed distribution may serve as a viable alternative to other distributions available in the literature for modeling count data exhibiting overdispersion, arising in various fields of scientific investigation such as genomics and biomedicine.

Optimization of the CBSMAP Queueing Model

The present paper is devoted to the research of controlled queueing models at control of CBSMAP （Controlled Batch Semi-Markov Arrival Process）. The control is based on the theory of controlled semi-markov processes for system optimization. The control is carried out using a type of the next batch and moments of batch arrivals.

FogQSYM: An Industry 4.0 Analytical Model for Fog Applications

Industry 4.0 refers to the fourth evolution of technology development,which strives to connect people to various industries in terms of achieving their expected outcomes efficiently.However,resource management in an Industry 4.0 network is very complex and challenging.To manage and provide suitable resources to each service,we propose a FogQSYM(Fog—Queuing system)model;it is an analytical model for Fog Applications that helps divide the application into several layers,then enables the sharing of the resources in an effective way according to the availability of memory,bandwidth,and network services.It follows theMarkovian queuing model that helps identify the service rates of the devices,the availability of the system,and the number of jobs in the Industry 4.0 systems,which helps applications process data with a reasonable response time.An experiment is conducted using a Cloud Analyst simulator with multiple segments of datacenters in a fog application,which shows that the model helps efficiently provide the arrival resources to the appropriate services with a low response time.After implementing the proposed model with different sizes of fog services in Industry 4.0 applications,FogQSYM provides a lower response time than the existing optimized response time model.It should also be noted that the average response time increases when the arrival rate increases.

The Effects of Absorbable Materials in the Treatment for Non-Weight-Bearing Bone Fractures of Extremities

With the application of queuing theory model,this paper regards breast cancer screening in primary health care service center as a queuing system.With the help of the tide of sharing economy,it puts forward a joint screening scheme based on M/M/s model under shared mode,and compares it with M/M/1 model of non-shared mode,shortens patient waiting time by sharing medical resources,plans existing resources reasonably,and enhances the comprehensive strength of primary health care system so as to optimize the screening of breast cancer at the grass-roots level.

Stochastic Model of Waiting Time: A Case of Two Selected Banks in the Sekondi-Takoradi Metropolis

Queue is an act of joining a line to be served and it is part of our everyday human involvement. The objectives of the study focused on using a mathematical model to determine the waiting time of two selected banks as well as compare the average waiting time between the banks. The study uncovered the extent of usage of queuing models in achieving customer satisfaction as well as permitting to make better decisions relating to potential waiting times for customers. The study adopted a case study and observational research with the source of data being primary. Purposive sampling technique was used to select the two banks under study with the target population comprising of all the customers who intended to transact businesses with the banks within the period of 11 am to 12 pm. The sample sizes for the first, second and third day of the first bank are twenty-eight (28), seventeen (17) and twenty (20) respectively with three servers on each day whereas that for the first, second and third day of the second bank is twenty (20), nine (9) and seventeen (17) with two servers on each day. A multiple server (M/M/s) Model was adopted, and Tora Software was the statistical tool used for the analysis. Findings of the study revealed that the second bank had a higher utilization factor than the first bank. Also, the number of customers in the banking hall of the second bank was higher than that of the first bank during the entire period of observation. Finally, it takes customers of the first bank lesser minutes to complete their transaction than the second bank. In conclusion, the three days observations revealed different banking situations faced by customers in both banks which had effect on waiting time of customer service. The waiting time of customer service has effect on the number of customers in the queue and system, the probability associated with the emptiness of the system and the utilization factor. Based on the results, the study recommended, inter alia, that the management of the second bank should adopt a three-server (M/M/3) model.

Improved Dynamic Johnson Sequencing Algorithm(DJS)in Cloud Computing Environment for Efficient Resource Scheduling for Distributed Overloading

This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task allocation.Utilizing Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task completion.It advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue lengths.The Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative analysis.The research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.

An Efficient Computational Method for Solving Nonlinear Matrix Equation and Its Application in Queuing Analysis

The matrir analytic analysis of queues with complex arrival, vacation and service characteristics requires the solution of nonlinear matrir equation. The complexity and large dimensionality of the model require an efficient and smart algorithm for the so-lution. In this paperl we propose an efficient Adaptive Newton-Kantorovich (ANK)method for speeding up the algorithm solving the nonlinear matrir equation which is an inevitable step in the analysis of the queue with embedded Markov chain such as BMAP/SMSP/1/ queue or its discrete version. BMAP/SMSP/1/ is a queu-ing model with a Semi Markov Service time Process (SMSP) and a Batch Markovian Arrival Process (BMAP). The numerical result is preselited for the discrete case of N-MMBP/D/1 queue which arises in analyzing traffic aspect of computer communica-tion network, where MMBP is Markov Modulated Bermoulli Process. The comparisons of Adaptive Newton-Kantorovich (ANK) with Modified NeWton-Kalltorovich (MNK)show that ANK saves 3o% of CPU time when the number of user N is 50.

On First Returning Time and Last Exit Time of a Class of Markov Chain

Let {Xn} be a Markov chain with transition probability pij =： aj-（i-1）＋,i,j ≥ 0, where aj=0 providedj 〈 0, a0 〉 0, a0＋a1〈 1 and ∑∞n=0 an= 1. Let μ∑∞n=1nan. It is known that {Xn} is positive recurrent when μ 〈 1; is null recurrent when μ= 1; and is transient when μ 〉 1. In this paper, the integrability of the first returning time and the last exit time are discussed. Keywords Geom/G/1 queuing model, first returning time, last exit time, Markov chain