Abstract: Urban population is rapidly increasing in Ilorin, (the capital of Kwara State of Nigeria) along with related increased water demand. The inadequacies of water supply services have forced the populace to depend on dug wells, boreholes, water tankers, street vendors etc. for their water needs. People spend hours daily carrying jerry can all around to collect and queue for water at the public water tap with high opportunity cost both in time and economic wastage. This situation motivated this study to assess the sustainability of an urban water supply services to unravel the factors undermining the effective delivery of services. Contingent Valuation Method was used to place value on water supply services using the Double Bounded Dichotomous Choice format for willingness to pay elicitation. A database was created with Microsoft Excel and Stata 12 Software to model and evaluate the variables that affect household willingness to pay. The results of the study reveal that about 92% of the total households surveyed were connected to the Government water supply out of which 87% reported that they were not satisfied with the existing services. The results furthered revealed that respondents are willing to pay ₦2500 monthly to enjoy sustainable water supply service delivery.
Abstract: A sequence of finite tandem queue is considered for
this study. Each one has a single server, which operates under the
egalitarian processor sharing discipline. External customers arrive at
each queue according to a renewal input process and having a general
service times distribution. Upon completing service, customers leave
the current queue and enter to the next. Under mild assumptions,
including critical data, we prove the existence and the uniqueness
of the fluid solution. For asymptotic behavior, we provide necessary
and sufficient conditions for the invariant state and the convergence
to this invariant state. In the end, we establish the convergence of a
correctly normalized state process to a fluid limit characterized by a
system of algebraic and integral equations.
Abstract: Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.
Abstract: Traffic congestion is the most critical issue faced by those in the transportation profession today. Over the past few years, roundabouts have been recognized as a measure to promote efficiency at intersections globally. In developing countries like India, this type of intersection still faces a lot of issues, such as bottleneck situations, long queues and increased waiting times, due to increasing traffic which in turn affect the performance of the entire urban network. This research is a case study of a non-conventional roundabout, in terms of geometric design, in a small town in India. These types of roundabouts should be analyzed for their functionality in mixed traffic conditions, prevalent in many developing countries. Microscopic traffic simulation is an effective tool to analyze traffic conditions and estimate various measures of operational performance of intersections such as capacity, vehicle delay, queue length and Level of Service (LOS) of urban roadway network. This study involves analyzation of an unsymmetrical non-circular 6-legged roundabout known as “Kala Aam Chauraha” in a small town Bulandshahr in Uttar Pradesh, India using VISSIM simulation package which is the most widely used software for microscopic traffic simulation. For coding in VISSIM, data are collected from the site during morning and evening peak hours of a weekday and then analyzed for base model building. The model is calibrated on driving behavior and vehicle parameters and an optimal set of calibrated parameters is obtained followed by validation of the model to obtain the base model which can replicate the real field conditions. This calibrated and validated model is then used to analyze the prevailing operational traffic performance of the roundabout which is then compared with a proposed alternative to improve efficiency of roundabout network and to accommodate pedestrians in the geometry. The study results show that the alternative proposed is an advantage over the present roundabout as it considerably reduces congestion, vehicle delay and queue length and hence, successfully improves roundabout performance without compromising on pedestrian safety. The study proposes similar designs for modification of existing non-conventional roundabouts experiencing excessive delays and queues in order to improve their efficiency especially in the case of developing countries. From this study, it can be concluded that there is a need to improve the current geometry of such roundabouts to ensure better traffic performance and safety of drivers and pedestrians negotiating the intersection and hence this proposal may be considered as a best fit.
Abstract: The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.
Abstract: In this paper, the flow of different classes of patients
into a hospital is modelled and analyzed by using the queueing
network analyzer (QNA) algorithm and discrete event simulation.
Input data for QNA are the rate and variability parameters of the
arrival and service times in addition to the number of servers in each
facility. Patient flows mostly match real flow for a hospital in Egypt.
Based on the analysis of the waiting times, two approaches are
suggested for improving performance: Separating patients into
service groups, and adopting different service policies for sequencing
patients through hospital units. The separation of a specific group of
patients, with higher performance target, to be served separately from
the rest of patients requiring lower performance target, requires the
same capacity while improves performance for the selected group of
patients with higher target. Besides, it is shown that adopting the
shortest processing time and shortest remaining processing time
service policies among other tested policies would results in,
respectively, 11.47% and 13.75% reduction in average waiting time
relative to first come first served policy.
Abstract: We analyze stochastic integrals associated with a mutation process. To be specific, we describe the cell population process and derive the differential equations for the joint generating functions for the number of mutants and their integrals in generating functions and their applications. We obtain first-order moments of the processes of the two-way mutation process in first-order moment structure of X (t) and Y (t) and the second-order moments of a one-way mutation process. In this paper, we obtain the limiting behaviour of the integrals in limiting distributions of X (t) and Y (t).
Abstract: We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.
Abstract: Nowadays, big companies such as Google, Microsoft,
which have adequate proxy servers, have perfectly implemented
their web crawlers for a certain website in parallel. But due to
lack of expensive proxy servers, it is still a puzzle for researchers
to crawl large amounts of information from a single website in
parallel. In this case, it is a good choice for researchers to use
free public proxy servers which are crawled from the Internet. In
order to improve efficiency of web crawler, the following two issues
should be considered primarily: (1) Tasks may fail owing to the
instability of free proxy servers; (2) A proxy server will be blocked
if it visits a single website frequently. In this paper, we propose
Proxisch, an optimization approach of large-scale unstable proxy
servers scheduling, which allow anyone with extremely low cost to
run a web crawler efficiently. Proxisch is designed to work efficiently
by making maximum use of reliable proxy servers. To solve second
problem, it establishes a frequency control mechanism which can
ensure the visiting frequency of any chosen proxy server below the
website’s limit. The results show that our approach performs better
than the other scheduling algorithms.
Abstract: Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.
Abstract: Due to the increasing growth of internet users, the emerging applications of multicast are growing day by day and there is a requisite for the design of high-speed switches/routers. Huge amounts of effort have been done into the research area of multicast switch fabric design and algorithms. Different traffic scenarios are the influencing factor which affect the throughput and delay of the switch. The pointer based multicast scheduling algorithms are not performed well under non-uniform traffic conditions. In this work, performance of the switch has been analyzed by applying the advanced multicast scheduling algorithm OQSMS (Optimal Queue Selection Based Multicast Scheduling Algorithm), MDDR (Multicast Due Date Round-Robin Scheduling Algorithm) and MDRR (Multicast Dual Round-Robin Scheduling Algorithm). The results show that OQSMS achieves better switching performance than other algorithms under the uniform, non-uniform and bursty traffic conditions and it estimates optimal queue in each time slot so that it achieves maximum possible throughput.
Abstract: The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.
Abstract: The check-in area of airport terminal is one of the
busiest sections at airports at certain periods. The passengers are
subjected to queues and delays during the check-in process. These
delays and queues are due to constraints in the capacity of service
facilities. In this project, the airport terminal is decomposed into
several check-in areas. The airport check-in scheduling problem
requires both a deterministic (integer programming) and stochastic
(simulation) approach. Integer programming formulations are
provided to minimize the total number of counters in each check-in
area under the realistic constraint that counters for one and the same
flight should be adjacent and the desired number of counters
remaining in each area should be fixed during check-in operations.
By using simulation, the airport system can be modeled to study the
effects of various parameters such as number of passengers on a
flight and check-in counter opening and closing time.
Abstract: The method of introducing the proxy interpretation for
sending and receiving requests increase the capability of the server
and our approach UDIV (User-Data Identity Security) to solve the
data and user authentication without extending size of the data makes
better than hybrid IDS (Intrusion Detection System). And at the same
time all the security stages we have framed have to pass through less
through that minimize the response time of the request. Even though
an anomaly detected, before rejecting it the proxy extracts its identity
to prevent it to enter into system. In case of false anomalies, the
request will be reshaped and transformed into legitimate request for
further response. Finally we are holding the normal and abnormal
requests in two different queues with own priorities.
Abstract: This paper evaluates the performance of a multi-lane
four legged modern roundabout operating in Muscat using SIDRA
model. The performance measures include Degree of Saturation
(DOS), average delay, and queue lengths. The geometric and traffic
data were used for model preparation. Gap acceptance parameters,
critical gap and follow up headway, were used for calibration of
SIDRA model. The results from the analysis showed that currently
the roundabout is experiencing delays up to 610 seconds per vehicle
with DOS 1.67 during peak hour. Further, sensitivity analysis for
general and roundabout parameters was performed, amongst lane
width, cruise speed, inscribed diameter, entry radius and entry angle
showed that inscribed diameter is most crucial factor affecting delay
and DOS. Up gradation of roundabout to fully signalized junction
was found as the suitable solution which will serve for future years
with LOS C for design year having DOS of 0.9 with average control
delay of 51.9 seconds per vehicle.
Abstract: Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.
Abstract: The advances in technology in the last five years
allowed an improvement in the educational area, as the increasing in
the development of educational software. One of the techniques that
emerged in this lapse is called Gamification, which is the utilization of
video game mechanics outside its bounds. Recent studies involving
this technique provided positive results in the application of these
concepts in many areas as marketing, health and education. In the last
area there are studies that covers from elementary to higher education,
with many variations to adequate to the educators methodologies.
Among higher education, focusing on IT courses, data structures are
an important subject taught in many of these courses, as they are
base for many systems. Based on the exposed this paper exposes
the development of an interactive web learning environment, called
DSLEP (Data Structure Learning Platform), to aid students in higher
education IT courses. The system includes basic concepts seen on
this subject such as stacks, queues, lists, arrays, trees and was
implemented to ease the insertion of new structures. It was also
implemented with gamification concepts, such as points, levels, and
leader boards, to engage students in the search for knowledge and
stimulate self-learning.
Abstract: This paper studies a random fuzzy queueing system
that the interarrival times of customers arriving at the server and
the service times are independent and identically distributed random
fuzzy variables. We match the random fuzzy queueing system with
the random fuzzy alternating renewal process and we do not use from
α-pessimistic and α-optimistic values to estimate the average chance
of the event ”random fuzzy queueing system is busy at time t”, we
employ the fuzzy simulation method in practical applications. Some
theorem is proved and finally we solve a numerical example with
fuzzy simulation method.
Abstract: Various fairness models and criteria proposed by academia and industries for wired networks can be applied for ad hoc wireless network. The end-to-end fairness in an ad hoc wireless network is a challenging task compared to wired networks, which has not been addressed effectively. Most of the traffic in an ad hoc network are transport layer flows and thus the fairness of transport layer flows has attracted the interest of the researchers. The factors such as MAC protocol, routing protocol, the length of a route, buffer size, active queue management algorithm and the congestion control algorithms affects the fairness of transport layer flows. In this paper, we have considered the rate of data transmission, the queue management and packet scheduling technique. The ad hoc network is dynamic in nature due to various parameters such as transmission of control packets, multihop nature of forwarding packets, changes in source and destination nodes, changes in the routing path influences determining throughput and fairness among the concurrent flows. In addition, the effect of interaction between the protocol in the data link and transport layers has also plays a role in determining the rate of the data transmission. We maintain queue for each flow and the delay information of each flow is maintained accordingly. The pre-processing of flow is done up to the network layer only. The source and destination address information is used for separating the flow and the transport layer information is not used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and the transport layer information is used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on not mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and MC-MLAS and the performance of the proposed approach is encouraging.
Abstract: The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.