A QoS performance measure framework for distributed heterogeneous networks

English language proficiency is an essential skill in security services, particularly for security personnel (satpam) who frequently interact with foreign guests. This article describes an English training program for security supervisors as an empowerment strategy to enhance the quality of communication and security services. The training was conducted in the form of an interactive workshop using a Training for Trainers (ToT) approach, where security supervisors were trained to become effective tutors for the personnel under their supervision. The training materials covered basic communication in security contexts, English teaching techniques, and teaching practice through simulations and role-plays. Evaluation was carried out using pre-tests and post-tests to measure participants’ improvement in English proficiency and pedagogical skills. The results showed an increase in post-training scores in both communication and teaching abilities. This program is expected to generate a sustainable multiplier effect through internal training conducted by the security supervisors, thereby contributing to the overall improvement of professionalism and the quality of security services.

The resource reservation protocol (RSVP) lets hosts request quality of (bandwidth) service for multicast applications on the Internet. As network equipment advances to provide improved bandwidth service, security service becomes the more critical problem. However, RSVP doesn't provide a flexible mechanism to support quality of security service (QoSS). Security service RSVP extends RSVP to provide the needed mechanism for dynamically negotiating QoSS among the senders and receivers of multicast applications on the Internet. SSRSVP provides different QoSS resolutions according to receiver nodes' security service needs.

Clusters of computers have emerged as mainstream parallel and distributed platforms for high‐performance, high‐throughput and high‐availability computing. To enable effective resource management on clusters, numerous cluster management systems and schedulers have been designed. However, their focus has essentially been on maximizing CPU performance, but not on improving the value of utility delivered to the user and quality of services. This paper presents a new computational economy driven scheduling system called Libra, which has been designed to support allocation of resources based on the users' quality of service requirements. It is intended to work as an add‐on to the existing queuing and resource management system. The first version has been implemented as a plugin scheduler to the Portable Batch System. The scheduler offers market‐based economy driven service for managing batch jobs on clusters by scheduling CPU time according to user‐perceived value (utility), determined by their budget and deadline rather than system performance considerations. The Libra scheduler has been simulated using the GridSim toolkit to carry out a detailed performance analysis. Results show that the deadline and budget based proportional resource allocation strategy improves the utility of the system and user satisfaction as compared with system‐centric scheduling strategies. Copyright © 2004 John Wiley & Sons, Ltd.

Οι συνθήκες που επικρατούν στην υγεία και η ποιότητα της παροχής των υπηρεσιών απασχολούν ολοένα και περισσότερο τους ανθρώπους που εργάζονται και ασχολούνται με τα θέματα διοίκησης και πολιτικών υγείας καθώς είναι ένα πλεονέκτημα το οποίο μπορεί να κάνει έναν οργανισμό υγείας να ξεχωρίσει. Από τη βιβλιογραφική ανασκόπηση που πραγματοποιήθηκε παρατηρήθηκε ενδιαφέρον για περαιτέρω έρευνα όσον αφορά την αξιολόγηση των παρεχόμενων υπηρεσιών από τους ασθενείς. Μέσα από τα αποτελέσματα τέτοιων μελετών ένας οργανισμός υγείας θα μπορέσει να εξελίξει και να αναβαθμίσει τις υπηρεσίες υγείας του κερδίζοντας την εμπιστοσύνη και την ικανοποίηση των ασθενών. Ο σκοπός της παρούσας μελέτης είναι η ανάλυση και η διερεύνηση του επιπέδου ικανοποίησης των ασθενών ως προς την ποιότητα των παρεχόμενων υπηρεσιών υγείας του Π.Γ.Ν. Αττικόν. Η μελέτη είναι περιγραφική και έγινε χρήση ερωτηματολογίου για τη συλλογή των δεδομένων. Το ερωτηματολόγιο που χρησιμοποιήθηκε απεικονίζει πέντε διαστάσεις ποιότητας και συγκεκριμένα την αξιοπιστία, τη διασφάλιση, την υλικοτεχνική υποδομή (απτότητα), την ενσυναίσθηση, και την ανταπόκριση. Η μελέτη πραγματοποιήθηκε στα εξωτερικά ιατρεία του Π.Γ.Ν. Αττικόν με δείγμα 120 άτομα. Σημαντικό γεγονός είναι ότι η μελέτη πραγματοποιήθηκε κατά τη διάρκεια της πανδημίας Covid - 19 και αυτό είχε σαν συνέπεια την περιορισμένη πρόσβαση. Επίσης επηρεάστηκε η επισκεψιμότητα των ασθενών ως προς το νοσοκομείο λόγω φόβου διασποράς του ιού, καθώς ενδέχεται και να επηρεάστηκαν οι προσδοκίες αλλά και οι αντιλήψεις των ασθενών. Συνολικά παρατηρήθηκε ότι οι προσδοκίες του δείγματος ήταν υψηλότερες από τις αντιλήψεις, δηλαδή ήταν υψηλότερες από την υπηρεσία που δέχτηκαν. Ακόμα από τη μελέτη που πραγματοποιήθηκε διακρίνεται ότι η αξιοπιστία και η ασφάλεια ταξινομούνται από τους ασθενείς έως οι πιο σημαντικές διαστάσεις όσον αφορά την αξιολόγηση της ποιότητας των παρεχόμενων υπηρεσιών. Τα αποτελέσματα της μελέτης παρουσιάζουν συνολικά μία σχετικά καλή εντύπωση παρόλα αυτά υπάρχουν τομείς όπου το δείγμα μας έδειξε ότι δεν είναι ικανοποιημένο και οι υπηρεσίες θα μπορούσαν να αναβαθμιστούν. Αυτά τα αποτελέσματα είναι το κλειδί για τους υπεύθυνους της διοίκησης ποιότητας του Π.Γ.Ν. Αττικόν με σκοπό την εξέλιξη της ποιότητας των υπηρεσιών του νοσοκομείου. Φυσικά η μελέτη της ικανοποίησης των ασθενών πρέπει να είναι συνεχής καθώς η ποιότητα που παρέχει ένας οργανισμός πρέπει να συνεχίζεται σε βάθος χρόνου και συνεχώς να αυξάνεται.

Real-time and embedded systems have traditionally been designed for closed environments where operating conditions, input workloads, and resource availability are known a priori and are subject to little or no change at runtime. There is an increasing demand, however, for autonomous capabilities in open distributed real-time and embedded (DRE) systems that execute in environments where input workload and resource availability cannot be accurately characterized a priori. These systems can benefit from autonomic computing capabilities, such as self-(re)configuration and self-optimization, that enable autonomous adaptation under varying-even unpredictable-operational conditions. A challenging problem faced by researchers and developers in enabling autonomic computing capabilities to open DRE systems involves devising adaptive planning and resource management strategies that can meet mission objectives and end-to-end quality of service (QoS) requirements of applications. To address this challenge, this paper presents the integrated planning, allocation, and control (IPAC) framework, which provides decision-theoretic planning, dynamic resource allocation, and runtime system control to provide coordinated system adaptation and enable the autonomous operation of open DRE systems. This paper presents two contributions to research on autonomic computing for open DRE systems. First, we describe the design of IPAC and show how IPAC resolves the challenges associated with the autonomous operation of a representative open DRE system case study. Second, we empirically evaluate the planning and adaptive resource management capabilities of IPAC in the context of our case study. Our experimental results demonstrate that IPAC enables the autonomous operation of open DRE systems by performing adaptive planning and management of system resources.

Internet of Things (IoT) services have grown substantially in recent years. Consequently, IoT service providers (SPs) are emerging in the market and competing to offer their services. Many IoT applications utilize these services in an integrated manner with different Quality-of-Service (QoS) requirements. Thus, the provisioning of end-to-end QoS is getting more indispensable for IoT platforms. However, provisioning the system by using only QoS metrics without considering user experiences is not sufficient. Recently, Quality of Experience (QoE) model has become a promising approach to quantify actual user experiences of services. A holistic design approach that considers constraints of various QoS/QoE metrics together is needed to satisfy requirements of these applications and services. Besides, IoT services may operate in environments with limited resources. Therefore, effective management of services and system resources is essential for QoS/QoE support. This paper provides a comprehensive survey for the state-of-the-art studies on IoT services with QoS/QoE perspective. Our contributions are threefold: (1) QoE-driven architecture is demonstrated by classifying vital components according to QoE-related functions in prior studies, (2) QoE metrics and QoE optimization objectives are classified by corresponding system and resource control problems in the architecture, and (3) QoE-aware resource management e.g., QoE-aware offloading, placement and data caching policies with recent Machine Learning approaches are extensively reviewed.

Fault-tolerant scheduling plays a significant role in improving system reliability of clusters. Although extensive fault-tolerant scheduling algorithms have been proposed for real-time tasks in parallel and distributed systems, quality of service (QoS) requirements of tasks have not been taken into account. This paper presents a fault-tolerant scheduling algorithm called QAFT that can tolerate one node's permanent failures at one time instant for real-time tasks with QoS needs on heterogeneous clusters. In order to improve system flexibility, reliability, schedulability, and resource utilization, QAFT strives to either advance the start time of primary copies and delay the start time of backup copies in order to help backup copies adopt the passive execution scheme, or to decrease the simultaneous execution time of the primary and backup copies of a task as much as possible to improve resource utilization. QAFT is capable of adaptively adjusting the QoS levels of tasks and the execution schemes of backup copies to attain high system flexibility. Furthermore, we employ the overlapping technology of backup copies. The latest start time of backup copies and their constraints are analyzed and discussed. We conduct extensive experiments to compare our QAFT with two existing schemes-NOQAFT and DYFARS. Experimental results show that QAFT significantly improves the scheduling quality of NOQAFT and DYFARS.

Der Ausdruck Quality of Service (QoS) beschreibt die Güte eines erbrachten Dienstes. QoS beschreibt Eigenschaften wie Antwortzeit, Verfügbarkeit, den Grad der Nachrichten-Verschlüsselung oder den Durchsatz. QoS ist sowohl für Multi-Media Anwendungen (Audio- und Video-Übertragung) als auch für Geschäftsanwendungen wichtig. Die vorgelegte Arbeit konzentriert sich dabei auf das Feld der Geschäftsanwendungen. Solche Anwendungen arbeiten mit Transaktionen wie etwa dem Bestellen eines Produkts oder der Überweisung von Geld zwischen Konten. QoS Eigenschaften solcher Anwendungen sind beispielsweise die Anzahl an Transaktionen während eines Zeitintervalls, die maximale Anzahl gleichzeitig mit dem System arbeitender Nutzer, oder die zu erwartende Verfügbarkeit. Durch Middleware kann die Realisierung von Verteilung vor dem Programmierer verborgen werden. In einer idealen Welt würde Middleware dasselbe für QoS leisten. Das heißt, der Entwickler spezifiziert nur die gewünschte Dienstgüte und kümmert sich nicht darum, wie sie realisiert wird. Das ist so aber nicht möglich, denn die zu erbringende Dienstgüte hat massive Auswirkungen auf das Design einer Applikation. Daher muss QoS schon in der Design-Phase angegangen werden, was mit einer rein Middleware-gestützten Herangehensweise nicht möglich ist. Die vorgelegte Arbeit zeigt, wie dieses Problem durch einen modellgetriebenen Ansatz behoben werden kann. Die Entwicklung beginnt dann mit einem Plattform-unabhängigen Modell (PIM), welches das Verhalten und die QoS Eigenschaften der Applikation beschreibt. Dieses Modell wird automatisch durch eine Modell-Transformation in ein Plattform-spezifisches Modell (PSM) umgewandelt. Das PSM beschreibt das Design einer Implementierung für eine spezifische Plattform und berücksichtigt dabei die im PIM beschriebenen QoS-Eigenschaften. Um dieses Szenario in der Praxis anwenden zu können, müssen zwei Probleme gelöst werden: das Modellieren von QoS Eigenschaften und die Modell-Transformation. Gegenwärtig erfordert das Erstellen einer Modell-Transformation detailliertes Wissen über die Modellierungssprache und ihre Interna. Um das zu vereinfachen, wurde im Rahmen dieser Arbeit die visuelle Regelbasierte Transformationssprache Kafka entwickelt. Kafka und die zugehörigen Werkzeuge bauen auf Graphtransformations-Theorie auf. Kafka vereinfacht das Erstellen von Transformationen weil es auf der Notation des PIM und PSM aufbaut. Daher muss der Entwickler nichts von den Interna (etwa dem Meta-Modell) verstehen. Um PIMs von QoS-fähigen Applikationen zu erstellen, wurde die Modellierungssprache PIQML entwickelt, welche auf UML 2.0 Komponenten, Hierarchischen Nachrichten Sequenz Diagrammen (HMSCs) und einer neuen Meta-Modell Erweiterung für QoS Verträge basiert. Die vorgelegte Arbeit zeigt, wie PIQML Modelle auf verschiedene Zielplattformen (Programmiersprachen und Middleware Produkte) abgebildet werden können. Basierend auf PIQML und Kafka wurde das Werkzeug Kase entwickelt, welches das Editieren von PIQML Modellen (PIMs), UML Modellen (PSMs) und Kafka Transformationen integriert. Das Ergebnis ist eine integrierte Werkzeug-Kette für das modellgetriebene Entwickeln QoS-fähiger verteilter Applikationen.

With the rapid growth of functionally identical web services, Quality of Service (QoS) plays vital role for deciding the most suitable services for consumers. Although, QoS for web services has gained extensive attention in the literature, most of the existing efforts are unable to consider the multiperspective QoS of web services. Unlike conventional software paradigms, web services are provided, developed and used by different users such as provider, consumer and broker. As a result, QoS requirements vary from user to user. Existing researches are unable to provide standard solution, which can deal with what service providers, consumers and broker should expose in service description as QoS parameters. Therefore, in this book chapter, a multiperspective PCB-QoS classification of non-functional parameters along with new QoS parameters, i.e. access rate and Overall Aggregated Effective Quality of Service (OAEQoS) is presented. Due to the extensible nature of PCB-QoS classification, it can be extended to accommodate more number of QoS parameters. This QoS classification is based on the idea of partitioning the generic QoS parameters according to multi-user’s perspective. An Average Real Value Sum Method (ARSM) based on default priority constraints is also proposed for ranking of web services that uses the presented QoS classification. With the help of proposed approach, the user can specify the service requirements without taking the hurdle of specifying the weights for each QoS parameter during web service operations. It also prevents the services from malicious service provider to publish the incorrect and inaccurate QoS information. Experimental evaluation shows the effectiveness of proposed approach over the existing approach.

Scheduling in workflows plays a crucial role in optimizing task execution and resource utilization in cloud computing systems, particularly when Quality of Service (QoS) requirements, such as deadlines and task priorities, have to be fulfilled. This paper presents a novel, lightweight heuristic scheduling algorithm that incorporates QoS metrics into the heuristic scheduling process using the WorkflowSim simulation framework. The algorithm filters tasks based on the feasibility of deadlines, computes dynamic priority scores based on a blend of urgency and task weight, and employs an earliest-finish-time (EFT) policy for task to VM allocation. To test the proposed approach, simulation experiments were performed with synthetic Directed Acyclic Graph (DAG) workflows in a heterogeneous VM (Virtual Machine) cloud environment. The performance of the algorithm was evaluated relative to traditional baseline approaches, including First-Come-FirstServe (FCFS), Round Robin (RR), and Min-Min, using the metrics makespan, deadline miss rate, workflow success rate, and VM utilization. The results demonstrate the effectiveness of the proposed method in reducing makespan by up to 31.7% and improving workflow success rate to $\mathbf{7 2 \%}$ while achieving $\mathbf{7 9 \%}$ VM utilization, outperforming traditional schedulers. These findings suggest that lightweight heuristics can graciously meet the objectives of QoS without suffering the computational cost of metaheuristics. Enhancements in the future may include energy- and cost-conscious goals, re- scheduling, and predictive models to make it applicable across the various dynamics of a production field.

Quality of Service on TCP / IP networks is focused on allocating bandwidth that flows in accordance with service requirements on the network. It aims to allocate guaranteed bandwidth for each service used. The increasing number of Internet users on campus networks will automatically affect the quality of services on the network. Therefore, we need a system that can improve the quality of network services by limiting the bandwidth for each service that runs. Hierarchical Token Bucket (HTB) is one method of bandwidth allocation. HTB has the task of limiting bandwidth and arranging packet queues based on priority. HTB method application is done using Software-Defined Networking (SDN) technology. SDN is a network technology that uses OpenFlow as the protocol. While OpenDaylight is one of the SDN-based controllers that supports the OpenFlow protocol. The HTB method is connected to the OpenDaylight controller via the REST API. The results obtained from four types of scenarios performed, resulting in a throughput of 10.15 Mbps, 7.08 Mbps, 3.08 Mbps for HTTP, FTP, and SMTP services respectively.

Modern drugstore franchise network that recently entered the Indonesian market retail pharmacy industry is bringing new concepts in retailing of pharmaceutical products. This makes the competition in the pharmaceutical world especially the drugstore increasingly competitive. One effort to increase the competitive advantage of the pharmaceutical products retailers is through quality of service strategy. This study was conducted to develop a strategy based on the quality of service at PT. Kimia Farma Pharmacy business unit Yogyakarta. Key success factors of the quality of service based strategy are developed from the policies in PT. Kimia Farma Pharmacy business unit Yogyakarta related with the quality of service that includes speed of service, range of products, hospitality services, and professionalism of the officers. Data about the performance and the customer expectations regarding speed of service, range of products, hospitality services, and professionalism of officers were obtained through interviews with 291 customers who arrived at the Kimia Farma pharmacy Yogyakarta business unit during the study period. The data were then analyzed using Importance Performance Analysis. The result of the Importance Performance Analysis shows that speed of service variable indicator which is non-stop service, located in keep up the good work quadrant, service time warranty of non dispensing drugs and dispensing drugs are in possible overkill quadrant, the availability of service delivery is at the low priority quadrant. The range of products variable indicator, namely the completeness of imported drugs in the low priority quadrant while the other four indicators, namely the completeness of the local production, the authenticity of drugs guarantee, OTC drugs completeness, and completeness of generic and patent drugs quadrant are keep up the good work; variables hospitality services, namely officer responsiveness indicators in quadrant concentration here, the ability to sell, said hello tenderness, and thank you in keep up the good work quadrant; greeting in the low priority quadrant, and customer orientation in possible overkill quadrant; salespersonprofessionalism variable shows two indicators that are in keep up the good work quadrant which are the pharmaceutical field experince and pharmacy management capabilities and one indicator in low priority quadrant which is product knowledge

To facilitate the development of Internet of Things (IoT) applications, numerous middleware protocols and APIs have been introduced. Such applications built atop reliable or unreliable protocols and they expose different characteristics. Additionally, with regard to the application context (e.g., emergency response operations), several Quality of Service (QoS) requirements must be satisfied. To study QoS in IoT applications, the provision of a generic performance analysis methodology is required. Queueing network models offer a simple modeling environment, which can be used to represent IoT interactions by combining multiple queueing model types for building queueing networks. The resulting networks can be used for performance analysis through analytical or simulation models. In this paper, we present several types of queueing models that represent different QoS settings of IoT interactions, such as intermittent mobile connectivity, message drop probabilities, message availability/validity and resource constrained devices. Using MobileJINQS, we simulate our models demonstrating the significant effect on response times and message success rates when varying QoS settings.

WiMAX refers to Wireless Interoperable implementations of the IEEE 802.16 standards ratified by the WiMAX Forum has a main goal to deliver wireless communications with quality of service in a secured environment. The WiMAX MAC layer is designed to support different types of applications and services having different Quality of service (QoS) requirements. In addition of providing higher throughput and less delay, a scheduling algorithm should also take into account the WiMAX Qos classes and service requirements at MAC layer. Proper scheduling algorithm will enhance the date rate of all the QoS classes of IEEE 802.16e standard. The problem of the scheduler is that there is no standard algorithm that will satisfy all the QoS parameters of IEEE 802.16e standard. We aim to highlight a problem of real-time (UGS a rtPS) service class and provide a feasible solution to it by directing our focus towards the real-time classes. We propose a review of uplink scheduling algorithms proposed for WiMAX and the problems connected with it. The solution to the proposed problem is that we structure a Cross layered hybrid up-link algorithm. NS3 simulations will lead us with interesting results and thus enhance throughput and minimize delay and jitter.

The aspect of customer loyalty is considered to be one of the important factors driving an organization’s longevity in today’s marketplace, as loyal customers show the desire to buy more the willingness to pay higher prices and engage in spreading the favourable word of mouth. Customer loyalty, along with customer satisfaction, is a consequence of three factors, especially service and product quality. Compared to existing customers, it is a commonly recognised notion that firms pay higher costs for marketing to new customers as the acquisition of new customers is perceived to be ten times more expensive than maintaining existing customers. It can be seen, despite understanding this, which many companies are still struggling to effectively maintain their customers. In view of this scenario, the current research upholds the objective of investigating the connections that take place in the context of the retail industry in Malaysia in the midst of the factors indicated above and consumer loyalty. Many hypotheses were built from a theoretical model for this reason, and the process that was applied to test them was also highlighted. Later on by means of questionnaires, the suggested hypotheses were checked. The findings of the empirical study revealed that service quality, product quality, and consumer satisfaction are three distinct constructs that are combined to measure customer loyalty, indicating that service and product quality have a comparatively greater effect on variable customer loyalty. It is suggested that future initiatives should be aimed at evaluating the effect on consumer loyalty of customer relationships, customer preferences and engagement, as well as extending research to other sectors in order to gain greater insights.