Quality Of Service Aspects Research Articles

Vehicle-to-Everything: Cybersecurity and Quality of Service Challenges

This paper is focused to the emerging technological development in the area of the advanced vehicular communication systems. It considers the most up to date Vehicular to Everything technologies and discusses the typical scenarios related to the communication between vehicles, between vehicles and infrastructure, vehicles and pedestrians and communication between vehicles and network environment. Paper also considers the arising issues and countermeasures related to the security, privacy and quality of service (QoS) as well as predictive QoS aspects.

A decade of research in fog computing: Relevance, challenges, and future directions

AbstractRecent developments in the Internet of Things (IoT) and real‐time applications, have led to the unprecedented growth in the connected devices and their generated data. Traditionally, this sensor data is transferred and processed at the cloud, and the control signals are sent back to the relevant actuators, as part of the IoT applications. This cloud‐centric IoT model, resulted in increased latencies and network load, and compromised privacy. To address these problems, Fog Computing was coined by Cisco in 2012, a decade ago, which utilizes proximal computational resources for processing the sensor data. Ever since its proposal, fog computing has attracted significant attention and the research fraternity focused at addressing different challenges such as fog frameworks, simulators, resource management, placement strategies, quality of service aspects, fog economics and so forth. However, after a decade of research, we still do not see large‐scale deployments of public/private fog networks, which can be utilized in realizing interesting IoT applications. In the literature, we only see pilot case studies and small‐scale testbeds, and utilization of simulators for demonstrating scale of the specified models addressing the respective technical challenges. There are several reasons for this, and most importantly, fog computing did not present a clear business case for the companies and participating individuals yet. This article summarizes the technical, non‐functional, and economic challenges, which have been posing hurdles in adopting fog computing, by consolidating them across different clusters. The article also summarizes the relevant academic and industrial contributions in addressing these challenges and provides future research directions in realizing real‐time fog computing applications, also considering the emerging trends such as federated learning and quantum computing.

An integrated optimal method for cloud service ranking

Many cloud providers present various services with different attributes. It is a complex, lengthy process to select a cloud service that meets user requirements from an assortment of services. At the same time, user requirements are sometimes defined with imprecision (sets or intervals), whereas it is also important to consider the quality of user feedback (QoU) and quality of service (QoS) attributes for ranking. Besides, each MADM method has a di erent procedure, which causes functional contradictions. These contradictions have led to confusion in choosing the best MADM method. It is necessary to provide a method that harmonizes the results. Therefore, choosing a method for ranking cloud services that addresses these issues is currently a challenge. This paper proposes an optimal cloud service ranking (OCSR) method that ranks cloud services efficiently based on imprecise user requirements in both QoS and QoU aspects. OCSR consists of four stages including receiving the requirements, preprocessing, ranking, and integrating the ranking results. At the receiving requirements stage, the query format is created. In the preprocessing stage, a requirement interval is created for considering imprecise user requirements in order to filter inappropriate services. Based on QoS and QoU attributes, cloud services are then ranked through multiple multi-attribute decision-making (multi-MADM) methods such as the prominent MADM techniques. Finally, the ranking outputs of various methods are integrated to obtain the optimal results. The experimental results confirm that the OCSR outperforms the previous methods in terms of optimality of ranking, sensitivity analyses, and scalability.

Rough set-based quality of service optimisation guidelines with stack parameter in MANET

In mobile ad hoc network (MANET), providing a guaranteed service for packet delivery has to pass through several hurdles. Providing guaranteed service should address multiple quality of service (QoS) parameters under uncertain network conditions. The QoS parameters should be prioritised in consideration of MANET constraints and applications running on MANET. The QoS aspects of MANET are impacted by the multi-layer stack parameters. An analysis has been conducted to identify the trade-off point for configuring the stack parameters to achieve better QoS in packet delivery. The outcome of analysis is discussed in terms of packet error rate, energy efficiency, goodput and delay with the support of rough set theory (RST). The multi-objective analysis capabilities of RST make it suitable for taking dynamic decision to prioritise the QoS parameter. The rough set derived decision rules are filtered out based on probabilistic properties like strength, certainty and coverage of the decision rules.

Rough set-based quality of service optimisation guidelines with stack parameter in MANET

In mobile ad hoc network (MANET), providing a guaranteed service for packet delivery has to pass through several hurdles. Providing guaranteed service should address multiple quality of service (QoS) parameters under uncertain network conditions. The QoS parameters should be prioritised in consideration of MANET constraints and applications running on MANET. The QoS aspects of MANET are impacted by the multi-layer stack parameters. An analysis has been conducted to identify the trade-off point for configuring the stack parameters to achieve better QoS in packet delivery. The outcome of analysis is discussed in terms of packet error rate, energy efficiency, goodput and delay with the support of rough set theory (RST). The multi-objective analysis capabilities of RST make it suitable for taking dynamic decision to prioritise the QoS parameter. The rough set derived decision rules are filtered out based on probabilistic properties like strength, certainty and coverage of the decision rules.

Customer-Oriented Quality of Service Management Method for the Future Intent-Based Networking

The rapid development and spread of communication technologies is now becoming a global information revolution. Customers have a need for communication services, which could be flexibly configured in accordance with their Quality of Experience (QoE) requirements. Realizing the close connection between customer experience and profitability, the service provider has been placing more and more attention on customer experience and QoE. The traditional quality of service management method based on SLA (Service Level Agreement) is not sufficient as a means to provide QoE-related contracts between service providers and customers. The current SLA method is mostly limited and focused on technical aspects of QoS (Quality of Service). Furthermore, they do not follow on the network the principles and semantic approach to the QoS specification for a communication service using QoE parameters. In this paper, we propose a customer-oriented quality of service management method for future IBN (Intent-Based Networking). It is based on a new QoE metric on a scale from 1 to 5, which allows one to take into account the commercial value of e-services for customers. Based on this approach, the network configuration and functionality of network equipment automatically changes depending on customer requirements. To implement the new method of service quality management, an algorithm for routing data packets in the network was developed, taking into account the current load of the forecast path. The algorithm of billing system functioning in conditions of customer-oriented quality management in telecommunication networks has been created. To investigate the effectiveness of the proposed method of service quality management with the traditional SLA method, we developed a simulation network model with the implementation of two approaches. By conducting a simulation, it was determined that the proposed method gives an average gain of 2–5 times for the criterion of the number of customers who require high quality of experience of the service.

Evolutionary many-objective assembly of cloud services via angle and adversarial direction driven search

Cloud service composition (CSC) is an effective way to carry out large-scale complicated applications by the ensemble of existing individual services. Each service typically involves several Quality of Service (QoS) criteria contracted for non-functional aspects like time or price, among others, which greatly influence the overall performance of the resulting applications. Service composition approaches have emerged as an important technique in leveraging the quality of composite service efficiently and have attracted significant attention. However, most existing proposals ignore the many-objective nature of CSC and consider up to three objectives, the optimization of diverse QoS aspects of CSC from a many-objective perspective (at least four) still lacks. On another aspect, due to the rapid growth of nondominated solutions in high-dimensional objective spaces, the traditional multi-objective optimization algorithms are usually not capable of handling problems possessing many objectives. To address the above issue, we develop an angle and adversarial direction based optimizer for many-objective CSC scenarios, which evolves a number of subpopulations with adversarial search directions in a parallel paradigm. Additionally, vector angle based selection criterion, which adaptively captures beacon individuals, is utilized to diversify the population. Extensive experiments are carried out on a series of CSC instances utilizing synthetic datasets and the results show that our proposition is competitive and has better versatility compared with the state-of-the-art.

Proposing a New Model for Quality of Service Acceptance

Quality of service (QoS) has been proofed to be a great significance effect in the utilization of cloud service in higher education institutions (HEI’s), due to having many aspects determine the acceptance level of QoS while providing cloud service, QoS acceptance not given sufficient attention from HEIs and decision-makers. In this research, previous QoS studies are review in this field to identify QoS acceptance variables by review studies for the last 5 years. Thus, with the aim to discover QoS aspects this research intends to develop an integrated model to understand these variables and relationship between QoS acceptance variables, which must be efficiently studied. Hence, the integrated model between TOE (Technological, Organizational, and environmental) and HOT (Human, Organizational, and Technological) theory is presented in this research to be the core contribution. The integrated model helps HEIs to evaluate and explore QoS aspects to increase utilizing of cloud service, improving HEIs efficiency, and help decision-makers to facilitate the acceptance of QoS in HEIs.

QoS-aware secure transaction framework for internet of things using blockchain mechanism

The Internet of Things (IoT) paradigm enables an enormous network with millions of connected smart things to control almost all aspect of services. In an IoT scenario, self-configured things are dynamically connected in a universal network. The small things are broadly distributed in a real world model with some essential processing capacity and finite storage. Security, privacy and reliability are the most important pillars of the IoT infrastructure. It is challenging to share personal data, highly confidential professional data over a centralized system. The infrastructure itself is capable to provide the guarantee to transmit data safely. However, a special attention for the data along with data consistency is required. Cyber attackers and hackers mostly target the centralized systems. To triumph over these types of situations we propose a security based blockchain service along with some encryption approaches for a secure communication. The encryption and decryption is performed by a hash based secret key. Risk modelling and relative risk reduction also done to prevent attacks under a virtual private network in IoT domain. Before and after attack users also wish to know quality of service (QoS). We have developed a mobile application framework which provides desire output of a user from different aspect of QoS for better understanding. The MQTT broker performs as a negotiator to convey data between cloud consumer and cloud provider. In QoS monitoring section user get chance to reconsider availability, reliability and responsibility like QoS factors while recovering resources and actual resources before attacking system based on CPU utilization, cache status and storage. As per experiment result we able to recover 100% RAM, 97.64% CPU utilization and 78.7% storage using proposed encryption and algorithm on blockchain infrastructure.

Realizing integrated prioritized service in the Hadoop cloud system

Cloud computing has profoundly influenced how people receive IT services nowadays. As the cloud offers more and more services to users, the Quality of Service (QoS) in cloud has become an important issue that could determine the success or failure of services on the cloud. Among the aspects of cloud QoS, job performance is an area which most cloud systems often have little or no control over it. To effectively manage job performance in cloud QoS, the collaboration between the cloud system and its underlying operating system is a must. Hadoop is one of the most popular cloud systems used today. Unfortunately, it does not support efficient schemes to manage job performance. Previously, we proposed a new approach, namely PYARN, to enable Hadoop to provide prioritized job scheduling service to help manage job performance in cloud QoS. In this paper, we report our efforts to make PYARN collaborate with PMMDO, a Linux module providing prioritized service we developed earlier. Compared with the original Hadoop, experiment results showed that the cooperation between PYARN and PMMDO could further expedite the execution of prioritized jobs by up to around 30% more than what PYARN could achieve alone. Our integrated system demonstrates that the cloud system and its host operating system should work together to help manage cloud QoS with regard to job performance.

Adaptive Data Synchronization Algorithm for IoT-Oriented Low-Power Wide-Area Networks.

The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications.

Delay-based and QoS-aware packet scheduling for RT and NRT multimedia services in LTE downlink systems

Guaranteeing Quality of Service (QoS) for heterogeneous traffic is a major challenge in the Fourth Generation (4G) mobile networks. Therein, the absence of sophisticated resources allocation process at the base station jeopardizes QoS in terms of latency data transfer. It has been observed from the literature that low delay bounds might be ensured, however, at the expense of other QoS aspects; for example, throughput and data loss. Therefore, in this article, we propose an effective Delay–based and QoS–Aware Scheduling (DQAS) scheme with a low complexity overhead as an efficient solution for the resource allocation issue in LTE Medium Access Control (MAC) layer. The ultimate aim of DQAS is to minimize delay for Real-Time (RT) traffic while still offering a good level of QoS. Complying with QoS of different traffic types, we effectively analyze the queue buffer of each user flow by developing an algorithm called Efficient Delay Control (EDC) that weights each flow priority in terms of delay. Then, this weight is utilized as a principle for the scheduling decision on the attending flows. Furthermore, the Least Delay Increase (LDI) algorithm is developed to tune the scheduler behavior to maintain a balance between delay and system throughput. Simulation results considering different user mobility levels reveal that DQAS significantly guarantees a low end-to-end delay trend that is independent of increased RT load, and moreover, a reasonable throughput and data drop levels compared to other existing schedulers.

Guidance Provision for Increasing Quality of Service of Public Transport

Travellers formulate their optimal strategyto follow for their trip, every time they may shift to another mode. Trip generalized cost is perceived based on quality of service aspects and type of traveller. One of the most known models to assess service quality is the GAP model, proposed by Parasuramanet al. (1985), which considersboth consumer and provider beliefs, expectations, perceptions and standards. The present paper deals with the fifth GAP of the model, known as the quality GAP, thus expected versus perceived quality of service, for the assessment of the transit service quality. This GAP has been estimated for the case of the transit system in Greece. An internet based questionnaire was used to collect user expectations and perceptions of 26 selected transit quality indicators, based on a 5 point likert scale. Then, a decision tree was developed, using the J48 algorithm, which linked user perceptions and expectations with the overall service quality assessment. The decision tree analysis depicts the importance of various quality components in the generalized cost estimation. Findings showed that the performance indicator “Availability of information by phone, mail”, was the most crucial parameter for the overall assessment of the service, while both performance and importance variables participated in the tree formulation. Tree paths provide guidance for transit operators and/or decision makers for increasing the quality of their services and at the same time enhance performance efficiency and operation profitability.

Evolutionary composition of QoS-aware web services: A many-objective perspective

Web service based applications often invoke services provided by third-parties in their workflow. The Quality of Service (QoS) provided by the invoked supplier can be expressed in terms of the Service Level Agreement specifying the values contracted for particular aspects like cost or throughput, among others. In this scenario, intelligent systems can support the engineer to scrutinise the service market in order to select those candidates that best fit with the expected composition focusing on different QoS aspects. This search problem, also known as QoS-aware web service composition, is characterised by the presence of many diverse QoS properties to be simultaneously optimised from a multi-objective perspective. Nevertheless, as the number of QoS properties considered during the design phase increases and a larger number of decision factors come into play, it becomes more difficult to find the most suitable candidate solutions, so more sophisticated techniques are required to explore and return diverse, competitive alternatives. With this aim, this paper explores the suitability of many-objective evolutionary algorithms for addressing the binding problem of web services on the basis of a real-world benchmark with 9 QoS properties. A complete comparative study demonstrates that these techniques, never before applied to this problem, can achieve a better trade-off between all the QoS properties, or even promote specific QoS properties while keeping high values for the rest. In addition, this search process can be performed within a reasonable computational cost, enabling its adoption by intelligent and decision-support systems in the field of service oriented computation.

Enhanced resource scheduling in Grid considering overload of different attributes

Most of scheduling methods in the Grid only consider one special attribute of the resource or one aspect of QoS (Quality of Service) of the job. In this paper, we focus on the problem that how to consider two aspects simultaneously. Based on the requirements of the jobs and the attributes of the resources, jobs are categorized into three kinds: CPU-overload, memory-overload, and bandwidth-overload jobs. One job may belong to different kinds according to different attributes. We schedule the jobs in different categories in different orders, and then propose a scheduling method-MTS (multiple attributes scheduling method) to schedule Grid resources. Based on the comparisons between our method, Min-min, ASJS (Adaptive Scoring Job Scheduling), and MRS (Multi-dimensional Scheduling) show: (1) MTS reduces the execution time more than 15% to other methods, (2) MTS improves the number of the finished jobs before the deadlines of the jobs, and (3) MTS enhances the file size of transmitted files (input files and output files) and improves the number of the instructions of the finished jobs.

Priority consideration in inter‐WBAN data scheduling and aggregation for monitoring systems

AbstractWireless body area networks (WBANs) are composed of small intelligent tiny wireless sensors; these sensors are responsible for collecting information of a patient's vital signs and transmitting vital information. WBAN offers mobility to patients and flexibility to medical staff. An increase of the deployment of monitoring systems on patients promotes researchers and developers to focus on issues related to WBAN. Quality of service (QoS) has been always treated as a major issue in WBAN technology, and scheduling as a packet prioritizing mechanism contributes to QoS guarantee provisioning significantly. In this paper, two novel inter‐WBAN data scheduling and aggregation are developed for monitoring systems in order to satisfy QoS requirements in WBAN networks. We introduced a novel parameter called critical delay to serve packets taking into account their priorities and classify them into an aggregated frame to be further transmitted to medical server. The proposed scheme provides QoS‐guaranteed service for the applications running on the sensor nodes in all the three aspects of QoS, that is, delay, throughput and packet loss. Copyright © 2015 John Wiley & Sons, Ltd.

Adaptive Packet Scheduling for Resource Interference Avoidance in LTE-Advanced Networks

Resource interference degrades the Quality of Service (QoS) in resource shared networks and this affects Device-to- Device (D2D) communications. This paper proposes an Adaptive Packet Scheduling Mechanism (APSM) to avoid resource interferences for (D2D) communication, which underlays Long-Term Evolution (LTE) networks. The proposed mechanism provides QoS-guaranteed service for D2D communications in all the three aspects of QoS, i.e. throughput, packet loss, and packet delay. The simulation results show that the proposed mechanism provides more efficient throughput compared to that of the regular cellular network.

Reliability of BPMN Business Processes

Organizations increasingly use business processes and the Business Process Model and Notation (BPMN) to model them. Taking into account the relevance of Quality of Service (QoS) aspects in business processes, we can find in the literature some proposals that already calculate reliability of structured workflows and service compositions, as well as some proposals that extend BPMN to include cost, availability, and reliability, among others QoS aspects. In this paper we focus on reliability and we calculate the reliability of the overall BPMN process starting from the reliability value of its activities. We use the Stochastic Workflow Reduction method, which applies a set of reductions rules to process blocks. To accomplish this, we extend BPMN with reliability information and we identify the BPMN process blocks for which we can apply a reduction. We apply our approach to a use case concerning a simplified paper reviewing process. In addition, we identify the limitations of our proposal, which are intrinsic to the BPMN non-block structure. To the best of our knowledge, this is the first proposal to compute the reliability of BPMN business processes.

Saas Quality of Service Attributes

Software as a Service (SaaS) is one of the cloud computing branch and it is rapidly growing. Quality of Service (QoS) for SaaS cloud is considered as an important concern among researchers. The QoS specification, particularly, for SaaS is known as a big gap in current researches. Therefore, in this study, the main QoS attributes for SaaS consisting of 33 attributes have been reviewed. The results show a comprehensive specification of QoS attributes for SaaS which cover more aspects of QoS for SaaS excluding the business perspective. The attributes then have been classified in terms of both user and provider perspectives and can be useful as a guideline for both users and providers.

A Review of Recent Patents for Quality Assessment of Multimedia Communications by Digital Watermarking

Multimedia communication has gained an increasing interest in the last decade. The design of services and distributed multimedia applications imposes a number of Quality of Service (QoS) requirements. In particular, the processing and delivery of multimedia content are not independent and their interaction has a major impact on the QoS aspects. Recently, tracing watermarking has been introduced as a blind method for evaluating the QoS of multimedia communications. This paper aims at presenting a review of recent patents, and state of art solutions as well, in the field of QoS assessment of multimedia communication by tracing watermarking. Finally, a discussion pointing out the current and future developments in this area summarizes the remarkable points of this work.