Quality Of Service For Users Research Articles

Self-organised resource assignment for on-demand services in the cloud platform

It is more popular for a multimedia service provider (MCSP) to deploy many data centres (DCs) in different geographic locations over cloud for delivering video-on-demand (VoD) services to a lot of users. One primary task of the MCSP is to maximise its profit while guarantee the user's quality-of-service (QoS) requirements. However, the stochastic arrival of user requests and the capacity restriction of individual DC make resource management in distributed cloud more challenging than in a general cloud. We present a resource assignment strategy that can accommodate heterogeneous network resources and QoS demands by converting the request distribution problem into the constrained function optimisation problem. An online algorithm is developed and certified approximating to the optimum solution. Compared with other alternatives, our algorithm can cut down more than 35% of operational cost without degrading the QoS of end users.

Multi-Agent Actor Critic for Channel Allocation in Heterogeneous Networks

Heterogeneous networks (HetNets) can equalize traffic loads and cut down the cost of deploying cells. Thus, it is regarded to be the significant technique of the next-generation communication networks. Due to the non-convexity nature of the channel allocation problem in HetNets, it is difficult to design an optimal approach for allocating channels. To ensure the user quality of service as well as the long-term total network utility, this article proposes a new method through utilizing multi-agent reinforcement learning. Moreover, for the purpose of solving computational complexity problem caused by the large action space, deep reinforcement learning is put forward to learn optimal policy. A nearly-optimal solution with high efficiency and rapid convergence speed could be obtained by this learning method. Simulation results reveal that this new method has the best performance than other methods.

Research on task offloading based on deep reinforcement learning in mobile edge environment

With the rapid development of Internet technology and mobile terminals, users’ demand for high-speed networks is increasing. Mobile edge computing proposes a distributed caching approach to deal with the impact of massive data traffic on communication networks, in order to reduce network latency and improve user service quality. In this paper, a deep reinforcement learning algorithm is proposed to solve the task unloading problem of multi-service nodes. The simulation platform iFogSim and data set Google Cluster Trace are used to carry out experiments. The final results show that the task offloading strategy based on DDQN algorithm has a good effect on energy consumption and cost, it has verified the application prospect of deep reinforcement learning algorithm in mobile edge computing.

Implementation of Vertical Handoff Over LTE, Wi-Fi and WiMAX Networks

The forthcoming wireless networks provide the continuous services to their users for different applications by the integration of diverse wireless access technologies known as heterogeneous wireless network. The heterogeneous wireless network improves the Quality of Service for stationary and non-stationary mobile users. Even when users are in mobility the services are provided by means of handoff or handover. In this paper, the integration of three different wireless networks such as LTE, WiMAX and Wi-Fi networks and their vertical handoff performance analysis are presented. These diverse wireless networks which are considered for integration are modeled as a heterogeneous wireless network. This network is designed using QualNet simulator. Furthermore, the designed heterogeneous network, vertical handoff performance is estimated by using factors such as throughput, jitter and End to End delay. With these performance factors, the designed network’s Quality of Service (QoS) is estimated under mobility conditions.

Energy-Efficient Switching ON/OFF Strategies Analysis for Dense Cellular Networks With Partial Conventional Base-Stations

Focusing on the energy efficiency (EE) improving problem in a densely deployed cellular network with partial conventional base stations (BSs) that cannot be frequently switched on/off, this paper jointly optimizes the switching on/off strategy and user association policy with the consideration of quality-of-service (QoS). By applying a modified switching cost model, we formulate the EE improving problem as an energy efficiency maximization problem (EEMP). To solve the EEMP efficiently, we first concentrate on the EEMP with a constant user distribution where switching cost is omitted temporarily, i.e., static- EEMP, and then the EEMP can be settled by using the results of the static-EEMP. After analyzing the hardness of solving the static-EEMP directly, several sub-optimal strategies are proposed for the static-EEMP to optimize the BSs working states and user association policy. With the results obtained from solving the static-EEMP, we propose a QoS First Maximum EE (QFMEE) scheme to solve the EEMP in two steps. In the first step, necessary BSs are switched on when the user distribution changes to ensure user QoS. In the second step, we judge the extra cost and the energy saving caused by the switching off operations to improve the network EE. Simulation results verify the effectiveness of our proposed strategies for static-EEMP and show that QFMEE can improve the network EE and reduce switching cost significantly when the switching cost occupies a considerable proportion in the total energy consumption.

TANGGAPAN KUALITI PERKHIDMATAN, KEPUASAN DAN NIAT TINGKAH LAKU PENGGUNA TRANSIT ALIRAN BERAT (MRT) DI MALAYSIA

The main aim of this study was to identify factors that influence the behaviour of consumers of the relatively new public transit system operating in Malaysia, the Mass Rapid Transit (MRT). Specifically, the objective of this study was to examine the relationship between perceived service quality, satisfaction and behavioural intention of MRT users in Malaysia. The structured questionnaire will be used as the primary method for collecting data from MRT users around the Klang Valley. They will be selected based on simple sampling techniques. The questionnaire developed will use instruments taken from previous studies. Feedback from MRT users to be collected at a mall intercept around Klang Valley will be analysed using Structured Equation Modelling (SEM) technique. The findings of this study are expected to help policy makers, especially transport policy to determine the direction of developing the public transport industry in Malaysia to improve the quality of life of the public service users in Malaysia, as well as contribute to the development and economy of the local and national population.

5G and IoT: Towards a new era of communications and measurements

The tremendous increase in the demand for data rates due to bandwidth-hungry applications, the explosive growth in the number of devices and the advent of new services have led to intensive efforts of researchers to develop 5G wireless networks and beyond. The quality of its service is very important, and measurements have already started to be performed around the world for different 5G associated frequency bands using new methods of instrumentation and measurement. 5G networks have a large coverage, presenting a perfect match for supporting IoT communications that will revolutionize the way of many everyday life activities. Application examples are in fields of transportation, manufacturing, and healthcare. In these applications, the characterization of IoT components including quality of RF signals or coverage is carried out using virtual and traditional instrumentation. Additionally, energy efficiency measurements are needed for 5G and IoT implementation and originate the development of specific automatic power measurement systems. 5G and IoT will improve the service quality and experience of users in various industries, with fundamental impact on people's lives. An overview of the upcoming 5G wireless systems is described, including a glimpse into the timeline, technical requirements, and enabling technologies. Other IoT solutions are presented, with a focus on applications to industrial settings, smart ports, and healthcare. Specific instrumentation setup and measurement methods associated with 5G and IoT implementations are discussed.

AI Agent in Software-Defined Network: Agent-Based Network Service Prediction and Wireless Resource Scheduling Optimization

With the development of software-defined network (SDN), there will be a large number of devices to access network, which may cause an incalculable burden to the communication network. In addition, due to the high bandwidth in the fifth-generation (5G) era, innovation will occur in different fields. There are not only strict requirements on the communication capability of SDN for these application scenarios but also a lot of computing resources. For massive access devices, it is difficult for the traditional service resource scheduling and the allocation system to meet user demand growth. To address the above-stated problems, an artificial intelligence agent (AI Agent) system is put forth in this article. AI Agents can be deployed in different layers of the SDN, thus realizing functions like network service prediction and resource scheduling. A brand new AI Agent framework is designed, and an AI algorithm is adopted to replace the traditional service prediction and resource scheduling strategies. In the meantime, a relevant agent deployment scheme is put forward. Finally, an AI Agent-based simulation experiment for resource scheduling is designed, and the accuracy in network service prediction and rationality in resource allocation based on this framework are tested. The experimental result showed that the operation efficiency of the SDN can be effectively improved, and the resource hit ratio and user service quality may be improved with AI-agent-based traffic prediction and resource allocation model.

How much the wavelength dimensioning methods and a tightened QoS provision impact on the dynamic WDM optical networks capacity?

This article gives an insight on the importance to assign a different capacity to each network link and to tighten the Quality of Service (QoS) provision in the network, in dynamic WDM Optical Networks with wavelength continuity constraints. In the text, several examples illustrate the performance of different strategies. The usual procedure to compute the number of wavelengths of each network link consists of choosing the same capacity to each link on the network. This decision is selected, in most cases, by simplicity and simulation limitations. Notwithstanding, there are no technical motives to force a uniform capacity on the network. In consequence, we analyze the impact on the network capacity of designating the minimum amount of wavelengths to each network link, while satisfying each user QoS requirement. Moreover, despite the chosen dimensioning strategy, it is usual to offer a much better QoS than requested for some users, with the corresponding waste of resources. We can amend this issue by limiting which wavelengths are available to each user according to its particular QoS constraint. This technique, known as Wavelength Grouping, seeks to provide to each user a QoS level closer to the one defined in the Service Level Agreement. By doing so, it is possible to reduce the network capacity needed to allow communication to its user, or diminishing the network blocking probability for a given wavelength capacity. In spite of the usual approach, in this work, we demonstrate that a non-uniform dimensioning strategy and a tighten QoS provision allows to save significant networks capacity, while simultaneously provisioning to each user the QoS established in its Service Level Agreement. This fact is very relevant nowadays, where an impending capacity crunch in optical networks is an important issue.

Social-aware mobile data offloading algorithm through small cell backhaul network: Direct and indirect user influence perspectives

Mobile data offloading is a promising solution to mitigate the explosive increasing traffic load in a mobile network operator (MNO)’s core network, where the MNO can deliver the mobile traffic without traversing the core network. Most of all, the social networking traffic has increased sharply due to the proliferation of online social networking services (SNSs), such as Facebook and Instagram. Thus, an effective mobile data offloading algorithm that considers the social context needs to be developed. In this paper, exploiting the social context from two perspectives, we propose the model to estimate the application selection probability considering a direct influence by each user and indirect influence by other users. Based on this, we propose the mobile data offloading algorithm considering the social context via small cell backhaul network, in order to maximize the quality of service (QoS) of a user and reduce the core network load of an MNO to the maximum. The results of the performance evaluation show that the proposed algorithm considering the social context can enhance the QoS of users and alleviate the core network load better than the other algorithm that does not exploit the social context.

Machine Learning Meets Computation and Communication Control in Evolving Edge and Cloud: Challenges and Future Perspective

Mobile Edge Computing (MEC) is considered an essential future service for the implementation of 5G networks and the Internet of Things, as it is the best method of delivering computation and communication resources to mobile devices. It is based on the connection of the users to servers located on the edge of the network, which is especially relevant for real-time applications that demand minimal latency. In order to guarantee a resource-efficient MEC (which, for example, could mean improved Quality of Service for users or lower costs for service providers), it is important to consider certain aspects of the service model, such as where to offload the tasks generated by the devices, how many resources to allocate to each user (specially in the wired or wireless device-server communication) and how to handle inter-server communication. However, in the MEC scenarios with many and varied users, servers and applications, these problems are characterized by parameters with exceedingly high levels of dimensionality, resulting in too much data to be processed and complicating the task of finding efficient configurations. This will be particularly troublesome when 5G networks and Internet of Things roll out, with their massive amounts of devices. To address this concern, the best solution is to utilize Machine Learning (ML) algorithms, which enable the computer to draw conclusions and make predictions based on existing data without human supervision, leading to quick near-optimal solutions even in problems with high dimensionality. Indeed, in scenarios with too much data and too many parameters, ML algorithms are often the only feasible alternative. In this paper, a comprehensive survey on the use of ML in MEC systems is provided, offering an insight into the current progress of this research area. Furthermore, helpful guidance is supplied by pointing out which MEC challenges can be solved by ML solutions, what are the current trending algorithms in frontier ML research and how they could be used in MEC. These pieces of information should prove fundamental in encouraging future research that combines ML and MEC.

Interference Management and Resource Sharing in Moving Networks

Cellular users on-board vehicles often experience low quality of service (QoS) due to the vehicular penetration loss. Hence, the so-called mobile-cells (MCs) have been proposed as a solution. The envisaged MCs will require additional radio resources, which will lead to poor spectral efficiency. This study proposes new methods by which MCs can share the resources of the other links. Firstly, this study presents resource sharing algorithms according to which, MC's access-link (AL) will share resources either with the backhaul-link (BL) or with a conventional user. Secondly, it proposes a scheme for controlling AL transmit power to reduce the interference caused to BL while maintaining the QoS for the in-vehicle users.

Profit-Driven User Association and Smart Grid Energy Transfer in Green Cellular Networks

On-grid brown energy consumption of cellular infrastructure is contributing to the detrimental impact on the environment, among which base stations (BSs) are guzzling the largest amount of energy in powering the cellular infrastructure. Leveraging green (renewable) energy to power cellular BSs is a radical energy solution. However, in order to minimize the consumption of on-grid brown energy, most related researches focus on maximizing the utilization of green energy in cellular BSs while compromising the user quality of service (QoS). In this paper, we jointly consider the network QoS and green energy utilization in the dual-battery architecture enabled green cellular network. The profit-driven user association and smart grid green energy transfer scheme is proposed to benefit the network providers, in which, some heuristics are further developed to reduce the computational complexity, as the profit-driven user association problem is NP-hard. Extensive simulations have been conducted to validate the proposed scheme. The systematic analysis of this work can serve as a benchmark for greening other information and communication technology infrastructures.

The role of caching in next generation cellular networks: A survey and research outlook

AbstractMobile applications and social networks tend to enhance the needs for high‐quality content access. To address the expeditious growing demand for data services in 5G cellular networks, it is important to develop distribution techniques and an efficient content caching, aiming to significantly reduce redundant data transmission and, thus, improve the efficiency of the networks. In modern communication systems, caching has emerged as a vital tool for reducing peak data rates. It is anticipated that energy harvesting and self‐powered small base stations are the fundamental part of next‐generation cellular networks. However, uncertainties in energy are the main reason to adopt energy efficient power control schemes to reduce SBS energy consumption and ensure the quality of services for users. Using the edge cooperative caching such as energy efficient design can also be achievable, which reduces the usage of the capacity limited SBSs backhaul and the energy consumption. To support the huge power demand of cellular network, renewable energy harvesting technologies can be leveraged. In addition to this, power supply to the infrastructures is the main challenge to the mobile network operators (MNOs) especially in terms of economic optimum, sustainability, and green energy in developing countries for the growth of cellular networks. Renewable energy–based solutions for MNOs not only reduce the overall carbon dioxide emissions but also provide numerous profits.

WITHDRAWN: Efficacy of upper limb robot-assisted therapy compared with conventional therapy in stroke patients: preliminary results on a daily task assessed by means of motion analysis

QoS-aware service composition aims to satisfy users’ quality of services (QoS) needs during service composition. Traditional methods simply attempt to maximize user satisfaction by provisioning the composite service instance with the best QoS. These “best-effort” methods fail to take into account that there also exist other consumers competing for the service resources and their decisions of service selection/composition can impact on QoS. Since user's QoS needs can be met once the demanded level is reached, in this paper, we propose an “on-demand” strategy for QoS-aware service composition to replace the traditional “best-effort” strategy. The service broker is introduced to facilitate implementation of this strategy: it first purchases a number of service instances for each component from providers and then provisions the composite services with different QoS classes to consumers. This paper focuses on how the broker follows the service level agreement (SLA) to provision composite services in the “on-demand” manner. This problem is formally expressed as the minimization of the QoS distance function between SLA and QoS of composite service instances, under a series of constraints. Heuristic approaches are proposed for the problem and experiments are conducted at last to verify their effectiveness and efficiency.

A Load Balancing Vertical Handoff Algorithm Considering QoS of Users for Heterogeneous Networks in Power Communication

With the increase of the number of users and the complexity of services, only single communication network cannot meet all its requests in power communication networks. Therefore, heterogeneous networks are an effective solution. Vertical handoff (VHO) is an important step in the process of heterogeneous network convergence. An appropriate handoff algorithm can improve the quality of service (QoS) of users. In order to solve the problem of network congestion caused by a large number of users connecting to partial networks in heterogeneous networks, a vertical handoff algorithm based on load balance is proposed. Among the networks that can meet users’ requirements, the most load-balancing network is obtained using optimal algorithm. In addition, to consider users’ requirements and ensure the QoS of network service, we use analytic hierarchy process (AHP) to weight different networks. This algorithm can take full use of the various network resources, so that the distribution of the load among networks is average. The simulation results show that the proposed algorithm can select the network according to the user’s demands and each network has close network utilization under the algorithm.

A Quality of Service (QoS) Aware Scheduling Algorithm to Boost QoS of Cell-Edge Users in LTE Networks

LTE is the abbreviation of Long Term Evolution. LTE networks are developed to provide enhanced Quality of Service (QoS), as today’s cellular world and its high speed multimedia applications demand variety of QoS along with a high speed data rate. Scheduling is a key feature of any network to achieve QoS requirements. The QoS widely depends on the distance of user from the Evolved- Node-B (eNB). The user near eNB experience good QoS and the user far away from eNB experiences poor QoS. The system performance is widely affected due to this. Hence, the ultimate and supreme goal of this research work is to enhance the QoS of the cell edge user and improve network performance. Proposed scheduling algorithm i.e. Improved Extended Modified Largest Weighted Delay First (IE-MLWDF) improves the cell edge throughput along with QoS of the cell - edge users. The paper compares IE-MLWDF with its previous versions namely Modified Largest Weighted Delay First (MLWDF) and Extended - MLWDF in terms of various network parameters. This paper presents a detailed analysis of a scheduling algorithm to enhance QoS of cell edge users to provide better network goals. This algorithm can further be extended or improved to make it more effective.

Mobility-aware dynamic service placement for edge computing

Edge computing provides capabilities similar to traditional cloud computing at network edge closer to users. Offloading applications from the cloud to the edge of the network can effectively diminish the latency of users waiting for applications to improve their quality of service(QoS). Due to the user mobility, however, the distance between the user and the edge device is constantly increasing, resulting in a degradation of the user’s QoS. To satisfy the QoS of mobile users, applications should be dynamically migrated to follow the user mobility. In this paper, we propose a mobility-aware dynamic service placement policy that reduces the number of virtual machine migrations and diminishes user-perceived latency simultaneously. The proposed scheme filters out the invalid migration that the user handoffs to another access point before the migration is completed. The simulation trials demonstrate that our solution improves the QoS of users and reduces the number of application migrations.

ANALISIS PERBANDINGAN PENGGUNAAN APLIKASI PENGOLAH KATA MICROSOFT WORD DAN OOW BERDASARKAN SERVQUAL

This research was motivated by problems because paid software as OpenOffice Writer and Abi Word are free software, MS Office and OpenOffice Writer have many similarities in word processing. The purpose of this research was to analyze the Microsoft word software and open office writer in its operation in terms of features, usage security, user interface and rights. This type of research was descriptive which is correlational. The population in this study were users of word processing software in 2015 Informatics and Computer Education Students as many as 69 people. The number of samples was 40 people. Research results show that 1) Usability Variables, Information Quality and Interaction Quality together have a significant effect of 80% on the level of service quality of word processing application users, 2) variable X was very influential on user satisfaction of word processing applications and 3) simultaneously (F test) can provide information that Usability, Information Quality and Interaction Quality from the application together must be considered to improve the word processing application service. Keywords: Comparison of Word Processing Applications, Microsoft Word and Open Office Writter

Privacy Preservation via Beamforming for NOMA

Non-orthogonal multiple access (NOMA) has been proposed as a promising multiple access approach for 5G mobile systems because of its superior spectrum efficiency. However, the privacy between the NOMA users may be compromised due to the transmission of a superposition of all users' signals to successive interference cancellation (SIC) receivers. In this paper, we propose two schemes based on beamforming optimization for NOMA that can enhance the security of a specific private user while guaranteeing the other users' quality of service (QoS). Specifically, in the first scheme, when the transmit antennas are inadequate, we intend to maximize the secrecy rate of the private user, under the constraint that the other users' QoS is satisfied. In the second scheme, the private user's signal is zero-forced at the other users when redundant antennas are available. In this case, the transmission rate of the private user is also maximized while satisfying the QoS of the other users. Due to the non-convexity of optimization in these two schemes, we first convert them into convex forms, and then, an iterative algorithm based on the Concave-Convex Procedure is proposed to obtain their solutions. The extensive simulation results are presented to evaluate the effectiveness of the proposed schemes.