Fash Safdari

Remote Framebuffer (RFB) protocol is a simple protocol for remote access to graphical user interfaces. The use of the RFB protocol has been developed as a means of streaming content, alleviating much of the processing requirements of games for the end user. Cloud gaming is currently an area of the gaming industry gaining large amounts of ground with respect to the potential viability in the future. Understanding how QoS can affect the development of cloud gaming, as well as the metrics involved, and how these metrics affect areas surrounding QoE could help aid developments in cloud gaming as an extremely viable process in the future.

Cloud computing is gaining growing interest from industry, organizations and the research community. The technology promises many advantages in terms of cost saving by allowing organizations and users to remotely gain access to a huge pool of data storage and processing power. However, migrating services to cloud computing introduce new challenges in performance and service quality. Quality of service (QoS) is and has been used as a means of monitoring cloud service performance. However, QoS is based on network parameters which do not necessarily reflect users' quality of experience. This paper discusses cloud computing quality of experience as perceived by the person using the cloud-based applications and services. We also review a selected current contribution to the quality of experience (QoE). We have expert reviews undertaken to identify six key performance indicators (PKIs). Based on these six KPIs, we sent our surveys, collected feedback and analyze data to confirm that QoE measurement can meet organizational goals, user satisfaction and stakeholders' requirements.

IEEE 802.11 wireless local area networks (WLANs) are shared networks, which use contention-based distributed coordination function (DCF) to share access to wireless medium among numerous wireless stations. The performance of the distributed coordination function mechanism mostly depends on the network load, number of wireless nodes and their data rates. The throughput unfairness, also known as performance anomaly is inherent in the very nature of mixed data rate Wi-Fi networks using the distributed coordination function. This unfairness exhibits itself through the fact that slow clients consume more airtime to transfer a given amount of data, leaving less airtime for fast clients. In this paper, we comprehensively examine the performance anomaly in multi-rate wireless networks using three approaches: experimental measurement, analytical modelling and simulation in Network Simulator v.3 (NS3). The results of our practical experiments benchmarking the throughput of a multi-rate 802.11ac wireless network clearly shows that even the recent wireless standards still suffer from airtime consumption unfairness. It was shown that even a single low-data rate station can decrease the throughput of high-data rate stations by 3–6 times. The simulation and analytical modelling confirm this finding with considerably high accuracy. Most of the theoretical models evaluating performance anomaly in Wi-Fi networks suggest that all stations get the same throughput independently of the used data rate. However, experimental and simulation results have demonstrated that despite a significant performance degradation high-speed stations still outperform stations with lower data rates once the difference between data rates becomes more significant. This is due to the better efficiency of the TCP protocol working over a fast wireless connection. It is also noteworthy that the throughput achieved by a station when it monopolistically uses the wireless media is considerably less than 50 % of its data rate due to significant overheads even in most recent Wi-Fi technologies. Mitigating performance anomaly in mixed-data rate WLANs requires a holistic approach that combines frame aggregation/fragmentation and adaption of data rates, contention window and other link-layer parameters.

IEEE 802.11 wireless local area networks (WLANs) are shared networks, which use contention-based distributed coordination function (DCF) to share access to wireless medium. The performance of DCF mechanism depends on the network load, number of wireless nodes and their data rates. The throughput unfairness also known as performance anomaly is inherent in the very nature of mixed-data rate Wi-Fi networks. This unfairness exhibits itself through the fact that slow clients consume more airtime to transfer a given amount of data, leaving less airtime for fast clients. In this paper, we evaluate the performance anomaly of mixed rate wireless networks and present the results of practical experiments benchmarking throughput of a mixed rate 802.11ac wireless network. These results clearly show that even the most recent wireless standard still suffers from the airtime consumption unfairness. At the end of the paper we analyse related works offering possible solutions and discuss our approach to evade performance degradation in mixed data rate Wi-Fi environments.

This paper discusses the adoption of cloud computing in education. It emphasizes the view that cloud computing is vital in the education sector because of its ability to reduce the overall costs of IT infrastructure installation and maintenance, improvement of efficiency, and the sharing of IT resources among students. The flexibility of cloud computing and its reliability makes it more appropriate for use in the educational environment. The Leeds Beckett University cloud project utilizes the SAS Educational Value-Added Assessment System, which gives lecturers the opportunity to deliver accurate content to students while monitoring their progress. Contemporary educational institutions must look forward to improve their research and education through cloud computing.