Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites.

Xatu: Richer Neural Network Based Prediction for Video Streaming

The performance of Adaptive Bitrate (ABR) algorithms for video streaming depends on accurately predicting the download time of video chunks. Existing prediction approaches (i) assume chunk download times are dominated by network throughput; and (ii) apriori cluster sessions (e.g., based on ISP and CDN) and only learn from sessions in the same cluster. We make three contributions. First, through analysis of data from real-world video streaming sessions, we show (i) apriori clustering prevents learning from related clusters; and (ii) factors such as the Time to First Byte (TTFB) are key components of chunk download times but not easily incorporated into existing prediction approaches. Second, we propose Xatu, a new prediction approach that jointly learns a neural network sequence model with an interpretable automatic session clustering method. Xatu learns clustering rules across all sessions it deems relevant, and models sequences with multiple chunk-dependent features (e.g., TTFB) rather than just throughput. Third, evaluations using the above datasets and emulation experiments show that Xatu significantly improves prediction accuracies by 23.8% relative to CS2P (a state-of-the-art predictor). We show Xatu provides substantial performance benefits when integrated with multiple ABR algorithms including MPC (a well studied ABR algorithm), and FuguABR (a recent algorithm using stochastic control) relative to their default predictors (CS2P and a fully connected neural network respectively). Further, Xatu combined with MPC outperforms Pensieve, an ABR based on deep reinforcement learning.

Modelling song popularity as a contagious process

Popular songs are often said to be ‘contagious’, ‘infectious’ or ‘viral’. We find that download count time series for many popular songs resemble infectious disease epidemic curves. This paper suggests infectious disease transmission models could help clarify mechanisms that contribute to the ‘spread’ of song preferences and how these mechanisms underlie song popularity. We analysed data from MixRadio, comprising song downloads through Nokia cell phones in Great Britain from 2007 to 2014. We compared the ability of the standard susceptible–infectious–recovered (SIR) epidemic model and a phenomenological (spline) model to fit download time series of popular songs. We fitted these same models to simulated epidemic time series generated by the SIR model. Song downloads are captured better by the SIR model, to the same extent that actual SIR simulations are fitted better by the SIR model than by splines. This suggests that the social processes underlying song popularity are similar to those that drive infectious disease transmission. We draw conclusions about song popularity within specific genres based on estimated SIR parameters. In particular, we argue that faster spread of preferences for Electronica songs may reflect stronger connectivity of the ‘susceptible community’, compared with the larger and broader community that listens to more common genres.

Novel One Item Network Coding Vectors

<div>This paper presents a novel approach that greatly reduces the network coding coefficients overhead to a very tiny value that does not exceed 8 bytes. Consequently, other performance metrics, e.g., download time and throughput, are improved.</div><div><br></div>

Novel One Item Network Coding Vectors

<div>This paper presents a novel approach that greatly reduces the network coding coefficients overhead to a very tiny value that does not exceed 8 bytes. Consequently, other performance metrics, e.g., download time and throughput, are improved.</div><div><br></div>

Evaluation of MPTCP Schedulers in Diverse Scenarios

Multipath Transmission Control Protocol (MPTCP) is an extension of TCP meant for multihomed devices, which uses all the available interfaces for a single connection. MPTCP was evolved for Bandwidth aggregation and re silence to network failure. The wireless networks of multihomed devices are of different characteristics, when used together decreases Quality of Service (QoS). MPTCP schedulers tried to fill this gap with different approaches. In this paper we tried to study these schedulers in different network scenarios and came with the findings that to achieve good throughput and decrease download time, only fast paths are preferred.

Analysis of the Quality of Digital Library Services in DKI Jakarta

This research was conducted to analyze in depth how the quality of Jakarta digital library services in the Jakarta Provincial Library and Archives Service. The theory analysis is a theory of five dimensions of service quality consisting of :Tangible, Reliability, Responsiveness, Assurance, and Empathy. The method in this study useds a qualitative approach with descriptive methods Data collection techniques are done through observation, interviews and documentation. Data validity test uses Triangulation. The results showed that the quality of digital library services in the DKI Jakarta Provincial Library and Archives Service has not been fully said to be good. Collection of books in the Department of Library and Archives of the DKI Jakarta Provincial Government is incomplete, iJakarta applications sometimes experience errors/bugs, other than that the download time of books to be read is relatively long, can reach 5 minutes per book, Inadequate complaints channel for users / users who want to convey the problem,Handling of complaints is still very dependent on PT.Aksaramaya. This can hinder readers/visitors who need a quick complaint handling because the Library and Archives Service must first coordinate with PT.Aksaramaya and There is no audio book facility that should be available for persons with disabilities from the blind group.

Analysis of Web Components in Website Design

The main objective of research article is to measure the download performance of website. In the methodology various elements are taken into consideration viz., HTML tags, Objects, Images, CSS, Scripting, Website size. The download time of website is measured in ranking grades viz. A, B, C, D, E, F etc. The website developer needs to observe the performance of various elements and optimum download time into order to improve the performance of website design.