Web browsing optimization over 2.5G and 3G: end-to-end mechanisms vs. usage of performance enhancing proxies

Published version on Wiley's platform: https://onlinelibrary.wiley.com/doi/abs/10.1002/wcm.4562.5 Generation (2.5G) and Third Generation (3G) cellular wireless networks allow mobile Internet access withbearers specifically designed for data communications. However, Internet protocols under-utilize wireless widearea network (WWAN) link resources, mainly due to large round trip times (RTTs) and request–reply protocolpatterns. Web browsing is a popular service that suffers significant performance degradation over 2.5G and 3G. Inthis paper, we review and compare the two main approaches for improving web browsing performance over wirelesslinks: (i) using adequate end-to-end parameters and mechanisms and (ii) interposing a performance enhancingproxy (PEP) between the wireless and wired parts. We conclude that PEPs are currently the only feasible way forsignificantly optimizing web browsing behavior over 2.5G and 3G. In addition, we evaluate the two main currentcommercial PEPs over live general packet radio service (GPRS) and universal mobile telecommunications system(UMTS) networks. The results show that PEPs can lead to near-ideal web browsing performance in certain scenarios.Postprint (published version

Optimized mobile thin clients through a MPEG-4 BiFS semantic remote display framework

According to the thin client computing principle, the user interface is physically separated from the application logic. In practice only a viewer component is executed on the client device, rendering the display updates received from the distant application server and capturing the user interaction. Existing remote display frameworks are not optimized to encode the complex scenes of modern applications, which are composed of objects with very diverse graphical characteristics. In order to tackle this challenge, we propose to transfer to the client, in addition to the binary encoded objects, semantic information about the characteristics of each object. Through this semantic knowledge, the client is enabled to react autonomously on user input and does not have to wait for the display update from the server. Resulting in a reduction of the interaction latency and a mitigation of the bursty remote display traffic pattern, the presented framework is of particular interest in a wireless context, where the bandwidth is limited and expensive. In this paper, we describe a generic architecture of a semantic remote display framework. Furthermore, we have developed a prototype using the MPEG-4 Binary Format for Scenes to convey the semantic information to the client. We experimentally compare the bandwidth consumption of MPEG-4 BiFS with existing, non-semantic, remote display frameworks. In a text editing scenario, we realize an average reduction of 23% of the data peaks that are observed in remote display protocol traffic

Metrics for the Adaptation of Site Structure

This paper presents an overview of metrics for web site structure and user navigation paths. Particular attention will be paid to the question what these metrics really say about a site and its usage, and how they can be applied for adapting navigation support to the mobile context

A machine learning-based framework for preventing video freezes in HTTP adaptive streaming

HTTP Adaptive Streaming (HAS) represents the dominant technology to deliver videos over the Internet, due to its ability to adapt the video quality to the available bandwidth. Despite that, HAS clients can still suffer from freezes in the video playout, the main factor influencing users' Quality of Experience (QoE). To reduce video freezes, we propose a network-based framework, where a network controller prioritizes the delivery of particular video segments to prevent freezes at the clients. This framework is based on OpenFlow, a widely adopted protocol to implement the software-defined networking principle. The main element of the controller is a Machine Learning (ML) engine based on the random undersampling boosting algorithm and fuzzy logic, which can detect when a client is close to a freeze and drive the network prioritization to avoid it. This decision is based on measurements collected from the network nodes only, without any knowledge on the streamed videos or on the clients' characteristics. In this paper, we detail the design of the proposed ML-based framework and compare its performance with other benchmarking HAS solutions, under various video streaming scenarios. Particularly, we show through extensive experimentation that the proposed approach can reduce video freezes and freeze time with about 65% and 45% respectively, when compared to benchmarking algorithms. These results represent a major improvement for the QoE of the users watching multimedia content online

Integrating E-Commerce and Data Mining: Architecture and Challenges

We show that the e-commerce domain can provide all the right ingredients for successful data mining and claim that it is a killer domain for data mining. We describe an integrated architecture, based on our expe-rience at Blue Martini Software, for supporting this integration. The architecture can dramatically reduce the pre-processing, cleaning, and data understanding effort often documented to take 80% of the time in knowledge discovery projects. We emphasize the need for data collection at the application server layer (not the web server) in order to support logging of data and metadata that is essential to the discovery process. We describe the data transformation bridges required from the transaction processing systems and customer event streams (e.g., clickstreams) to the data warehouse. We detail the mining workbench, which needs to provide multiple views of the data through reporting, data mining algorithms, visualization, and OLAP. We con-clude with a set of challenges.Comment: KDD workshop: WebKDD 200

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

A Latency-Determining/User Directed Firefox Browser Extension

As the World Wide Web continues to evolve as the preferred choice for information access it is critical that its utility to the user remains. Latency as a result of network congestion, bandwidth availability, server processing delays, embedded objects, and transmission delays and errors can impact the utility of the web browser application. To improve the overall user experience the application needs to not only provide feedback to the end user about the latency of links that are available but to also provide them controls in the retrieval of the web content. This thesis presents a background and related work relating to latency and web optimization techniques to reduce this latency and then introduce an improvement to the ``latency aware" Mozilla Firefox extension which was originally developed by Sterbenz et. al., in 2002. This these describes the architecture and prototype implementation, followed with an analysis of its effectiveness to predict latency and future wor