Measuring Internet performance for home users can provide useful information for improving network performance. Such measurements typically require users to install special software on their machines, a major impediment to use. To overcome this impediment, we designed and implemented several scripting techniques to predict Internet performance within the tightly constrained sandbox environment of a Web browser. Our techniques are integrated into a Web site project called "How's My Network" that provides performance predictions for common Internet activities, with this thesis concentrating on the performance of online news, social networks, and online shopping. We started our approach by characterizing news sites to understand their structures. After that, we designed models to predict the user's performance for reading news online. We then implement these models using Javascript and evaluate their results. We find out that news sites share common characteristics in their structures with outliers for some. Predicting the page load time according to number objects coming from dominant domain, the one providing the most number of objects, gives more accurate predictions than using total number of objects across all domains. The contributions of this work include the design of new approaches for predicting Web browser performance, and the implementation and evaluation of the effectiveness of our approach to predict Web browser performance.

Critical networked services established between service provider and customers are expected to operate respecting Service Level Agreements (SLAs). An interesting possibility to monitor such SLAs is using active measurement mechanisms. However, these mechanisms are expensive in terms of network devices resource consumption and also increase the network load because of the injected traffic. In addition, if the number of SLA violations in a given time is higher than the number of available measurement sessions (common place in large and complex network infrastructures), certainly some violations will be missed. The current best practice, the observation of just a subset of network destinations driven by human administrators expertise, is error prone, does not scale well, and is ineffective on dynamic network conditions. This practice can lead to SLA violations being missed, which invariably affect the performance of several applications. In the present thesis, we advocated the use of Peer-to-Peer (P2P) technology to improve the detection of SLA violations. Such use is described using principles to control active measurement mechanisms. These principles are accomplished through strategies to activate measurement sessions. In this context, the major contributions of this thesis are: i) An approach to improve the detection of SLA violations through the steering of the activation of active measurement sessions using local and remote past service level measurement results and resource utilization constraints; ii) The concept of destination rank as an approach to autonomically prioritize destinations for the activation of active measurement sessions using destination scores; iii) The concept of correlated peers to enable the autonomic provisioning of a P2P measurement overlay for the exchange of relevant active measurement results; iv) The concept of virtual measurement sessions to enable the sharing of measurement results among correlated peers in order to save network devices resources and to improve SLA monitoring coverage; v) The definition of decentralized strategies to steer the activation of active measurement sessions using P2P principles. The method used on the investigation started with the execution of literature reviews on the networkwide control of measurement mechanisms and the employment of P2P technology on network management. After that, the proposed principles to control active measurement mechanisms and the strategies to activate measurement sessions were described. Finally, experiments were performed to evaluate the performance as well as to highlight properties of such principles and strategies. The findings showed properties which improve the detection of SLA violations in terms of the number of detected violations and the adaptivity to network dynamics. We expect that such findings can lead to better SLA monitoring tools and methods.

Critical networked services established between service provider and customers are expected to operate respecting Service Level Agreements (SLAs). An interesting possibility to monitor such SLAs is using active measurement mechanisms. However, these mechanisms are expensive in terms of network devices resource consumption and also increase the network load because of the injected traffic. In addition, if the number of SLA violations in a given time is higher than the number of available measurement sessions (common place in large and complex network infrastructures), certainly some violations will be missed. The current best practice, the observation of just a subset of network destinations driven by human administrators expertise, is error prone, does not scale well, and is ineffective on dynamic network conditions. This practice can lead to SLA violations being missed, which invariably affect the performance of several applications. In the present thesis, we advocated the use of Peer-to-Peer (P2P) technology to improve the detection of SLA violations. Such use is described using principles to control active measurement mechanisms. These principles are accomplished through strategies to activate measurement sessions. In this context, the major contributions of this thesis are: i) An approach to improve the detection of SLA violations through the steering of the activation of active measurement sessions using local and remote past service level measurement results and resource utilization constraints; ii) The concept of destination rank as an approach to autonomically prioritize destinations for the activation of active measurement sessions using destination scores; iii) The concept of correlated peers to enable the autonomic provisioning of a P2P measurement overlay for the exchange of relevant active measurement results; iv) The concept of virtual measurement sessions to enable the sharing of measurement results among correlated peers in order to save network devices resources and to improve SLA monitoring coverage; v) The definition of decentralized strategies to steer the activation of active measurement sessions using P2P principles. The method used on the investigation started with the execution of literature reviews on the networkwide control of measurement mechanisms and the employment of P2P technology on network management. After that, the proposed principles to control active measurement mechanisms and the strategies to activate measurement sessions were described. Finally, experiments were performed to evaluate the performance as well as to highlight properties of such principles and strategies. The findings showed properties which improve the detection of SLA violations in terms of the number of detected violations and the adaptivity to network dynamics. We expect that such findings can lead to better SLA monitoring tools and methods.

Critical networked services established between service provider and customers are expected to operate respecting Service Level Agreements (SLAs). An interesting possibility to monitor such SLAs is using active measurement mechanisms. However, these mechanisms are expensive in terms of network devices resource consumption and also increase the network load because of the injected traffic. In addition, if the number of SLA violations in a given time is higher than the number of available measurement sessions (common place in large and complex network infrastructures), certainly some violations will be missed. The current best practice, the observation of just a subset of network destinations driven by human administrators expertise, is error prone, does not scale well, and is ineffective on dynamic network conditions. This practice can lead to SLA violations being missed, which invariably affect the performance of several applications. In the present thesis, we advocated the use of Peer-to-Peer (P2P) technology to improve the detection of SLA violations. Such use is described using principles to control active measurement mechanisms. These principles are accomplished through strategies to activate measurement sessions. In this context, the major contributions of this thesis are: i) An approach to improve the detection of SLA violations through the steering of the activation of active measurement sessions using local and remote past service level measurement results and resource utilization constraints; ii) The concept of destination rank as an approach to autonomically prioritize destinations for the activation of active measurement sessions using destination scores; iii) The concept of correlated peers to enable the autonomic provisioning of a P2P measurement overlay for the exchange of relevant active measurement results; iv) The concept of virtual measurement sessions to enable the sharing of measurement results among correlated peers in order to save network devices resources and to improve SLA monitoring coverage; v) The definition of decentralized strategies to steer the activation of active measurement sessions using P2P principles. The method used on the investigation started with the execution of literature reviews on the networkwide control of measurement mechanisms and the employment of P2P technology on network management. After that, the proposed principles to control active measurement mechanisms and the strategies to activate measurement sessions were described. Finally, experiments were performed to evaluate the performance as well as to highlight properties of such principles and strategies. The findings showed properties which improve the detection of SLA violations in terms of the number of detected violations and the adaptivity to network dynamics. We expect that such findings can lead to better SLA monitoring tools and methods.