Ítalo Cunha

Analyzing client interactivity in streaming media

This paper provides an extensive analysis of pre-stored streaming media workloads, focusing on the client interactive behavior. We analyze four workloads that fall into three different domains, namely, education, entertainment video and entertainment audio. Our main goals are: (a) to identify qualitative similarities and differences in the typical client behavior for the three workload classes and (b) to provide data for generating realistic synthetic workloads.

Self-Adaptive Capacity Management for Multi-Tier Virtualized Environments

This paper addresses the problem of hosting multiple applications on a providers virtualized multi-tier infrastructure. Building from a previous model, we design a new self-adaptive capacity management framework, which combines a two-level SLA-driven pricing model, an optimization model and an analytical queuing-based performance model to maximize the providers business objective. Our main contributions are the more accurate multi-queue performance model, which captures application specific bottlenecks and the parallelism inherent to multi-tier platforms, as well as the solution of the extended and much more complex optimization model. Our approach is evaluated via simulation with synthetic as well as realistic workloads, in various scenarios. The results show that our solution is significantly more cost-effective, in terms of the providers achieved revenues, than the approach it is built upon, which uses a single-resource performance model. It also significantly outperforms a multi-tier static allocation strategy for heavy and unbalanced workloads. Finally, preliminary experiments assess the applicability of our framework to virtualized environments subjected to capacity variations caused by the processing of management and security-related tasks.

LIFEGUARD: practical repair of persistent route failures

The Internet was designed to always find a route if there is a policy-compliant path. However, in many cases, connectivity is disrupted despite the existence of an underlying valid path. The research community has focused on short-term outages that occur during route convergence. There has been less progress on addressing avoidable long-lasting outages. Our measurements show that long-lasting events contribute significantly to overall unavailability. To address these problems, we develop LIFEGUARD, a system for automatic failure localization and remediation. LIFEGUARD uses active measurements and a historical path atlas to locate faults, even in the presence of asymmetric paths and failures. Given the ability to locate faults, we argue that the Internet protocols should allow edge ISPs to steer traffic to them around failures, without requiring the involvement of the network causing the failure. Although the Internet does not explicitly support this functionality today, we show how to approximate it using carefully crafted BGP messages. LIFEGUARD employs a set of techniques to reroute around failures with low impact on working routes. Deploying LIFEGUARD on the Internet, we find that it can effectively route traffic around an AS without causing widespread disruption.

Scalable media streaming to interactive users

Recently, a number of scalable stream sharing protocols have been proposed with the promise of great reductions in the server and network bandwidth required for delivering popular media content. Although the scalability of these protocols has been evaluated mostly for sequential user accesses, a high degree of interactivity has been observed in the accesses to several real media servers. Moreover, some studies have indicated that user interactivity can severely penalize the scalability of stream sharing protocols.This paper investigates alternative mechanisms for scalable streaming to interactive users. We first identify a set of workload aspects that are determinant to the scalability of classes of streaming protocols. Using real workloads and a new interactive media workload generator, we build a rich set of realistic synthetic workloads. We evaluate Bandwidth Skimming and Patching, two state-of-the-art streaming protocols, covering, with our workloads, a larger region of the design space than previous work. Finally, we propose and evaluate five optimizations to Bandwidth Skimming, the most scalable of the two protocols. Our best optimization reduces the average server bandwidth required for interactive workloads in up to 54%, for unlimited client buffers, and 29%, if buffers are constrained to 25% of media size.

Measuring and characterizing end-to-end route dynamics in the presence of load balancing

Since Paxsons study over ten years ago, the Internet has changed considerably. In particular, routers often perform load balancing. Disambiguating routing changes from load balancing using traceroute-like probing requires a large number of probes. Our first contribution is FastMapping, a probing method that exploits load balancing characteristics to reduce the number of probes needed to measure accurate route dynamics. Our second contribution is to reappraise Paxsons results using datasets with high-frequency route measurements and complete load balancing information. Our analysis shows that, after removing dynamics due to load balancing, Paxsons observations on route prevalence and persistence still hold.

Predicting and tracking internet path changes

This paper investigates to what extent it is possible to use traceroute-style probing for accurately tracking Internet path changes. When the number of paths is large, the usual traceroute based approach misses many path changes because it probes all paths equally. Based on empirical observations, we argue that monitors can optimize probing according to the likelihood of path changes. We design a simple predictor of path changes using a nearest neighbor model. Although predicting path changes is not very accurate, we show that it can be used to improve probe targeting. Our path tracking method, called DTrack, detects up to two times more path changes than traditional probing, with lower detection delay, as well as providing complete load-balancer information.

Investigating Interdomain Routing Policies in the Wild

Models of Internet routing are critical for studies of Internet security, reliability and evolution, which often rely on simulations of the Internets routing system. Accurate models are difficult to build and suffer from a dearth of ground truth data, as ISPs often treat their connectivity and routing policies as trade secrets. In this environment, researchers rely on a number of simplifying assumptions and models proposed over a decade ago, which are widely criticized for their inability to capture routing policies employed in practice. In this study we put Internet topologies and models under the microscope to understand where they fail to capture real routing behavior. We measure data plane paths from thousands of vantage points, located in eyeball networks around the globe, and find that between 14-35% of routing decisions are not explained by existing models. We then investigate these cases, and identify root causes such as selective prefix announcement, misclassification of undersea cables, and geographic constraints. Our work highlights the need for models that address such cases, and motivates the need for further investigation of evolving Internet connectivity.

AoT: Authentication and Access Control for the Entire IoT Device Life-Cycle

The consumer electronics industry is witnessing a surge in Internet of Things (IoT) devices, ranging from mundane artifacts to complex biosensors connected across disparate networks. As the demand for IoT devices grows, the need for stronger authentication and access control mechanisms is greater than ever. Legacy authentication and access control mechanisms do not meet the growing needs of IoT. In particular, there is a dire need for a holistic authentication mechanism throughout the IoT device life-cycle, namely from the manufacturing to the retirement of the device. As a plausible solution, we present Authentication of Things (AoT), a suite of protocols that incorporate authentication and access control during the entire IoT device life span. Primarily, AoT relies on Identity- and Attribute-Based Cryptography to cryptographically enforce Attribute-Based Access Control (ABAC). Additionally, AoT facilitates secure (in terms of stronger authentication) wireless interoperability of new and guest devices in a seamless manner. To validate our solution, we have developed AoT for Android smartphones like the LG G4 and evaluated all the cryptographic primitives over more constrained devices like the Intel Edison and the Arduino Due. This included the implementation of an Attribute-Based Signature (ABS) scheme. Our results indicate AoT ranges from highly efficient on resource-rich devices to affordable on resource-constrained IoT-like devices. Typically, an ABS generation takes around 27 ms on the LG G4, 282 ms on the Intel Edison, and 1.5 s on the Arduino Due.

End-to-end authentication in Under-Water Sensor Networks

Under-Water Wireless Sensor Networks (UWSNs) are a particular class of Wireless Sensor Networks (WSNs) in which sensors are located, as the name suggests, underwater. Applications of UWSNs range from oceanographic data collection to disaster prevention. UWSNs are vulnerable to attacks and because of their idiosyncrasies, security solutions for ground WSNs might not be applicable underwater. As a result, there is a need for mechanisms exclusively tailored to underwater environments. In this work we address the problem of authentication in UWSNs. We evaluate energy costs for different digital signature schemes for end-to-end authentication and discuss the tradeoffs involved in a number of scenarios. Our results show that schemes that perform well in ground WSN do not necessarily do well in UWSNs; and shed light on characteristics of a digital signature scheme that make them particularly suited to underwater networks.

DTRACK: a system to predict and track internet path changes

In this paper, we implement and evaluate a system that predicts and tracks Internet path changes to maintain an up-to-date network topology. Based on empirical observations, we claim that monitors can enhance probing according to the likelihood of path changes. We design a simple predictor of path changes and show that it can be used to enhance probe targeting. Our path tracking system, called DTRACK, focuses probes on unstable paths and spreads probes over time to minimize the chances of missing path changes. Our evaluations of DTRACK with trace-driven simulations and with a prototype show that DTRACK can detect up to three times more path changes than traditional trace-route-based topology mapping techniques.