Content distribution systems have traditionally adopted one of two architectures: infrastructure-based content delivery networks (CDNs), in which clients download content from dedicated, centrally managed servers, and peer-topeer CDNs, in which clients download content from each other. The advantages and disadvantages of each architecture have been studied in great detail. Recently, hybrid, or "peer-assisted", CDNs have emerged, which combine elements from both architectures. The properties of such systems, however, are not as well understood.In this paper, we discuss the potential risks and benefits of peer-assisted CDNs, and we study one specific instance, Akamai's NetSession system, to examine the impact of these risks and benefits in practice. NetSession is a mature system that has been operating commercially since 2010 and currently has more than 25 million users in 239 countries and territories. Our results show that NetSession can deliver several of the key benefits of both infrastructure-based and peer-to-peer CDNs-for instance, it can offload 70-80% of the traffic to the peers without a corresponding loss of performance or reliabilityand that the risks can be managed well.This suggests that hybrid designs may be an attractive option for future CDNs.

Abstract-Coverage is a fundamental problem in Wireless Sensor Networks (WSNs). Existing studies on this topic focus on 2D ideal plane coverage and 3D full space coverage. The 3D surface of a targeted Field of Interest is complex in many real world applications; and yet, existing studies on coverage do not produce practical results. In this paper, we propose a new coverage model called surface coverage. In surface coverage, the targeted Field of Interest is a complex surface in 3D space and sensors can be deployed only on the surface. We show that existing 2D plane coverage is merely a special case of surface coverage. Simulations point out that existing sensor deployment schemes for a 2D plane cannot be directly applied to surface coverage cases. In this paper, we target two problems assuming cases of surface coverage to be true. One, under stochastic deployment, how many sensors are needed to reach a certain expected coverage ratio? Two, if sensor deployment can be planned, what is the optimal deployment strategy with guaranteed full coverage with the least number of sensors? We show that the latter problem is NP-complete and propose three approximation algorithms. We further prove that these algorithms have a provable approximation ratio. We also conduct comprehensive simulations to evaluate the performance of the proposed algorithms.

When debugging a distributed system, it is sometimes necessary to explain the absence of an event-for instance, why a certain route is not available, or why a certain packet did not arrive. Existing debuggers offer some support for explaining the presence of events, usually by providing the equivalent of a backtrace in conventional debuggers, but they are not very good at answering "Why not?" questions: there is simply no starting point for a possible backtrace. In this paper, we show that the concept of negative provenance can be used to explain the absence of events in distributed systems. Negative provenance relies on counterfactual reasoning to identify the conditions under which the missing event could have occurred. We define a formal model of negative provenance for distributed systems, and we present the design of a system called Y! that tracks both positive and negative provenance and can use them to answer diagnostic queries. We describe how we have used Y! to debug several realistic problems in two application domains: softwaredefined networks and BGP interdomain routing. Results from our experimental evaluation show that the overhead of Y! is moderate.

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