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Abstract-For a long time, traceroute measurements combined with alias resolution methods have been the sole way to collect Internet router level maps. Recently, a new approach has been introduced with the use of a multicast management tool, mrinfo, and a recursive probing scheme. In this paper, after analyzing advantages and drawbacks of probing approaches based on traceroute and mrinfo, we propose a hybrid discovery tool, MERLIN (MEasure the Router Level of the INternet), mixing mrinfo and traceroute probes. Using a central server controlling a set of distributed vantage points in order to increase the exploration coverage while limiting the probing redundancy, the purpose of MERLIN is to provide an accurate router level map inside a targeted Autonomous System (AS). MERLIN also takes advantage of alias resolution methods to reconnect scattered multicast components. To evaluate the performance of MERLIN, we report experimental results describing its efficiency in topology exploration and reconstruction of several ASes.

Cloud providers employ sophisticated virtualization techniques and strategies for sharing resources among a high number of largely uncoordinated and mutually untrusted customers. The shared networking environment, in particular, dictates the need for mechanisms to partition network resources among virtual machines. At the same time, the performance of applications deployed over these virtual machines may be heavily impacted by the performance of the underlying network, and therefore by such mechanisms. Nevertheless, due to security and commercial reasons, providers rarely provide detailed information on network organization, performance, and mechanisms employed to regulate it. In addition, the scientific literature only provides a blurring image of the network performance inside the cloud. The few available pioneer works marginally focus on this aspect, use different methodologies, operate in few limited scenarios, or report conflicting results.In this paper, we present a detailed analysis of the performance of the internal network of Amazon EC2, performed by adopting a non-cooperative experimental evaluation approach (i.e. not relying on provider support). Our aim is to provide a quantitative assessment of the networking performance as a function of the several variables available, such as geographic region, resource price or size. We propose a detailed methodology to perform this kind of analysis, which we believe is essential in a such complex and dynamic environment. During this analysis we have discovered and analyzed the limitations enforced by Amazon over customer traffic in terms of maximum throughput allowed. Thanks to our work it is possible to understand how the complex mechanisms enforced by the provider in order to manage its infrastructure impact the performance perceived by the cloud customers and potentially tamper with monitoring and controlling approaches previously proposed in literature. Leveraging our knowledge of the bandwidth-limiting mechanisms, we then present a clear picture of the maximum throughput achievable in Amazon EC2 network, shedding light on when and how such maximum can be achieved and at which cost.

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In the last years, network measurements have shown a growing interest in active probing techniques. Recent works propose approaches based on the IP prespecified timestamp option and consider its support to be enough for their purposes. On the other hand, other works found that IP options are usually filtered, poorly implemented, or not widely supported. In this paper, to shed light on this controversial topic, we investigate the responsiveness obtained targeting more than 1.7M IPs using several probes (ICMP, UDP, TCP, and SKIP), with and without the IP prespecified timestamp option. Our results show that: (i) the option has a significant impact on the responsiveness to the probes; (ii) a not−negligible amount of targeted addresses return several categories of non RFC−compliant replies; (iii) by considering only the RFC−compliant replies which preserve the option, the probes ranking by responsiveness considerably changes. Finally, we discuss the large−scale applicability of two proposed techniques based on the IP prespecified timestamp option.