Internet route survey systems such as Ark and IPRS have typically been evaluated on how well they uncover internet topology (nodes and links from consecutive traceroutehops). We present a new metric, the forwarding score, better adapted to assessing how these systems capture routing behavior, and compare this metric over eight days' data.

The EdgeNet software is free, open-source, liberally licensed code that extends the Kubernetes container orchestration system to the edge cloud. We use this code to run the EdgeNet testbed, an internet-scale edge cloud for distributed systems researchers. This demonstration showcases three features of EdgeNet: its multitenancy model, its multi-provider aspect, and its geographically-based selective deployment capability. Multitenancy allows multiple teams to use the platform concurrently; being multi-provider, independent contributors can make nodes available to the platform; and selective deployment facilitates location-based placement of software. Under our guidance, demo participants invoke the Kubernetes command-line interface to use the testbed. In so doing, they get experience with the testbed, which they can continue to use afterwards. They also gain insight into how the demonstrated features are useful for edge cloud container deployment in general. Participants who volunteer to help EdgeNet nodes receive Odroid devices to host in their homes or workplaces.

EdgeNet is the prototype of a scalable, sustainable general-purpose testbed for very wide area distributed systems and extremely low-latency distributed services. In this, it is aimed at the same experimenters and systems that formed the core usage of previous, highly-successful wide-area testbeds such as PlanetLab [1], G-Lab [2], V-Node [5], GENI [4], and SAVI [3], and it incorporates many of the features that characterized those previous testbeds. EdgeNet's goal is to achieve the usability and research value of the previous generations of wide area testbed, whilst offering radical improvements in the scalability and sustainability of those systems. It achieves this scalability and sustainability through a strategy of using industry-standard open-source software as the basis of its software stack, and by a strategy of hardwarefree, bottom-up, site-driven deployment. EdgeNet follows the Seattle [6] and PlanetIgnite [9] strategy of permitting sites to join the testbed with purely local action.

Use of IP-layer anycast has increased in the last few years beyond the DNS realm. Existing measurement techniques to identify and enumerate anycast replicas exploit specifics of the DNS protocol, which limits their applicability to this particular service. In this paper, we propose and thoroughly validate a protocol-agnostic technique for anycast replicas discovery and geolocation. Furthermore, we also provide the community with open-source software and data sets allowing others to replicate our experimental results, potentially facilitating the development of new techniques such as ours. In particular, our proposed method achieves thorough enumeration and city-level geolocalization of anycast instances from a set of known vantage points. The algorithm features an iterative workflow, pipelining enumeration (an optimization problem using latency as an input), and geolocalization (a classification problem using side channel information, such as city population) of anycast replicas. Results of a thorough validation campaign show our algorithm to be robust to measurement noise, and very lightweight as it requires only a handful of latency measurements.

This paper provides a comprehensive picture of IP-layer anycast adoption in the current Internet. We carry on multiple IPv4 anycast censuses, relying on latency measurement from PlanetLab. Next, we leverage our novel technique for anycast detection, enumeration, and geolocation [17] to quantify anycast adoption in the Internet. Our technique is scalable and, unlike previous efforts that are bound to exploiting DNS, is protocol-agnostic. Our results show that major Internet companies (including tier-1 ISPs, over-the-top operators, Cloud providers and equipment vendors) use anycast: we find that a broad range of TCP services are offered over anycast, the most popular of which include HTTP and HTTPS by anycast CDNs that serve websites from the top-100k Alexa list. Additionally, we complement our characterization of IPv4 anycast with a description of the challenges we faced to collect and analyze large-scale delay measurements, and the lessons learned.

Use of IP-layer anycast has increased in the last few years: once relegated to DNS root and top-level domain servers, anycast is now commonly used to assist distribution of general purpose content by CDN providers. Yet, the measurement techniques for discovering anycast replicas have been designed around DNS, limiting their usefulness to this particular service. This raises the need for protocol agnostic methodologies, that should additionally be as lightweight as possible in order to scale up anycast service discovery. This is precisely the aim of this paper, which proposes a new method for exhaustive and accurate enumeration and city-level geolocation of anycast instances, requiring only a handful of latency measurements from a set of known vantage points. Our method exploits an iterative workflow that enumerates (an optimization problem) and geolocates (a classification problem) anycast replicas. We thoroughly validate our methodology on available ground truth (several DNS root servers), using multiple measurement infrastructures (PlanetLab, RIPE), obtaining extremely accurate results (even with simple algorithms, that we compare with the global optimum), that we make available to the scientific community. Compared to the state of the art work that appeared in INFOCOM 2013 and IMC 2013, our technique (i) is not bound to a specific protocol, (ii) requires 1000 times fewer vantage points, not only (iii) achieves over 50% recall but also (iv) accurately identifies the city-level geolocation for over 78% of the enumerated servers, with (v) a mean geolocation error of 361 km for all enumerated servers.

Gathering the required measurements to produce accurate results for mobile communications and wireless networking protocols, technologies and applications, relies on the use of expensive experimental computer networking facilities. Until very recently, large-scale testbed facilities have existed in separate silos, each with its own authentication mechanisms and experiment support tools. There lacked a viable federation model that reconciled the challenges posed by how to provide a single entry point to access heterogeneous and distributed resources, and how to federate these resources that are under the control of multiple authorities. The OneLab experimental facility, which came online in 2014, realizes this model, making a set of world-class testbeds freely available to researchers through a unique credential for each user and a common set of tools. We allow users to deploy innovative experiments across our federated platforms that include the embedded object testbeds of FIT IoT-Lab, the cognitive radio testbed of FIT CorteXlab, the wireless testbeds of NITOS-Lab, and the internet overlay testbed PlanetLab Europe (PLE), which together provide thousands of nodes for experimentation. Also federated under OneLab are the FUSECO Playground, which includes cloud, M2M, SDN, and mobile broadband; w-iLab.t wireless facilities; and the Virtual Wall testbed of wired networks and applications. Our demo describes the resources offered by the OneLab platforms, and illustrates how any member of the MobiCom community can create an account and start using these platforms today to deploy experiments for mobile and wireless testing.

“Bufferbloat” is the growth in buffer size that has led Internet delays to occasionally exceed the light propagation delay from the Earth to the Moon. Manufacturers have built in large buffers to prevent losses on Wi-Fi, cable and ADSL links. But the combination of some links' limited bandwidth with TCP's tendency to saturate that bandwidth results in excessive queuing delays. In response, new congestion control protocols such as BitTorrent's uTP/LEDBAT aim at explicitly limiting the delay that they add at the bottleneck link. This work proposes a methodology to monitor the upstream queuing delay experienced by remote hosts, both those using LEDBAT, through LEDBAT's native one-way delay measurements, and those using TCP, through the Timestamp Option. We report preliminary findings on bufferbloat-related queuing delays on an Internet measurement campaign involving a few thousand hosts.

Nowadays, due to excessive queuing, Internet delays grow sometimes as large as the propagation delay from moon to earth - for which the bufferbloat term was recently coined. Some points to active queue management (AQM) as its solution, others propose end-to-end congestion control techniques - like BitTorrent that recently replaced TCP with the LEDBAT transport protocol. In this demo, we implement a methodology to monitor the upstream queuing delay experienced by remote hosts, both those using LEDBAT, through LEDBAT's native one-way delay measurements, and those using TCP, through the timestamp option. By actively taking part into torrent downloads as leechers, our software is able to infer (and visualize) the amount of access delay suffered by the remote peers.

Tools to measure Internet properties usually assume the existence of just one single path from a source to a destination. However, load-balancing capabilities, which create multiple active paths between two end-hosts, are available in most contemporary routers. This paper extends Paris trace route and proposes an extensive characterization of multipath routing in the Internet. We use Paris traceroute from RON and PlanetLab nodes to collect various datasets in 2007 and 2009. Our results show that the traditional concept of a single network path between hosts no longer holds. For instance, 39% of the source-destination pairs in our 2007 traces traverse a load balancer. This fraction increases to 72% if we consider the paths between a source and a destination network. In 2009, we notice a consolidation of per-flow and per-destination techniques and confirm that per-packet load balancing is rare.

International audience

Traceroute is widely used to report the path packets take between two Internet hosts, but the widespread deployment of load balancing routers breaks a basic assumption - that there is only a single such path. We specify an adaptive, stochastic probing algorithm, the multipath detection algorithm (MDA), to report all paths that probes can follow between a source and a destination. We establish the foundations of, and show how to calculate, rigorous statistical guarantees for the discovery of the entire multipath route. We explore algorithm cost/guarantee tradeoffs in real experiments and show the inadequacy of the classic practice of sending three probes per hop.

We propose in this work a single copy and multi-hop opportunistic routing scheme for sparse delay tolerant networks (DTNs). The scheme uses as only input the estimates of the average inter-contact times between the nodes in the network. Defined as the fixed point of a recursive process, it aims at minimizing delivery time in case of independent exponential pairwise inter-contacts. The two properties of loop-free forwarding and polynomial convergence make the scheme workable for routing in DTNs. The routing performances of the scheme are evaluated on three publicly available reference data sets. Comparisons with well known single-copy schemes, including MED and thetwohoprelay strategy, consistently demonstrate improvements for both delivery ratio and delay.

Tools to measure internet properties usually assume the existence of a single path from a source to a destination. However, load-balancing capabilities, which create multiple active paths between two end-hosts, are available in most contemporary routers. This paper proposes a methodology to identify load-balancing routers and characterize load-balanced paths. We enhance our traceroute-like tool, called Paris traceroute, to find all paths between a pair of hosts, and use it from 15 sources to over 68 thousand destinations. Our results show that the traditional concept of a single network path between hosts no longer holds. For instance, 39% of the source-destination pairs in our traces traverse a load balancer. Furthermore, this fraction increases to 70% if we consider the paths between a source and a destination network.

Abstract Because a delay‐tolerant network (DTN) can often be partitioned, routing is a challenge. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high‐dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and a large‐scale evaluation of routing schemes using MobySpace by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visits of nodes to each possible location. We present simulation results for single‐copy and multi‐copy routing strategies that use MobySpace as a means to route bundles or to control flooding. We show that routing based on MobySpace can achieve good performance compared to a number of common algorithms. Copyright © 2007 John Wiley & Sons, Ltd.

Traceroute [2] is used to learn the path between two machines in the internet. Uses range from the diagnosis of network problems to the assemblage of internet maps. Unfortunately, traceroute measurements can be inaccurate and incomplete when the measured route traverses a load balancer.

Where distributed agents must share voluminous set membership information, Bloom filters provide a compact, though lossy, way for them to do so. Numerous recent networking papers have examined the trade-offs between the bandwidth consumed by the transmission of Bloom filters, and the error rate, which takes the form of false positives, and which rises the more the filters are compressed. In this paper, we introduce the retouched Bloom filter (RBF), an extension that makes the Bloom filter more flexible by permitting the removal of selected false positives at the expense of generating random false negatives. We analytically show that RBFs created through a random process maintain an overall error rate, expressed as a combination of the false positive rate and the false negative rate, that is equal to the false positive rate of the corresponding Bloom filters. We further provide some simple heuristics that decrease the false positive rate more than than the corresponding increase in the false negative rate, when creating RBFs. Finally, we demonstrate the advantages of an RBF over a Bloom filter in a distributed network topology measurement application, where information about large stop sets must be shared among route tracing monitors.

Traceroute is widely used, from the diagnosis of network problems to the assemblage of internet maps. However, there are a few serious problems with this tool, in particular due to the presence of load balancing routers in the network. This paper describes a number of anomalies that arise in nearly all traceroute-based measurements. We categorize them as "loops", "cycles", and "diamonds". We provide a new publicly-available traceroute, called Paris traceroute, which controls packet header contents to obtain a more precise picture of the actual routes that packets follow. This new tool allows us to find conclusive explanations for some of the anomalies, and to suggest possible causes for others.

Because a delay tolerant network (DTN) can often be partitioned, routing is a challenge. However, routing benefits considerably if one can take advantage of knowledge concerning node mobility. This paper addresses this problem with a generic algorithm based on the use of a high-dimensional Euclidean space, that we call MobySpace, constructed upon nodes' mobility patterns. We provide here an analysis and a large scale evaluation of this routing scheme in the context of ambient networking by replaying real mobility traces. The specific MobySpace evaluated is based on the frequency of visits of nodes to each possible location. We show that routing based on MobySpace can achieve good performance compared to that of a number of standard algorithms, especially for nodes that are present in the network a large portion of the time. We determine that the degree of homogeneity of node mobility patterns has a high impact on routing. And finally, we study the ability of nodes to learn their own mobility patterns.

Topology discovery systems are starting to be introduced in the form of easily and widely deployed software. Unfortunately, the research community has not examined the problem of how to perform such measurements efficiently and in a network-friendly manner. This paper describes several contributions towards that end. These were first presented in the proceedings of ACM Sigmetrics 2005. We show that standard topology discovery methods (e.g., skitter) are quite inefficient, repeatedly probing the same interfaces. This is a concern, because when scaled up, such methods will generate so much traffic that they will begin to resemble distributed denial-of-service attacks. We propose two metrics focusing on redundancy in probing and show that both are important. We also propose and evaluate Doubletree, an algorithm that strongly reduces redundancy, while maintaining nearly the same level of node and link coverage. The key ideas are to exploit the tree-like structure of routes to and from a single point in order to guide when to stop probing, and to probe each path by starting near its midpoint. Following the Sigmetrics work, we implemented Doubletree, and deployed it in a real-network environment. This paper describes that implementation, as well as preliminary favorable results

There is a growing interest in discovery of internet topology at the interface level. A new generation of highly distributed measurement systems is currently being deployed. Unfortunately, the research community has not examined the problem of how to perform such measurements efficiently and in a network-friendly manner. In this paper we make two contributions toward that end. First, we show that standard topology discovery methods (e.g., skitter) are quite inefficient, repeatedly probing the same interfaces. This is a concern, because when scaled up, such methods will generate so much traffic that they will begin to resemble DDoS attacks. We measure two kinds of redundancy in probing (intra- and inter-monitor) and show that both kinds are important. We show that straightforward approaches to addressing these two kinds of redundancy must take opposite tacks, and are thus fundamentally in conflict. Our second contribution is to propose and evaluate Doubletree, an algorithm that reduces both types of redundancy simultaneously on routers and end systems. The key ideas are to exploit the tree-like structure of routes to and from a single point in order to guide when to stop probing, and to probe each path by starting near its midpoint. Our results show that Doubletree can reduce both types of measurement load on the network dramatically, while permitting discovery of nearly the same set of nodes and links.

Dedicated infrastructures for end-to-end measurements are complex to deploy and manage. Equipment cost, the requirements for reporting bandwidth, and the administrative diversity of the Internet, are factors that potentially hamper scalability. This paper describes the architecture and implementation of an alternative approach in which the end-to-end probing and measurement reporting functions are embedded in a transport protocol, namely RTP (real-time transport protocol). Suitably enabled hosts in a multicast group are effectively co-opted to form an impromptu measurement infrastructure. Coupled with our previous work on multicast-based inference (see Adams, A. et al., IEEE Commun. Magazine, 2000), this enables the determination of the performance characteristics of internal network links of very large multicast distribution trees. Our experimental results show that an accuracy of about 1 part in 10 is attainable when inferring link loss rates in the 1% to 10% range, down to 1 part in 3 for loss rates down to 0.1%, this for probes generated by a regular audio source over a few hundred seconds.

Network tomography using multicast probes enables inference of loss characteristics of internal network links from reports of end-to-end loss seen at multicast receivers. We develop estimators for internal loss rates when reports are not available on all probes or from all receivers. This problem is motivated by the use of unreliable transport protocols, such as reliable transport protocol, to transmit loss reports to a collector for inference. We use a maximum-likelihood (ML) approach in which we apply the expectation maximization (EM) algorithm to provide an approximating solution to the the ML estimator for the incomplete data problem. We present a concrete realization of the algorithm that can be applied to measured data. For classes of models, we establish identifiability of the probe and report loss parameters, and convergence of the EM sequence to the maximum-likelihood estimator (MLE). Numerical results suggest that these properties hold more generally. We derive convergence rates for the EM iterates, and the estimation error of the MLE. Finally, we evaluate the accuracy and convergence rate through extensive simulations.

We derive estimators and bounds that drive probabilistic polling algorithms for the estimation of the session size, n, of any potentially large scale multicast session. We base our analysis upon a mapping of polling mechanisms to the problem of estimating the parameter n of the binomial (n,p) distribution. From the binomial model, we derive an interval estimator for n, and we characterize the tradeoff between the estimator's quality and its overhead in a manner readily matched to application requirements. We derive other estimators and bounds that enable applications to treat as a tunable parameter the confidence that they will not exceed their overhead limits. We also suggest revised estimators and other improvements for the mechanisms proposed by Bolot, Turletti and Wakeman (1994), and Nonnenmacher and Biersack (see Proceedings of IEEE INFOCOM '98, Los Alamitos, California, IEEE Computer Society Press, 1998).

Article Free Access Share on Detecting change in legal concepts Authors: Edwina L. Rissland Department of Computer Science, University of Massachusetts, Amherst, MA Department of Computer Science, University of Massachusetts, Amherst, MAView Profile , M. Timur Friedman Department of Computer Science, University of Massachusetts, Amherst, MA Department of Computer Science, University of Massachusetts, Amherst, MAView Profile Authors Info & Claims ICAIL '95: Proceedings of the 5th international conference on Artificial intelligence and lawMay 1995 Pages 127–136https://doi.org/10.1145/222092.222209Online:24 May 1995Publication History 25citation356DownloadsMetricsTotal Citations25Total Downloads356Last 12 Months9Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

In this paper we describe a system, called BankXX, which generates arguments by performing a heuristic best-first search of a highly interconnected network of legal knowledge. The legal knowledge includes cases represented from a variety of points of view—cases as collections of facts, cases as dimensionally-analyzed fact situations, cases as bundles of citations, and cases as prototypical factual scripts—as well as legal theories represented in terms of domain factors. BankXX performs its search for useful information using one of three evaluation functions encoded at different levels of abstraction: the domain level, an “argument-piece” level, and the overall argument level. Evaluation at the domain level uses easily accessible information about the nodes, such as their type; evaluation at the argument-piece level uses information about generally useful components of case-based argument, such as best cases and supporting legal theories; evaluation at the overall-argument level uses factors, called argument dimensions, which address the overall substance and quality of an argument, such as the centrality of its supporting cases or the success record of its best theory. BankXX is instantiated in the area of personal bankruptcy governed by Chapter 13 of the U.S. Bankruptcy Code, which permits a debtor to be discharged from debts through completion of a court-approved payment plan. In particular, our system addresses the requirement that such Chapter 13 plans be “proposed in good faith.”