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Poor visibility into the network hampers progress in a number of important research areas, from network troubleshooting to Internet topology and performance mapping. This persistent, well-known problem has served as motivation for numerous proposals to build or extend existing Internet measurement platforms by recruiting larger, more diverse vantage points. Capturing the edge of the network, however, remains an elusive goal. We argue that at its root the problem is one of incentives. Today's measurement platforms build on the assumption that the goals of experimenters and those hosting the platform are the same. As much of the Internet growth occurs in residential broadband networks, this assumption no longer holds. We present a measurement experimentation platform that reaches the network edge by explicitly aligning the objectives of the experimenters with those of the users hosting the platform. Dasu—our current prototype—is designed to support both network measurement experimentation and broadband characterization. Dasu has been publicly available since July 2010 and has been installed by over 100 $\,$ 000 users with a heterogeneous set of connections spreading across 2431 autonomous systems (ASs) and 166 countries. We discuss some of the challenges we faced building and using a platform for the Internet's edge, describe its design and implementation, and illustrate the unique perspective its current deployment brings to Internet measurement.

This paper seeks to historicize Twitter within a longer historical framework of diaries to better understand Twitter and broader communication practices and patterns. Based on a review of historical literature regarding 18th and 19th century diaries, we created a content analysis coding scheme to analyze a random sample of publicly available Twitter messages according to themes in the diaries. Findings suggest commentary and accounting styles are the most popular narrative styles on Twitter. Despite important differences between the historical diaries and Twitter, this analysis reveals long-standing social needs to account, reflect, communicate, and share with others using media of the times.

One definition of privacy is the selective revelation of information about oneself. With billions of people using social media, it's increasingly difficult for users to control what they're disclosing and to whom. Current privacy protection measures block leakages via privacy settings that are syntactic in nature, but existing solutions don't attempt to cover all the entities who might end up receiving the data, ensure the need for or use of the data collected, determine the duration of data retention, or reveal if the data is merged with external information to reveal the user's full identity. The title of the article is from linguist Noam Chomsky, who used it to distinguish between syntax and semantics. Virtually all privacy solutions thus far handle issues relating only to the first hop of the personal data flow from a user. The gap can only be filled by examining the semantics behind the multihop flow of user data over time. This article surveys the state of the art and presents some potential directions in moving from a syntactic approach to a more holistic semantics-based approach.

The increasingly prominent new subset of Web pages, called 'blogs' differs from traditional Web pages both in characteristics and potential to applications. We explore three aspects of the blogistan: its overall scope and size, identification of emerging hot topics of discussion and link patterns, and implications both to blogs and applications such as search. Beyond blogs, we develop a general methodology of mining evolving networks and connections. The first part of our study is longitudinal-based on a five-week continuous fetch of a seed collection of nearly 10,000 blog URLs. The second part is based on a successive crawl of pages suspected to be blogs leading to a larger collection of several million URLs. The collection is examined for a variety of properties. We characterize blogs and study different facets of the link structure in blogs and its evolution over time, attributes of servers and domains that host many of the blogs including their IP addresses, and how blogs behave with respect to various HTTP/1.1 protocol issues. Inferences from our in-depth exploration are relevant to applications ranging from mining to hosting of blogs and other issues of relevance to the measurement community.

Traffic, usage, and performance measurements are crucial to the design, operation and control of Internet protocol networks. This article describes a prototype infrastructure for the measurement, storage, and correlation of network data of different types and origins from AT&T's commercial IP network. We focus first on some novel aspects of the measurement infrastructure, then describe analyses that illustrate the power of joining different measured data sets for network planning and design.

We present a piggyback server invalidation (PSI) mechanism for maintaining stronger cache coherency in Web proxy caches while reducing overall costs. The basic idea is for servers to piggyback on a reply to a proxy client, the list of resources that have changed since the last access by the client. The proxy client invalidates cached entries on the list and can extend the lifetime of entries not on the list. This continues our prior work on piggyback cache validation (PCV) where we focused on piggybacking validation requests from the proxy cache to the server. Trace-driven simulation of PSI on two large, independent proxy log data sets, augmented with data from several server logs, shows PSI provides close to strong cache coherency while reducing the request traffic compared to existing cache coherency techniques. The best overall performance is obtained when the PSI and PCV techniques are combined. Compared to the best TTL-based policy, this hybrid policy reduces the average cost (considering response latency, request messages and bandwidth) by 7–9%, reduces the staleness ratio by 82–86%, yielding a staleness ratio of 0.001. © 1998 Published by Elsevier Science B.V. All rights reserved.

Distributed networks of personal workstations are becoming the dominant computing environment for software development organizations. Many cooperative activities that are carried out in such environments are particularly well suited for automated support. Taking the point of view that such activities are modeled most naturally as the occurrence of events requiring actions to be performed, we developed a system called Yeast (Yet another Event Action Specification Tool). Yeast is a client server system in which distributed clients register event action specifications with a centralized server, which performs event detection and specification management. Each specification submitted by a client defines a pattern of events that is of interest to the client's application plus an action that is to be executed in response to an occurrence of the event pattern; the server triggers the action of a specification once it has detected an occurrence of the associated event pattern. Yeast provides a global space of events that is visible to and shared by all users. In particular, events generated by one user can trigger specifications registered by another user. Higher level applications are built as collections of Yeast specifications. We use Yeast on a daily basis for a variety of applications, from deadline notification to software process automation. The paper presents an in depth description of Yeast and an example application of Yeast, in which Yeast specifications are used to automate a software distribution process involving several interdependent software tools. >