Location-based computing (LBC) is becoming increasing important in both industry and academia. A key challenge is the pervasive deployment of LBC technologies; to be effective they must run on a wide variety of client platforms, including laptops, PDAs, and mobile phones, so that location data can be acquired anywhere and accessed by any application. Moreover, as a nascent area, LBC is experiencing rapid innovation in sensing technologies, the positioning algorithms themselves, and the applications they support. Lastly, as a newcomer, LBC must integrate with existing communications and application technologies, including web browsers and location data interchange standard.This paper describes our experience in developing the Place Lab architecture, a widely used first-generation open source toolkit for client-side location sensing. Using a layered, pattern-based architecture, it supports modular development in any dimension of LBC, enabling the field to move forward more rapidly as these innovations are shared with the community as pluggable components. Our experience shows the benefits of domain-specific abstractions, and how we overcame high-level language constraints to support a wide array of platforms in this emerging space. We also describe our experience in re-engineering parts of the architecture based on the needs of the user community, including insights on software licensing issues.

We present Topology-based Geolocation (TBG), a novel approach to estimating the geographic location of arbitrary Internet hosts. We motivate our work by showing that 1) existing approaches, based on end-to-end delay measurements from a set of landmarks, fail to outperform much simpler techniques, and 2) the error of these approaches is strongly determined by the distance to the nearest landmark, even when triangulation is used to combine estimates from different landmarks. Our approach improves on these earlier techniques by leveraging network topology, along with measurements of network delay, to constrain host position. We convert topology and delay data into a set of constraints, then solve for router and host locations simultaneously. This approach improves the consistency of location estimates, reducing the error substantially for structured networks in our experiments on Abilene and Sprint. For networks with insufficient structural constraints, our techniques integrate external hints that are validated using measurements before being trusted. Together, these techniques lower the median estimation error for our university-based dataset to 67 km vs. 228 km for the best previous approach.

This paper presents Virgil, an automatic access point discovery and selection system. Unlike existing systems that select access points based entirely on received signal strength, Virgil scans for all available APs at a location, quickly associates to each, and runs a battery of tests to estimate the quality of each AP's connection to the Internet. Virgil also probes for blocked or redirected ports, to guide AP selection in favor of preserving application services that are currently in use. Results of our evaluation across five neighborhoods in three cities show Virgil finds a usable connection from 22% to 100% more often than selecting based on signal strength alone. By caching AP test results, Virgil both improves performance and success rate. Our overhead is acceptable and is shown to be faster than manually selecting an AP with Windows XP.

Location systems have long been identified as an important component of emerging mobile applications. Most research on location systems has focused on precise location in indoor environments. However, many location applications (for example, location-aware web search) become interesting only when the underlying location system is available ubiquitously and is not limited to a single office environment. Unfortunately, the installation and calibration overhead involved for most of the existing research systems is too prohibitive to imagine deploying them across, say, an entire city. In this work, we evaluate the feasibility of building a wide-area 802.11 Wi-Fi-based positioning system. We compare a suite of wireless-radio-based positioning algorithms to understand how they can be adapted for such ubiquitous deployment with minimal calibration. In particular, we study the impact of this limited calibration on the accuracy of the positioning algorithms. Our experiments show that we can estimate a user's position with a median positioning error of 13-40 meters (depending upon the characteristics of the environment). Although this accuracy is lower than existing positioning systems, it requires substantially lower calibration overhead and provides easy deployment and coverage across large metropolitan areas.

Recent research has shown that one can use Distributed Hash Tables (DHTs) to build scalable, robust and efficient applications. One question that is often left unanswered is that of simplicity of implementation and deployment. In this paper, we explore a case study of building an application for which ease of deployment dominated the need for high performance. The application we focus on is Place Lab, an end-user positioning system. We evaluate whether it is feasible to use DHTs as an application-independent building block to implement a key component of Place Lab: its "mapping infrastructure." We present Prefix Hash Trees, a data structure used by Place Lab for geographic range queries that is built entire on top of a standard DHT. By strictly layering Place Lab's data structures on top of a generic DHT service, we were able to decouple the deployment and management of Place Lab from that of the underlying DHT. We identify the characteristics of Place Lab that made it amenable for deploying in this layered manner, and comment on its effect on performance.

Napster pioneered the idea of peer-to-peer file sharing, and supported it with a centralized file search facility. Subsequent P2P systems like Gnutella adopted decentralized search algorithms. However, Gnutella's notoriously poor scaling led some to propose distributed hash table solutions to the wide-area file search problem. Contrary to that trend, we advocate retaining Gnutella's simplicity while proposing new mechanisms that greatly improve its scalability. Building upon prior research [1, 12, 22], we propose several modifications to Gnutella's design that dynamically adapt the overlay topology and the search algorithms in order to accommodate the natural heterogeneity present in most peer-to-peer systems. We test our design through simulations and the results show three to five orders of magnitude improvement in total system capacity. We also report on a prototype implementation and its deployment on a testbed.

Researchers and commercial developers have proposed several protocols to enable efficient multi-point communication both at the IP layer and at the application or overlay layer. However, no single protocol has made enough headway in terms of deployment for it to span the entire Internet. In fact, we believe that none of the existing multicast or broadcast protocols will become the sole dominant Internet broadcasting technology any time in the near future. Instead, we expect islands of non-interoperable broadcast connectivity. To address this, we propose an architecture that enables the composition of different broadcast protocol, to provide an end-to-end broadcast service. We call this architecture the Broadcast Federation. In this paper, we describe the architecture along with a prototype implementation and preliminary results from the prototype.

Although IP multicast is an effective network primitive for best-effort, large-scale, multi-point communication, many multicast applications such as shared whiteboards, multi-player games and software distribution require reliable data delivery. Building services like reliable sequenced delivery on top of IP multicast has proven to be a hard problem. The enormous extent of network and end-system heterogeneity in multipoint communication exacerbates the design of scalable end-to-end reliable multicast protocols. In this paper, we propose a radical departure from the traditional end-to-end model for reliable multicast and instead propose a hybrid approach that leverages the successes of unicast reliability protocols such as TCP while retaining the efficiency of IP multicast for multi-point data delivery. Our approach splits a large heterogeneous reliable multicast session into a number of multicast data groups of co-located homogeneous participants. A collection of application-aware agents-reliable multicast proxies (RMX)-organizes these data groups into a spanning tree using an overlay network of TCP connections. Sources transmit data to their local group, and the RMX in that group forwards the data towards the rest of the data groups. RMX use detailed knowledge of application semantics to adapt to the effects of heterogeneity in the environment. To demonstrate the efficacy of our architecture, we have built a prototype implementation that can be customized for different kinds of applications.

IP Multicast has proven to be an effective communication primitive for best effort, large-scale, multi-point audio/video conferencing applications. While the best-effort transport of real-time digital audio/video is a relatively straightforward and well understood problem, many other applications like multicast-based shared whiteboards and shared text editors are more challenging to design because their underlying media require reliable transport, i.e., a "reliable multicast" protocol. The design of scalable end-to-end reliable multicast protocols has unfortunately proven to be an especially hard problem, exacerbated by the enormous degree of network and system heterogeneity present in the Internet. In this paper, we propose to tackle the heterogeneity problem with a hybrid model for reliable multicast that relies in part on end-to-end loss recovery mechanisms and in part on intelligent and application-aware adaptation carried out within the network. In our framework, application-aware agents -- or proxies -- use detailed knowledge of application semantics to hide the effects of heterogeneity from the rest of the system. We present a general architecture for proxy-based reliable multicast called the Reliable Multicast proXy (RMX) model and describe a prototype implementation of an RMX for a shared whiteboard application for hand-held PDAs.

We identifit three fundamental requirements for scalable network services: incremental scalability and oveflow growth provisioning, 24x7 availability through fault masking, and costeffectiveness.We argue that clusters of commodity workstations interconnected by a high-speed SAN are exceptionally well-suited to meeting these challenges for Internet-server workloads, provided the software infrastructure for managing partial failures and administering a large cluster does not have to be reinvented for each new service.To this end, we propose a general, layered architecture for building cluster-based scalable network services that encapsulates the above requirements for reuse, and a service-programming model based on composable workers thatpe$onn transformation, aggregation, caching, i and customization (TACC) of Internet content.For both performance and implementation simplicity, the architecture and TACC programming model exploit BASE, a weaker-than-ACID data semantics that results from trading consistency for availability and relying on sof state for robustness in failure management., Our ,qychitecture can be used as an "off the shelf * irtfrastructural platfonn for creating new network services, allowing authors to focus on the "content" of the service {by composing TACC building blocks) rather than its implementation.We discuss two real implemeritations of services based on this architecture: TranSend, a Web distillation proxy deployed to the UC Berkeley dialup IP population, and HotBot, the commercial implementation of the Inktomi search engine.We present detailed measurements of TranSend's performance based on substantial client traces, as well as anecdotal evidence from the TranSend and HotBot experience, to support the claims made for the architecture.

lligent services. Our extensions are orthogonal in that they provide an interface to a service, which complements the Web browsing experience but is independent of the content of any particular site. We base our experiments on the TranSend service at UC Berkeley, which performs lossy compression on inline images to accelerate dialup Web access for a community of 25,000 subscribers. The service keeps a separate "preferences profile" for each user, which allows each user to vary the aggressiveness of lossy compression, selectively turn off the service for certain pages, and select the type of interface provided for refinement of degraded (lossily compressed) content. We are exploring three technologies for implementing the TranSend service interface: HTML decoration, Java, and JavaS- Server Client Browser Client Browser Proxy Server Server cript. The accompanying video demonstrates prototypes of all three mechanisms. We no