Metaphor: a System for Related Search Recommendations

Search plays an important role in online social networks as it provides an essential mechanism for discovering members and content on the network. Related search recommendation is one of several mechanisms used for improving members’ search experience in finding relevant results to their queries. This paper describes the design, implementation, and deployment of Metaphor, the related search recommendation system on LinkedIn, a professional social networking site with over 175 million members worldwide. Metaphor builds on a number of signals and filters that capture several dimensions of relatedness across member search activity. The system, which has been in live operation for over a year, has gone through multiple iterations and evaluation cycles. This paper makes three contributions. First, we provide a discussion of a large-scale related search recommendation system. Second, we describe a mechanism for effectively combining several signals in building a unified dataset for related search recommendations. Third, we introduce a query length model for capturing bias in recommendation click behavior. We also discuss some of the practical concerns in deploying related search recommendations.

The moving cloud is a proactive data delivery framework that leverages route fingerprints in individual mobility with users' contextualized behavior of data access for predictive data placement. Essentially, we are trading bandwidth and storage for latency, exchanging resources that grow more quickly for the one that grows most slowly. The moving cloud alleviates the latency problem by proactively placing content where it needs to be in the near future, so that resources are closely and readily available when requested by the user. This paradigm enables a number of networking scenarios including mobile resource augmentation, on-demand social networks, personal content distribution and vehicular applications.

Online social networks have enjoyed significant growth over the past several years. With improvements in mobile and Internet penetration, developing countries are participating in increasing numbers in online communities. This paper provides the first large scale and detailed analysis of social networking usage in developing country contexts. The analysis is based on data from LinkedIn, a professional social network with over 100 million members worldwide. LinkedIn has members from every country in the world, including millions in Africa, Asia, and South America. The goal of this paper is to provide researchers with a detailed look at the growth, adoption, and other characteristics of social networking usage in developing countries compared to the developed world. To this end, we discuss several themes that illustrate different dimensions of social networking use, ranging from interconnectedness of members in geographic regions to the impact of local languages on social network participation.

Several forms of vehicular fraud cause significant losses to the transportation and freight industry in Ethiopia. For a land-locked country that mostly relies on ground shipping and public transportation for connectivity, vehicular fraud is an important problem in the Ethiopian context. In order to start tackling this problem, this paper presents the design and implementation of a commercial grade GPS tracking system for nationwide deployment in Ethiopia, and the process of building a business around the technology. The paper makes three contributions. First, we present vehicular fraud, an important problem in developing regions, with a case study from Ethiopia. Second, we discuss the process of building an ICT system in developing regions for a practical and wide-scale deployment beyond experimental pilots. Compared to conducting research projects, this process often involves stringent requirements and considerations such as scalability, sustainability and security. Finally, we discuss the challenges and opportunities of building technology based businesses in Africa. We discuss entrepreneurship as a model for delivering ICT services in developing regions, and present some of the hurdles we faced and lessons learned in building a tech business in Ethiopia. We have deployed the system on the ground, and currently support an initial set of clients who are trying the system.

Web acceleration mechanisms play an important role in challenged network environments where connectivity is limited or expensive. However, as web usage gets increasingly personal and fragmented, traditional web acceleration systems that leverage redundancy in user requests to optimize performance find it difficult to perform well. This is unfortunate because personalization is an otherwise important trend that allows users to focus on content that is relevant to them. To start tackling this growing problem, this paper makes three contributions. First, we provide the first personalized, large scale web usage data in a developing country context. This allows researchers to get a nuanced understanding of access behavior that is not offered by aggregate data. Second, we present some analysis on this dataset, which provides tangible evidence for describing the increasingly fragmented and personal nature of web access even in developing countries. Finally, based on lessons learned from the analysis, we provide some recommendations for building effective web acceleration mechanisms in the face of an increasingly personal web. We believe the next generation of web acceleration systems for challenged networks need to have a strong personal component.

Tracking attendance is an important consideration for many developing world interventions. In many cases, these interventions are located in remote areas where its not always feasible to deploy expensive attendance tracking systems. In addition, since many existing systems focus on tracking participants (such as patients or students), rather than agents (such as teachers or health workers), they assume a trusted administrative staff on-site to record attendance. In this paper, we present the design of Hyke, a system for remote and cost effective attendance tracking in developing regions. Hyke combines voice-biometrics with accurate location tagging for tracking attendance in remote locations without the need for a trusted mediator on-site. Hyke was designed based on our observation of a currently deployed teacher attendance tracking system in rural Rajasthan, India. We have implemented some of the key components in Hyke, and discuss some of the security concerns in the system. The Hyke biometric stack for voice recognition is built atop several open source technologies, and provides a simple interface for non-expert users. Our evaluations with Indian speakers over telephone audio suggests the biometric stack is at par with the current state of the art. We believe this will be a useful tool for researchers who would like to incorporate voice technologies in their developing world projects.

Mobility powered systems provide the core routing mechanism in many ad-hoc and delay tolerant networks. Evaluating such systems under real life scenarios is often not practical because they involve multiple moving participants over a wide area. As a result, the principal way these systems are evaluated is though discrete event simulators that are often specific to the system at hand. While these systems provide a valid way to test ideas, and get some numbers, they often require systems to be built towards the simulation platform rather than deployment. As a result, researchers often stop at simulation. MobLab provides a mobility emulation platform for evaluating systems, while still working towards deployment. By providing an easy way to iteratively debug and evaluate production ready code, MobLab enables developers to deploy their mobility powered systems as soon as they are done evaluating them, rather than going through a different phase of implementing a simulation result. Our system can utilize mobility models or recoded traces to drive node mobility in the system, and provides a simple way for aggregating and presenting emulation results. MobLab is built on top of EmuLab, a network emulation platform, and has been successfully used to evaluate two mobility based systems.

Open and competitive marketplaces, like those enabled by the internet, bring enormous value to consumers while fostering innovation and growth across a wide variety of businesses. Electronic commerce has forever changed how people trade goods and services. Last year alone, US consumers spent more than $150 billion dollars on internet sales. However, developing countries largely have not benefited from these advances, often due to low network penetration, lack of locally relevant markets, and requirements for additional facilities (such as credit cards, shipping arrangements etc.) to take advantage of such marketplaces. Even when these markets are established with local content and poor connectivity in mind, they are often specific to a certain domain or community. This paper introduces Robit, an extensible auction-based market platform for use in challenged network environments. Robit enables developers to incorporate a market layer in their applications and open their service to a wider audience. Robit is built with challenged environments in mind, where communication channels are narrow and potentially expensive. The market structure in Robit is based on a survey of studies in auction theory and economics, and incorporates widely available communication tools. To demonstrate how Robit can be used to add a market layer to digital services, we have modified an open source data fetching application targeted towards challenged environments to use our platform. In addition, we analyze a standalone auction-based marketplace constructed using the Robit infrastructure. We also describe an in-country user study and a small pilot deployment for proof-of-concept.

Mobile devices face a diverse and dynamic set of networking options. Using those options to the fullest requires knowledge of application intent. This paper describes Intentional Networking, a simple but powerful mechanism for handling network diversity. Applications supply a declarative label for network transmissions, and the system matches transmissions to the most appropriate network. The system may also defer and re-order opportunistic transmissions subject to application-supplied mutual exclusion and ordering constraints. We have modified three applications to use Intentional Networking: BlueFS, a distributed file system for pervasive computing, Mozilla's Thunderbird e-mail client, and a vehicular participatory sensing application. We evaluated the performance of these applications using measurements obtained by driving a vehicle through WiFi and cellular 3G network coverage. Compared to an idealized solution that makes optimal use of all aggregated available networks but that lacks knowledge of application intent, Intentional Networking improves the latency of interactive messages from 48% to 13x, while adding no more than 7% throughput overhead.

Developing countries face significant challenges in network access, making even simple network tasks unpleasant. Many standard techniques---caching and predictive prefetching---help somewhat, but provide little or no assistance for personal data that is needed only by a single user. Sulula addresses this problem by leveraging the near-ubiquity of cellular phones able to send and receive simple SMS messages. Rather than visit a kiosk and fetch data on demand---a tiresome process at best---users request a future visit. If capacity exists, the kiosk can schedule secure retrieval of that user's data, saving time and more efficiently utilizing the kiosk's limited connectivity. When the user arrives at a provisioned kiosk, she need only obtain the session key on-demand, and thereafter has instant access. In addition, Sulula allows users to schedule data uploads. Experimental results show significant gains for the end user, saving tens of minutes of time for a typical email/news reading session. We also describe a small, ongoing deployment in-country for proof-of-concept, lessons learned from that experience, and provide a discussion on pricing and marketplace issues that remain to be addressed to make the system viable for developing-world access.

Even as wireless technologies are enabling anytime, anywhere internet connectivity, developing countries still face significant challenges in network access---bandwidth is low, latency is high and packets get dropped all the time. Wireless devices bring new promises to these areas, and in fact, most of the world's population will probably experience the internet for the first time on cellular telephones. Nonetheless, severe infrastructure challenges limit the extent to which the traditional networking stack can be helpful in these areas. We propose to augment the existing network infrastructure with calculated uses of individual mobility, coupled with excess storage in devices, to support bulk data transfer in challenged network environments. Our system uses estimates of natural principal mobility and existing network connectivity for delivering bulk data. We employ results from a large scale human mobility study to build a decentralized model that captures system transitions efficiently. Weak connectivity, when available, is used for improving performance, while the occasional fat pipe is used for shortcuts and last mile delivery. Results with real life traces show substantial savings in using our system for delivering bulk data compared to the network alone, and at the same time improved delivery rates compared to solutions that use only ad hoc routing between mobile peers.

Wireless infrastructures are increasingly diverse, complex, and difficult to manage. Those who restrict themselves to homogeneous, managed campus or corporate networks are a vanishing breed. In the wild, users are confronted with many overlapping infrastructures with a broad variety of strengths and weaknesses. Such diversity of infrastructure is both a challenge and an opportunity. The challenge lies in presenting the alternatives to applications and users in a way that provides the best possible utility to both. However,by managing these many alternatives, we can provide significant benefits, exploiting multiple networks concurrently and planning future transmissions intelligently.
To this end, we are developing Intentional Networking - a set of interfaces and mechanisms that allow applications,users, and the operating system to proactively manage current and expected future connectivity. We do this through extensions to the networking API. Applications can label sockets or individual transmissions with a label, a qualitative statement about the flow. The operating system can then best match eachflow with network capabilities. In some cases this requires a re-ordering of the application's send order; our API offers both blocking and event-based interfaces to allow this reordering.

An increasing amount of data is being stored on mobile devices with growing storage capacity and functional specializations. As a result, searching through a user's distributed data set effectively is crucial. Previous search architectures tuned for single, stationary devices are not effective at managing the challenges associated with querying data across heterogeneous machines. These designs do not consider the complex set of constraints and challenges in the distributed search domain. We propose a distributed architecture, DSearch, to manage the complexities of a mobile data set to improve query performance across all the devices in a user's personal area network. First, we provide a light-weight infrastructure that can efficiently organize and search a set of devices. Second, we develop a membership system to manage the dynamics of multiple devices in a network. Third, we analyze three search index replication schemes to improve query performance. We developed the DSearch distributed search architecture and evaluated its performance.