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36 results on '"Erramilli, Vijay"'

1. Information Market for Web Browsing: Design, Usability and Incremental Adoption

Author

Kakhki, Arash Molavi, Erramilli, Vijay, Gill, Phillipa, Chaintreau, Augustin, and Krishnamurthy, Balachander

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Computer Science and Game Theory
Abstract

Browsing privacy solutions face an uphill battle to deployment. Many operate counter to the economic objectives of popular online services (e.g., by completely blocking ads) and do not provide enough incentive for users who may be subject to performance degradation for deploying them. In this study, we take a step towards realizing a system for online privacy that is mutually beneficial to users and online advertisers: an information market. This system not only maintains economic viability for online services, but also provides users with financial compensation to encourage them to participate. We prototype and evaluate an information market that provides privacy and revenue to users while preserving and sometimes improving their Web performance. We evaluate feasibility of the market via a one month field study with 63 users and find that users are indeed willing to sell their browsing information. We also use Web traces of millions of users to drive a simulation study to evaluate the system at scale. We find that the system can indeed be profitable to both users and online advertisers., Comment: 12 pages, 9 figures, 3 tables, 2 appendixes To appear in Performance18, December 5-7, 2018, Toulouse, France

Published
2018

2. Crowd-assisted Search for Price Discrimination in E-Commerce: First results

Author

Mikians, Jakub, Gyarmati, László, Erramilli, Vijay, and Laoutaris, Nikolaos

Subjects
Computer Science - Computers and Society
Abstract

After years of speculation, price discrimination in e-commerce driven by the personal information that users leave (involuntarily) online, has started attracting the attention of privacy researchers, regulators, and the press. In our previous work we demonstrated instances of products whose prices varied online depending on the location and the characteristics of perspective online buyers. In an effort to scale up our study we have turned to crowd-sourcing. Using a browser extension we have collected the prices obtained by an initial set of 340 test users as they surf the web for products of their interest. This initial dataset has permitted us to identify a set of online stores where price variation is more pronounced. We have focused on this subset, and performed a systematic crawl of their products and logged the prices obtained from different vantage points and browser configurations. By analyzing this dataset we see that there exist several retailers that return prices for the same product that vary by 10%-30% whereas there also exist isolated cases that may vary up to a multiplicative factor, e.g., x2. To the best of our efforts we could not attribute the observed price gaps to currency, shipping, or taxation differences.

Published
2013

3. Your browsing behavior for a Big Mac: Economics of Personal Information Online

Author

Carrascal, Juan Pablo, Riederer, Christopher, Erramilli, Vijay, Cherubini, Mauro, and de Oliveira, Rodrigo

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computers and Society, Computer Science - Social and Information Networks
Abstract

Most online services (Google, Facebook etc.) operate by providing a service to users for free, and in return they collect and monetize personal information (PI) of the users. This operational model is inherently economic, as the "good" being traded and monetized is PI. This model is coming under increased scrutiny as online services are moving to capture more PI of users, raising serious privacy concerns. However, little is known on how users valuate different types of PI while being online, as well as the perceptions of users with regards to exploitation of their PI by online service providers. In this paper, we study how users valuate different types of PI while being online, while capturing the context by relying on Experience Sampling. We were able to extract the monetary value that 168 participants put on different pieces of PI. We find that users value their PI related to their offline identities more (3 times) than their browsing behavior. Users also value information pertaining to financial transactions and social network interactions more than activities like search and shopping. We also found that while users are overwhelmingly in favor of exchanging their PI in return for improved online services, they are uncomfortable if these same providers monetize their PI., Comment: 11 Pages

Published
2011

4. Explore what-if scenarios with SONG: Social Network Write Generator

Author

Erramilli, Vijay, Yang, Xiaoyuan, and Rodriguez, Pablo

Subjects
Computer Science - Social and Information Networks, Computer Science - Networking and Internet Architecture, Physics - Physics and Society
Abstract

Online Social Networks (OSNs) have witnessed a tremendous growth the last few years, becoming a platform for online users to communicate, exchange content and even find employment. The emergence of OSNs has attracted researchers and analysts and much data-driven research has been conducted. However, collecting data-sets is non-trivial and sometimes it is difficult for data-sets to be shared between researchers. The main contribution of this paper is a framework called SONG (Social Network Write Generator) to generate synthetic traces of write activity on OSNs. We build our framework based on a characterization study of a large Twitter data-set and identifying the important factors that need to be accounted for. We show how one can generate traces with SONG and validate it by comparing against real data. We discuss how one can extend and use SONG to explore different `what-if' scenarios. We build a Twitter clone using 16 machines and Cassandra. We then show by example the usefulness of SONG by stress-testing our implementation. We hope that SONG is used by researchers and analysts for their own work that involves write activity., Comment: 11 pages

Published
2011

5. Divide and Conquer: Partitioning Online Social Networks

Author

Pujol, Josep M., Erramilli, Vijay, and Rodriguez, Pablo

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Online Social Networks (OSNs) have exploded in terms of scale and scope over the last few years. The unprecedented growth of these networks present challenges in terms of system design and maintenance. One way to cope with this is by partitioning such large networks and assigning these partitions to different machines. However, social networks possess unique properties that make the partitioning problem non-trivial. The main contribution of this paper is to understand different properties of social networks and how these properties can guide the choice of a partitioning algorithm. Using large scale measurements representing real OSNs, we first characterize different properties of social networks, and then we evaluate qualitatively different partitioning methods that cover the design space. We expose different trade-offs involved and understand them in light of properties of social networks. We show that a judicious choice of a partitioning scheme can help improve performance., Comment: 7 pages, 4 figures

Published
2009

7. I always feel like somebody's watching me measuring online behavioural advertising

Author

Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla, Carrascosa, Juan Miguel, Mikians, Jakub, Cuevas, Ruben, Erramilli, Vijay, Laoutaris, Nikolaos, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla, Carrascosa, Juan Miguel, Mikians, Jakub, Cuevas, Ruben, Erramilli, Vijay, and Laoutaris, Nikolaos

Abstract

Online Behavioural targeted Advertising (OBA) has risen in prominence as a method to increase the effectiveness of online advertising. OBA operates by associating tags or labels to users based on their online activity and then using these labels to target them. This rise has been accompanied by privacy concerns from researchers, regulators and the press. In this paper, we present a novel methodology for measuring and understanding OBA in the online advertising market. We rely on training artificial online personas representing behavioural traits like 'cooking', 'movies', 'motor sports', etc. and build a measurement system that is automated, scalable and supports testing of multiple configurations. We observe that OBA is a frequent practice and notice that categories valued more by advertisers are more intensely targeted. In addition, we provide evidences showing that the advertising market targets sensitive topics (e.g, religion or health) despite the existence of regulation that bans such practices. We also compare the volume of OBA advertising for our personas in two different geographical locations (US and Spain) and see little geographic bias in terms of intensity of OBA targeting. Finally, we check for targeting with do-not-track (DNT) enabled and discover that DNT is not yet enforced in the web., Peer Reviewed, Postprint (published version)

Published
2015

9. WYT: Optimized Consistency for Geo-Diverse Online Social Networks

Author

Huguenin, Kévin, Trestian, Ionut, Erramilli, Vijay, Laoutaris, Nikolaos, As Scalable As Possible: foundations of large scale dynamic distributed systems (ASAP), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Department of Electrical Engineering and Computer Science (EECS), Northwestern University, Telefonica Investigación y Desarrollo (Telefonica I+D), Telefonica Group, INRIA, SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, and Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Social Networks, Replication, Data centers, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

Large scale Online Social Networks (OSNs) like Facebook and Twitter are hosted out of multiple geo-diverse data centers to provide low latency and high fault tolerance. Such geo-diversity creates large amounts of WAN traffic for maintaining the consistency of replicas at different locations. Despite the dropping price of WAN bandwidth, the growth rate of OSNs combined with the incorporation of media rich long tail content (including images and videos) makes WAN traffic costs an increasing concern for OSN operators. At the heart of the problem lies a tradeoff between consistency and WAN bandwidth cost. In this paper, we propose the "Wait Your Turn"; WYT system that optimizes the tradeoff by leveraging: (i) knowledge of mapping between social relationships and geographic location, and (ii) knowledge of timing regularities in end user activity patterns. We quantify the benefits of such an OSN-aware update propagation strategy through a trace-driven analysis and show that it reduces WAN traffic by 55% compared to an immediate update of all replicas, while having minimal impact on consistency. Furthermore, for a given budget for WAN bandwidth, WYT increases consistency by several orders of magnitude compared to FIFO scheduling of updates.

Published
2010

11. Detecting price and search discrimination on the Internet

Author

Universitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla, Mikians, Jakub, Gyarmati, Laszlo, Erramilli, Vijay, Laoutaris, Nikolaos, Universitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla, Mikians, Jakub, Gyarmati, Laszlo, Erramilli, Vijay, and Laoutaris, Nikolaos

Abstract

Price discrimination, setting the price of a given product for each customer individually according to his valuation for it, can benefit from extensive information collected online on the customers and thus contribute to the profitability of e-commerce services. Another way to discriminate among customers with different willingness to pay is to steer them towards different sets of products when they search within a product category (i.e., search discrimination). Our main contribution in this paper is to empirically demonstrate the existence of signs of both price and search discrimination on the Internet, and to uncover the information vectors used to facilitate them. Supported by our findings, we outline the design of a large-scale, distributed watchdog system that allows users to detect discriminatory practices., Peer Reviewed, Postprint (published version)

Published
2012

12. 3GOL

Author

Rossi, Claudio, primary, Vallina-Rodriguez, Narseo, additional, Erramilli, Vijay, additional, Grunenberger, Yan, additional, Gyarmati, Laszlo, additional, Laoutaris, Nikolaos, additional, Stanojevic, Rade, additional, Papagiannaki, Konstantina, additional, and Rodriguez, Pablo, additional

Published
2013
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14. Staying online while mobile

Author

Aucinas, Andrius, primary, Vallina-Rodriguez, Narseo, additional, Grunenberger, Yan, additional, Erramilli, Vijay, additional, Papagiannaki, Konstantina, additional, Crowcroft, Jon, additional, and Wetherall, David, additional

Published
2013
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17. Best paper -- Follow the money

Author

Gill, Phillipa, primary, Erramilli, Vijay, additional, Chaintreau, Augustin, additional, Krishnamurthy, Balachander, additional, Papagiannaki, Konstantina, additional, and Rodriguez, Pablo, additional

Published
2013
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19. Last call for the buffet

Author

Blackburn, Jeremy, primary, Stanojevic, Rade, additional, Erramilli, Vijay, additional, Iamnitchi, Adriana, additional, and Papagiannaki, Konstantina, additional

Published
2013
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20. When David helps Goliath

Author

Vallina-Rodriguez, Narseo, primary, Erramilli, Vijay, additional, Grunenberger, Yan, additional, Gyarmati, Laszlo, additional, Laoutaris, Nikolaos, additional, Stanojevic, Rade, additional, and Papagiannaki, Konstantina, additional

Published
2012
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25. TailGate

Author

Traverso, Stefano, primary, Huguenin, Kévin, additional, Trestian, Ionut, additional, Erramilli, Vijay, additional, Laoutaris, Nikolaos, additional, and Papagiannaki, Kostantina, additional

Published
2012
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26. For sale : your data

Author

Riederer, Christopher, primary, Erramilli, Vijay, additional, Chaintreau, Augustin, additional, Krishnamurthy, Balachander, additional, and Rodriguez, Pablo, additional

Published
2011
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28. The little engine(s) that could

Author

Pujol, Josep M., primary, Erramilli, Vijay, additional, Siganos, Georgos, additional, Yang, Xiaoyuan, additional, Laoutaris, Nikos, additional, Chhabra, Parminder, additional, and Rodriguez, Pablo, additional

Published
2010
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30. Delegation forwarding

Author

Erramilli, Vijay, primary, Crovella, Mark, additional, Chaintreau, Augustin, additional, and Diot, Christophe, additional

Published
2008
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32. Last Call for the Buffet: Economics of Cellular Networks.

Author

Blackburn, Jeremy, Stanojevic, Rade, Erramilli, Vijay, Iamnitchi, Adriana, and Papagiannaki, Konstantina

Subjects
WIRELESS telecommunication services industry, CELL phone systems, NETWORK effect, SOCIAL networks
Abstract

Voice and data traffic growth over the last several years has become a major challenge for cellular operators with a direct impact on revenues, infrastructure investments, and enduser performance. The economics of these operators depend on various incentives used to attract users in the form of unlimited, bullet-like voice/sms/data packages. However, our understanding of the effects of user behavior under these offerings on operator revenues/costs remains poor. Using two years of detailed usage information of ... 1 million users across three services, voice, sms and data, combined with payment and cost information, we study how user behavior affects the economics of cellular operators. We discover that around 20% of the users consume more resources than what they pay for and hence are non-profitable. In addition to the individual user behavior, we study how the user interactions in the call graph affect the operator's revenues and cost, drawing on tools from social network analysis. We develop a framework that incorporates both the individual and social user behavior for studying how volume caps influence the revenues and the traffic costs. Using this framework we empirically show that volume caps can increase the difference between the revenues and the traffic costs of the studied operator by a factor of 2, while affecting only 16% of the existing user base. [ABSTRACT FROM AUTHOR]

Published
2013

33. Forwarding in opportunistic networks with resource constraints.

Author

Erramilli, Vijay and Crovella, Mark

Abstract

Effective forwarding in mobile opportunistic networks is a challenge, given the unpredictable mobility of nodes, short contact durations between nodes, wireless interference and limited buffer sizes. Most forwarding algorithms aim at decreasing costs (relative to flooding the network) by forwarding only to nodes which are likely to be good relays. While it is non-trivial to decide if an encountered node is a good relay or not at the moment of encounter, it is harder still to prioritize which messages to transmit under the presence of short contact durations and which messages to drop when buffers become full. The main objective of this paper is to study different message prioritization schemes using real measurements. Such schemes can be broadly divided into two categories - schemes which do not use any network information, and schemes which do. Examples of the former set of schemes include FIFO/LIFO etc. For the latter set of schemes, there is a key design choice: On one hand, we have the following scheme: when a forwarding opportunity presents itself, assign high priorities to messages which are relatively close to their intended destination. On the other hand, we can assign high priorities to messages which are farther away from their destination than closer messages. In order to decide if messages are close to their destination or not, we have to rely on a forwarding algorithm. For this, we use delegation forwarding schemes which have been shown to be efficient in terms of cost incurred in the network. We develop a new set of prioritization schemes based on delegation schemes. We consider these schemes in our empirical study. [ABSTRACT FROM AUTHOR]

Published
2008
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34. The little engine(s) that could

Author

Pujol, Josep, Erramilli, Vijay, Siganos, Georgos, Yang, Xiaoyuan, Laoutaris, Nikos, Chhabra, Parminder, and Rodriguez, Pablo

Abstract

The difficulty of scaling Online Social Networks (OSNs) has introduced new system design challenges that has often caused costly re-architecting for services like Twitter and Facebook. The complexity of interconnection of users in social networks has introduced new scalability challenges. Conventional vertical scaling by resorting to full replication can be a costly proposition. Horizontal scaling by partitioning and distributing data among multiples servers - e.g. using DHTs - can lead to costly inter-server communication. We design, implement, and evaluate SPAR, a social partitioning and replication middle-ware that transparently leverages the social graph structure to achieve data locality while minimizing replication. SPAR guarantees that for all users in an OSN, their direct neighbor's data is co-located in the same server. The gains from this approach are multi-fold: application developers can assume local semantics, i.e., develop as they would for a single server; scalability is achieved by adding commodity servers with low memory and network I/O requirements; and redundancy is achieved at a fraction of the cost. We detail our system design and an evaluation based on datasets from Twitter, Orkut, and Facebook, with a working implementation. We show that SPAR incurs minimum overhead, and can help a well-known open-source Twitter clone reach Twitter's scale without changing a line of its application logic and achieves higher throughput than Cassandra, Facebook's DHT based key-value store database.

Published
2011
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35. The little engine(s) that could

Author

Pujol, Josep, Erramilli, Vijay, Siganos, Georgos, Yang, Xiaoyuan, Laoutaris, Nikos, Chhabra, Parminder, and Rodriguez, Pablo

Abstract

The difficulty of scaling Online Social Networks (OSNs) has introduced new system design challenges that has often caused costly re-architecting for services like Twitter and Facebook. The complexity of interconnection of users in social networks has introduced new scalability challenges. Conventional vertical scaling by resorting to full replication can be a costly proposition. Horizontal scaling by partitioning and distributing data among multiples servers - e.g. using DHTs - can lead to costly inter-server communication. We design, implement, and evaluate SPAR, a social partitioning and replication middle-ware that transparently leverages the social graph structure to achieve data locality while minimizing replication. SPAR guarantees that for all users in an OSN, their direct neighbor's data is co-located in the same server. The gains from this approach are multi-fold: application developers can assume local semantics, i.e., develop as they would for a single server; scalability is achieved by adding commodity servers with low memory and network I/O requirements; and redundancy is achieved at a fraction of the cost. We detail our system design and an evaluation based on datasets from Twitter, Orkut, and Facebook, with a working implementation. We show that SPAR incurs minimum overhead, and can help a well-known open-source Twitter clone reach Twitter's scale without changing a line of its application logic and achieves higher throughput than Cassandra, Facebook's DHT based key-value store database.

Published
2010
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36. Forewarding in Mobile Opportunistic Networks

Author

Erramilli, Vijay

Abstract

Recent advances in processor speeds, mobile communications and battery life have enabled computers to evolve from completely wired to completely mobile. In the most extreme case, all nodes are mobile and communication takes place at available opportunities – using both traditional communication infrastructure as well as the mobility of intermediate nodes. These are mobile opportunistic networks. Data communication in such networks is a difficult problem, because of the dynamic underlying topology, the scarcity of network resources and the lack of global information. Establishing end-to-end routes in such networks is usually not feasible. Instead a store-and-carry forwarding paradigm is better suited for such networks. This dissertation describes and analyzes algorithms for forwarding of messages in such networks. In order to design effective forwarding algorithms for mobile opportunistic networks, we start by first building an understanding of the set of all paths between nodes, which represent the available opportunities for any forwarding algorithm. Relying on real measurements, we enumerate paths between nodes and uncover what we refer to as the path explosion effect. The term path explosion refers to the fact that the number of paths between a randomly selected pair of nodes increases exponentially with time. We draw from the theory of epidemics to model and explain the path explosion effect. This is the first contribution of the thesis, and is a key observation that underlies subsequent results. Our second contribution is the study of forwarding algorithms. For this, we rely on trace driven simulations of different algorithms that span a range of design dimensions. We compare the performance (success rate and average delay) of these algorithms. We make the surprising observation that most algorithms we consider have roughly similar performance. We explain this result in light of the path explosion phenomenon. While the performance of most algorithms we studied was roughly the same, these algorithms differed in terms of cost. This prompted us to focus on designing algorithms with the explicit intent of reducing costs. For this, we cast the problem of forwarding as an optimal stopping problem. Our third main contribution is the design of strategies based on optimal stopping principles which we refer to as Delegation schemes. Our analysis shows that using a delegation scheme reduces cost over naive forwarding by a factor of O(√N), where N is the number of nodes in the network. We further validate this result on real traces, where the cost reduction observed is even greater. Our results so far include a key assumption, which is unbounded buffers on nodes. Next, we relax this assumption, so that the problem shifts to one of prioritization of messages for transmission and dropping. Our fourth contribution is the study of message prioritization schemes, combined with forwarding. Our main result is that one achieves higher performance by assigning higher priorities to young messages in the network. We again interpret this result in light of the path explosion effect.

Published
2009

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