A Massively Scalable Architecture For Instant Messaging & Presence

This paper analyzes the scalability of Instant Messaging & Presence (IM&P) architectures. We take a queueing-based modelling and analysis approach to find the bottlenecks of the current IM&P architecture at the Dutch social network Hyves, as well as of alternative architectures. We use the Hierarchical Evaluation Tool (HIT) to create and analyse models analytically. Based on these results, we recommend a new architecture that provides better scalability than the current one. \u

The Lifecycle and Cascade of WeChat Social Messaging Groups

Social instant messaging services are emerging as a transformative form with which people connect, communicate with friends in their daily life - they catalyze the formation of social groups, and they bring people stronger sense of community and connection. However, research community still knows little about the formation and evolution of groups in the context of social messaging - their lifecycles, the change in their underlying structures over time, and the diffusion processes by which they develop new members. In this paper, we analyze the daily usage logs from WeChat group messaging platform - the largest standalone messaging communication service in China - with the goal of understanding the processes by which social messaging groups come together, grow new members, and evolve over time. Specifically, we discover a strong dichotomy among groups in terms of their lifecycle, and develop a separability model by taking into account a broad range of group-level features, showing that long-term and short-term groups are inherently distinct. We also found that the lifecycle of messaging groups is largely dependent on their social roles and functions in users' daily social experiences and specific purposes. Given the strong separability between the long-term and short-term groups, we further address the problem concerning the early prediction of successful communities. In addition to modeling the growth and evolution from group-level perspective, we investigate the individual-level attributes of group members and study the diffusion process by which groups gain new members. By considering members' historical engagement behavior as well as the local social network structure that they embedded in, we develop a membership cascade model and demonstrate the effectiveness by achieving AUC of 95.31% in predicting inviter, and an AUC of 98.66% in predicting invitee.Comment: 10 pages, 8 figures, to appear in proceedings of the 25th International World Wide Web Conference (WWW 2016

A Novel Uplink Data Transmission Scheme For Small Packets In Massive MIMO System

Intelligent terminals often produce a large number of data packets of small lengths. For these packets, it is inefficient to follow the conventional medium access control (MAC) protocols because they lead to poor utilization of service resources. We propose a novel multiple access scheme that targets massive multiple-input multiple-output (MIMO) systems based on compressive sensing (CS). We employ block precoding in the time domain to enable the simultaneous transmissions of many users, which could be even more than the number of receive antennas at the base station. We develop a block-sparse system model and adopt the block orthogonal matching pursuit (BOMP) algorithm to recover the transmitted signals. Conditions for data recovery guarantees are identified and numerical results demonstrate that our scheme is efficient for uplink small packet transmission.Comment: IEEE/CIC ICCC 2014 Symposium on Signal Processing for Communication

A Dynamic Profile Questions Approach to Mitigate Impersonation in Online Examinations

© The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Online examinations are an integral component of many online learning environments, which face many security challenges. Collusion is seen as a major security threat to such examinations, when a student invites a third party to impersonate or abet in a test. This work aims to strengthen the authentication of students via the use of dynamic profile questions. The study reported in this paper involved 31 online participants from five countries over a five-week period. The results of usability and security analysis are reported. The dynamic profile questions were more usable than both the text-based and image-based questions (p < 0.01). An impersonation abuse scenario was simulated using email and mobile phone. The impersonation attack via email was not successful, however, students were able to share answers to dynamic profile questions with a third party impersonator in real time, which resulted in 93% correct answers. The sharing of information via phone took place in real time during an online test and the response time of an impersonator was significantly different (p < 0.01) than a student. The study also revealed that a response time factor may be implemented to identify and report impersonation attacks.Peer reviewe

A Survey of Green Networking Research

Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks. In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate; Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications. 18 pages, 6 figures, 2 table

Flight Awareness Collaboration Tool Development

NASA is developing the Flight Awareness Collaboration Tool (FACT) to support airline and airport operations during winter storms. The goal is to reduce flight delays and cancellations due to winter weather. FACT concentrates relevant information from the Internet and FAA databases on one screen for easy access. It provides collaboration tools for those managing the winter weather event including the airline operations center, airport authority (runway treatment), the Federal Aviation Administration air traffic control tower, and de-icing operators. Prediction tools are being added to improve FACT capabilities including one that anticipates changes in airport departure rates from weather forecasts. We have formed two user teams from affected airports to guide the design and evaluate the web-based prototype. Future work includes adding more automated capabilities and conducting a simulation to evaluate FACT in a realistic environment

Share and multiply: modeling communication and generated traffic in private WhatsApp groups

Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group