In Vivo Evaluation of the Secure Opportunistic Schemes Middleware using a Delay Tolerant Social Network

Over the past decade, online social networks (OSNs) such as Twitter and Facebook have thrived and experienced rapid growth to over 1 billion users. A major evolution would be to leverage the characteristics of OSNs to evaluate the effectiveness of the many routing schemes developed by the research community in real-world scenarios. In this paper, we showcase the Secure Opportunistic Schemes (SOS) middleware which allows different routing schemes to be easily implemented relieving the burden of security and connection establishment. The feasibility of creating a delay tolerant social network is demonstrated by using SOS to power AlleyOop Social, a secure delay tolerant networking research platform that serves as a real-life mobile social networking application for iOS devices. SOS and AlleyOop Social allow users to interact, publish messages, and discover others that share common interests in an intermittent network using Bluetooth, peer-to-peer WiFi, and infrastructure WiFi.Comment: 6 pages, 4 figures, accepted in ICDCS 2017. arXiv admin note: text overlap with arXiv:1702.0565

Offloading cellular traffic through opportunistic communications: analysis and optimization

Offloading traffic through opportunistic communications has been recently proposed as a way to relieve the current overload of cellular networks. Opportunistic communication can occur when mobile device users are (temporarily) in each other's proximity, such that the devices can establish a local peer-to-peer connection (e.g., via WLAN or Bluetooth). Since opportunistic communication is based on the spontaneous mobility of the participants, it is inherently unreliable. This poses a serious challenge to the design of any cellular offloading solutions, that must meet the applications' requirements. In this paper, we address this challenge from an optimization analysis perspective, in contrast to the existing heuristic solutions. We first model the dissemination of content (injected through the cellular interface) in an opportunistic network with heterogeneous node mobility. Then, based on this model, we derive the optimal content injection strategy, which minimizes the load of the cellular network while meeting the applications' constraints. Finally, we propose an adaptive algorithm based on control theory that implements this optimal strategy without requiring any data on the mobility patterns or the mobile nodes' contact rates. The proposed approach is extensively evaluated with both a heterogeneous mobility model as well as real-world contact traces, showing that it substantially outperforms previous approaches proposed in the literature.This work has been sponsored by the HyCloud project, supported by Microsoft Innovation Cluster for Embedded Software (ICES), and by the EU H2020-ICT-2014-2 Flex5Gware project, no. 671563

Mobile Computing in Digital Ecosystems: Design Issues and Challenges

In this paper we argue that the set of wireless, mobile devices (e.g., portable telephones, tablet PCs, GPS navigators, media players) commonly used by human users enables the construction of what we term a digital ecosystem, i.e., an ecosystem constructed out of so-called digital organisms (see below), that can foster the development of novel distributed services. In this context, a human user equipped with his/her own mobile devices, can be though of as a digital organism (DO), a subsystem characterized by a set of peculiar features and resources it can offer to the rest of the ecosystem for use from its peer DOs. The internal organization of the DO must address issues of management of its own resources, including power consumption. Inside the DO and among DOs, peer-to-peer interaction mechanisms can be conveniently deployed to favor resource sharing and data dissemination. Throughout this paper, we show that most of the solutions and technologies needed to construct a digital ecosystem are already available. What is still missing is a framework (i.e., mechanisms, protocols, services) that can support effectively the integration and cooperation of these technologies. In addition, in the following we show that that framework can be implemented as a middleware subsystem that enables novel and ubiquitous forms of computation and communication. Finally, in order to illustrate the effectiveness of our approach, we introduce some experimental results we have obtained from preliminary implementations of (parts of) that subsystem.Comment: Proceedings of the 7th International wireless Communications and Mobile Computing conference (IWCMC-2011), Emergency Management: Communication and Computing Platforms Worksho

Three applications for mobile epidemic algorithms

This paper presents a framework for the pervasive sharing of data using wireless networks. 'FarCry' uses the mobility of users to carry files between separated networks. Through a mix of ad-hoc and infrastructure-based wireless networking, files are transferred between users without their direct involvement. As users move to different locations, files are then transmitted on to other users, spreading and sharing information. We examine three applications of this framework. Each of these exploits the physically proximate nature of social gatherings. As people group together in, for example, business meetings and cafés, this can be taken as an indication of similar interests, e.g. in the same presentation or in a type of music. MediaNet affords sharing of media files between strangers or friends, MeetingNet shares business documents in meetings, and NewsNet shares RSS feeds between mobile users. NewsNet also develops the use of pre-emptive caching: collecting information from others not for oneself, but for the predicted later sharing with others. We offer observations on developing this system for a mobile, multi-user, multi-device environment

Social group discovery using using co-location traces

Social information can be used to enhance existing applications and services or can be utilized to devise entirely new applications. Examples of such applications include recommendation systems, peer-to-peer networks, opportunistic data dissemination in ad hoc networks, or mobile friend finder. Social information can be collected from either online or mobile sources. This thesis focuses on identifying social groups based on data collected from mobile phones. These data can be either location or co-location traces. Unfortunately, location traces require a localization system for every mobile device, and users are reluctant to share absolute location due to privacy concerns. On the other hand, co- location can be collected using the embedded Bluetooth interface, present on almost all phones, and alleviates the privacy concerns as it does not collect user location. Existing graph algorithms, such as K-Clique and WNA, applied on co-location traces achieve low group detection accuracy because they focus on pair-wise ties, which cannot tell if multiple users spent time together simultaneously or how often they met. This thesis proposes the Group Discovery using Co-location (GDC) algorithm, which leverages the meeting frequency and meeting duration to accurately detect social groups. These parameters allow us to compare, categorize, and rank the groups discovered by GDC. This algorithm is tested and validated on data collected from 141 active users who carried mobile phones on our campus over the duration of one month. GDC received ratings that were 30% better than the K-Clique algorithm