Ilias Leontiadis

GeOpps: Geographical Opportunistic Routing for Vehicular Networks

Vehicular networks can be seen as an example of hybrid delay tolerant network where a mixture of infostations and vehicles can be used to geographically route the information messages to the right location. In this paper we present a forwarding protocol which exploits both the opportunistic nature and the inherent characteristics of the vehicular network in terms of mobility patterns and encounters, and the geographical information present in navigator systems of vehicles. We also report about our evaluation of the protocol over a simulator using realistic vehicular traces and in comparison with other geographical routing protocols.

On the Effectiveness of an Opportunistic Traffic Management System for Vehicular Networks

Road congestion results in a huge waste of time and productivity for millions of people. A possible way to deal with this problem is to have transportation authorities distribute traffic information to drivers, which, in turn, can decide (or be aided by a navigator) to route around congested areas. Such traffic information can be gathered by relying on static sensors placed at specific road locations (e.g., induction loops and video cameras) or by having single vehicles report their location, speed, and travel time. While the former approach has been widely exploited, the latter has come about only more recently; consequently, its potential is less understood. For this reason, in this paper, we study a realistic test case that allows the evaluation of the effectiveness of such a solution. As part of this process, (a) we designed a system that allows vehicles to crowd-source traffic information in an ad hoc manner, allowing them to dynamically reroute based on individually collected traffic information; (b) we implemented a realistic network-mobility simulator that allowed us to evaluate such a model; and (c) we performed a case study that evaluates whether such a decentralized system can help drivers to minimize trip times, which is the main focus of this paper. This study is based on traffic survey data from Portland, OR, and our results indicate that such navigation systems can indeed greatly improve traffic flow. Finally, to test the feasibility of our approach, we implemented our system and ran some real experiments at UCLAs C-Vet test bed.

Opportunistic spatio-temporal dissemination system for vehicular networks

Opportunistic dissemination protocols have potentially applications in the domain of vehicular networking, ranging from advertising to emergency/traffic/parking information spreading: one of the characteristics of vehicular networks is that they are often partitioned due to lack of continuity in connectivity among cars or limited coverage of infostations in remote areas. Most available opportunistic, or delay tolerant, networking protocols, however, fail to take into account the peculiarities of vehicular networks. This paper introduces a novel opportunistic event dissemination protocol for vehicular networks. The protocol takes into account the characteristics of these networks in order to dispatch the publications to the subscribers. Furthermore, it uses opportunistic cache and replay mechanisms to deliver the notifications to new subscribers in the area throughout the publication interval. We evaluate our approach through simulation using realistic vehicular traces. We compare our algorithm with a standard epidemic protocol, which offer the best alternative in terms of message delivery, by measuring overhead and delivery over a number of scenarios.

Don't kill my ads!: balancing privacy in an ad-supported mobile application market

Application markets have revolutionized the software download model of mobile phones: third-party application developers offer software on the market that users can effortlessly install on their phones. This great step forward, however, also imposes some threats to user privacy: applications often ask for permissions that reveal private information such as the users location, contacts and messages. While some mechanisms to prevent leaks of user privacy to applications have been proposed by the research community, these solutions fail to consider that application markets are primarily driven by advertisements that rely on accurately profiling the user. In this paper we take into account that there are two parties with conflicting interests: the user, interested in maintaining their privacy and the developer who would like to maximize their advertisement revenue through user profiling. We have conducted an extensive analysis of more than 250,000 applications in the Android market. Our results indicate that the current privacy protection mechanisms are not effective as developers and advert companies are not deterred. Therefore, we designed and implemented a market-aware privacy protection framework that aims to achieve an equilibrium between the developers revenue and the users privacy. The proposed framework is based on the establishment of a feedback control loop that adjusts the level of privacy protection on mobile phones, in response to advertisement generated revenue.

SenShare: transforming sensor networks into multi-application sensing infrastructures

Sensor networks are typically purpose-built, designed to support a single running application. As the demand for applications that can harness the capabilities of a sensor-rich environment increases, and the availability of sensing infrastructure put in place to monitor various quantities soars, there are clear benefits in a model where infrastructure can be shared amongst multiple applications. This model however introduces many challenges, mainly related to the management of the communication of the same application running on different network nodes, and the isolation of applications within the network. In this work we present SenShare, a platform that attempts to address the technical challenges in transforming sensor networks into open access infrastructures capable of supporting multiple co-running applications. SenShare provides a clear decoupling between the infrastructure and the running application, building on the concept of overlay networks. Each application operates in an isolated environment consisting of an in-node hardware abstraction layer, and a dedicated overlay sensor network. We further report on the deployment of SenShare within our building, which presently supports the operation of multiple sensing applications, including office occupancy monitoring and environmental monitoring.

The Cost of the "S" in HTTPS

Increased user concern over security and privacy on the Internet has led to widespread adoption of HTTPS, the secure version of HTTP. HTTPS authenticates the communicating end points and provides confidentiality for the ensuing communication. However, as with any security solution, it does not come for free. HTTPS may introduce overhead in terms of infrastructure costs, communication latency, data usage, and energy consumption. Moreover, given the opaqueness of the encrypted communication, any in-network value added services requiring visibility into application layer content, such as caches and virus scanners, become ineffective. This paper attempts to shed some light on these costs. First, taking advantage of datasets collected from large ISPs, we examine the accelerating adoption of HTTPS over the last three years. Second, we quantify the direct and indirect costs of this evolution. Our results show that, indeed, security does not come for free. This work thus aims to stimulate discussion on technologies that can mitigate the costs of HTTPS while still protecting the users privacy.

Extending Access Point Connectivity through Opportunistic Routing in Vehicular Networks

Abstract-Nowadays, the navigation systems available on cars are becoming more and more sophisticated. They greatly improve the experience of drivers and passengers by enabling them to receive map and traffic updates, news feeds, advertisements, media files, etc. Unfortunately, the bandwidth available to each vehicle with the current technology is severely limited. There have been many reports on the inability of 3G networks to cope with large size file downloads, especially in dense and mobile settings. A possible alternative is provided by WiFi access points (APs) that are being installed in several countries along the main routes and in popular areas. Although this approach significantly increases the available bandwidth, it still does not provide a fully satisfactory solution due to the limited transmission range (usually a few hundred meters). In this paper we present a novel routing protocol, based on opportunistic vehicle to vehicle communication, to enable efficient multi-hop routing capabilities between mobile vehicles and APs. Unlike prior work, this protocol fully supports two- way communication, i.e., the traditional vehicle-to-AP as well as the more challenging AP-to-vehicle. We leverage the information offered by the navigation system in terms of final destination and path, to i) route packets to the closest AP and ii) to route replies back to the moving vehicle efficiently.

Persistent content-based information dissemination in hybrid vehicular networks

Content-based information dissemination has a potential number of applications in vehicular networking, including advertising, traffic and parking notifications and emergency announcements. In this paper we describe a protocol for content based information dissemination in hybrid (i.e., partially structureless) vehicular networks. The protocol allows content to “stick” to areas where vehicles need to receive it. The vehicles subscriptions indicate the drivers interests about types of content and are used to filter and route information to affected vehicles. The publications, generated by other vehicles or by central servers, are first routed into the area, then continuously propagated for a specified time interval. The protocol takes advantage of both the infrastructure (i.e., wireless base stations), if this exists, and the decentralized vehicle-to-vehicle communication technologies. We evaluate our approach by simulation over a number of realistic vehicular traces based scenarios. Results show that our protocol achieves high message delivery while introducing low overhead, even in scenarios where no infrastructure is available.

SpotME If You Can: Randomized Responses for Location Obfuscation on Mobile Phones

Nowadays companies increasingly aggregate location data from different sources on the Internet to offer location-based services such as estimating current road traffic conditions, and finding the best nightlife locations in a city. However, these services have also caused outcries over privacy issues. As the volume of location data being aggregated expands, the comfort of sharing ones whereabouts with the public at large will unavoidably decrease. Existing ways of aggregating location data in the privacy literature are largely centralized in that they rely on a trusted location-based service. Instead, we propose a piece of software (Spot Me) that can run on a mobile phone and is able to estimate the number of people in geographic locations in a privacy-preserving way: accurate estimations are made possible in the presence of privacy-conscious users who report, in addition to their actual locations, a very large number of erroneous locations. The erroneous locations are selected by a randomized response algorithm. We evaluate the accuracy of Spot Me in estimating the number of people upon two very different realistic mobility traces: the mobility of vehicles in urban, suburban and rural areas, and the mobility of subway train passengers in Greater London. We find that erroneous locations have little effect on the estimations (in both traces, the error is below 18% for a situation in which more than 99% of the locations are erroneous), yet they guarantee that users cannot be localized with high probability. Also, the computational and storage overheads for a mobile phone running Spot Me are negligible, and the communication overhead is limited.

METIS: Exploring mobile phone sensing offloading for efficiently supporting social sensing applications

Mobile phones play a pivotal role in supporting ubiquitous and unobtrusive sensing of human activities. However, maintaining a highly accurate record of a users behavior throughout the day imposes significant energy demands on the phones battery. In this paper, we present the design, implementation, and evaluation of METIS: an adaptive mobile sensing platform that efficiently supports social sensing applications. The platform implements a novel sensor task distribution scheme that dynamically decides whether to perform sensing on the phone or in the infrastructure, considering the energy consumption, accuracy, and mobility patterns of the user. By comparing the sensing distribution scheme with sensing performed solely on the phone or exclusively on the fixed remote sensors, we show, through benchmarks using real traces, that the opportunistic sensing distribution achieves over 60% and 40% energy savings, respectively. This is confirmed through a real world deployment in an office environment for over a month: we developed a social application over our frameworks, that is able to infer the collaborations and meetings of the users. In this setting the system preserves over 35% more battery life over pure phone sensing.