Social hierarchy and stratification among humans is a well studied concept in sociology. The popularity of online social networks presents an opportunity to study social hierarchy for different types of networks and at different scales. We adopt the premise that people form connections in a social network based on their perceived social hierarchy; as a result, the edge directions in directed social networks can be leveraged to infer hierarchy. In this paper, we define a measure of hierarchy in a directed online social network, and present an efficient algorithm to compute this measure. We validate our measure using ground truth including Wikipedia notability score. We use this measure to study hierarchy in several directed online social networks including Twitter, Delicious, YouTube, Flickr, LiveJournal, and curated lists of several categories of people based on different occupations, and different organizations. Our experiments on different online social networks show how hierarchy emerges as we increase the size of the network. This is in contrast to random graphs, where the hierarchy decreases as the network size increases. Further, we show that the degree of stratification in a network increases very slowly as we increase the size of the graph.

To usefully query a location-based service, a mobile device must typically present its own location in its query to the server. This may not be acceptable to clients that wish to protect the privacy of their location. This paper presents the design and implementation of SybilQuery, a fully decentralized and autonomous k-anonymity-based scheme to privately query location-based services. SybilQuery is a client-side tool that generates k − 1 Sybil queries for each query by the client. The location-based server is presented with a set of k queries and is unable to distinguish between the client's query and the Sybil queries, thereby achieving k-anonymity. We tested our implementation of SybilQuery on real mobility traces of approximately 500 cabs in the San Francisco Bay area. Our experiments show that SybilQuery can efficiently generate Sybil queries and that these queries are indistinguishable from real queries.

VANETs (vehicular ad hoc networks)

Abstract-Traffic querying, road sensing and mobile content delivery are emerging application domains for vehicular networks whose performance depends on the throughput these networks can sustain. Rate adaptation is one of the key mechanisms at the link layer that determine this performance. Rate adaptation in vehicular networks faces the following key challenges: (1) due to the rapid variations of the link quality caused by fading and mobility at vehicular speeds, the transmission rate must adapt fast in order to be effective, (2) during infrequent and bursty transmission, the rate adaptation scheme must be able to estimate the link quality with few or no packets transmitted in the estimation window, (3) the rate adaptation scheme must distinguish losses due to environment from those due to hiddenstation induced collision. Our extensive outdoor experiments show that the existing rate adaptation schemes for 802.11 wireless networks underutilize the link capacity in vehicular environments. In this paper, we design, implement and evaluate CARS, a novel Context-Aware Rate Selection algorithm that makes use of context information (e.g. vehicle speed and distance from neighbor) to systematically address the above challenges, while maximizing the link throughput. Our experimental evaluation in real outdoor vehicular environments with different mobility scenarios shows that CARS adapts to changing link conditions at high vehicular speeds faster than existing rate-adaptation algorithms. Our scheme achieves significantly higher throughput, up to 79%, in all the tested scenarios, and is robust to packet loss due to collisions, improving the throughput by up to 256% in the presence of hidden stations.

Abstract-In this paper we present empirical results from a study examining the effects of antenna diversity and placement on vehicle-to-vehicle link performance in vehicular ad hoc networks. The experiments use roofand in-vehicle mounted omni-directional antennas and IEEE 802.11a radios operating in the 5GHz band, which is of interest for planned inter-vehicular communication standards. Our main findings are two-fold. First, we show that radio reception performance is sensitive to antenna placement in the 5Ghz band. Second, our results show that, surprisingly, a packet level selection diversity scheme using multiple antennas and radios, Multi-Radio Packet Selection (MRPS), improves performance not only in a fading channel but also in line-of-sight conditions. This is due to propagation being affected by car geometry, leading to the highly non-uniform antenna patterns. These patterns are very sensitive to the exact antenna position on the roof, for example at a transmit power of 40mW the line-of-sight communication range varied between 50 and 250m depending on the orientation of the cars. These findings have implications for vehicular MAC protocol design. Protocols may have to cope with an increased number of hidden nodes due to the directional antenna patterns. However, car makers can reduce these effects through careful antenna placement and diversity.