245 research outputs found
Adaptive routing for intermittently connected mobile ad hoe networks
The vast majority of mobile ad hoc networking research makes a very large assumption: that communication can only take place between nodes that are simultaneously accessible within in the same connected cloud (i.e., that communication is synchronous). In reality, this assumption is likely to be a poor one, particularly for sparsely or irregularly populated environments.In this paper we present the Context-Aware Routing (CAR) algorithm. CAR is a novel approach to the provision of asynchronous communication in partially-connected mobile ad hoc networks, based on the intelligent placement of messages. We discuss the details of the algorithm, and then present simulation results demonstrating that it is possible for nodes to exploit context information in making local decisions that lead to good delivery ratios and latencies with small overheads.</p
Exploiting Temporal Complex Network Metrics in Mobile Malware Containment
Malicious mobile phone worms spread between devices via short-range Bluetooth
contacts, similar to the propagation of human and other biological viruses.
Recent work has employed models from epidemiology and complex networks to
analyse the spread of malware and the effect of patching specific nodes. These
approaches have adopted a static view of the mobile networks, i.e., by
aggregating all the edges that appear over time, which leads to an approximate
representation of the real interactions: instead, these networks are inherently
dynamic and the edge appearance and disappearance is highly influenced by the
ordering of the human contacts, something which is not captured at all by
existing complex network measures. In this paper we first study how the
blocking of malware propagation through immunisation of key nodes (even if
carefully chosen through static or temporal betweenness centrality metrics) is
ineffective: this is due to the richness of alternative paths in these
networks. Then we introduce a time-aware containment strategy that spreads a
patch message starting from nodes with high temporal closeness centrality and
show its effectiveness using three real-world datasets. Temporal closeness
allows the identification of nodes able to reach most nodes quickly: we show
that this scheme can reduce the cellular network resource consumption and
associated costs, achieving, at the same time, a complete containment of the
malware in a limited amount of time.Comment: 9 Pages, 13 Figures, In Proceedings of IEEE 12th International
Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM '11
The Anatomy of a Scientific Rumor
The announcement of the discovery of a Higgs boson-like particle at CERN will
be remembered as one of the milestones of the scientific endeavor of the 21st
century. In this paper we present a study of information spreading processes on
Twitter before, during and after the announcement of the discovery of a new
particle with the features of the elusive Higgs boson on 4th July 2012. We
report evidence for non-trivial spatio-temporal patterns in user activities at
individual and global level, such as tweeting, re-tweeting and replying to
existing tweets. We provide a possible explanation for the observed
time-varying dynamics of user activities during the spreading of this
scientific "rumor". We model the information spreading in the corresponding
network of individuals who posted a tweet related to the Higgs boson discovery.
Finally, we show that we are able to reproduce the global behavior of about
500,000 individuals with remarkable accuracy.Comment: 11 pages, 8 figure
Epcast: Controlled Dissemination in Human-based Wireless Networks by means of Epidemic Spreading Models
Epidemics-inspired techniques have received huge attention in recent years
from the distributed systems and networking communities. These algorithms and
protocols rely on probabilistic message replication and redundancy to ensure
reliable communication. Moreover, they have been successfully exploited to
support group communication in distributed systems, broadcasting, multicasting
and information dissemination in fixed and mobile networks. However, in most of
the existing work, the probability of infection is determined heuristically,
without relying on any analytical model. This often leads to unnecessarily high
transmission overheads.
In this paper we show that models of epidemic spreading in complex networks
can be applied to the problem of tuning and controlling the dissemination of
information in wireless ad hoc networks composed of devices carried by
individuals, i.e., human-based networks. The novelty of our idea resides in the
evaluation and exploitation of the structure of the underlying human network
for the automatic tuning of the dissemination process in order to improve the
protocol performance. We evaluate the results using synthetic mobility models
and real human contacts traces
Spatio-temporal networks: reachability, centrality and robustness
Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks
Fatal attraction: identifying mobile devices through electromagnetic emissions
Smartphones are increasingly augmented with sensors for a variety of purposes. In this paper, we show how magnetic field emissions can be used to fingerprint smartphones. Previous work on identification rely on specific characteristics that vary with the settings and components available on a device. This limits the number of devices on which one approach is effective. By contrast, all electronic devices emit a magnetic field which is accessible either through the API or measured through an external device.
We conducted an in-the-wild study over four months and collected mobile sensor data from 175 devices. In our experiments we observed that the electromagnetic field measured by the magnetometer identifies devices with an accuracy of 98.9%. Furthermore, we show that even if the sensor was removed from the device or access to it was discontinued, identification would still be possible from a secondary device in close proximity to the target. Our findings suggest that the magnetic field emitted by smartphones is unique and fingerprinting devices based on this feature can be performed without the knowledge or cooperation of users
Precise time-matching in chimpanzee allogrooming does not occur after a short delay
Allogrooming is a key aspect of chimpanzee sociality and many studies have investigated the role of reciprocity in a biological market. One theoretical form of reciprocity is time-matching, where payback consists of an equal duration of effort (e.g. twenty seconds of grooming repaid with twenty seconds of grooming). Here, we report a study of allogrooming in a group of twenty-six captive chimpanzees (Chester Zoo, UK), based on more than 150 hours of data. For analysis, we introduce a methodological innovation called the "Delta scale", which unidimensionally measures the accuracy of time-matching according to the extent of delay after the cessation of grooming. Delta is positive when reciprocation occurs after any non-zero delay (e.g. A grooms B and then B grooms A after a five second break) and it is negative when reciprocation begins whilst the original grooming has not yet ceased. Using a generalized linear mixed-method, we found evidence for time matched reciprocation. However, this was true only for immediate reciprocation (Delta less than zero). If there was a temporal break in grooming between two members of a dyad, then there was no evidence that chimpanzees were using new bouts to retroactively correct for time-matching imbalances from previous bouts. Our results have implications for some of the cognitive constraints that differentiate real-life reciprocation from abstract theoretical models. Furthermore, we suggest that some apparent patterns of time-matched reciprocity may arise merely due to the law of large numbers, and we introduce a statistical test which takes this into account when aggregating grooming durations over a window of time
FutureWare: Designing a Middleware for Anticipatory Mobile Computing
Ubiquitous computing is moving from context-awareness to context-prediction. In order to build truly anticipatory systems
developers have to deal with many challenges, from multimodal sensing to modeling context from sensed data, and, when necessary,
coordinating multiple predictive models across devices. Novel expressive programming interfaces and paradigms are needed for this
new class of mobile and ubiquitous applications.
In this paper we present FutureWare, a middleware for seamless development of mobile applications that rely on context prediction.
FutureWare exposes an expressive API to lift the burden of mobile sensing, individual and group behavior modeling, and future context
querying, from an application developer. We implement FutureWare as an Android library, and through a scenario-based testing and a
demo app we show that it represents an efficient way of supporting anticipatory applications, reducing the necessary coding effort by
two orders of magnitude
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