939 research outputs found
Participatory sensing as an enabler for self-organisation in future cellular networks
In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells
Earthquake Early Warning and Beyond: Systems Challenges in Smartphone-based Seismic Network
Earthquake Early Warning (EEW) systems can effectively reduce fatalities,
injuries, and damages caused by earthquakes. Current EEW systems are mostly
based on traditional seismic and geodetic networks, and exist only in a few
countries due to the high cost of installing and maintaining such systems. The
MyShake system takes a different approach and turns people's smartphones into
portable seismic sensors to detect earthquake-like motions. However, to issue
EEW messages with high accuracy and low latency in the real world, we need to
address a number of challenges related to mobile computing. In this paper, we
first summarize our experience building and deploying the MyShake system, then
focus on two key challenges for smartphone-based EEW (sensing heterogeneity and
user/system dynamics) and some preliminary exploration. We also discuss other
challenges and new research directions associated with smartphone-based seismic
network.Comment: 6 pages, conference paper, already accepted at hotmobile 201
IoT Maps : Charting the Internet of Things
Internet of Things (IoT) devices are becoming increasingly ubiquitous in our everyday environments. While the number of devices and the degree of connectivity is growing, it is striking that as a society we are increasingly unaware of the locations and purposes of such devices. Indeed, much of the IoT technology being deployed is invisible and does not communicate its presence or purpose to the inhabitants of the spaces within which it is deployed. In this paper, we explore the potential benefits and challenges of constructing IoT maps that record the location of IoT devices. To illustrate the need for such maps, we draw on our experiences from multiple deployments of IoT systems.Peer reviewe
Defending against Sybil Devices in Crowdsourced Mapping Services
Real-time crowdsourced maps such as Waze provide timely updates on traffic,
congestion, accidents and points of interest. In this paper, we demonstrate how
lack of strong location authentication allows creation of software-based {\em
Sybil devices} that expose crowdsourced map systems to a variety of security
and privacy attacks. Our experiments show that a single Sybil device with
limited resources can cause havoc on Waze, reporting false congestion and
accidents and automatically rerouting user traffic. More importantly, we
describe techniques to generate Sybil devices at scale, creating armies of
virtual vehicles capable of remotely tracking precise movements for large user
populations while avoiding detection. We propose a new approach to defend
against Sybil devices based on {\em co-location edges}, authenticated records
that attest to the one-time physical co-location of a pair of devices. Over
time, co-location edges combine to form large {\em proximity graphs} that
attest to physical interactions between devices, allowing scalable detection of
virtual vehicles. We demonstrate the efficacy of this approach using
large-scale simulations, and discuss how they can be used to dramatically
reduce the impact of attacks against crowdsourced mapping services.Comment: Measure and integratio
Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges
Today's mobile phones are far from mere communication devices they were ten
years ago. Equipped with sophisticated sensors and advanced computing hardware,
phones can be used to infer users' location, activity, social setting and more.
As devices become increasingly intelligent, their capabilities evolve beyond
inferring context to predicting it, and then reasoning and acting upon the
predicted context. This article provides an overview of the current state of
the art in mobile sensing and context prediction paving the way for
full-fledged anticipatory mobile computing. We present a survey of phenomena
that mobile phones can infer and predict, and offer a description of machine
learning techniques used for such predictions. We then discuss proactive
decision making and decision delivery via the user-device feedback loop.
Finally, we discuss the challenges and opportunities of anticipatory mobile
computing.Comment: 29 pages, 5 figure
- …