Presented by:
Hong Lu
Nicholas D. Lane
Shane B. Eisenman
Andrew T. Campbell

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Abstract

We propose Bubble-Sensing, a new sensor network abstraction that allows mobile phones users to create a binding between tasks (e.g., take a photo, or sample audio every hour indefinitely) and the physical world at locations of interest, that remains active for a duration set by the user. We envision mobile phones being able to affix task bubbles at places of interest and then receive sensed data as it becomes available in a delay-tolerant fashion, in essence, creating a living documentary of places of interest in the physical world. The system relies on other mobile phones that opportunistically pass through bubble-sensing locations to acquire tasks and do the sensing on behalf of the initiator, and deliver the data to the bubblesensing server for retrieval by the user that initiated the task. We describe an implementation of the bubble-sensing system using sensor-enabled mobile phones, specifically, Nokia’s N80 and N95 (with GPS, accelerometers, microphone, camera). Task bubbles are maintained at locations through the interaction of “bubble carriers”, which carry the sensing task into the area of interest, and “bubble anchors”, which maintain the task bubble in the area when the bubble carrier is no longer present. In our implementation, bubble carriers and bubble anchors implement a number of simple mobile-phone based protocols that refresh the task bubble state as new mobile phones move through the area. Phones communicate using the local ad hoc 802.11g radio to transfer task state and maintain the task in the region of interest. This task bubble state is ephemeral and times out when no bubble carriers or bubble anchors are in the area. Our design is resilient to periods when no mobiles pass through the bubble-area and is capable of “reloading” the task into the bubble region. In this paper, we describe the bubble-sensing system and a simple proof of concept experiment.


Introduction

The mobile phone has become a ubiquitous tool for communications, computing, and increasingly, sensing. Many mobile phone and PDA models (e.g., Nokia’s N95 and 5500 Sport, Apple’s iPhone and iPod Touch, and Sony Ericsson’s W580 and W910) commercially released over the past couple years have integrated sensors (e.g., accelerometer, camera, microphone) that can be accessed programmatically, or support access to external sensor modules connected via Bluetooth. The sensed data gathered from these devices form the basis of a number of new architectures and applications We present the Bubble-Sensing system, that acts to support the persistent sensing of a particular location, as required by user requests. Conceptually, a user with a phone that has opted into the Bubble-Sensing system visits a location of interest, presses a button on his phone to affix the sensing request to the location, and then walks away. The sensing request persists at the location until the timeout set by the initiator is reached. This mechanism can be viewed as an application in its own right (e.g., a user slogging his life), and as a persistent sensing building block for other applications.

While the notion of virtually affixing sensor tasks to locations is appealing, it requires some work to implement this service on top of a cloud of human-carried phone-based sensors. First, since the mobility of the phones is uncontrolled - there is no guarantee that sensors will be well-placed to sample the desired location specified by the sensing task. Further, there is the issue of communicating the sensing task to potential sensers when they are well-positioned. This is made more difficult when, either due to hardware or user policy limitations, an always-on cellular page link and localization capabilities are not available on all phones. For example, wireless data access via EDGE, 3G, or open WiFi infrastructure is increasingly available, as is the location service via on-board GPS, WiFi, or cellular tower triangulation. However, for example, only a subset of mobile phones on the market have GPS and WiFi, and even when devices have all the required capabilities, users may disable the GPS and or limit data upload via WiFi and cellular data channels to manage privacy, energy consumption, and monetary cost.

Though the mobility in a people-centric sensor network is not controllable, it is also not random. In an urban sensing scenario, the visited areas of interest for one person are likely to be visited by many others (e.g., street corners, bus/subway stations, schools, restaurants, night clubs, etc.). We imagine a heterogeneous system where users are willing to share resources and data and to fulfill sensing tasks. Therefore, the bubble-sensing system opportunistically leverages other mobile phones as they pass by on behalf of a sensing task initiator. We adopt a two tier hardware architecture comprising the bubble server on the back end; and sensor-enabled mobile phones that can initiate sensing bubbles, maintain sensing bubbles in the designated location, replace bubbles that disappear due to phone mobility, enact the sampling as indicated by the sensing bubble, and report the sensed data back to the bubble server. Mobile phones participating in the bubble-sensing system take on one or more roles depending on their mobility characteristic, hardware capabilities, and user profiles. The bubble creator is the device whose user initiates the sensing request that leads to the creation of the sensing bubble. The bubble anchor keeps the bubble in the region of interest by broadcasting the sensing request. The sensing node perceives the bubble by listening to the broadcasts, takes samples within the area of interest according sensing request, and then uploads the results to the bubble server. The bubble carrier can help to restore a bubble if all bubble anchors are lost. The bubble server binds the results to the bubble, which can be queried by the bubble creator at any time.

We have implemented the bubble-sensing system using Nokia N95 mobile phones. In Section II, we describe the specific responsibilities of the virtual roles mentioned above and provide details on the communication protocols required to implement these roles. Sections III and IV decribes our current implementation and a preliminary evaluation of bubble-sensing using a N95 testbed, reporting on temporal sensing coverage, and on a measure of sensed data quality. In Section V, we investigate the performance of the system at scale and under a different mobility patter to extend our testbed results. We discuss related work from the pervasive and mobile ad hoc networking communities, including comparisons to alternative implementation choices, in Section VI. In Section VII, we discuss possibilities for extending the current work and offer
concluding remarks.

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for more details, please visit
http://cs.dartmouth.edu/~campbell/bubble-sensing.pdf