TRACCS: Trajectory-Aware Coordinated Urban Crowd-Sourcing

We investigate the problem of large-scale mobile crowd-tasking, where a large pool of citizen crowd-workers are used to perform a variety of location-specific urban logis-tics tasks. Current approaches to such mobile crowd-tasking are very decentralized: a crowd-tasking platform usually pro-vides each worker a set of available tasks close to the worker’s current location; each worker then independently chooses which tasks she wants to accept and perform. In contrast, we propose TRACCS, a more coordinated task assignment ap-proach, where the crowd-tasking platform assigns a sequence of tasks to each worker, taking into account their expected location trajectory over a wider time horizon, as opposed to just instantaneous location. We formulate such task assign-ment as an optimization problem, that seeks to maximize the total payoff from all assigned tasks, subject to a maximum bound on the detour (from the expected path) that a worker will experience to complete her assigned tasks. We develop credible computationally-efficient heuristics to address this optimization problem (whose exact solution requires solving a complex integer linear program), and show, via simulations with realistic topologies and commuting patterns, that a spe-cific heuristic (called Greedy-ILS) increases the fraction of assigned tasks by more than 20%, and reduces the average detour overhead by more than 60%, compared to the current decentralized approach

TASKer: Behavioral insights via campus-based experimental mobile crowd-sourcing

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

<p>Abstract</p> <p>Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD) protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN). DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP) distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW) protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.</p

Layered data aggregation in cell-phone based wireless sensor networks

The ubiquitous use of mobile phones motivates the idea of ‘participatory sensing’ with a cell-phone based sensor network. In our work, we consider a layered architecture for a query-based urban monitoring application using mobile phones. The key contribution of the paper is a Data-Aware Layered Waiting (DA-LW) time aggregation protocol in cell-phone based wireless sensor networks. To motivate the DA-LW protocol, we first develop a Cluster-Head (CH) based data aggregation protocol. The performance of the proposed protocols is evaluated in terms of energy, delay and resolution, which are primarily important for the monitoring application. Simulation results demonstrate the overall superiority in performance of the Data-Aware Layered Waiting algorithm over the Cluster-Head based algorithm.© IEE

CrowdLoc

Determining the location of a mobile user is central to several crowd-sensing applications. Using a Global Positioning System is not only power-hungry, but also unavailable in many locations. While there has been work on cellular-based localization, we consider an unexplored opportunity to improve location accuracy by combining cellular information across multiple mobile devices located near each other. For instance, this opportunity may arise in the context of public transport units having multiple travelers. Based on theoretical analysis and an extensive experimental study on several public transportation routes in two cities, we show that combining cellular information across nearby phones considerably improves location accuracy. Combining information across phones is especially useful when a phone has to use another phone’s fingerprint database, in a fingerprinting-based localization scheme. Both the median and 90 percentile errors reduce significantly. The location accuracy also improves irrespective of whether we combine information across phones connected to the same or different cellular operators. Sharing information across phones can raise privacy concerns. To address this, we have developed an id-free broadcast mechanism, using audio as a medium, to share information among mobile phones. We show that such communication can work effectively on smartphones, even in real-life, noisy-road conditions