A budget feasible peer graded mechanism for iot-based crowdsourcing

We develop and extend a line of recent works on the design of mechanisms for heterogeneous tasks assignment problem in ’crowdsourcing’. The budgeted market we consider consists of multiple task requesters and multiple IoT devices as task executers. In this, each task requester is endowed with a single distinct task along with the publicly known budget. Also, each IoT device has valuations as the cost for executing the tasks and quality, which are private. Given such scenario, the objective is to select a subset of IoT devices for each task, such that the total payment made is within the allotted quota of the budget while attaining a threshold quality. For the purpose of determining the unknown quality of the IoT devices we have utilized the concept of peer grading. In this paper, we have carefully crafted a truthful budget feasible mechanism for the problem under investigation that also allows us to have the true information about the quality of the IoT devices. Further, we have extended the set-up considering the case where the tasks are divisible in nature and the IoT devices are working collaboratively, instead of, a single entity for executing each task. We have designed the budget feasible mechanisms for the extended versions. The simulations are performed in order to measure the efficacy of our proposed mechanismPeer ReviewedPostprint (author's final draft

FOUGERE: User-Centric Location Privacy in Mobile Crowdsourcing Apps

International audienceMobile crowdsourcing is being increasingly used by industrial and research communities to build realistic datasets. By leveraging the capabilities of mobile devices, mobile crowdsourcing apps can be used to track participants' activity and to collect insightful reports from the environment (e.g., air quality, network quality). However, most of existing crowdsourced datasets systematically tag data samples with time and location stamps, which may inevitably lead to user privacy leaks by discarding sensitive information. This paper addresses this critical limitation of the state of the art by proposing a software library that improves user privacy without compromising the overall quality of the crowdsourced datasets. We propose a decentralized approach, named Fougere, to convey data samples from user devices to third-party servers. By introducing an a priori data anonymization process, we show that Fougere defeats state-of-the-art location-based privacy attacks with little impact on the quality of crowd-sourced datasets

Embracing open innovation to acquire external ideas and technologies and to transfer internal ideas and technologies outside

The objective of this dissertation is to increase understanding of how organizations can embrace open innovation in order to acquire external ideas and technologies from outside the organization, and to transfer internal ideas and technologies to outside the organization. The objective encompasses six sub-objectives, each addressed in one or more substudies. Altogether, the dissertation consists of nine substudies and a compendium summarizing the substudies. An extensive literature review was conducted on open innovation and crowdsourcing literature (substudies 1–4). In the subsequent empirical substudies, both qualitative research methods (substudies 5–7) and quantitative research methods (substudies 8–9) were applied. The four literature review substudies provided insights on the body of knowledge on open innovation and crowdsourcing. These substudies unveiled most of the influential articles, authors, and journals of open innovation and crowdsourcing disciplines. Moreover, they identified research gaps in the current literature. The empirical substudies offer several insightful findings. Substudy 5 shows how non-core ideas and technologies of a large firm can become valuable, especially for small firms. Intermediary platforms can find solutions to many pressing problems of large organizations by engaging renowned scientists from all over world (substudy 6). Intermediary platforms can also bring breakthrough innovations with novel mechanisms (substudy 7). Large firms are not only able to garner ideas by engaging their customers through crowdsourcing but they can also build long-lasting relations with their customers (substudies 8 and 9). Embracing open innovation brings challenges for firms too. Firms need to change their organizational structures in order to be able to fully benefit from open innovation. When crowdsourcing is successful, it produces a very large number of new ideas. This has the consequence that firms need to allocate a significant amount of resources in order to identify the most promising ideas. In an idea contest, customarily, only one or a few best ideas are rewarded (substudy 7). Sometimes, no reward is provided for the selected idea (substudies 8 and 9). Most of the ideas that are received are not implemented in practice

A Low-Cost, Linux-Based Virtual Environment for Visualizing Vascular Structures

The analysis of morphometric data of the vasculature of any organ requires appropriate visualization methods to be applied due to the vast number of vessels that can be present in such data. In addition, the geometric properties of vessel segments, i.e. being rather long and thin, can make it difficult to judge on relative position, despite depth cues such as proper lighting and shading of the vessels. Virtual environments that provide true 3-D visualization of the data can help enhance the visual perception. Ideally, the system should be relatively cost-effective. Hence, this paper describes a Linux-based virtual environment that utilizes a 50 inch plasma screen as its main display. The overall cost of the entire system is less than $3,500 which is considerably less than other commercial systems. The system was successfully used for visualizing vascular data sets providing true three-dimensional perception of the morphometric data

Applying electromagnetic field theory concepts to clustering with constraints

This work shows how concepts from the electromagnetic field theory can be efficiently used in clustering with constraints. The proposed framework transforms vector data into a fully connected graph, or just works straight on the given graph data. User constraints are represented by electromagnetic fields that affect the weight of the graph's edges. A clustering algorithm is then applied on the adjusted graph, using k-distinct shortest paths as the distance measure. Our framework provides better accuracy compared to MPCK-Means, SS-Kernel-KMeans and Kmeans+Diagonal Metric even when very few constraints are used, significantly improves clustering performance on some datasets that other methods fail to partition successfully, and can cluster both vector and graph datasets. All these advantages are demonstrated through thorough experimental evaluation. © 2009 Springer

A Novel Distributed Framework For Optimizing Query Routing Trees In Wireless Sensor Networks Via Optimal Operator Placement

In this paper, we focus the attention on the operator placement problem in Wireless Sensor Networks (WSN). This problem is very relevant for in-network query processing over WSN, where query routing trees are decomposed into three sub-components that must be processed at query time, namely operator tree, operator placement assignment scheme and routing scheme. In particular, the operator placement assignment defines on which node of the network each (query) operator will be hosted and executed. Hence, operator placement plays a key role in the context of query optimization issues in WSN research. In line with this main motivation, in this paper we present an optimal distributed algorithm to adapt the placement of a single operator in high communication cost networks, such as a wireless sensor network. Our parameter-free algorithm finds the optimal node to host the operator with minimum communication cost overhead. Three techniques, proposed here, make this feature possible: (1) identifying the special, and most frequent case, where no flooding is needed, otherwise (2) limitation of the neighborhood to be flooded and (3) variable speed flooding and eves-dropping. When no flooding is needed the communication cost overhead for adapting the operator placement is negligible. In addition, our algorithm does not require any extra communication cost while the query is executed. In our experiments we show that for the rest of cases our algorithm saves 30%\u201385% of the energy compared to previously proposed techniques. To our knowledge this is the first optimal and distributed algorithm to solve the 1-median (Fermat node) problem. A comprehensive experimental evaluation and the proposal of two solutions that are capable of dealing with adaptive properties of the operator placement problem, which is an innovative perspective of research in this scientific field, represent two further contributions of our research

A novel distributed framework for optimizing query routing trees in wireless sensor networks via optimal operator placement

In this paper, we focus the attention on the operator placement problem in Wireless Sensor Networks (WSN). This problem is very relevant for in-network query processing over WSN, where query routing trees are decomposed into three sub-components that must be processed at query time, namely operator tree, operator placement assignment scheme and routing scheme. In particular, the operator placement assignment defines on which node of the network each (query) operator will be hosted and executed. Hence, operator placement plays a key role in the context of query optimization issues in WSN research. In line with this main motivation, in this paper we present an optimal distributed algorithm to adapt the placement of a single operator in high communication cost networks, such as a wireless sensor network. Our parameter-free algorithm finds the optimal node to host the operator with minimum communication cost overhead. Three techniques, proposed here, make this feature possible: (1) identifying the special, and most frequent case, where no flooding is needed, otherwise (2) limitation of the neighborhood to be flooded and (3) variable speed flooding and eves-dropping. When no flooding is needed the communication cost overhead for adapting the operator placement is negligible. In addition, our algorithm does not require any extra communication cost while the query is executed. In our experiments we show that for the rest of cases our algorithm saves 30%-85% of the energy compared to previously proposed techniques. To our knowledge this is the first optimal and distributed algorithm to solve the 1-median (Fermat node) problem. A comprehensive experimental evaluation and the proposal of two solutions that are capable of dealing with adaptive properties of the operator placement problem, which is an innovative perspective of research in this scientific field, represent two further contributions of our research. © 2012 Published by Elsevier Inc