Do individuals recognize cascade behavior of others? An Experimental Study

In an information cascade experiment participants are confronted with artificial predecessors predicting in line with the BHW model (Bikchandani et al., 1992). Using the BDM (Becker et al., 1964) mechanism we study participants' probability perceptions based on maximum prices for participating in the prediction game. We find increasing maximum prices the more coinciding predictions of predecessors are observed, regardless of whether additional information is revealed by these predictions. Individual price patterns of more than two thirds of the participants indicate that cascade behavior of predecessors is not recognized

Parallel Hierarchical Affinity Propagation with MapReduce

The accelerated evolution and explosion of the Internet and social media is generating voluminous quantities of data (on zettabyte scales). Paramount amongst the desires to manipulate and extract actionable intelligence from vast big data volumes is the need for scalable, performance-conscious analytics algorithms. To directly address this need, we propose a novel MapReduce implementation of the exemplar-based clustering algorithm known as Affinity Propagation. Our parallelization strategy extends to the multilevel Hierarchical Affinity Propagation algorithm and enables tiered aggregation of unstructured data with minimal free parameters, in principle requiring only a similarity measure between data points. We detail the linear run-time complexity of our approach, overcoming the limiting quadratic complexity of the original algorithm. Experimental validation of our clustering methodology on a variety of synthetic and real data sets (e.g. images and point data) demonstrates our competitiveness against other state-of-the-art MapReduce clustering techniques

Remote software upload techniques in future vehicles and their performance analysis

Updating software in vehicle Electronic Control Units (ECUs) will become a mandatory requirement for a variety of reasons, for examples, to update/fix functionality of an existing system, add new functionality, remove software bugs and to cope up with ITS infrastructure. Software modules of advanced vehicles can be updated using Remote Software Upload (RSU) technique. The RSU employs infrastructure-based wireless communication technique where the software supplier sends the software to the targeted vehicle via a roadside Base Station (BS). However, security is critically important in RSU to avoid any disasters due to malfunctions of the vehicle or to protect the proprietary algorithms from hackers, competitors or people with malicious intent. In this thesis, a mechanism of secure software upload in advanced vehicles is presented which employs mutual authentication of the software provider and the vehicle using a pre-shared authentication key before sending the software. The software packets are sent encrypted with a secret key along with the Message Digest (MD). In order to increase the security level, it is proposed the vehicle to receive more than one copy of the software along with the MD in each copy. The vehicle will install the new software only when it receives more than one identical copies of the software. In order to validate the proposition, analytical expressions of average number of packet transmissions for successful software update is determined. Different cases are investigated depending on the vehicle\u27s buffer size and verification methods. The analytical and simulation results show that it is sufficient to send two copies of the software to the vehicle to thwart any security attack while uploading the software. The above mentioned unicast method for RSU is suitable when software needs to be uploaded to a single vehicle. Since multicasting is the most efficient method of group communication, updating software in an ECU of a large number of vehicles could benefit from it. However, like the unicast RSU, the security requirements of multicast communication, i.e., authenticity, confidentiality and integrity of the software transmitted and access control of the group members is challenging. In this thesis, an infrastructure-based mobile multicasting for RSU in vehicle ECUs is proposed where an ECU receives the software from a remote software distribution center using the road side BSs as gateways. The Vehicular Software Distribution Network (VSDN) is divided into small regions administered by a Regional Group Manager (RGM). Two multicast Group Key Management (GKM) techniques are proposed based on the degree of trust on the BSs named Fully-trusted (FT) and Semi-trusted (ST) systems. Analytical models are developed to find the multicast session establishment latency and handover latency for these two protocols. The average latency to perform mutual authentication of the software vendor and a vehicle, and to send the multicast session key by the software provider during multicast session initialization, and the handoff latency during multicast session is calculated. Analytical and simulation results show that the link establishment latency per vehicle of our proposed schemes is in the range of few seconds and the ST system requires few ms higher time than the FT system. The handoff latency is also in the range of few seconds and in some cases ST system requires less handoff time than the FT system. Thus, it is possible to build an efficient GKM protocol without putting too much trust on the BSs

Do individuals recognize cascade behavior of others? An Experimental Study

In an information cascade experiment participants are confronted with artificial predecessors predicting in line with the BHW model (Bikchandani et al., 1992). Using the BDM (Becker et al., 1964) mechanism we study participants' probability perceptions based on maximum prices for participating in the prediction game. We find increasing maximum prices the more coinciding predictions of predecessors are observed, regardless of whether additional information is revealed by these predictions. Individual price patterns of more than two thirds of the participants indicate that cascade behavior of predecessors is not recognized.information cascades; Bayes' Rule; decision under risk and uncertainty; experimental economics

Do Individuals Recognize Cascade Behavior of Others? - An Experimental Study -

In an information cascade experiment participants are confronted with artificial predecessors predicting in line with the BHW model (Bikchandani et al., 1992). Using the BDM (Becker et al., 1964) mechanism we study participants' probability perceptions based on maximum prices for participating in the prediction game. We find increasing maximum prices the more coinciding predictions of predecessors are observed, regardless of whether additional information is revealed by these predictions. Individual price patterns of more than two thirds of the participants indicate that cascade behavior of predecessors is not recognized.Information Cascades, Bayes' Rule, Decision Under Risk and Uncertainty, Experimental Economics.