Immersion on the Edge: A Cooperative Framework for Mobile Immersive Computing

Immersive computing (IC) technologies such as virtual reality and augmented reality are gaining tremendous popularity. In this poster, we present CoIC, a Cooperative framework for mobile Immersive Computing. The design of CoIC is based on a key insight that IC tasks among different applications or users might be similar or redundant. CoIC enhances the performance of mobile IC applications by caching and sharing computation-intensive IC results on the edge. Our preliminary evaluation results on an AR application show that CoIC can reduce the recognition and rendering latency by up to 52.28% and 75.86% respectively on current mobile devices.Comment: This poster has been accepted by the SIGCOMM in June 201

The Effect of Switching Costs on the Satisfaction-Continuance Relationship: An Extension of Expectation-Confirmation Model

The expectation-confirmation model (ECM) has been applied to investigate the satisfaction with and continuance of information technology (IT) after its adoption. However, the ECM assumes that the satisfaction-continuance relationship is linear. In the electronics market, however, such a linear relationship may be susceptible to the influence of new variants unique to the Internet. In addition, the ECM-based satisfaction-continuance relationship explains psychological motives for IS continuance nicely, but its framework is insufficient to capture the non-psychological dimensions of IS continuance intention. Subsequently, the inclusion of switching costs, which has been frequently proposed as a determinant of loyalty and a moderator of the satisfaction-loyalty relationship, as a construct of ECM may enrich our understanding of the continuance and the satisfaction-continuance relationship of online services. The addition of switching costs can also improve the theoretical completeness of the model, particularly in the online services context

An Empirical Investigation of Bidding Strategies and Their Effects on Online Single-Unit Auctions

Online bidding strategy is one of the most discussed topics in online auction research. This research aims to empirically confirm online bidding strategies in single-unit auctions and evaluate these strategies in the context of auction winning outcome, final price evaluation, and perceived enjoyment. Both objective and subjective data of online single-unit auctions were collected to validate our postulated hypotheses. Our findings suggest that there are three basic bidding strategies in single-unit auctions and they indeed have different impacts on auction biddings

A Linear Network Code Construction for General Integer Connections Based on the Constraint Satisfaction Problem

The problem of finding network codes for general connections is inherently difficult in capacity constrained networks. Resource minimization for general connections with network coding is further complicated. Existing methods for identifying solutions mainly rely on highly restricted classes of network codes, and are almost all centralized. In this paper, we introduce linear network mixing coefficients for code constructions of general connections that generalize random linear network coding (RLNC) for multicast connections. For such code constructions, we pose the problem of cost minimization for the subgraph involved in the coding solution and relate this minimization to a path-based Constraint Satisfaction Problem (CSP) and an edge-based CSP. While CSPs are NP-complete in general, we present a path-based probabilistic distributed algorithm and an edge-based probabilistic distributed algorithm with almost sure convergence in finite time by applying Communication Free Learning (CFL). Our approach allows fairly general coding across flows, guarantees no greater cost than routing, and shows a possible distributed implementation. Numerical results illustrate the performance improvement of our approach over existing methods.Comment: submitted to TON (conference version published at IEEE GLOBECOM 2015

Sorry seems to be the hardest word : the effect of self-attribution when apologizing for a brand crisis

When apologizing for a product failure, self-attribution by a business inevitably affects consumer attitude and behavior. This study draws from the dissonance-attribution model and investigates the effect of self-attribution in apologies on consumers\u27 brand attitude. Using a 2x2 experiment, the results show that internal attribution generates significant change in brand attitude in a positive direction, while external attribution leads to negative change in brand attitude. Dispositional attribution leads to significantly more positive brand attitude than situational attribution. Internal/dispositional attribution produces significantly more positive effect on consumer attitude than the other three types of attribution. Moreover, perceived risk is found to mediate the relationship between attributions and brand attitude, and such mediating effect is moderated by consumers\u27 corporate associations. Clearly, how a company apologizes for a product crisis makes a big difference in the effectiveness of recovery strategies to restore consumer confidence