Mobile Apps

1 .  STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

Technology : Android
IEEE2016-Location-based services are quickly becoming immensely popular. In addition to services based on users’ current location, many potential services rely on users’ location history, or their spatial-temporal provenance. Malicious users may lie about their spatial-temporal provenance without a carefully designed security system for users to prove their past locations. In this paper, we present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting.

2 .  SmartPhoto: A Resource-Aware Crowdsourcing Approach for Image Sensing with Smartphones

Technology : Android
IEEE2015-Photos obtained via crowdsourcing can be used in many critical applications. Due to the limitations of communication bandwidth, storage and processing capability, it is a challenge to transfer the huge amount of crowdsourced photos. To address this problem, we propose a framework, called SmartPhoto, to quantify the quality (utility) of crowd-sourced photos based on the accessible geographical and geo-metrical information (called metadata) including the smart-phone’s orientation, position and all related parameters of the built-in camera. From the metadata, we can infer where and how the photo is taken, and then only transmit the most useful photos.

3 .  Performance and Availability Modeling of IT Systems with Data Backup and Restore

Technology : Android
IEEE2015-In modern IT systems, data backup and restore operations are essential for providing protection against data loss from both natural and man-made incidents. On the other hand, data backup and restore operations can be resource-intensive and lead to performance degradation, or may require the system to be offline entirely. Therefore, it is important to properly choose backup and restore techniques and policies to ensure adequate data protection while minimizing the impact on system availability and performance. In this paper, we present an analytical modeling approach for such a purpose. We study a file service system that undergoes periodic data backups, and investigate metrics concerning system availability, data loss and rejection of user requests

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