Designing Storage and Privacy-Preserving Systems for Large-Scale Cloud Applications

Abstract

Today's mobile devices sense, collect, and store huge amounts of personal information, which users share with family and friends through a wide range of cloud applications. Many of these applications are large-scale -- they must support millions of users from all over the world. These applications must manage a massive amount of user-generated content, they must ensure that this content is always available, and they must protect users' privacy. To deal with the complexity of managing a large amount of data and ensure its availability, large-scale cloud applications rely on transactional, fault-tolerant, distributed storage systems. Latest hardware advancements and new design trends, such as in-memory storage, kernel-bypass message processing, and geo-distribution, have significantly improved the transaction processing times. However, they have also exposed overheads in the protocols used to implement these systems, which hinder their performance; specifically, existing protocols require unnecessary cross-datacenter and cross-processor coordination. This thesis introduces Meerkat}, a new replicated storage system that avoids all cross-core and cross-replica coordination for transactions that do not conflict. Moreover, replica recovery protocols that do not require persistent storage devices, are proposed; these protocols can be easily integrated with existing storage systems. Almost all applications offer their users a choice of privacy policies; unfortunately, they frequently violate these policies due to bugs or other reasons. Therefore, this thesis introduces SAFE, a privacy-preserving system that automatically enforces users' privacy policies on untrusted mobile-cloud applications. Our results demonstrate that SAFE is a practical way for users to create a chain of trust from their mobile devices to the cloud.