Quantifying Eventual Consistency with PBS

Data replication results in a fundamental trade-off between operation latency and consistency. At the weak end of the spectrum of possible consistency models is eventual consistency, which provides no limit to the staleness of data returned. However, anecdotally, eventual consistency is often “good enough ” for practitioners given its latency and availability benefits. In this work, we explain this phenomenon and demonstrate that, despite their weak guarantees, eventually consistent systems regularly return consistent data while providing lower latency than their strongly consistent counterparts. To quantify the behavior of eventually consistent stores, we introduce Probabilistically Bounded Staleness (PBS), a consistency model that provides expected bounds on data staleness with respect to both versions and wall clock time. We derive a closed-form solution for version-based staleness and model real-time staleness for a large class of quorum replicated, Dynamo-style stores. Using PBS, we measure the trade-off between latency and consistency for partial, non-overlapping quorum systems under Internet production workloads. We quantitatively demonstrate how and why eventually consistent systems frequently return consistent data within tens of milliseconds while offering large latency benefits. 1

Supporting disconnected operations in mobile computing

Mobile computing has enabled users to seamlessly access databases even when they are on the move. However, in the absence of readily available high-quality communication, users are often forced to operate disconnected from the network. As a result, software applications have to be redesigned to take advantage of this environment while accommodating the new challenges posed by mobility. In particular, there is a need for replication and synchronization services in order to guarantee availability of data and functionality, (including updates) in disconnected mode. To this end we propose a scalable and highly available data replication and management service. The proposed replication technique is compared with a baseline replication technique and shown to exhibit high availability, fault tolerance and minimal access times of the data and services, which are very important in an environment with low-quality communication links.<br /

Consistency Management Strategies for Data Replication in Mobile Ad Hoc Networks

In a mobile ad hoc network, data replication drastically improves data availability. However, since mobile hosts\u27 mobility causes frequent network partitioning, consistency management of data operations on replicas becomes a crucial issue. In such an environment, the global consistency of data operations on replicas is not desirable by many applications. Thus, new consistency maintenance based on local conditions such as location and time need to be investigated. This paper attempts to classify different consistency levels according to requirements from applications and provides protocols to realize them. We report simulation results to investigate the characteristics of these consistency protocols in a mobile ad hoc network

Towards robust and reliable multimedia analysis through semantic integration of services

Thanks to ubiquitous Web connectivity and portable multimedia devices, it has never been so easy to produce and distribute new multimedia resources such as videos, photos, and audio. This ever-increasing production leads to an information overload for consumers, which calls for efficient multimedia retrieval techniques. Multimedia resources can be efficiently retrieved using their metadata, but the multimedia analysis methods that can automatically generate this metadata are currently not reliable enough for highly diverse multimedia content. A reliable and automatic method for analyzing general multimedia content is needed. We introduce a domain-agnostic framework that annotates multimedia resources using currently available multimedia analysis methods. By using a three-step reasoning cycle, this framework can assess and improve the quality of multimedia analysis results, by consecutively (1) combining analysis results effectively, (2) predicting which results might need improvement, and (3) invoking compatible analysis methods to retrieve new results. By using semantic descriptions for the Web services that wrap the multimedia analysis methods, compatible services can be automatically selected. By using additional semantic reasoning on these semantic descriptions, the different services can be repurposed across different use cases. We evaluated this problem-agnostic framework in the context of video face detection, and showed that it is capable of providing the best analysis results regardless of the input video. The proposed methodology can serve as a basis to build a generic multimedia annotation platform, which returns reliable results for diverse multimedia analysis problems. This allows for better metadata generation, and improves the efficient retrieval of multimedia resources

Enabling Data Security and Privacy for Database Services in the Cloud

Substantial advances in cloud technologies have made outsourcing data to the cloud highly beneficial today (e.g., costs savings, scalability, provisioning time). However, strong concerns from private companies and public institutions about the security of the outsourced data still hamper the adoption of cloud solutions. This reluctance is fed by frequent massive data breaches either caused by external attacks against cloud service providers or by negligent or opaque practices from the service provider itself. For broader adoption of cloud services, this dissertation addresses the data security and privacy concerns in the cloud setting. The goal is to ensure security and privacy of outsourced data while maintaining the ability to execute queries efficiently. Security/privacy comes at a cost of functionality/performance. Therefore, we seek for a proper balance in the space of security, privacy, functionality, and performance. This dissertation works the problems of range query execution over encrypted data, privacy preserving data mining in the context of environmental sustainability studies, and access privacy in the cloud. To enable efficient and secure range query processing over traditional databases, we introduce PINED-RQ, a highly efficient and differentially private range query execution framework that constructs a novel differentially private index over an outsourced database. Second, this dissertation presents a comprehensive study of the environmental sustainability metrics. Our contributions in this context are twofold: 1) to better evaluate the environmental impacts of the industrial processes privately, we formally define privacy preserving certification paradigm and develop a framework that enables untrusted third party to certify parties based on a well agreed upon set of criteria. 2) to explore the privacy concerns over publicizing the industrial activities in the form of life cycle assessment (LCA) computations, which is a standard way of evaluating an impact of a product and service. This dissertation initiates a study to explore privacy and security challenges that prevent organizations from making public disclosures about their activities. Finally, this dissertation explores access privacy in the cloud setting. We design and develop TaoStore, a highly efficient and practical cloud data store, which secures data confidentiality and hides access patterns from adversaries. Additionally, we propose a new ORAM security model, called aaob-security, which considers completely asynchronous network communication and concurrent processing of requests. This dissertation shows that it is possible to deliver practical and high-performance data services in the cloud without sacrificing securityand privacy if the requirements of each application are analyzed correctly and a correct balance is found in the space of security, privacy, functionality, and performance