Interactive Consistency in practical, mostly-asynchronous systems

Interactive consistency is the problem in which n nodes, where up to t may be byzantine, each with its own private value, run an algorithm that allows all non-faulty nodes to infer the values of each other node. This problem is relevant to critical applications that rely on the combination of the opinions of multiple peers to provide a service. Examples include monitoring a content source to prevent equivocation or to track variability in the content provided, and resolving divergent state amongst the nodes of a distributed system. Previous works assume a fully synchronous system, where one can make strong assumptions such as negligible message delivery delays and/or detection of absent messages. However, practical, real-world systems are mostly asynchronous, i.e., they exhibit only some periods of synchrony during which message delivery is timely, thus requiring a different approach. In this paper, we present a thorough study on practical interactive consistency. We leverage the vast prior work on broadcast and byzantine consensus algorithms to design, implement and evaluate a set of algorithms, with varying timing assumptions and message complexity, that can be used to achieve interactive consistency in real-world distributed systems. We provide a complete, open-source implementation of each proposed interactive consistency algorithm by building a multi-layered stack of protocols that include several broadcast protocols, as well as a binary and a multi-valued consensus protocol. Most of these protocols have never been implemented and evaluated in a real system before. We analyze the performance of our suite of algorithms experimentally by engaging in both single instance and multiple parallel instances of each alternative.Comment: 13 pages, 10 figure

Teaching Concurrent Software Design: A Case Study Using Android

In this article, we explore various parallel and distributed computing topics from a user-centric software engineering perspective. Specifically, in the context of mobile application development, we study the basic building blocks of interactive applications in the form of events, timers, and asynchronous activities, along with related software modeling, architecture, and design topics.Comment: Submitted to CDER NSF/IEEE-TCPP Curriculum Initiative on Parallel and Distributed Computing - Core Topics for Undergraduate

Incremental Consistency Guarantees for Replicated Objects

Programming with replicated objects is difficult. Developers must face the fundamental trade-off between consistency and performance head on, while struggling with the complexity of distributed storage stacks. We introduce Correctables, a novel abstraction that hides most of this complexity, allowing developers to focus on the task of balancing consistency and performance. To aid developers with this task, Correctables provide incremental consistency guarantees, which capture successive refinements on the result of an ongoing operation on a replicated object. In short, applications receive both a preliminary---fast, possibly inconsistent---result, as well as a final---consistent---result that arrives later. We show how to leverage incremental consistency guarantees by speculating on preliminary values, trading throughput and bandwidth for improved latency. We experiment with two popular storage systems (Cassandra and ZooKeeper) and three applications: a Twissandra-based microblogging service, an ad serving system, and a ticket selling system. Our evaluation on the Amazon EC2 platform with YCSB workloads A, B, and C shows that we can reduce the latency of strongly consistent operations by up to 40% (from 100ms to 60ms) at little cost (10% bandwidth increase, 6% throughput drop) in the ad system. Even if the preliminary result is frequently inconsistent (25% of accesses), incremental consistency incurs a bandwidth overhead of only 27%.Comment: 16 total pages, 12 figures. OSDI'16 (to appear

Seamful interweaving: heterogeneity in the theory and design of interactive systems

Design experience and theoretical discussion suggest that a narrow design focus on one tool or medium as primary may clash with the way that everyday activity involves the interweaving and combination of many heterogeneous media. Interaction may become seamless and unproblematic, even if the differences, boundaries and 'seams' in media are objectively perceivable. People accommodate and take advantage of seams and heterogeneity, in and through the process of interaction. We use an experiment with a mixed reality system to ground and detail our discussion of seamful design, which takes account of this process, and theory that reflects and informs such design. We critique the 'disappearance' mentioned by Weiser as a goal for ubicomp, and Dourish's 'embodied interaction' approach to HCI, suggesting that these design ideals may be unachievable or incomplete because they underemphasise the interdependence of 'invisible' non-rationalising interaction and focused rationalising interaction within ongoing activity

Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable