Remote, in-memory key-value (RINK) stores such as Memcached [6] and Redis [7] are widely used in industry and are an active area of academic research. Coupled with stateless application servers to execute business logic and a databaselike system to provide persistent storage, they form a core component of popular data center service architectures. We argue that the time of the RINK store has come and gone: their domain-independent APIs (e.g., PUT/GET) push complexity back to the application, leading to extra (un)marshalling overheads and network hops. Instead, data center services should be built using stateful application servers or custom in-memory stores with domain-specific APIs, which offer higher performance than RINKS at lower cost. Such designs have been avoided because they are challenging to implement without appropriate infrastructure support. Given recent advances in auto-sharding [8, 9], we argue it is time to revisit these decisions. In this paper, we evaluate the potential performance improvements of stateful designs, propose a new abstraction, the linked, in-memory key-value (LINK) store, to enable developers to easily implement stateful services, and discuss areas for future research.

RAMCloud is a storage system that provides low-latency access to large-scale datasets. To achieve low latency, RAMCloud stores all data in DRAM at all times. To support large capacities (1PB or more), it aggregates the memories of thousands of servers into a single coherent key-value store. RAMCloud ensures the durability of DRAM-based data by keeping backup copies on secondary storage. It uses a uniform log-structured mechanism to manage both DRAM and secondary storage, which results in high performance and efficient memory usage. RAMCloud uses a polling-based approach to communication, bypassing the kernel to communicate directly with NICs; with this approach, client applications can read small objects from any RAMCloud storage server in less than 5μs, durable writes of small objects take about 13.5μs. RAMCloud does not keep multiple copies of data online; instead, it provides high availability by recovering from crashes very quickly (1 to 2 seconds). RAMCloud’s crash recovery mechanism harnesses the resources of the entire cluster working concurrently so that recovery performance scales with cluster size.

JFLAP is software for experimenting with formal languages and automata theory. In this Tips and Techniques session we describe the recent changes to JFLAP to make it more usable in an automata theory course.

As more services have come to rely on sensor data such as audio and photos collected by mobile phone users, verifying the authenticity of this data has become critical for service correctness. At the same time, clients require the flexibility to tradeoff the fidelity of the data they contribute for resource efficiency or privacy. This paper describes YouProve, a partnership between a mobile device's trusted hardware and software that allows untrusted client applications to directly control the fidelity of data they upload and services to verify that the meaning of source data is preserved. The key to our approach is trusted analysis of derived data, which generates statements comparing the content of a derived data item to its source. Experiments with a prototype implementation for Android demonstrate that YouProve is feasible. Our photo analyzer is over 99% accurate at identifying regions changed only through meaning-preserving modifications such as cropping, compression, and scaling. Our audio analyzer is similarly accurate at detecting which sub-clips of a source audio clip are present in a derived version, even in the face of compression, normalization, splicing, and other modifications. Finally, performance and power costs are reasonable, with analyzers having little noticeable effect on interactive applications and CPU-intensive analysis completing asynchronously in under 70 seconds for 5-minute audio clips and under 30 seconds for 5-megapixel photos.

This paper describes the integration of the Alice 3D virtual worlds environment into many disciplines in elementary school, middle school and high school. We have developed a wide range of Alice instructional materials including tutorials for both computer science concepts and animation concepts. To encourage the building of more complicated worlds, we have developed template Alice classes and worlds. With our materials, teachers and students are exposed to computing concepts while using Alice to create projects, stories, games and quizzes. These materials were successfully used in the summers 2008 and 2009 in training and working with over 130 teachers.

This paper describes the integration of the Alice 3D virtual worlds environment into a diverse set of subjects in middle school, including the development of tutorials, example worlds and lesson plans. In the summer of 2008 our experiences with middle school teachers included three-weeks of training in Alice and guidance in the development of lesson plans. Our experiences with middle school students involved two one-week summer camps of instruction in Alice. We found both the teachers and the students strongly engaged with Alice. The teachers created lesson plans with Alice worlds to interactively teach a topic and other lesson plans in which students build an Alice world on a particular topic either from scratch or using a template world. The students in the Alice camps had both instruction in Alice and free time to develop Alice worlds of their choice. We found that the students used a large variety of basic Alice concepts and computer science concepts in the worlds they built in their free time.