Ryan Stutsman

The case for RAMClouds: scalable high-performance storage entirely in DRAM

Disk-oriented approaches to online storage are becoming increasingly problematic: they do not scale gracefully to meet the needs of large-scale Web applications, and improvements in disk capacity have far outstripped improvements in access latency and bandwidth. This paper argues for a new approach to datacenter storage called RAMCloud, where information is kept entirely in DRAM and large-scale systems are created by aggregating the main memories of thousands of commodity servers. We believe that RAMClouds can provide durable and available storage with 100-1000x the throughput of disk-based systems and 100-1000x lower access latency. The combination of low latency and large scale will enable a new breed of dataintensive applications.

Fast crash recovery in RAMCloud

RAMCloud is a DRAM-based storage system that provides inexpensive durability and availability by recovering quickly after crashes, rather than storing replicas in DRAM. RAMCloud scatters backup data across hundreds or thousands of disks, and it harnesses hundreds of servers in parallel to reconstruct lost data. The system uses a log-structured approach for all its data, in DRAM as well as on disk: this provides high performance both during normal operation and during recovery. RAMCloud employs randomized techniques to manage the system in a scalable and decentralized fashion. In a 60-node cluster, RAMCloud recovers 35 GB of data from a failed server in 1.6 seconds. Our measurements suggest that the approach will scale to recover larger memory sizes (64 GB or more) in less time with larger clusters.

Energy management in mobile devices with the cinder operating system

We argue that controlling energy allocation is an increasingly useful and important feature for operating systems, especially on mobile devices. We present two new low-level abstractions in the Cinder operating system, reserves and taps, which store and distribute energy for application use. We identify three key properties of control -- isolation, delegation, and subdivision -- and show how using these abstractions can achieve them. We also show how the architecture of the HiStar information-flow control kernel lends itself well to energy control. We prototype and evaluate Cinder on a popular smartphone, the Android G1.

The case for RAMCloud

With scalable high-performance storage entirely in DRAM, RAMCloud will enable a new breed of data-intensive applications.

The RAMCloud Storage System

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.

Lost in just the translation

This paper describes the design and implementation of a scheme for hiding information in translated natural language text, and presents experimental results using the implemented system. Unlike the previous work, which required the presence of both the source and the translation, the protocol presented in this paper requires only the translated text for recovering the hidden message. This is a significant improvement, as transmitting the source text was both wasteful of resources and less secure. The security of the system is now improved not only because the source text is no longer available to the adversary, but also because a broader repertoire of defenses (such as mixing human and machine translation) can now be used.

Translation-based steganography

This paper investigates the possibilities of steganographically embedding information in the “noise” created by automatic translation of natural language documents. Because the inherent redundancy of natural language creates plenty of room for variation in translation, machine translation is ideal for steganographic applications. Also, because there are frequent errors in legitimate automatic text translations, additional errors inserted by an information hiding mechanism are plausibly undetectable and would appear to be part of the normal noise associated with translation. Significantly, it should be extremely difficult for an adversary to determine if inaccuracies in the translation are caused by the use of steganography or by deficiencies of the translation software.

Apprehending joule thieves with cinder

Energy is the critical limiting resource to mobile computing devices. Correspondingly, an operating system must track, provision, and ration how applications consume energy. The emergence of third-party application stores and marketplaces makes this concern even more pressing. A third-party application must not deny service through excessive, unforeseen energy expenditure, whether accidental or malicious. Previous research has shown promise in tracking energy usage and rationing it to meet device lifetime goals, but such mechanisms and policies are still nascent, especially regarding user interaction. We argue for a new operating system, called Cinder, which builds on top of the HiStar OS. Cinders energy awareness is based on hierarchical capacitors and task profiles. We introduce and explore these abstractions, paying particular attention to the ways in which policies could be generated and enforced in a dynamic system.

To lock, swap, or elide: on the interplay of hardware transactional memory and lock-free indexing

The release of hardware transactional memory (HTM) in commodity CPUs has major implications on the design and implementation of main-memory databases, especially on the architecture of high-performance lock-free indexing methods at the core of several of these systems. This paper studies the interplay of HTM and lock-free indexing methods. First, we evaluate whether HTM will obviate the need for crafty lock-free index designs by integrating it in a traditional B-tree architecture. HTM performs well for simple data sets with small fixed-length keys and payloads, but its benefits disappear for more complex scenarios (e.g., larger variable-length keys and payloads), making it unattractive as a general solution for achieving high performance. Second, we explore fundamental differences between HTM-based and lock-free B-tree designs. While lock-freedom entails design complexity and extra mechanism, it has performance advantages in several scenarios, especially high-contention cases where readers proceed uncontested (whereas HTM aborts readers). Finally, we explore the use of HTM as a method to simplify lock-free design. We find that using HTM to implement a multi-word compare-and-swap greatly reduces lock-free programming complexity at the cost of only a 10-15% performance degradation. Our study uses two state-of-the-art index implementations: a memory-optimized B-tree extended with HTM to provide multi-threaded concurrency and the Bw-tree lock-free B-tree used in several Microsoft production environments.

Multi-version range concurrency control in Deuteronomy

The Deuteronomy transactional key value store executes millions of serializable transactions/second by exploiting multi-version timestamp order concurrency control. However, it has not supported range operations, only individual record operations (e.g., create, read, update, delete). In this paper, we enhance our multi-version timestamp order technique to handle range concurrency and prevent phantoms. Importantly, we maintain high performance while respecting the clean separation of duties required by Deuteronomy, where a transaction component performs purely logical concurrency control (including range support), while a data component performs data storage and management duties. Like the rest of the Deuteronomy stack, our range technique manages concurrency information in a latch-free manner. With our range enhancement, Deuteronomy can reach scan speeds of nearly 250 million records/s (more than 27 GB/s) on modern hardware, while providing serializable isolation complete with phantom prevention.