SYSTOR

In this paper, we study how web-server architecture and implementation affect performance when trying to obtain high throughput on a 4-core system servicing static content. We focus on static content as a growing numbers of servers are dedicated to ...

Recent increases in live and on-demand video streaming have dramatically changed the Internet landscape. In North America, Netflix alone accounts for 28% of all and 33% of peak downstream Internet traffic on fixed access links, with further rapid growth ...

Activity logs from large-scale systems facilitate the study of user behavior, which can be used to improve and tune the user experience. However, the available data often lacks important elements such as the identification of user sessions. Previous ...

Distributed Transactional Memory (DTM) is a recent but promising model for programming distributed systems. It aims to present programmers with a simple to use distributed concurrency control abstraction (transactions), while maintaining performance and ...

A dynamic binary translator (DBT) is a runtime system that translates binary code on the fly, for example to emulate the execution of the binary code on a processor with a different instruction set. One of the major sources of the overhead is the ...

BFQ (Budget Fair Queueing) is a production-quality, proportional-share disk scheduler with a relatively large user base. Part of its success is due to a set of simple heuristics that we added to the original algorithm about one year ago. These ...

We implement and experimentally evaluate the timeliness and energy consumption behaviors of fourteen Real-Time Dynamic Voltage and Frequency Scaling (RT-DVFS) schedulers on two hardware platforms. The schedulers include CC-EDF, LA-EDF, REUA, DRA, and ...

Processing vast numbers of data streams is a common problem in modern computer systems and is known as the "online big data problem." Adding hard real-time constraints to the processing makes the scheduling problem a very challenging task that this ...

Many storage systems include computationally expensive components. Examples include encryption for confidentiality, checksums for integrity, and error correcting codes for reliability. As storage systems become larger, faster, and serve more clients, ...

Virtualization is a prominent technology used in data centers around the world. While many kinds of workloads can run at near-native performance even when virtualized, I/O intensive workloads still suffer from high overhead precluding the use of ...

Time-traveling ability, which enables storage state to be reverted to any previous timepoints, is a highly desirable functionality in modern storage systems to ensure storage continuity. Continuous Data Protection (CDP) is a typical time-traveling ...

Solid state drives (SSDs) update data by writing a new copy, rather than overwriting old data, causing prior copies of the same data to be invalidated. These writes are performed in units of pages, while space is reclaimed in units of multi-page erase ...

Solid-state drives (SSDs) are widely used in storage systems. However, algorithms adopted by existing operating systems generally consider the underlying devices as hard disks, and thus are rarely optimized for SSDs. In this paper, we focus on a ...

A cloud storage with persistence shows solid performance only with a read heavy or write heavy workload. There is a trade-off between the read-optimized and write-optimized design of a cloud storage. This is dominated by its storage engine, which is a ...

Deduplication results inevitably in data fragmentation, because logically continuous data is scattered across many disk locations. In this work we focus on fragmentation caused by duplicates from previous backups of the same backup set, since such ...

Preserving data for a long period of time in the face of faults, large and small, is crucial for designing reliable archival storage systems. However, the survivability of data is different from the reliability of storage because typically, data are ...

There has been increasing interest in deploying data reduction techniques in primary storage systems. This paper analyzes large datasets in four typical enterprise data environments to find patterns that can suggest good design choices for such systems. ...