General-purpose operating systems provide inadequate support for resource management in large-scale servers. Applications lack sufficient control over scheduling and management of machine resources, which makes it difficult to enforce priority policies, and to provide robust and controlled service

We describe an operating system architecture that securely multiplexes machine resources while permitting an unprecedented degree of application-specific customization of traditional operating system abstractions. By abstracting physical hardware resources, traditional operating systems have

cache coherence gives

this article, we discuss the fundamentals of distributed DBMS technology. We address the data distribution and architectural design issues as well as the algorithms that need to be implemented to provide the basic DBMS functions such as query processing, concurrency control, reliability

We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs

Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications

A shared data structure is lock-free if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly concurrent systems, lock-free data structures avoid common problems

simultaneously track multiple sources of sensitive data. TaintDroid’s efficiency to perform real-time analysis stems from its novel system design that leverages the mobile platform’s virtualized system architecture. TaintDroid incurs only 14 % performance overhead on a CPU-bound micro-benchmark with little

The 4+1 View Model organizes a description of a software architecture using five concurrent views, each of which addresses a specific set of concerns. Architects capture their design decisions in four views and use the fifth view to illustrate and validate them.

As we learn from the literature, flexibility in choosing synchronization operations greatly simplifies the task of designing highly concurrent programs. Unfortunately, existing hardware is inflexible and is at best on the level of a Load Linked/Store Conditional operation on a single word. Building