Windows Server

Résumé

Windows Server (formerly Windows NT Server) is a group of operating systems (OS) for servers that Microsoft has been developing since July 27, 1993. The first OS that was released for this platform is Windows NT 3.1 Advanced Server. With the release of Windows Server 2003, the brand name was changed to Windows Server. The latest release of Windows Server is Windows Server 2022, which was released in 2021. Microsoft's history of developing operating systems for servers goes back to Windows NT 3.1 Advanced Server. Windows 2000 Server is the first OS to include Active Directory, DNS Server, DHCP Server, and Group Policy. Members Main releases Main releases include: *Windows NT 3.1 Advanced Server (July 1993) *Windows NT Server 3.5 (September 1994) *Windows NT Server 3.51 (May 1995) *Windows NT 4.0 Server (July 1996) *Windows 2000 Server (December 1999) *Windows Server 2003 (April 2003) *Windows Server 2003 R2 (December 2005) *Windows Server 2008 (February 2008) *W

Source officielle

https://en.wikipedia.org/wiki/Windows_Server

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Timed-Release Encryption With Master Time Bound Key

Gwangbae Choi, Serge Vaudenay

Timed-release encryption allows senders to send a message to a receiver which cannot decrypt until a server releases a time bound key at the release time. The release time usually supposed to be known to the receiver, the ciphertext therefore cannot be decrypted if the release time is lost. We solve this problem in this paper by having a master time bound key which can replace the time bound key of any release time. We first present security models of the timed-release encryption with master time bound key. We present a provably secure construction based on the Weil pairing.

2019

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Scale-Out Processors

Al Mutaz Adileh, Babak Falsafi, Michael Ferdman, Boris Robert Grot, Yusuf Onur Koçberber, Pejman Lotfi Kamran, Javier Picorel Obando, Stavros Volos

Scale-out datacenters mandate high per-server throughput to get the maximum benefit from the large TCO investment. Emerging applications (e.g., data serving and web search) that run in these datacenters operate on vast datasets that are not accommodated by on-die caches of existing server chips. Large caches reduce the die area available for cores and lower performance through long access latency when instructions are fetched. Performance on scale-out workloads is maximized through a modestly-sized last-level cache that captures the instruction footprint at the lowest possible access latency. In this work, we introduce a methodology for designing scalable and efficient scale-out server processors. Based on a metric of performance-density, we facilitate the design of optimal multi-core configurations, called pods. Each pod is a complete server that tightly couples a number of cores to a small last-level cache using a fast interconnect. Replicating the pod to fill the die area yields processors which have optimal performance density, leading to maximum per-chip throughput. Moreover, as each pod is a stand-alone server, scale-out processors avoid the expense of global (i.e., interpod) interconnect and coherence. These features synergistically maximize throughput, lower design complexity, and improve technology scalability. In 20nm technology, scale-out chips improve throughput by 5x-6.5x over conventional and by 1.6x-1.9x over emerging tiled organizations.

Ieee2012

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