We report on the design, implementation, and evaluation of a system called Cedar that enables mobile database access with good performance over low-bandwidth networks. This is accomplished without degrading consistency. Cedar exploits the disk storage and processing power of a mobile client to compensate for weak connectivity. Its central organizing principle is that even a stale client replica can be used to reduce data transmission volume from a database server. The reduction is achieved by using content addressable storage to discover and elide commonality between client and server results. This organizing principle allows Cedar to use an optimistic approach to solving the difficult problem of database replica control. For laptop-class clients, our experiments show that Cedar improves the throughput of read-write workloads by 39% to as much as 224% while reducing response time by 28% to as much as 79%.

Graphical processing units (GPUs) are critical to high-quality visualization in many application domains. Running such applications in virtual machine monitor (VMM) environments is difficult for a number of reasons, all relating to the fact that the GPU hardware interface is proprietary rather than standardized. This paper describes the design, implementation, and evaluation of VMGL, a VMM-independent, GPU-independent, cross-platform solution to this problem. VMGL virtualizes at the OpenGL software interface, recognizing its widespread use in graphics-intensive applica-tions. Our experiments confirm excellent rendering performance with VMGL, coming within 14% or better of native hardware accelerated performance measured in frames per second. This is two orders of magnitude better than software rendering, which is the commonly available alternative today for graphics-intensive applications running in virtualized environments. Our results confirm VMGL’s portability across VMware Workstation and Xen (on VT and non-VT hardware), and across Linux (with and without paravirtualization), FreeBSD, and Solaris. Our results also show

With the growing use of dynamic web content generated from relational databases, traditional caching solutions for through put and latency improvements are ineffective. We describe a middleware layer called Ganesh that reduces the volume of data transmitted without semantic interpretation of queries or results. It achieves this reduction through the use of cryptographic hashing to detect similarities with previous results. These benefits do not require any compromise of the strict consistency semantics provided by the back-end database. Further, Ganesh does not require modifications to applications, web servers, or database servers, and works with closed-source applications and databases. Using two bench marks representative of dynamic web sites, measurements of our prototype show that it can increase end-to-end throughput by as much as two fold for non-data intensive applications and by as much as ten fold for dataintensive ones.

This WIP proposes a new architecture for applications that perform bulk data transfers. This architecture, called DOT (for data-oriented transfer), cleanly separates out two functions that are comingled in today's applications. Using DOT, applications perform content negotiation to determine what content to send. They then pass that data object to the transfer service to perform the actual data transmission. This separation increases application flexibility, enables the rapid development of innovative transfer mechanisms, reduces developer effort, and allows increased efficiency through cross-application sharing.