Modeling remote desktop systems in utility environments with application to QoS management

A remote desktop utility system is an emerging client/server networked model for enterprise desktops. In this model, a shared pool of consolidated compute and storage servers host users' desktop applications and data respectively. End-users are allocated resources for a desktop session from the shared pool on-demand, and they interact with their applications over the network using remote display technologies. Understanding the detailed behavior of applications in these remote desktop utilities is crucial for more effective QoS management. However, there are challenges due to hard-to-predict workloads, complexity, and scale. In this paper, we present a detailed modeling of a remote desktop system through case study of an Office application — email. The characterization provides insights into workload and user model, the effect of remote display technology, and implications of shared infrastructure. We then apply these learnings and modeling results for improved QoS resource management decisions — achieving over 90% improvement compared to state of the art allocation mechanisms. We also present discussion on generalizing a methodology for a broader applicability of model-driven resource management.

[1]  Min Zhou,et al.  Analysis of personal computer workloads , 1999, MASCOTS '99. Proceedings of the Seventh International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.

[2]  Zheng Wang,et al.  Using latency to evaluate interactive system performance , 1996, OSDI '96.

[3]  Asser N. Tantawi,et al.  An analytical model for multi-tier internet services and its applications , 2005, SIGMETRICS '05.

[4]  Andy Hopper,et al.  Virtual Network Computing , 1998, IEEE Internet Comput..

[5]  Xiaoyun Zhu,et al.  Statistical service assurances for applications in utility grid environments , 2004, Perform. Evaluation.

[6]  Ray Jain,et al.  The art of computer systems performance analysis - techniques for experimental design, measurement, simulation, and modeling , 1991, Wiley professional computing.

[7]  Nickolai Zeldovich,et al.  Interactive Performance Measurement with VNCPlay , 2005, USENIX Annual Technical Conference, FREENIX Track.

[8]  Jason Nieh,et al.  Measuring thin-client performance using slow-motion benchmarking , 2001, TOCS.

[9]  Michel Dagenais,et al.  Measuring and Characterizing System Behavior Using Kernel-Level Event Logging , 2000, USENIX Annual Technical Conference, General Track.

[10]  J. Duane Northcutt,et al.  The interactive performance of SLIM: a stateless, thin-client architecture , 1999, SOSP.

[11]  Jason Nieh,et al.  THINC: a virtual display architecture for thin-client computing , 2005, SOSP '05.

[12]  Monica S. Lam,et al.  The collective: a cache-based system management architecture , 2005, NSDI.

[13]  Timothy Roscoe,et al.  Resource overbooking and application profiling in shared hosting platforms , 2002, OSDI '02.

[14]  Jason Nieh,et al.  Limits of wide-area thin-client computing , 2002, SIGMETRICS '02.