Understanding the management of client perceived response time

Understanding and managing the response time of web services is of key importance as dependence on the World Wide Web continues to grow. We present Remote Latency-based Management (RLM), a novel server-side approach for managing pageview response times as perceived by remote clients, in real-time. RLM passively monitors server-side network traffic, accurately tracks the progress of page downloads and their response times in real-time, and dynamically adapts connection setup behavior and web page content as needed to meet response time goals. To manage client perceived pageview response times, RLM builds a novel event node model to guide the use of several techniques for manipulating the packet traffic in and out of a web server complex, including fast SYN and SYN/ACK retransmission, and embedded object removal and rewrite. RLM operates as a stand-alone appliance that simply sits in front of a web server complex, without any changes to existing web clients, servers, or applications. We have implemented RLM on an inexpensive, commodity, Linux-based PC and present experimental results that demonstrate its effectiveness in managing client perceived pageview response times on transactional e-commerce web workloads.

[1]  Donald F. Towsley,et al.  Modeling TCP throughput: a simple model and its empirical validation , 1998, SIGCOMM '98.

[2]  Srinivasan Seshan,et al.  BENEFITS OF TRANSPARENT CONTENT NEGOTIATION IN HTTP , 1998 .

[3]  Nina Bhatti,et al.  Web server support for tiered services , 1999, IEEE Netw..

[4]  K. K. Ramakrishnan,et al.  Eliminating receive livelock in an interrupt-driven kernel , 1996, TOCS.

[5]  Carey L. Williamson,et al.  A case for context-aware TCP/IP , 2002, PERV.

[6]  Lui Sha,et al.  Online response time optimization of Apache web server , 2003, IWQoS'03.

[7]  L. Cherkasova,et al.  Session-based admission control: a mechanism for improving performance of commercial Web sites , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[8]  Yixin Diao,et al.  Optimizing Quality of Service Using Fuzzy Control , 2002, DSOM.

[9]  Maria Kihl,et al.  Admission control schemes guaranteeing customer QOS in commercial web sites , 2002, Net-Con.

[10]  Mor Harchol-Balter,et al.  Connection Scheduling in Web Servers , 1999, USENIX Symposium on Internet Technologies and Systems.

[11]  Douglas M. Freimuth,et al.  Kernel Mechanisms for Service Differentiation in Overloaded Web Servers , 2001, USENIX Annual Technical Conference, General Track.

[12]  Amin Vahdat,et al.  Differentiated multimedia Web services using quality aware transcoding , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[13]  TowsleyDon,et al.  Modeling TCP throughput , 1998 .

[14]  Tarek F. Abdelzaher,et al.  Web Content Adaptation to Improve Server Overload Behavior , 1999, Comput. Networks.

[15]  Paul Barford,et al.  Critical path analysis of TCP transactions , 2000, SIGCOMM.

[16]  K. Shin,et al.  Performance Guarantees for Web Server End-Systems: A Control-Theoretical Approach , 2002, IEEE Trans. Parallel Distributed Syst..

[17]  Biplab Sikdar,et al.  Analytic models and comparative study of the latency and steady-state throughput of TCP Tahoe, Reno and SACK , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[18]  Srinivasan Seshan,et al.  The effects of wide-area conditions on WWW server performance , 2001, SIGMETRICS '01.

[19]  Richard Wolski,et al.  Quorum: flexible quality of service for internet services , 2005, NSDI.

[20]  Stefan Savage,et al.  Modeling TCP latency , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[21]  Kang G. Shin,et al.  Persistent dropping: an efficient control of traffic aggregates , 2003, SIGCOMM '03.

[22]  Cheng-Zhong Xu,et al.  eQoS: Provisioning of Client-Perceived End-to-End QoS Guarantees in Web Servers , 2006, IEEE Transactions on Computers.

[23]  Erich M. Nahum,et al.  A method for transparent admission control and request scheduling in e-commerce web sites , 2004, WWW '04.

[24]  Dakshi Agrawal,et al.  Using certes to infer client response time at the web server , 2004, TOCS.

[25]  Amin Vahdat,et al.  EtE: Passive End-to-End Internet Service Performance Monitoring , 2002, USENIX Annual Technical Conference, General Track.

[26]  Robert Grimm,et al.  Application performance and flexibility on exokernel systems , 1997, SOSP.

[27]  Paul Barford,et al.  Critical path analysis of TCP transactions , 2000, SIGCOMM 2000.

[28]  Kang G. Shin,et al.  Resynchronization and controllability of bursty service requests , 2004, IEEE/ACM Transactions on Networking.

[29]  Erich M. Nahum,et al.  ksniffer: Determining the Remote Client Perceived Response Time from Live Packet Streams , 2004, OSDI.

[30]  Allan Kuchinsky,et al.  Integrating user-perceived quality into Web server design , 2000, Comput. Networks.

[31]  Yin Zhang,et al.  On the constancy of internet path properties , 2001, IMW '01.

[32]  Srinivasan Seshan,et al.  Improving reliable transport and handoff performance in cellular wireless networks , 1995, Wirel. Networks.

[33]  John M. Tracey,et al.  Adaptive Fast Path Architecture , 2001, IBM J. Res. Dev..

[34]  Jeffrey S. Chase,et al.  Correlating Instrumentation Data to System States: A Building Block for Automated Diagnosis and Control , 2004, OSDI.