Using JavaNws to compare C and Java TCP‐Socket performance

As research and implementation continue to facilitate high‐performance computing in Java, applications can benefit from resource management and prediction tools. In this work, we present such a tool for network round‐trip time and bandwidth between a user's desktop and any machine running a Web server (this assumes that the user's browser is capable of supporting Java 1.1 and above). JavaNws is a Java implementation and extension of a powerful subset of the Network Weather Service (NWS), a performance prediction toolkit that dynamically characterizes and forecasts the performance available to an application. However, due to the Java language implementation and functionality (portability, security, etc.), it is unclear whether a Java program is able to measure and predict the network performance experienced by C‐applications with the same accuracy as an equivalent C program. We provide a quantitative equivalence study of the Java and C TCP‐socket interface and show that the data collected by the JavaNws is as predictable as that collected by the NWS (using C). Copyright © 2001 John Wiley & Sons, Ltd.

[1]  F. Berman,et al.  Adaptive Performance Prediction for Distributed Data-Intensive Applications , 1999, ACM/IEEE SC 1999 Conference (SC'99).

[2]  Stephen Taylor,et al.  Forecasting Economic Time Series , 1979 .

[3]  Chandra Krintz,et al.  JavaNws: the network weather service for the desktop , 2000, JAVA '00.

[4]  WillingerWalter,et al.  On the self-similar nature of Ethernet traffic , 1993 .

[5]  Guy L. Steele,et al.  The Java Language Specification , 1996 .

[6]  Jeffrey D. Case,et al.  Simple Network Management Protocol (SNMP) , 1989, RFC.

[7]  Jonathan D. Cryer,et al.  Time Series Analysis , 1986 .

[8]  Richard Wolski,et al.  The network weather service: a distributed resource performance forecasting service for metacomputing , 1999, Future Gener. Comput. Syst..

[9]  Francine Berman,et al.  Using Apples to Schedule Simple SARA on the Computational Grid , 1999, Int. J. High Perform. Comput. Appl..

[10]  Thomas W. Parsons,et al.  Digital signal processing: theory, applications, and hardware , 1991 .

[11]  Walter Willinger,et al.  On the Self-Similar Nature of Ethernet Traffic ( extended version ) , 1995 .

[12]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1972 .

[13]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[14]  Frank Yellin,et al.  The Java Virtual Machine Specification , 1996 .

[15]  Roy T. Fielding,et al.  Hypertext Transfer Protocol - HTTP/1.1 , 1997, RFC.

[16]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[17]  WolskiRich.  Dynamically forecasting network performance using the Network Weather Service , 1998 .

[18]  Message Passing Interface Forum.  MPI: A message - passing interface standard , 1994 .

[19]  Jack Dongarra,et al.  PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing , 1995 .

[20]  M. Pernice,et al.  PVM: Parallel Virtual Machine - A User's Guide and Tutorial for Networked Parallel Computing [Book Review] , 1996, IEEE Parallel & Distributed Technology: Systems & Applications.

[21]  Van Jacobson,et al.  A tool to infer characteristics of internet paths , 1997 .