The present invention is directed to an implementation/method that identifies how to create a new measuring “sense” for measuring business bandwidth performance. This new “sense” is the ability to “see” (observe & measure) in real time business bandwidth latencies and the rate of change of the latency, known as latency jitter.
In a networked environment, the length of time for packets to travel from a source to a destination can vary for many reasons, including delays due to routers, communication, media, and the like. Although attempts have been made to determine latency and latency jitter through use of remote monitoring devices (RMONSs) and the like, such efforts have generally been unsatisfactory. It is desirable to make such measures in an accurate and precise manner.
The present process is able to determine business bandwidth performance by determining real-time bandwidth latency and latency jitter. Observations are continuously and simultaneously made over the network in order to measure:
Multiple end-to-end paths.
Individual components that make up paths (those components that affect latency jitter).
This ability to continually and simultaneously measure latency (both end-to-end and for each component) allows the measurement “sense” to identify the specific component that may be causing latency jitter that exceeds thresholds and cause intermittent business bandwidth problems. Additionally, the ability to synchronize measurements taken from multiple tools/end points (and correlate/analyze in real time this information) is what is referred to as the Real Time Mesh Measurement System.
Definitions
Token: a single packet or packet train. It represents an application profile (such as two packets, a pause, then three more packets).
Packet Train: a packet train simulates the traffic generated by specific applications.
Tracer: the same as “marker”.
Marker: an inserted packet pair that frames (e.g., beginning and end) a stream of actual customer traffic).
The present invention defines a new type of network service monitoring and measurement system that can fully measure key performance characteristics of specific network service offerings, targeted for identifying specific customer utilization and performance metrics utilizing those specific services. This new monitoring system/method is primarily based on the ability to insert management traffic onto a specific customer service or a specific service provider's service channel. The two types of inserted traffic are:
Tokens: tokens simulate different network traffic types.
Markers/Tracers: these inserted packets frame (one at the beginning and one at the end) streams of network traffic for specific services and/or specific customers.
The key components necessary to enable this new monitoring service to utilize these inserted packets and fully capture the critical performance statistics are as follows:
As best seen in
For the methods according to the present invention to be implemented, in addition to the various types of bandwidth monitoring devices, the present invention further includes one or more director consoles 54 which pool and further analyze the bandwidth data associated with the bandwidth monitoring devices. It should be noted that
The present invention provides a process that identifies how to measure business bandwidth performance and in particular, to determine business bandwidth latencies and the rate of change of such latency known as latency jitter through observations that are continuously made in order to determine multiple end-to-end paths for packets traversing from a source to a destination, as well as individual components that make up such paths and which may therefore affect latency and latency jitter.
In order to determine such latency and jitter concerning business bandwidth, it is necessary that the present invention be implemented through a distribution of bandwidth monitoring devices 40, wherein real-time time stamping is performed. Details of the bandwidth monitoring device, including the bandwidth interconnecting module 41 and the master control module 43 are shown in
Referring again to the flow chart shown in
Overall, the present invention has a distributed set of bandwidth monitoring devices which automatically identify key components to be measured based upon accurate real-time autolearning and autobaselining modules with respect to key users and applications which are deemed to be important by the user. Such information can be configured by the user.
The present invention further provides the ability to deploy these distributed tools at key locations in the network such as those shown in
Through this information, the system can configure and autotune the distributed tools for specific path measurements which thereby enables critical end-to-end and component views to be developed such as those set forth in
The use of virtual token ring technology on these specified paths allows stream-based messages to circle a virtual ring by enabling component to component stream latency and jitter measurements. See
Furthermore, the present invention provides the ability to use and configure different message types such as unicast, multicast, COS, POS, RSVP, which thereby allows for measuring variations in latency due to message type.
Time Clock Synchronization
The present invention, through its distributed tool time clock, is able to accurately synchronize these clocks coupled with the above virtual token, and allows for highly accurate latency and jitter measurements to be made for specific paths and specific components. Furthermore, the present invention provides the ability to continually calibrate and synchronize the distributed clocks based upon transaction response time and other observed or monitored data. See
Thus the present invention provides that all latency measurements with respect to the network can be accurately time stamped. By so doing, the collection analysis and correlation of multiple transactions and (virtual token) stream latency measurements are made. The analysis output forms a complete end-to-end/component latency and jitter measurement (also known as Mesh). Furthermore, the ability to store time stamps for specific application messages as they are observed passing through the bandwidth monitoring devices, allows for the measuring “sense” to automatically validate (and calibrate/tune measurements) the latency measurement results. It should be pointed out that user messages are tagged as tracers as shown in the figures. This validation is accomplished by selecting specific message types to be traced and collecting/analyzing tracer message time stamps, and comparing them against Mesh measurements. The Mesh measurements are the ability to use the Mesh tracer comparison to modify the Mesh token path (rate, specific information) so as to more accurately measure latency which allows a closed-loop tuning process for the Mesh measurements.
In Summary, the methodology according to the present invention provides a new business bandwidth measurement system that measures on a continuous and simultaneous basis, multiple end-to-end and component latency and latency jitter (also known as Mesh). The components of the business bandwidth Mesh sense include the ability to automatically identify specific points in the Mesh (end nodes, servers, tools, network products) that are critical points for observation such as high usage, important services, specific funnel points/bottleneck locations; the ability to automatically develop a latency map (list and operational state) for each latency measurement, thereby allowing for user input so as to tune the latency map; the ability to accurately synchronize multiple latency measurements and to accurately time-stamp these measurements, thereby enabling accurate remote collection and data analysis; wherein the new latency/jitter measurements based on both virtual token ring technology and synchronized clocks and time stamps. Such measurements allow stream data types (such as voice/video/UDP) to be measured accurately for critical metrics such as latency, latency jitter verses “burst load”.
Furthermore, the Mesh sense provide for the ability to collect latency measurements from multiple bandwidth measuring devices and to create a real-time Mesh view of latency and latency jitter throughout the network. It is also able to validate latency measurements by identifying application message types to be used as tracers in the Mesh; by accurately time stamping tracer messages passing through bandwidth measuring devices; and by collecting and analyzing tracer messages by a centralized validation module such as located in the director console. Furthermore, the Mesh sense components provide for the ability to continually observe change in latency which would require recommendation changes in the latency map, as well as the addition of specific points for latency measurements and the latency rate for more accuracy.
This application is a continuation of U.S. patent application Ser. No. 10/222,211 filed on Aug. 16, 2002 now U.S. Pat. No. 7,260,627 and claims domestic priority to said application under 35 USC §120.
Number | Name | Date | Kind |
---|---|---|---|
5535193 | Zhang et al. | Jul 1996 | A |
5557748 | Norris | Sep 1996 | A |
5775996 | Othmer et al. | Jul 1998 | A |
5805602 | Cloutier et al. | Sep 1998 | A |
5944840 | Lever | Aug 1999 | A |
6012096 | Link et al. | Jan 2000 | A |
6052363 | Koch | Apr 2000 | A |
6134531 | Trewitt et al. | Oct 2000 | A |
6175872 | Neumann et al. | Jan 2001 | B1 |
6286004 | Yoshiura et al. | Sep 2001 | B1 |
6393126 | van der Kaay et al. | May 2002 | B1 |
6535892 | LaRue et al. | Mar 2003 | B1 |
6560648 | Dunn et al. | May 2003 | B1 |
6662223 | Zhang et al. | Dec 2003 | B1 |
6665317 | Scott | Dec 2003 | B1 |
6801939 | Chafe | Oct 2004 | B1 |
6922417 | Vanlint | Jul 2005 | B2 |
6970424 | Fawaz et al. | Nov 2005 | B2 |
20020037732 | Gous et al. | Mar 2002 | A1 |
20020105911 | Pruthi et al. | Aug 2002 | A1 |
20050007952 | Scott | Jan 2005 | A1 |
20050058149 | Howe | Mar 2005 | A1 |
Number | Date | Country | |
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20080005354 A1 | Jan 2008 | US |
Number | Date | Country | |
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Parent | 10222211 | Aug 2002 | US |
Child | 11888935 | US |