CORRELATIVE MONITORING, ANALYSIS, AND CONTROL OF MULTI-SERVICE, MULTI-NETWORK SYSTEMS

• US 20140149569A1
• Filed: 11/26/2012
• Published: 05/29/2014
• Est. Priority Date: 11/26/2012
• Status: Active Grant

• Current Assignee: Emc IP Holding Company LLC (Dell Technologies Inc.)
• Original Assignee: Emc IP Holding Company LLC (Dell Technologies Inc.)
• Inventors: Wittenstein, Andreas, Eynon, Mike, Chiles, Richard, Nair, Rakesh, Campbell, Brian
• Granted Patent: US 9,774,517 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 43/028 by filtering
• CPC Class Codes: H04L 43/106 using time related information in packets, e.g. by adding timestamps
• CPC Class Codes: H04L 43/12 Network monitoring probes

Abstract

Methods and devices for correlative monitoring, analysis, and control of multi-service, multi-network systems are provided herein. Exemplary methods may include generating a network topology graph of a metanetwork using traffic records obtained from the metanetwork, generating a causal digraph of the metanetwork using the traffic records and the network topology graph, and transmitting one or more of the network topology graph and the causal digraph to a computing system.

Claims

1. A method, comprising:

generating a network topology graph of a metanetwork using traffic records obtained from the metanetwork;

generating a causal digraph of the metanetwork using the traffic records and the network topology graph; and

transmitting one or more of the network topology graph and the causal digraph to a computing system.

2. The method according to claim 1, wherein the traffic records comprise message segments obtained from node points within the metanetwork, wherein the node points are communicatively coupled with services of the metanetwork.

3. The method according to claim 1, further comprising:

obtaining message segments from the metanetwork;

time stamping the message segments;

pre-filtering the time stamped message segments to determine a source, destination, and segment size of the time stamped message segments; and

assembling the time stamped message segments into a traffic record.

4. The method according to claim 3, further comprising one or more of decrypting and decoding the time stamped message segments and performing deep packet inspection of the time stamped message segments.

5. The method according to claim 4, further comprising determining a user identification associated with message segments that have been subjected to deep packet inspection.

6. The method according to claim 1, further comprising modeling congestion delay for the metanetwork using the causal digraph and predicting a service delay by comparing a benchmark congestion model to a subsequent congestion model.

7. The method according to claim 1, further comprising storing the network topology graph and the causal digraph in a record, the record being stored in a storage media.

8. A system, comprising:

at least one computing device comprising a memory that includes executable instructions and a processor executing the instructions to;

generate a network topology graph of a metanetwork using traffic records obtained from a metanetwork;

generate a causal digraph of the metanetwork using the traffic records; and

transmit one or more of the network topology graph and the causal digraph to a computing system.

9. The system according to claim 8, wherein the processor further executes the instructions to:

obtain message segments from the metanetwork via node points;

time stamp the message segments;

pre-filter the time stamped message segments to determine a source, destination, and segment size of the time stamped message segments; and

assemble the time stamped message segments into a traffic record.

10. The system according to claim 9, wherein the processor further executes the instructions to one or more of decrypt and decode the time stamped message segments.

11. The system according to claim 9, wherein the processor further executes the instructions to perform deep packet inspection of the time stamped message segments.

12. The system according to claim 8, wherein the processor further executes the instructions to:

model congestion delay for at least a portion of the metanetwork using the causal digraph; and

predict delay for a message segment being transmitted through at least a portion of the metanetwork.

13. The system according to claim 8, wherein the processor further executes the instructions to store the network topology graph and the causal digraph in a record, the record being stored in a storage media.

14. The system according to claim 8, wherein the traffic records comprise message segments obtained from node points within the metanetwork, wherein the node points are communicatively coupled with services of the metanetwork.

15. The system according to claim 14, wherein the node points comprise bidirectional taps that detect input and output message segments of the services and networks, wherein the system further comprises a traffic monitor that receives traffic records from the bidirectional taps.

16. The system according to claim 14, wherein the node points comprise bidirectional shunts that divert input and output message segments of the services and networks to a traffic monitor.

17. The system according to claim 14, wherein a node point comprises any of a pair of unidirectional taps, a bidirectional multitap, a multiplexing bidirectional tap, or combinations thereof.

18. The system according to claim 14, wherein the metanetwork comprises any of a shared-hub network, a shared-bus network, a token-ring network, a daisy-chain network, a switched network comprising a port mirroring switch, a switched network comprising bidirectional shunts,

19. The system according to claim 14, wherein the at least one computing system and the node points are in apposed communicative coupling with the metanetwork.

20. The system according to claim 14, wherein the at least one computing system and the node points are in interposed communicative coupling with the metanetwork.