LATE DATA DETECTION IN DATA CENTER

• US 20160359711A1
• Filed: 02/10/2016
• Published: 12/08/2016
• Est. Priority Date: 06/05/2015
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Singh, Abhishek Ranjan, Deen, Khawar, Yadav, Navindra, Gupta, Anubhav, Gandham, Shashidhar, Prasad, Rohit Chandra, Chang, Shih-Chun
• Granted Patent: US 10,536,357 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/122 using management policies backup systems G06F11/1446; file migration policies for HSM systems G06F16/185
• CPC Class Codes: G06F 16/137 Hash-based content-based indexing of textual data G06F16/31
• CPC Class Codes: G06F 16/162 Delete operations erasing in storage systems G06F3/0652
• CPC Class Codes: G06F 16/17 Details of further file system functions
• CPC Class Codes: G06F 16/173 Customisation support for file systems, e.g. localisation, multi-language support, personalisation
• CPC Class Codes: G06F 16/174 Redundancy elimination performed by the file system management of the data involved in backup or backup restore using de-duplication of the data G06F11/14
• CPC Class Codes: G06F 16/1744 using compression, e.g. sparse files
• CPC Class Codes: G06F 16/1748 De-duplication implemented within the file system, e.g. based on file segments de-duplication techniques in storage systems for the management of data blocks G06F3/0641
• CPC Class Codes: G06F 16/2322 using timestamps
• CPC Class Codes: G06F 16/235 Update request formulation
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 2009/45587 Isolation or security of virtual machine instances
• CPC Class Codes: G06F 2009/45591 Monitoring or debugging support
• CPC Class Codes: G06F 2009/45595 : Network integration; Enabling network access in virtual machine instances
• CPC Class Codes: G06F 21/53 : by executing in a restricted environment, e.g. sandbox or secure virtual machine
• CPC Class Codes: G06F 21/552 : involving long-term monitoring or reporting
• CPC Class Codes: G06F 21/556 : involving covert channels, i.e. data leakage between processes inhibiting the analysis of circuitry or operation with measures against power attack G06F21/755
• CPC Class Codes: G06F 21/566 : Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities
• CPC Class Codes: G06F 2221/033 : Test or assess software
• CPC Class Codes: G06F 2221/2101 : Auditing as a secondary aspect
• CPC Class Codes: G06F 2221/2105 : Dual mode as a secondary aspect
• CPC Class Codes: G06F 2221/2111 : Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G06F 2221/2115 : Third party
• CPC Class Codes: G06F 2221/2145 : Inheriting rights or properties, e.g., propagation of permissions or restrictions within a hierarchy
• CPC Class Codes: G06F 3/0482 : Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 : Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 : Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 9/45558 : Hypervisor-specific management and integration aspects
• CPC Class Codes: G06N 20/00 : Machine learning
• CPC Class Codes: G06N 99/00 : Subject matter not provided for in other groups of this subclass
• CPC Class Codes: G06T 11/206 : Drawing of charts or graphs
• CPC Class Codes: H04J 3/0661 : using timestamps
• CPC Class Codes: H04J 3/14 : Monitoring arrangements for SDH/SONET rings H04J3/085
• CPC Class Codes: H04L 1/242 : by comparing a transmitted test signal with a locally generated replica
• CPC Class Codes: H04L 41/046 : comprising network management agents or mobile agents therefor
• CPC Class Codes: H04L 41/0668 : by dynamic selection of recovery network elements, e.g. replacement by the most appropriate element after failure
• CPC Class Codes: H04L 41/0803 : Configuration setting
• CPC Class Codes: H04L 41/0806 : for initial configuration or provisioning, e.g. plug-and-play
• CPC Class Codes: H04L 41/0816 : the condition being an adaptation, e.g. in response to network events
• CPC Class Codes: H04L 41/0893 : Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 : Policy-based network configuration management
• CPC Class Codes: H04L 41/12 : Discovery or management of network topologies
• CPC Class Codes: H04L 41/16 : using machine learning or artificial intelligence
• CPC Class Codes: H04L 41/22 : comprising specially adapted graphical user interfaces [GUI]
• CPC Class Codes: H04L 41/40 : using virtualisation of network functions or resources, e.g. SDN or NFV entities
• CPC Class Codes: H04L 43/02 : Capturing of monitoring data
• CPC Class Codes: H04L 43/026 : using flow identification
• CPC Class Codes: H04L 43/04 : Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04L 43/045 : for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/062 : related to network traffic
• CPC Class Codes: H04L 43/08 : Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 43/0805 : by checking availability
• CPC Class Codes: H04L 43/0811 : by checking connectivity
• CPC Class Codes: H04L 43/0829 : Packet loss
• CPC Class Codes: H04L 43/0841 : Round trip packet loss
• CPC Class Codes: H04L 43/0858 : One way delays
• CPC Class Codes: H04L 43/0864 : Round trip delays
• CPC Class Codes: H04L 43/0876 : Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 43/0882 : Utilisation of link capacity
• CPC Class Codes: H04L 43/0888 : Throughput
• CPC Class Codes: H04L 43/10 : Active monitoring, e.g. heartbeat, ping or trace-route
• 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
• CPC Class Codes: H04L 43/16 : Threshold monitoring
• CPC Class Codes: H04L 43/20 : the monitoring system or the monitored elements being virtualised, abstracted or software-defined entities, e.g. SDN or NFV
• CPC Class Codes: H04L 45/306 : Route determination based on the nature of the carried application
• CPC Class Codes: H04L 45/38 : Flow based routing
• CPC Class Codes: H04L 45/46 : Cluster building
• CPC Class Codes: H04L 45/507 : Label distribution
• CPC Class Codes: H04L 45/66 : Layer 2 routing, e.g. in Ethernet based MAN's
• CPC Class Codes: H04L 45/74 : Address processing for routing
• CPC Class Codes: H04L 47/11 : Identifying congestion
• CPC Class Codes: H04L 47/20 : Traffic policing
• CPC Class Codes: H04L 47/2441 : relying on flow classification, e.g. using integrated services [IntServ]
• CPC Class Codes: H04L 47/2483 : involving identification of individual flows
• CPC Class Codes: H04L 47/28 : in relation to timing considerations
• CPC Class Codes: H04L 47/31 : by tagging of packets, e.g. using discard eligibility [DE] bits
• CPC Class Codes: H04L 47/32 : by discarding or delaying data units, e.g. packets or frames
• CPC Class Codes: H04L 61/5007 : Internet protocol [IP] addresses
• CPC Class Codes: H04L 63/0227 : Filtering policies mail message filtering H04L51/212
• CPC Class Codes: H04L 63/0263 : Rule management
• CPC Class Codes: H04L 63/06 : for supporting key management in a packet data network cryptographic mechanisms or cryptographic arrangements for key management H04L9/08
• CPC Class Codes: H04L 63/0876 : based on the identity of the terminal or configuration, e.g. MAC address, hardware or software configuration or device fingerprint
• CPC Class Codes: H04L 63/1408 : by monitoring network traffic monitoring network traffic per se H04L43/00
• CPC Class Codes: H04L 63/1416 : Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1425 : Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04L 63/1433 : Vulnerability analysis
• CPC Class Codes: H04L 63/1441 : Countermeasures against malicious traffic countermeasures against attacks on cryptographic mechanisms H04L9/002
• CPC Class Codes: H04L 63/145 : the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
• CPC Class Codes: H04L 63/1458 : Denial of Service
• CPC Class Codes: H04L 63/1466 : Active attacks involving interception, injection, modification, spoofing of data unit addresses, e.g. hijacking, packet injection or TCP sequence number attacks
• CPC Class Codes: H04L 63/16 : Implementing security features at a particular protocol layer
• CPC Class Codes: H04L 63/20 : for managing network security; network security policies in general filtering policies H04L63/0227
• CPC Class Codes: H04L 67/01 : Protocols
• CPC Class Codes: H04L 67/10 : in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/1001 : for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/12 : specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/51 : Discovery or management thereof, e.g. service location protocol [SLP] or web services
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/75 : Indicating network or usage conditions on the user display
• CPC Class Codes: H04L 69/16 : Implementation or adaptation of Internet protocol [IP], of transmission control protocol [TCP] or of user datagram protocol [UDP]
• CPC Class Codes: H04L 69/22 : Parsing or analysis of headers
• CPC Class Codes: H04L 7/10 : Arrangements for initial synchronisation
• CPC Class Codes: H04L 9/0866 : involving user or device identifiers, e.g. serial number, physical or biometrical information, DNA, hand-signature or measurable physical characteristics
• CPC Class Codes: H04L 9/3239 : involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
• CPC Class Codes: H04L 9/3242 : involving keyed hash functions, e.g. message authentication codes [MACs], CBC-MAC or HMAC
• CPC Class Codes: H04W 72/54 : based on quality criteria
• CPC Class Codes: H04W 84/18 : Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

Systems, methods, and non-transitory computer-readable storage media for synchronizing timestamps of a sensor report to the clock of a device. In one embodiment, the device receives a report from a sensor of a node. The report can include a network activity of the node captured by the sensor and a first timestamp relative to the clock of the node. The device can then determine a second timestamp relative to the clock of the collector indicating receipt of the report by the device and from the sensor at the node. The device can also determine a delta between the first timestamp and the second timestamp, and a communication latency associated with a communication channel between the device and the sensor. Next, the device can adjust the delta based on the communication latency, and generate a third timestamp based on the adjusted delta.

Claims

1. A method comprising:

receiving, by a device and from a sensor at a node, a report comprising a network activity of the node captured by the sensor and a first timestamp relative to a first clock of the node;

determining, by the device, a second timestamp relative to a second clock of the device, the second timestamp indicating a receipt of the report by the device from the sensor at the node;

determining a delta, by the device, between the first timestamp and the second timestamp;

determining, by the device, a communication latency associated with a communication channel between the device and the sensor;

adjusting, by the device, the delta based on the communication latency; and

generating, by the device, a third timestamp based on the adjusted delta.

2. The method of claim 1, further comprising:

associating, by the device, the third timestamp to the received report from the sensor.

3. The method of claim 1, wherein the determining of the communication latency associated with the communication channel between the device and the sensor further comprises:

determining, by the device, a fourth timestamp indicating when a message was sent to the sensor by the device, the message requesting a reply;

determining, by the device, a fifth timestamp of when the reply was received by the device; and

determining a difference between the fourth timestamp and the fifth timestamp.

4. The method of claim 1, wherein the sensor is a first sensor, the report is a first report and the delta is a first delta, the method further comprising:

receiving, by the device and from a second sensor, a second report comprising a network activity captured by the second sensor and a sixth timestamp relative to a third clock associated with the second sensor;

determining, by the device, a seventh timestamp relative to second clock of the device, the seventh timestamp indicating receipt of the second report by the device from the second sensor;

determining a second delta, by the device, between the sixth timestamp and the seventh timestamp;

determining, by the device, a communication latency associated with a second communication channel between the device and the second sensor;

adjusting, by the device, the second delta by the second communication latency; and

generating, by the device, an eighth timestamp based on the adjusted second delta.

5. The method of claim 4, further comprising:

associating, by the device, the third timestamp to the received first report from the first sensor and the eighth timestamp to the received second report from the second sensor; and

determining a sequence of events reported in the first report and the second report based on the third timestamp and the eighth timestamp.

6. The method of claim 1, wherein the report is a first report, the method further comprising:

receiving, by the device and from the sensor at the node, a second report comprising a network activity of the node captured by the sensor and a fourth timestamp relative to the first clock of the node;

determining, by the device, that a timeframe threshold has not been met; and

generating, by the device, a fifth timestamp based on the adjusted delta.

7. The method of claim 4, wherein the first node and the second node are different.

8. A non-transitory computer-readable medium having computer readable instructions stored on the computer readable medium that, when executed are effective to cause a computing device to:

receive, from a sensor at a node, a report comprising a network activity of the node captured by the sensor and a first timestamp relative to a first clock of the node;

determine a second timestamp relative to a second clock of the device, the second timestamp indicating a receipt of the report by the device from the sensor at the node;

determine a delta between the first timestamp and the second timestamp;

determine a communication latency associated with a communication channel between the device and the sensor;

adjust the delta based on the communication latency; and

generate a third timestamp based on the adjusted delta.

9. The non-transitory computer-readable medium of claim 8, wherein the instructions further cause the computing device to:

replace the first timestamp of the received report, with the third timestamp.

10. The non-transitory computer-readable medium of claim 8, wherein the instructions for determining the communication latency associated with the communication channel between the computing device and the sensor further cause the computing device to:

receive multiple communication latencies associated with the communication channel between the device and the sensor; and

based on the multiple communication latencies, determine an average communication latency associated with the communication channel between the computing device and the sensor.

11. The non-transitory computer-readable medium of claim 8, wherein the sensor is a first sensor, the report is a first report and the delta is a first delta, and wherein the instructions further cause the computing device to:

receive and from a second sensor, a second report comprising a network activity captured by the second sensor and a sixth timestamp relative to a third clock associated with the second sensor;

determine a fourth timestamp relative to second clock of the device, the fourth timestamp indicating receipt of the second report by the device from the second sensor;

determine a second delta between the fifth timestamp and the fifth timestamp;

determine a communication latency associated with a second communication channel between the device and the second sensor;

adjust the second delta by the second communication latency; and

generate a sixth timestamp based on the adjusted second delta.

12. The non-transitory computer-readable medium of claim 11, wherein the instructions further cause the computing device to:

associate the third timestamp to the received first report from the first sensor and the sixth timestamp to the received second report from the second sensor; and

determine a sequence of events reported in the first report and the second report based on the third timestamp and the sixth timestamp.

13. The non-transitory computer-readable medium of claim 8, wherein the report is a first report, and wherein the instructions further cause the computing device to:

receive, from the sensor at the node, a second report comprising a network activity of the node captured by the sensor and a fourth timestamp relative to the first clock of the node;

determine a timeframe threshold has not been met; and

generate a fifth timestamp based on the adjusted delta.

14. The non-transitory computer-readable medium of claim 8, wherein the first node and the second node are different.

15. A computing system comprising:

a computing device; and

a memory containing instructions that, when executed by the computing device, cause the computing system to;

receive, from a sensor at a node, a report comprising a network activity of the node captured by the sensor and a first timestamp relative to a first clock of the node;

determine a second timestamp relative to a second clock of the device, the second timestamp indicating a receipt of the report by the device from the sensor at the node;

determine a delta between the first timestamp and the second timestamp;

determine a communication latency associated with a communication channel between the device and the sensor;

adjust the delta based on the communication latency;

generate a third timestamp based on the adjusted delta; and

associating, by the device, the third timestamp to the received report from the sensor.

16. The computing system of claim 15, wherein the instructions to determine the communication latency associated with the communication channel between the computing device and the sensor, further cause the computing system to:

identify historical data comprising a plurality of data describing latencies associated with the communication channel between the computing device and the sensor; and

infer a historical communication latency associated with the communication channel between the computing device and the sensor.

17. The computing system of claim 16, wherein the instructions further cause the computing system to:

receive from the sensor, a second report comprising a network activity captured by the sensor and a fourth timestamp relative to the first clock of the node;

determine a fifth timestamp relative to the second clock of the device, the fifth timestamp indicating a receipt of the second report by the device from the sensor at the node;

determine a delta between the fourth timestamp and the fifth timestamp;

determine a communication latency associated with a communication channel between the device and the sensor;

adjust the delta based on the communication latency;

generate a sixth timestamp based on the adjusted delta;

associate by the device, the sixth timestamp to the received report from the sensor; and

determine whether the sixth timestamp is within the historical communication latency associated with the communication channel between the computing device and the sensor

18. The computing system of claim 15, wherein the sensor is a first sensor, the report is a first report and the delta is a first delta, and wherein the instructions further cause the computing system to:

receive and from a second sensor, a second report comprising a network activity captured by the second sensor and a sixth timestamp relative to a third clock associated with the second sensor;

determine a fourth timestamp relative to second clock of the device, the fourth timestamp indicating receipt of the second report by the device from the second sensor;

determine a second delta between the fifth timestamp and the fifth timestamp;

determine a communication latency associated with a second communication channel between the device and the second sensor;

adjust the second delta by the second communication latency; and

generate a sixth timestamp based on the adjusted second delta.

19. The computing system of claim 17, wherein the instructions further cause the computing system to:

associate the third timestamp to the received first report from the first sensor and the sixth timestamp to the received second report from the second sensor; and

determine a sequence of events reported in the first report and the second report based on the third timestamp and the sixth timestamp.

20. The computing system of claim 17, wherein the instructions further cause the computing system to:

receive, from the sensor at the node, a second report comprising a network activity of the node captured by the sensor and a fourth timestamp relative to the first clock of the node;

determine a timeframe threshold has not been met; and

generate a fifth timestamp based on the adjusted delta.