DETECTING THE STATUS OF A MESH NODE IN A WIRELESS MESH NETWORK

• US 20170251387A1
• Filed: 09/12/2014
• Published: 08/31/2017
• Est. Priority Date: 09/12/2014
• Status: Active Grant

• Current Assignee: Hitachi Energy Limited (Hitachi, Ltd.)
• Original Assignee: ABB Schweiz AG (ABB Limited)
• Inventors: Rosseb, Judith, Chari, Amalavoyal, Ray, Apala, Chowdhury, Mohammad
• Granted Patent: US 10,362,500 B2
• Time in Patent Office: Days
• CPC Class Codes: H04L 41/069 using logs of notifications; Post-processing of notifications
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/30 Decision processes by autonomous network management units using voting and bidding
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04L 43/0817 by checking functioning
• CPC Class Codes: H04L 43/10 Active monitoring, e.g. heartbeat, ping or trace-route
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 63/1425 Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04W 24/06 Testing, supervising or monitoring using simulated traffic
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

A method for detecting the status of a mesh node in a wireless mesh network, wherein a gateway is building up a vector over time by combining active detection, passive detection and binary tests on anomaly metrics and wherein the status of the mesh node is regarded as misbehaving when the vector reaches a certain level.

Claims

1. A method for detecting the status of a mesh node in a wireless mesh network of one or a plurality of mesh nodes, wherein a gateway is building up a vector over time by combining:

active detection of the status of a mesh node by accumulating responses to transmitted queries,

passive detection of the status of a mesh node by monitoring and collecting routing metric values and storing the values in a table, and

binary tests on anomaly metrics; and

wherein,

the status of the mesh node is regarded as misbehaving when the vector reaches a certain level.

2. The method according to claim 1, wherein active detection of the status of a mesh node includes accumulating responses to transmitted queries, wherein a mesh node is:

sending a query to a mesh node neighbour according to a communications protocol, and

checking whether the response received is the expected response, and

wherein;

if the response received is the expected response,

storing a positive value in a table, and if the response received is not the response expected,

storing a negative value in a table.

3. The method according to claim 2, wherein passive detection of the status of a mesh node includes monitoring and collecting routing metric values and storing the values in a table, wherein each mesh node is:

monitoring the behavior of their upstream neighbours, with respect to link quality,

collecting the link quality values in a table,

storing the link quality values about its neighbours periodically in the table, based on a routing tree.

storing the time at which the link quality is measured along with the link quality and a neighbor identifier, thereby enable link quality values to be stored over time.

4. The method according to claim 3, wherein passive detection of the status of a mesh node includes monitoring of a beacon passive success rate, wherein the beacon passive success rate is equal to Y/X, wherein X is the number of beacons transmitted by a gateway and Y is the number of beacons received by a specific node whose value is being computed and wherein:

if Y is less than X and the beacon passive success rate is less than 100%, the experience incidence is termed as packet discard by the upstream neighbour nodes.

5. The method according to claim 4, wherein determining the anomaly metrics includes that each mesh node sends its collected link quality values from its upstream neighbours stored in a table to a gateway, and wherein the gateway, based on the received link quality values, determines an aggregated value.

6. The method according to claim 5, wherein determining the anomaly metrics further comprises including weighting based on how many times the mesh node that sends its collected link quality values appears in the routing tree as a downstream node to the mesh node it collects link quality values from.

7. The method according to claim 6, wherein a reputation manager at each mesh node sends the vector [AEcB, AKcB, ψ

RcB] at regular intervals to the gateway, wherein the vector comprising valuation based on the gateway'"'"'s direct experience with the mesh node, valuation based on what the gateway knows about the mesh node and valuation based on collected recommendations from other mesh nodes or other gateways.

8. The method according to claim 7, wherein determining trust values includes that the reputation manager in each mesh node computes the trust values based on policies and sends the trust values at regular intervals to the gateway, wherein the policies includes mathematical logics and/or functions.

9. The method according to claim 5, wherein monitored and collected routing metric values that each node has stored in its table are used to compute the link quality values based on a pre-defined policy, wherein the policy includes mathematical logics or functions.

10. The method according to claim 1, wherein action is taken when the vector reaches a certain level.

14. A computer program product comprising program code instructions for implementing the method according to claim 1, when the program is executed on a computer or a processor.

11. A gateway in a wireless mesh network comprising a memory and a processor, wherein the processor is configured for detecting the status of a mesh node in the wireless mesh network, the processor comprising means for:

active detection of the status of a mesh node by accumulating responses to transmitted queries,

passive detection of the status of a mesh node by monitoring and collecting routing metric values and storing the values in a table, and

performing binary tests on anomaly metrics, and wherein the processor is adapted to build up a vector over time by combining the active detection, passive detection and binary tests, and wherein the status of the mesh node is regarded as misbehaving when the vector reaches a certain level.

12. A gateway according to claim 11, wherein active detection of the status of a mesh node by accumulating responses to transmitted queries includes:

sending a query to a mesh node neighbour according to a communications protocol, and

checking whether the response received is the expected response, and

wherein;

if the response received is the expected response,

storing a positive value in a table, and if the response received is not the response expected, storing a negative value in a table.

13. A gateway according to claim 12, wherein passive detection of the status of a mesh node by monitoring and collecting routing metric values and storing the values in a table includes:

monitoring the behavior of the upstream neighbours, with respect to link quality,

collecting the link quality in a table,

storing values about its neighbours periodically in the table, based on a routing tree,

storing the time at which the link quality is measured along with the link quality and a neighbour identifier, thereby enabling link quality values to be stored over time.