IP Library › Granted Patent US 10,050,712
Granted Patent B2
US 10,050,712 · App. 15/508,978 · Granted Aug 14, 2018

Method and device for determining location of optical splitter

Inventors: Gangxiang Shen (Jiangsu, CN); Hao Chen (Jiangsu, CN); Yongcheng Li (Jiangsu, CN)
Assignee: SOOCHOW UNIVERSITY
H04B10/27H04B10/07H04B10/2504H04B10/272H04B10/00
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Quick Facts
Patent No.
US 10,050,712
App. No.
15/508,978
Granted
Aug 14, 2018
Kind
B2
Abstract

A method and a device for determining a location of an optical splitter are provided. With the method, optical network units in a PON network are classified into K clusters based on locations of the optical network units with a K-means clustering-based algorithm. Distances between multiple optical network units in the same cluster are small. If it is determined that the number of the optical network units in each of the clusters does not exceed a threshold, a central office is added into the K clusters to obtain K new clusters; and for each of the new clusters, a location of an optical splitter corresponding to the new cluster is determined, so as to ensure that a sum of distances between the location of the optical splitter and locations of all elements in the new cluster is minimized.

Claims (35)

1. A method for determining a location of an optical splitter, comprising:

inputting a location of a central office and locations of optical network units in a PON network;

classifying, with a K-means clustering-based algorithm, the optical network units into K clusters based on the locations of the optical network units;

dividing the cluster having a number of optical network units exceeding a threshold as a maximum optical split ratio if it is determined that there is a cluster having a number of optical network units exceeding the threshold, such that obtained clusters meet the requirement of the threshold;

adding the central office to the obtained clusters to obtain new clusters;

determining, for each of the new clusters, a location of an optical splitter corresponding to the new cluster, with a Weiszfeld algorithm, based on the locations of the central office and the optical network units in the new cluster, wherein a sum of distances between the location of the optical splitter and the locations of the central office and the optical network units in the new cluster is minimized; and

placing the optical splitters at the determined locations in the PON,

wherein when classifying with a K-means clustering-based algorithm the optical network units into K clusters, a value of K is determined by:

creating a curve by taking a value of K as an argument on an X axis and taking a clustering metric value as a dependent variable on a Y axis, wherein the clustering metric value is defined as an average value of clustering index values of the K clusters classified with the K-means clustering-based algorithm; and

selecting a value of K corresponding to a point in the curve having a maximum rate of change in the clustering metric value, as a target value of K.

2. The method according to claim 1 , wherein if it is determined that there is a cluster having the number of optical network units exceeding the threshold among the K clusters, the dividing the cluster having the number of optical network units exceeding the threshold further comprises:

determining the cluster having the number of optical network units exceeding the threshold as a target cluster;

classifying, with the K-means clustering-based algorithm, the optical network units in the target cluster into a plurality of sub-clusters based on locations of the optical network units in the target cluster; and

detecting whether there is a sub-cluster having the number of optical network units exceeding the threshold; and returning to the process of determining the cluster having the number of optical network units exceeding the threshold as a target cluster, if it is detected that there is a sub-cluster having the number of optical network units exceeding the threshold.

3. The method according to claim 2 , further comprising:

constituting a target set by the central office and the optical splitters corresponding to the sub-clusters obtained by dividing the target cluster;

determining, with the Weiszfeld algorithm, a location of a target point corresponding to the target set, wherein a sum of distances between the location of the target point and locations of all elements in the target set is minimized; and

determining a route from the location of the central office to the location of the target point as a target fiber conduit route, wherein the target fiber conduit route is shared by a plurality of optical fibers arranged between the central office and the optical splitters in the target set.

4. A device for determining a location of an optical splitter, comprising a processor and a memory having program instructions stored therein, when the program instructions are executed by the processor, the processor is configured to:

receive a location of a central office and locations of optical network units in a PON network;

classify, with a K-means clustering-based algorithm, the optical network units into K clusters based on the locations of the optical network units;

divide the cluster having the number of optical network units exceeding a threshold as a maximum optical split ratio if it is determined that there is a cluster having the number of optical network units exceeding the threshold, such that obtained clusters meet the requirement of the threshold;

add the central office to the obtained clusters to obtain new clusters; and

determine, for each of the new clusters, a location of an optical splitter corresponding to the new cluster, with a Weiszfeld algorithm, based on the locations of the central office and the optical network units in the new cluster, wherein a sum of distances between the location of the optical splitter and locations of the central office and the optical network units in the new cluster is minimized,

wherein the processor is further configured to:

create a curve by taking a value of K as an argument on an X axis and taking a clustering metric value as a dependent variable on a Y axis, wherein the clustering metric value is defined as an average value of clustering index values of the K clusters classified with the K-means clustering-based algorithm; and

select a value of K corresponding to a point in the curve having a maximum rate of change in the clustering metric value, as a target value of K.

5. The device according to claim 4 , wherein the processor is further configured to:

determine, if it is determined that there is a cluster having the number of optical network units exceeding the threshold among the K clusters, the cluster having the number of optical network units exceeding the threshold as a target cluster;

classify, with the K-means clustering-based algorithm, the optical network units in the target cluster into a plurality of sub-clusters based on locations of the optical network units in the target cluster; and

detect whether there is a sub-cluster having the number of optical network units exceeding the threshold; and return to perform the operation of the target cluster determining unit if it is detected that there is a sub-cluster having the number of optical network units exceeding the threshold.

6. The device according to claim 5 , wherein the processor is further configured to:

constitute a target set by the central office and the optical splitters corresponding to the sub-clusters obtained by dividing the target cluster;

determine, with the Weiszfeld algorithm, a location of a target point corresponding to the target set, wherein a sum of distances between the location of the target point and locations of all elements in the target set is minimized; and

determine a route from the location of the central office to the location of the target point as a target fiber conduit route, wherein the target fiber conduit route is shared by a plurality of optical fibers arranged between the central office and the optical splitters in the target set.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 6, 2017
From: SHEN, GANGXIANG; CHEN, HAO; LI, YONGCHENG
To: SOOCHOW UNIVERSITY
Reel/Frame 041895/0052 →
Priority Claims (1)
CN 2015 1 0551398 · Sep 1, 2015 · national
Continuity (1)
Related Publication 20170288778A1 · Oct 5, 2017