CN103384353B - Passive optical network and the detection method of ustomer premises access equipment - Google Patents
Passive optical network and the detection method of ustomer premises access equipment Download PDFInfo
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Abstract
The invention provides a kind of passive optical network and the detection method of ustomer premises access equipment, detection method comprises: when there is abnormal ustomer premises access equipment and received signal strength is zero, adopt binary chop total collection is carried out three times two points, respectively the first subset sums second is gathered by burst clock data reconstruction method, second subset sums second is gathered, three subsetss and first are gathered and the set of the 4th subset sums first is tested, if test result has occurred for correct test result, then subset corresponding for correct test result is excluded, remaining formation total collection recycling binary chop carries out two atomistic tests, if test result is the test result of mistake, the randomly ordered algorithm of equiprobability is then adopted to carry out once randomly ordered to all ustomer premises access equipments in total collection, recycling binary chop carries out two atomistic tests, until detect the ustomer premises access equipment of all exceptions.The present invention's short, logical complexity consuming time reduce and detection method flexible.
Description
Technical field
The present invention relates to a kind of passive optical network, the detection method of the ustomer premises access equipment particularly in a kind of passive optical network and comprise the passive optical network of this detection method.
Background technology
Along with the continuous maturation of passive optical access network network technology, and the continuous expansion of passive optical access network network scale, operator transfers to the construction of passive optical access network network operation and maintenance gradually from functional realiey and network size, and this needs network equipment vendor to provide corresponding technical scheme to solve.
On the operation and maintenance of passive optical access network network, the diagnosis of optical link and fault restoration are very important, particularly rogue ONU(optical network unit) quick position and isolation be the most important thing, because once optical link breaks down, by the business on ONU a large amount of for impact, greatly reducing the QOS(service quality of network, is a kind of security mechanism of network, is used to a kind of technology solving the problem such as network delay and obstruction).
So-called rogue ONU(rogueONU) refer to the ONU that other functional modules are controlled all normally except the existence of light transmitting portion is abnormal.From the phenomenon that rogue ONU causes, the rogue ONU of the rogue ONU of long hair light and non-long hair light can be divided into.The rogue ONU of long hair light refers to that the control logic existence due to transmitting portion causes long-time luminescence extremely, and can cause very large impact to up link, the ONU causing other all cannot normally work at up direction.The rogue ONU of non-long hair light refers to because the reasons such as optical module is aging may open luminescence or delay shutoff luminescence in advance, causes when sending data beyond the ascending time slot distributed, thus can have influence on the ONU being assigned with contiguous time slot.
Introduce existing detection PON(EPON below) method of rogue ONU in system:
When occurring that ONU business is frequently interrupted in a PON mouth, roll off the production line on ONU is frequent, all ONU of PON mouth cannot register or receive LOS(Received Loss Of Signal) phenomenon such as alarm time, the method of general employing: close the ONU upstream data transmission that PON mouth has found one by one, after running into certain ONU of closedown, optical link recovers normal (can find that ONU or ONU succeeds in registration), then can judge that this ONU is rogue ONU, the upstream data continuing long-time this ONU of closedown sends, solve until the upstream data of this ONU sends fault or replace this ONU, then the detection of next ONU is carried out.
Above-mentioned detection rogue ONU method existing defects, whether such as need to detect each ONU is one by one rogue ONU, when the ONU number in a PON mouth is more, above-mentioned detection method length consuming time.And when detecting an ONU for rogue ONU, after only having the fault that existed by this ONU to solve, next ONU could be detected, length consuming time and detection method is dumb.In addition, this detection method cannot detect the rogue ONU that influencing each other between multiple ONU causes.
Introduce the method for rogue ONU in another detection PON system existing below:
Suppose there be M ONU, the detection of all rogue ONU under this PON mouth be completed in a PON mouth to be detected, just need M to take turns test.Often all need to close the n-th ONU(n wherein during wheel test from 1), the ONU number therefore under the i-th mouth of PON when taking turns test is M
i=M-i+1(i is from 1), the time that the n-th ONU closes is (M
i-n) t
d.When often taking turns test, if the ONU number now in PON mouth is greater than 1, then need OLT(optical line terminal) issue Temporarily Closed optical module t to each ONU
dthe order of time.The time that n-th ONU closes is (M
i-n) t
dbeing to ensure when each takes turns test, opening just the ONU closed above will be unified in after this takes turns test.After closedown 1 ONU optical module, OLT will at the observation cycle t of 1 setting
din, observe all uplink messages LLID(logical links mark) situation:
If an OLT issues orders closedown n-th ONU optical module after t
din time, no longer occur the unmatched situation of LLID, the ONU so just closed is exactly rogue ONU, and does not just have rogue ONU in M-n remaining ONU, now only n-1 the ONU closed above need be detected again, now i can be arranged to i=M-n+2.
If after two closedown the n-th ONU optical modules, OLT is at t
dinside still have the unmatched situation of LLID to occur, then need to close next ONU optical module again.
If three has been now last ONU, then can determines that this ONU is exactly rogue ONU, then not need to close this ONU again.
Above-mentioned detection rogue ONU method subsistence logic is too complicated, length consuming time and cannot detect the defects such as the rogue ONU that influencing each other between multiple ONU causes.
Summary of the invention
The technical problem to be solved in the present invention be in order to overcome in prior art the method detecting rogue ONU length consuming time, logic is complicated, detection method is dumb and cannot detect the defect of the rogue ONU that influencing each other between multiple ONU causes, provide a kind of relatively short, logical complexity consuming time to reduce and can detect the rogue ONU that influencing each other between multiple ONU causes passive optical network and the detection method of ustomer premises access equipment.
The present invention solves above-mentioned technical problem by following technical proposals:
The invention provides the detection method of the ustomer premises access equipment in a kind of passive optical network, this passive optical network comprises an OLT, this OLT is to there being N number of ustomer premises access equipment, this ustomer premises access equipment is ONU or ONT, and wherein, N is positive integer, this N number of ustomer premises access equipment forms a total collection, its feature is, setting m=0, and this detection method comprises the following steps:
S
1, judge whether occur abnormal ustomer premises access equipment in this ustomer premises access equipment, if so, then enter step S
2, if not, then process ends;
S
2, detect whether the received signal strength that this ustomer premises access equipment sends is zero, if received signal strength is zero, illustrates in this PON system to there is controlled rogue ONU, then enter step S
3, if not, then process ends;
S
3, adopt binary chop this total collection is divided into the first set and second set, by this first set be divided into the first subset sums second subset, and by this second set be divided into three subsetss and the 4th subset;
S
4, by burst clock data reconstruction method, this second set of this first subset sums is tested, if test result is correct test result, then this second set of this second subset sums is integrated to form after this total collection and again performs S
3if test result is the test result of mistake, then enter step S
5;
S
5, by burst clock data reconstruction method, this second set of this second subset sums is tested, if test result is correct test result, then this second set of this first subset sums is integrated to form after this total collection and again performs S
3if test result is the test result of mistake, then enter step S
6;
S
6, by burst clock data reconstruction method, these three subsetss and this first set are tested, if test result is correct test result, then this first set of the 4th subset sums is integrated to form after this total collection and again performs S
3if test result is the test result of mistake, then enter step S
7;
S
7, by burst clock data reconstruction method, this first set of the 4th subset sums is tested, if test result is correct test result, then these three subsetss and this first set is integrated to form after this total collection and again perform S
3if test result is the test result of mistake, then enter step S
8;
S
8, judge whether the numerical value of m reaches a setting numerical value, if not, then enters S
9, if so, then enter S
10;
S
9, adopt equiprobability randomly ordered algorithm to carry out once randomly ordered to all ustomer premises access equipments in this total collection, and enter step S after the numerical value of m is added 1
3;
S
10, ustomer premises access equipment in this total collection is abnormal ustomer premises access equipment, and process ends.
By the detection method of this programme, the controlled rogue's ustomer premises access equipment existed in this PON system can be detected, this controlled rogue's ustomer premises access equipment not only can cause for single ustomer premises access equipment, can also be that influencing each other between multiple ustomer premises access equipment causes.
Step S
1middlely judge in this ustomer premises access equipment, whether to occur that abnormal ustomer premises access equipment is by existing techniques in realizing, there is characterizing consumer end equipment in the prior art and whether occur that abnormal parameter is as Signal Degrade and flow process etc., just no longer describe in detail here.
" correct test result " that this programme is mentioned refers to test result corresponding when ustomer premises access equipment can work, by burst clock data reconstruction method, ustomer premises access equipment is tested, if compared with the test result that the parameter of characterization test result obtains as Signal Degrade and flow process etc. and all ustomer premises access equipments when all intact, with ustomer premises access equipment whole intact time test result identical or whole than ustomer premises access equipment intact time test result poor but do not affect the work of ustomer premises access equipment, be correct test result.
Five grades such as the test result recorded by burst clock data reconstruction method are divided into be respectively outstanding test result, good test result, medium test result, difference test result and very poor test result, " correct test result " is the test result of difference test result and above grade thereof, and these test results do not affect the work of ustomer premises access equipment.
Similarly, this programme is mentioned " test result of mistake " refers to test result corresponding when ustomer premises access equipment can not work.By burst clock data reconstruction method, ustomer premises access equipment is tested, if compared with the test result that the parameter of characterization test result and all ustomer premises access equipments obtain when all intact, whole than ustomer premises access equipment intact time the test result work that have impact on ustomer premises access equipment far short of what is expected, ustomer premises access equipment cannot be worked, be the test result of mistake.What such as " test result of mistake " was corresponding is very poor test result, and ustomer premises access equipment cannot be worked, and namely very significant degradation trend has appearred in the test result of this programme.
And when any one subset in this first subset, this second subset, these three subsetss and the 4th subset is empty set, the set corresponding to this subset sums by burst clock data reconstruction method is tested, test result is the test result of mistake.Such as, this first subset is empty set, and tested this second set of this first subset sums by burst clock data reconstruction method, then test result is the test result of mistake.
In addition, the process ends described in this programme refers to the end of the flow process of this programme related to, instead of refers to the end of entire flow.As related to a lot of flow processs in this PON system, as the detection method flow process of this programme, the upgrade method flow process of ustomer premises access equipment and other flow process, when PON system performs the process ends of this programme, just mean that the detection method flow process of this programme terminates, and the upgrade method flow process of ustomer premises access equipment and other flow process do not terminate.
And the randomly ordered algorithm of burst clock data reconstruction method, binary chop and equiprobability used in this programme is prior art, just repeats no more here.
Preferably, the feature database that comprises multiple setting feature is stored in this OLT, step S
1comprise:
S
1, receive this ustomer premises access equipment occur feature after, judge whether this feature mates with the setting feature in this feature database, if result for mate, judge in this ustomer premises access equipment, to have occurred abnormal ustomer premises access equipment, then enter step S
2if result, for not mate, judges not occur abnormal ustomer premises access equipment in this ustomer premises access equipment, then process ends.
Preferably, this setting feature comprises: this ustomer premises access equipment business is frequently interrupted, this ustomer premises access equipment frequent on roll off the production line, all ustomer premises access equipments of the PON mouth correspondence of this OLT all cannot register and this OLT receives loss of signal alarm.
Preferably, by RSSI(ReceivedSignalStrengthIndication, the signal strength signal intensity of reception instruction) testing mechanism detects the received signal strength that this ustomer premises access equipment sends.This RSSI testing mechanism is prior art, just no longer describes in detail here.
Preferably, this sets numerical value as in step S
8time total collection in the quantity of all ustomer premises access equipments.This setting numerical value is step S
7tune goes to step S
8time total collection corresponding to that moment in the quantity of all ustomer premises access equipments.As entered step S
8time that moment total collection in the quantity of ustomer premises access equipment be 8, then this set numerical value as (factorials of 8).When again entering step S
8time that moment total collection in the quantity of ustomer premises access equipment be 6, then this set numerical value as .
The present invention also provides the detection method of the ustomer premises access equipment in a kind of passive optical network, this passive optical network comprises an OLT, this OLT is to there being N number of ustomer premises access equipment, this ustomer premises access equipment is ONU or ONT, and wherein, N is positive integer, this N number of ustomer premises access equipment forms a total collection, its feature is, setting m=0, and this detection method comprises the following steps:
S
1, judge whether occur potential abnormal ustomer premises access equipment in this ustomer premises access equipment, if so, then enter step S
2, if not, then process ends;
S
2, adopt binary chop this total collection is divided into the first set and second set, by this first set be divided into the first subset sums second subset, and by this second set be divided into three subsetss and the 4th subset;
S
3, by burst clock data reconstruction method, this second set of this first subset sums is tested, if test result is correct test result, then this second set of this second subset sums is integrated to form after this total collection and again performs S
2if test result is the test result of mistake, then enter step S
4;
S
4, by burst clock data reconstruction method, this second set of this second subset sums is tested, if test result is correct test result, then this second set of this first subset sums is integrated to form after this total collection and again performs S
2if test result is the test result of mistake, then enter step S
5;
S
5, by burst clock data reconstruction method, these three subsetss and this first set are tested, if test result is correct test result, then this first set of the 4th subset sums is integrated to form after this total collection and again performs S
2if test result is the test result of mistake, then enter step S
6;
S
6, by burst clock data reconstruction method, this first set of the 4th subset sums is tested, if test result is correct test result, then these three subsetss and this first set is integrated to form after this total collection and again perform S
2if test result is the test result of mistake, then enter step S
7;
S
7, judge whether the numerical value of m reaches a setting numerical value, if not, then enters S
8, if so, then enter S
9;
S
8, adopt equiprobability randomly ordered algorithm to carry out once randomly ordered to all ustomer premises access equipments in this total collection, and enter step S after the numerical value of m is added 1
2;
S
9, ustomer premises access equipment in this total collection is potential abnormal ustomer premises access equipment, and process ends.
Step S
1in potential abnormal ustomer premises access equipment be different from the ustomer premises access equipment of the above-mentioned exception mentioned, this potential abnormal ustomer premises access equipment refers to when a certain or some special characteristic appear in ustomer premises access equipment, just there is potential abnormal ustomer premises access equipment in characterizing consumer end equipment.
Five grades such as the test result recorded by burst clock data reconstruction method are divided into be respectively outstanding test result, good test result, medium test result, difference test result and very poor test result, " correct test result " that this programme is mentioned refer to ustomer premises access equipment can work and the grade of test result be good test result and outstanding test result time corresponding test result, these test results do not affect the work of ustomer premises access equipment.And " test result of mistake " that this programme is mentioned refer to ustomer premises access equipment can work and the grade of test result be medium test result and difference test result time corresponding test result, these test results do not affect the work of ustomer premises access equipment.
Preferably, the feature database that comprises multiple setting feature is stored in this OLT, step S
1comprise:
S
1, receive this ustomer premises access equipment occur feature after, judge whether this feature mates with the setting feature in this feature database, if result for mate, judge in this ustomer premises access equipment, to have occurred potential abnormal ustomer premises access equipment, then enter step S
2if result, for not mate, judges not occur potential abnormal ustomer premises access equipment in this ustomer premises access equipment, then process ends.
Preferably, this sets numerical value as in step S
7time total collection in the quantity of all ustomer premises access equipments.This setting numerical value is step S
6tune goes to step S
7time total collection corresponding to that moment in the quantity of all ustomer premises access equipments.
The present invention provides again a kind of passive optical network, and its feature is, this passive optical network uses above-mentioned detection method.
On the basis meeting this area general knowledge, above-mentioned each optimum condition, can combination in any, obtains the preferred embodiments of the invention.
Positive progressive effect of the present invention is:
The present invention to all ustomer premises access equipments occurred in the PON system of abnormal conditions by binary chop and the randomly ordered algorithm of equiprobability to find out rogue ONU, the present invention can not only find out single rogue ONU, the rogue ONU that influencing each other between multiple ONU causes can also be found out, search accuracy rate high and comprehensively, and there is relatively short, logical complexity consuming time reduce and detection method advantage flexibly.
Accompanying drawing explanation
Fig. 1 is the flow chart of the detection method of ustomer premises access equipment in the passive optical network of the embodiment of the present invention 1.
Fig. 2 is the flow chart of the detection method of ustomer premises access equipment in the passive optical network of the embodiment of the present invention 2.
Embodiment
Mode below by embodiment further illustrates the present invention, but does not therefore limit the present invention among described scope of embodiments.
Embodiment 1
The present embodiment provides the detection method of the ustomer premises access equipment in a kind of passive optical network, this passive optical network comprises an OLT, this OLT is to there being N number of ustomer premises access equipment, this ustomer premises access equipment is ONU or ONT, wherein, N is positive integer, this N number of ustomer premises access equipment forms a total collection, the feature database that one comprises multiple setting feature is stored in this OLT, this setting feature comprises: this ustomer premises access equipment business is frequently interrupted, roll off the production line on this ustomer premises access equipment is frequent, all ustomer premises access equipments of the PON mouth correspondence of this OLT all cannot register and this OLT receives loss of signal alarm.
Setting m=0, as shown in Figure 1, this detection method comprises the following steps:
Step 101, receive this ustomer premises access equipment occur feature after, judge whether this feature mates with the setting feature in this feature database, if result is coupling, judge in this ustomer premises access equipment, to have occurred abnormal ustomer premises access equipment, then enter step 102, if result is not for mate, judge not occur abnormal ustomer premises access equipment in this ustomer premises access equipment, then process ends;
Step 102, to be detected by RSSI testing mechanism whether the received signal strength that this ustomer premises access equipment sends is zero, if received signal strength is zero, then enter step 103, if not, then process ends;
This total collection is divided into the first set and the second set by step 103, employing binary chop, and this first set is divided into the first subset sums second subset, and this second set is divided into three subsetss and the 4th subset;
Step 104, by burst clock data reconstruction method to this first subset sums this second set test, if test result is correct test result, then this second set of this second subset sums is integrated after forming this total collection and again perform step 103, if test result is the test result of mistake, then enter step 105;
Step 105, by burst clock data reconstruction method to this second subset sums this second set test, if test result is correct test result, then this second set of this first subset sums is integrated after forming this total collection and again perform step 103, if test result is the test result of mistake, then enter step 106;
Step 106, by burst clock data reconstruction method to these three subsetss and this first set test, if test result is correct test result, then this first set of the 4th subset sums is integrated after forming this total collection and again perform step 103, if test result is the test result of mistake, then enter step 107;
Step 107, by burst clock data reconstruction method to the 4th subset sums this first set test, if test result is correct test result, then these three subsetss and this first set are integrated after forming this total collection and again perform step 103, if test result is the test result of mistake, then enter step 108;
Step 108, judge whether the numerical value of m reaches a setting numerical value, if not, then enters step 109, if so, then enters step 110, wherein, this setting numerical value is the quantity of all ustomer premises access equipments in the total collection when step 108;
Step 109, the randomly ordered algorithm of employing equiprobability carry out once randomly ordered to all ustomer premises access equipments in this total collection, and enter step 103 after the numerical value of m is added 1;
Ustomer premises access equipment in step 110, this total collection is abnormal ustomer premises access equipment, and process ends.
In the present embodiment, after the feature occurred by the ustomer premises access equipment received, judge whether this feature and the setting feature in this feature database mate the object realizing judging whether to occur abnormal ustomer premises access equipment further.But it will be recognized by those skilled in the art that embodiment just exemplifies, the present invention is not limited to above-described embodiment.In fact the present invention can adopt other prior art to reach the object judging whether to have occurred abnormal ustomer premises access equipment.
The present embodiment also provides a kind of passive optical network using above-mentioned detection method.
Based on detection method and the passive optical network of the ustomer premises access equipment in above-mentioned passive optical network, further illustrate the present invention below by a concrete example:
This passive optical network comprises an OLT, and this OLT corresponds to A respectively to there being 8 ustomer premises access equipments, B, C, D, E, F, G, H, these 8 ustomer premises access equipments form a total collection, when having occurred that ustomer premises access equipment business is frequently interrupted in these 8 ustomer premises access equipments, roll off the production line on ustomer premises access equipment is frequent, when all ustomer premises access equipments of the PON mouth correspondence of OLT all cannot register one or more features received with OLT in loss of signal alarm, detect whether the received signal strength that these 8 ustomer premises access equipments send is zero by RSSI testing mechanism, if received signal strength is zero, then adopt binary chop that this total collection is divided into the first set { A, B, C, D} and second set { E, F, G, H}, namely this first set and this second set include 4 ustomer premises access equipments, and this first set is divided into the first subset { A, B} and the second subset { C, D}, and this second set is divided into three subsetss { E, F} and the 4th subset { G, H}, i.e. this first subset, this second subset, these three subsetss and the 4th subset include 2 ustomer premises access equipments.
By burst clock data reconstruction method to this first subset { A, B} and this second set { E, F, G, H} tests, test result is correct test result, illustrate that A in this first subset and party B-subscriber hold equipment to be normal ustomer premises access equipment, then by this second subset { C, D} and this second set { E, F, G, H} integrates and forms this total collection { C, D, E, F, G, binary chop is again utilized to carry out being divided into this first set { C for three times two after H}, D, E} and this second set { F, G, H}, this first subset { C, D}, this second subset { E}, these three subsetss { F, G} and the 4th subset { H}.
By burst clock data reconstruction method to this first subset { C, D} and this second set { F, G, H} tests, test result is the test result of mistake, then pass through burst clock data reconstruction method again to this second subset { E} and this second set { F, G, H} tests, test result is correct test result, illustrate that the E ustomer premises access equipment in this second subset is normal ustomer premises access equipment, then by this first subset { C, D} and this second set { F, G, H} integrates and forms this total collection { C, D, F, G, binary chop is again utilized to carry out being divided into this first set { C for three times two after H}, D, F} and this second set { G, H}, this first subset { C, D}, this second subset { F}, these three subsetss { G} and the 4th subset { H}.
By burst clock data reconstruction method to this first subset { C, D} and this second set { G, H} tests, test result is the test result of mistake, then pass through burst clock data reconstruction method again to this second subset { F} and this second set { G, H} tests, test result is correct test result, illustrate that the F ustomer premises access equipment in this second subset is normal ustomer premises access equipment, then by this first subset { C, D} and this second set { G, H} integrates and forms this total collection { C, D, G, binary chop is again utilized to carry out being divided into this first set { C for three times two after H}, D} and this second set { G, H}, this first subset { C}, this second subset { D}, these three subsetss { G} and the 4th subset { H}.
By burst clock data reconstruction method, to this first subset, { { G, H} test for C} and this second set, test result is correct test result, illustrate that the C ustomer premises access equipment in this first subset is normal ustomer premises access equipment, then by this second subset, { { G, H} integrate this total collection of formation, and { { { G, H}, { D}, this second subset are empty set, these three subsetss { G} and the 4th subset { H} to this first subset for D} and this second set again to utilize binary chop to carry out being divided into this first set for three times two after D, G, H} for D} and this second set.
By burst clock data reconstruction method to this first subset { D} and this second set { G, H} tests, test result is the test result of mistake, then pass through burst clock data reconstruction method again to this second subset empty set and this second set { G, H} tests, test result is the test result of mistake, then by burst clock data reconstruction method, to this first set, { { G} tests D} with these three subsetss again, test result is correct test result, illustrate that the G ustomer premises access equipment in these three subsetss is normal ustomer premises access equipment, by this first set, { { H} integrates and forms this total collection { D for D} and the 4th subset, binary chop is again utilized to carry out being divided into this first set { D} and this second set { H} for three times two after H}, this first subset { D}, this second subset is empty, { H} and the 4th subset are empty set to these three subsetss.
By burst clock data reconstruction method successively to this first subset { D} and this second set { H}, this the second subset empty set and this second set { H}, this first set { D} and the 3rd set { H}, { D} and the 4th subset empty set are tested in this first set, test result is the test result of mistake, the randomly ordered algorithm of equiprobability is then adopted to carry out once randomly ordered to all ustomer premises access equipments in this total collection, this general collection after sequence is combined into { H, D}, pass through burst clock data reconstruction method more respectively to this first subset { H} and this second set { D}, this the second subset empty set and this second set { D}, this first set { H} and these three subsetss { D}, { H} and the 4th subset empty set are tested in this first set, test result is the test result of mistake, the randomly ordered algorithm of equiprobability is then adopted to carry out once randomly ordered to all ustomer premises access equipments in this total collection, again tested by burst clock data reconstruction method, test result is the test result of mistake, ustomer premises access equipment D and H then in this total collection is abnormal ustomer premises access equipment.In this course, randomly ordered number of times be 2! , namely 2 times.
Embodiment 2
The present embodiment also provides the detection method of the ustomer premises access equipment in a kind of passive optical network on the basis of embodiment 1, and as shown in Figure 2, this detection method comprises the following steps:
Step 201, receive this ustomer premises access equipment occur feature after, judge whether this feature mates with the setting feature in this feature database, if result is coupling, judge in this ustomer premises access equipment, to have occurred potential abnormal ustomer premises access equipment, then enter step 202, if result is not for mate, judge not occur potential abnormal ustomer premises access equipment in this ustomer premises access equipment, then process ends;
This total collection is divided into the first set and the second set by step 202, employing binary chop, and this first set is divided into the first subset sums second subset, and this second set is divided into three subsetss and the 4th subset;
Step 203, by burst clock data reconstruction method to this first subset sums this second set test, if test result is correct test result, then this second set of this second subset sums is integrated after forming this total collection and again perform step 202, if test result is the test result of mistake, then enter step 204;
Step 204, by burst clock data reconstruction method to this second subset sums this second set test, if test result is correct test result, then this second set of this first subset sums is integrated after forming this total collection and again perform step 202, if test result is the test result of mistake, then enter step 205;
Step 205, by burst clock data reconstruction method to these three subsetss and this first set test, if test result is correct test result, then this first set of the 4th subset sums is integrated after forming this total collection and again perform step 202, if test result is the test result of mistake, then enter step 206;
Step 206, by burst clock data reconstruction method to the 4th subset sums this first set test, if test result is correct test result, then these three subsetss and this first set are integrated after forming this total collection and again perform step 202, if test result is the test result of mistake, then enter step 207;
Step 207, judge whether the numerical value of m reaches a setting numerical value, if not, then enters step 208, if so, then enters step 209, wherein, this setting numerical value is the quantity of all ustomer premises access equipments in the total collection when step 207;
Step 208, the randomly ordered algorithm of employing equiprobability carry out once randomly ordered to all ustomer premises access equipments in this total collection, and enter step 202 after the numerical value of m is added 1;
Ustomer premises access equipment in step 209, this total collection is potential abnormal ustomer premises access equipment, and process ends.
The present embodiment also provides a kind of passive optical network using above-mentioned detection method.
Based on detection method and the passive optical network of the ustomer premises access equipment in above-mentioned passive optical network, further illustrate the present invention below by a concrete example:
This passive optical network comprises an OLT, this OLT corresponds to A respectively to there being 6 ustomer premises access equipments, B, C, D, E, F, these 6 ustomer premises access equipments form a total collection, when having occurred that ustomer premises access equipment business is frequently interrupted in these 6 ustomer premises access equipments, roll off the production line on ustomer premises access equipment is frequent, when all ustomer premises access equipments of the PON mouth correspondence of OLT all cannot register one or more features received with OLT in loss of signal alarm, then adopt binary chop that this total collection is divided into the first set { A, B, C} and second set { D, E, F}, this first set is divided into the first subset { A, B} and the second subset { C}, and this second set is divided into three subsetss { D, E} and the 4th subset { F}.
By burst clock data reconstruction method to this first subset { A, B} and this second set { D, E, F} tests, test result is the test result of mistake, then pass through burst clock data reconstruction method again to this second subset { C} and this second set { D, E, F} tests, test result is correct test result, illustrate that the C ustomer premises access equipment in this second subset is normal ustomer premises access equipment, then by this first subset { A, B} and this second set { D, E, F} integrates and forms this total collection { A, B, D, E, binary chop is again utilized to carry out being divided into this first set { A for three times two after F}, B, D} and this second set { E, F}, this first subset { A, B}, this second subset { D}, these three subsetss { E} and the 4th subset { F}.
By burst clock data reconstruction method to this first subset { A, B} and this second set { E, F} tests, test result is the test result of mistake, then pass through burst clock data reconstruction method again to this second subset { D} and this second set { E, F} tests, test result is correct test result, illustrate that the D ustomer premises access equipment in this second subset is normal ustomer premises access equipment, then by this first subset { A, B} and this second set { E, F} integrates and forms this total collection { A, B, E, binary chop is again utilized to carry out being divided into this first set { A for three times two after F}, B} and this second set { E, F}, this first subset { A}, this second subset { B}, these three subsetss { E} and the 4th subset { F}.
By burst clock data reconstruction method, to this first subset, { { E, F} test for A} and this second set, test result is correct test result, illustrate that the party A-subscriber in this second subset holds equipment to be normal ustomer premises access equipment, then by this second subset, { { E, F} integrate this total collection of formation and { again utilize binary chop to carry out being divided into this first set { B, E} and this second set { F}, this first subset { B}, this second subset { E}, these three subsetss { F} and the 4th subset empty set for three times two after B, E, F} for B} and this second set.
By burst clock data reconstruction method successively to this first subset { B} and this second set { F}, this second subset { E} and this second set { F}, this first set { B, E} and these three subsetss { H}, this first set { B, E} and the 4th subset empty set are tested, test result is the test result of mistake, the randomly ordered algorithm of equiprobability is then adopted to carry out once randomly ordered to all ustomer premises access equipments in this total collection, to the total collection after randomly ordered utilize binary chop carry out three times two points, and by burst clock data reconstruction method successively to this second set of this first subset sums, this second set of this second subset sums, these first set and these three subsetss, this first set and the 4th subset are tested, test result is the test result of mistake, then adopt equiprobability randomly ordered algorithm to all ustomer premises access equipments in this total collection carry out randomly ordered 3! secondary is that after 6 times, each test result is still the test result of mistake, then can show that ustomer premises access equipment B, E, the H in total collection is abnormal ustomer premises access equipment.
Can show that the detection method of this ustomer premises access equipment can not only find out single rogue ONU from embodiment 1 and embodiment 2, the rogue ONU that influencing each other between multiple ONU causes can also be found out, search accuracy rate high and comprehensively, and there is relatively short, logical complexity consuming time reduce and detection method advantage flexibly.
Although the foregoing describe the specific embodiment of the present invention, it will be understood by those of skill in the art that these only illustrate, protection scope of the present invention is defined by the appended claims.Those skilled in the art, under the prerequisite not deviating from principle of the present invention and essence, can make various changes or modifications to these execution modes, but these change and amendment all falls into protection scope of the present invention.
Claims (9)
1. the detection method of the ustomer premises access equipment in a passive optical network, this passive optical network comprises an OLT, this OLT is to there being N number of ustomer premises access equipment, this ustomer premises access equipment is ONU or ONT, and wherein, N is positive integer, this N number of ustomer premises access equipment forms a total collection, it is characterized in that, setting m=0, this detection method comprises the following steps:
S
1, judge whether occur abnormal ustomer premises access equipment in this ustomer premises access equipment, if so, then enter step S
2, if not, then process ends;
S
2, detect whether the received signal strength that this ustomer premises access equipment sends is zero, if received signal strength is zero, then enter step S
3, if not, then process ends;
S
3, adopt binary chop this total collection is divided into the first set and second set, by this first set be divided into the first subset sums second subset, and by this second set be divided into three subsetss and the 4th subset,
S
4, by burst clock data reconstruction method, this second set of this first subset sums is tested, if test result is correct test result, then this second set of this second subset sums is integrated to form after this total collection and again performs S
3if test result is the test result of mistake, then enter step S
5;
S
5, by burst clock data reconstruction method, this second set of this second subset sums is tested, if test result is correct test result, then this second set of this first subset sums is integrated to form after this total collection and again performs S
3if test result is the test result of mistake, then enter step S
6;
S
6, by burst clock data reconstruction method, these three subsetss and this first set are tested, if test result is correct test result, then this first set of the 4th subset sums is integrated to form after this total collection and again performs S
3if test result is the test result of mistake, then enter step S
7;
S
7, by burst clock data reconstruction method, this first set of the 4th subset sums is tested, if test result is correct test result, then these three subsetss and this first set is integrated to form after this total collection and again perform S
3if test result is the test result of mistake, then enter step S
8,
Wherein, when any one subset in this first subset, this second subset, these three subsetss and the 4th subset is empty set, the set corresponding to this subset sums by burst clock data reconstruction method is tested, and test result is the test result of mistake;
S8, judge whether the numerical value of m reaches a setting numerical value, if not, then enters S9, if so, then enters S
10;
S
9, adopt equiprobability randomly ordered algorithm to carry out once randomly ordered to all ustomer premises access equipments in this total collection, and enter step S after the numerical value of m is added 1
3;
S
10, ustomer premises access equipment in this total collection is abnormal ustomer premises access equipment, and process ends.
2. detection method as claimed in claim 1, is characterized in that, store the feature database that comprises multiple setting feature, step S in this OLT
1comprise:
S
1, receive this ustomer premises access equipment occur feature after, judge whether this feature mates with the setting feature in this feature database, if result for mate, judge in this ustomer premises access equipment, to have occurred abnormal ustomer premises access equipment, then enter step S
2if result, for not mate, judges not occur abnormal ustomer premises access equipment in this ustomer premises access equipment, then process ends.
3. detection method as claimed in claim 2, it is characterized in that, this setting feature comprises: this ustomer premises access equipment business is frequently interrupted, this ustomer premises access equipment frequent on roll off the production line, all ustomer premises access equipments of the PON mouth correspondence of this OLT all cannot register and this OLT receives loss of signal alarm.
4. detection method as claimed in claim 1, is characterized in that, detects by RSSI testing mechanism the received signal strength that this ustomer premises access equipment sends.
5. detection method as claimed in claim 1, is characterized in that, this sets numerical value as in step S
8time total collection in the quantity of all ustomer premises access equipments.
6. the detection method of the ustomer premises access equipment in a passive optical network, this passive optical network comprises an OLT, this OLT is to there being N number of ustomer premises access equipment, this ustomer premises access equipment is ONU or ONT, and wherein, N is positive integer, this N number of ustomer premises access equipment forms a total collection, it is characterized in that, setting m=0, this detection method comprises the following steps:
S
1, judge whether occur potential abnormal ustomer premises access equipment in this ustomer premises access equipment, if so, then enter step S
2, if not, then process ends;
S
2, adopt binary chop this total collection is divided into the first set and second set, by this first set be divided into the first subset sums second subset, and by this second set be divided into three subsetss and the 4th subset,
S
3, by burst clock data reconstruction method, this second set of this first subset sums is tested, if test result is correct test result, then this second set of this second subset sums is integrated to form after this total collection and again performs S
2if test result is the test result of mistake, then enter step S
4;
S
4, by burst clock data reconstruction method, this second set of this second subset sums is tested, if test result is correct test result, then this second set of this first subset sums is integrated to form after this total collection and again performs S
2if test result is the test result of mistake, then enter step S
5;
S
5, by burst clock data reconstruction method, these three subsetss and this first set are tested, if test result is correct test result, then this first set of the 4th subset sums is integrated to form after this total collection and again performs S
2if test result is the test result of mistake, then enter step S
6;
S
6, by burst clock data reconstruction method, this first set of the 4th subset sums is tested, if test result is correct test result, then these three subsetss and this first set is integrated to form after this total collection and again perform S
2if test result is the test result of mistake, then enter step S
7,
Wherein, when any one subset in this first subset, this second subset, these three subsetss and the 4th subset is empty set, the set corresponding to this subset sums by burst clock data reconstruction method is tested, and test result is the test result of mistake;
S
7, judge whether the numerical value of m reaches a setting numerical value, if not, then enters S
8, if so, then enter S
9;
S
8, adopt equiprobability randomly ordered algorithm to carry out once randomly ordered to all ustomer premises access equipments in this total collection, and enter step S after the numerical value of m is added 1
2;
S
9, ustomer premises access equipment in this total collection is potential abnormal ustomer premises access equipment, and process ends.
7. detection method as claimed in claim 6, is characterized in that, store the feature database that comprises multiple setting feature, step S in this OLT
1comprise:
S
1, receive this ustomer premises access equipment occur feature after, judge whether this feature mates with the setting feature in this feature database, if result for mate, judge in this ustomer premises access equipment, to have occurred potential abnormal ustomer premises access equipment, then enter step S
2if result, for not mate, judges not occur potential abnormal ustomer premises access equipment in this ustomer premises access equipment, then process ends.
8. detection method as claimed in claim 6, is characterized in that, this sets numerical value as in step S
7time total collection in the quantity of all ustomer premises access equipments.
9. a passive optical network, is characterized in that, this passive optical network uses as the detection method in claim 1-5 as described in any one, and/or this passive optical network uses as the detection method in claim 6-8 as described in any one.
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| CN102142897A (en) * | 2011-03-29 | 2011-08-03 | 华为技术有限公司 | Detection method and device of ONU (optical network unit) as well as passive optical network system |
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| CN102142897A (en) * | 2011-03-29 | 2011-08-03 | 华为技术有限公司 | Detection method and device of ONU (optical network unit) as well as passive optical network system |
| CN103036612A (en) * | 2012-12-18 | 2013-04-10 | 华为技术有限公司 | Detection method, isolation method and device of rascal optical network unit (ONU) |
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