ÕªÒª: ±¾ÎÄͨ¹ý IBM SPSS Statistics ÖÐµÄ Python
±à³ÌÄ£¿é¶ÔÔʼ AT&T ÍøÂçÊý¾Ý½øÐÐÔ¤´¦Àí£¬È»ºó½áºÏÏßÐÔÄ£ÐͺÍÃÉÌØ¿¨Âå·ÂÕæ·ÖÎö£¬¿ÉÒÔÔÚÔʼÉÙÁ¿Êý¾ÝµÄ»ù´¡ÉÏ´óÁ¿·ÂÕæÄ£ÄâÆóÒµµÄÕæʵÍøÂç´ø¿íʹÓÃÇé¿ö£¬´Ó¶øΪÆóÒµµÄ´ø
...
ÏÖ×´ºÍÒâÒå
Ô½À´Ô½¶àµÄÆóÒµ£¬¿ªÊ¼¹Ø×¢Æä¹ãÓòÍø´ø¿íµÄʹÓÃ×´¿ö¡£¶Ô¹ãÓòÍø´ø¿íµÄʹÓ÷ÖÎö£¬²»½ö¿ÉÒÔÈ·±£ÆóÒµ¹Ø¼üÒµÎñµÃµ½³ä·ÖµÄ´ø¿í±£ÕÏ£¬¶øÇÒÒ²¿ÉÒÔ·¢ÏÖ´ø¿íʹÓÃÖÐ×î´óµÄÍþвÀ´×ÔÄÄÀï¡£ÓÉÓڴ󲿷ֵÄÆóÒµ¶¼ÒѾ²¿ÊðÁË»ùÓÚ
SNMP »òÕß Netflow µÄÍø¹Üƽ̨£¬Òò´Ë¶ÔÆóÒµ¶øÑÔ£¬´ø¿íµ±Ç°µÄʹÓÃ×´¿öÊÇÁ˽âµÄ¡£È»¶ø£¬ÎªÁ˽â¾öÒµÎñ·¢Õ¹¶Ô´ø¿íÔö³¤µÄÐèÇ󣬾ÍÐèÒª¼°Ê±Ô¤²âδÀ´´ø¿íµÄÐèÇó×´¿ö£¬´Ó¶øΪÉý¼¶´ø¿íÌṩÒÀ¾Ý¡£
ÓÉÓÚ¹ãÓòÍø´ø¿í·Ç³£°º¹ó£¬Òò´Ë£¬µ±ÆóÒµ¾ö¶¨Éý¼¶¹ãÓòÍø´ø¿íʱ£¬¶ÔÉý¼¶ºóµÄ´ø¿í»áÓÐÑϸñµÄÒªÇó¡£¼ÈÒª±£Ö¤ÆóÒµÒµÎñ¶Ô´ø¿íÔö³¤µÄÐèÇó£¬ÓÖ²»ÄÜÉý¼¶¹ý¶à£¬³öÏÖͶ×ÊÀ˷ѵÄÇé¿ö¡£
ÎÊÌâÃèÊö
Ä¿Ç°£¬¶Ô´ø¿íµÄÔ¤²âÖ÷ÒªÓÐÒÔϼ¸ÖÖ·½·¨¡£µÚÒ»ÖÖ·½·¨£¬Í¨¹ý¼ÆËãµÃµ½¡£¸Ã·½·¨Í¨¹ýÀۼӹؼüÒµÎñËùÕ¼Óôø¿í£¬È»ºó³ËÒÔͬʱÔÚÏߵĸÅÂÊ¡£µÚ¶þÖÖ·½·¨£¬Í¨¹ýÆóÒµÏÖÓÐÍø¹ÜÊý¾Ý×ö¼òµ¥ÍÆÑÝ¡£µÚÈýÖÖ·½·¨£¬Í¨¹ýÆóÒµÏÖÓÐÍø¹ÜÊý¾Ý½¨Á¢ÊýѧģÐÍ£¬´Ó¶øÔ¤²âδÀ´´ø¿íÐèÇó¡£
ÉÏÊöÇ°Á½ÖÖ·½·¨Îó²î½Ï´ó£¬ÎÞ·¨Âú×ãÆóÒµÉý¼¶´ø¿íʱ£¬¶Ô׼ȷÐÔµÄÒªÇ󡣶ø±¾ÎÄËùÒªÌÖÂ۵ģ¬ÕýÊÇ´ÓÆóÒµÍø¹ÜÊý¾Ý×ÅÊÖ½¨Á¢ÊýѧģÐÍ£¬×¼È·µØÔ¤²âδÀ´´ø¿íÐèÇó¡£
´ø¿í·ÖÎö·½·¨
Êý¾ÝÉú³É·½·¨
ÆóÒµÍø¹Ü¹¤¾ß½éÉÜ
Ä¿Ç°£¬ÃæÏò´óÖÐÐÍÆóÒµµÄÍø¹Ü²úÆ·Ö÷ÒªÊÇ»ùÓÚ SNMP ÐÒé»òÕß˼¿ÆµÄ Netflow ¼¼Êõ¡£»ùÓÚ SNMP
ÐÒéµÄÍø¹Ü²úÆ·£¬ÓÅÊÆÔÚÓÚ²¶»ñÁ´Â·µÄÀûÓÃÂÊ£¬ÓÃÀ´Éú³ÉÀûÓÃÂÊ»ùÏßÒÔ¼°²¶»ñÍøÂçÉ豸µÄÐÔÄܲÎÊý£¬±ÈÈç CUP¡¢MEM
µÈ¡£·Ç³£ÖøÃûµÄ Orion NPM ¾ÍÊÇÕâÀàÍø¹Ü²úÆ·£»ÁíÍâÒ»ÀàÊÇ»ùÓÚ Netflow µÄÍø¹Ü²úÆ·¡£ËüµÄÓÅÊÆÔÚÓÚ¶Ô
IP µØÖ·ºÍÁ÷Á¿ÐÒéµÄ·ÖÎö£¬Èç Orion NTA¡£½üÄêÀ´£¬Íø¹Ü²úÆ·Ò²³öÏÖ¶ÔÁ½ÖÖ¼¼ÊõÈںϵÄÇ÷ÊÆ¡£
ʵÀý£ºAT&T ¹¤¾ß»ñÈ¡Êý¾Ý
±¾ÎÄËùʹÓõÄÍø¹Üƽ̨£¬À´×Ô»ùÓÚ Netflow µÄÍø¹Ü²úÆ· Application Traffic Analyzer£¬ÈçÏÂͼ
1 Ëùʾ¡£Éú³É±¨±íʱ£¬¿ÉÒÔ¶¨ÒåµÄÖ÷Òª×Ö¶ÎÖ÷ÒªÓУº
Function£º¸Ã×Ö¶ÎÓÃÀ´¶¨Ò屨±íµÄ¹¦ÄÜ£¬±ÈÈ磬¿ÉÒÔÉú³ÉÒÔÐÒé¡¢»á»°¡¢Ä¿µÄ IP¡¢·þÎñ·ÖÀàΪÖ÷ÒªÄÚÈݵı¨±í£»
Report Type£º¸Ã×Ö¶ÎÓÃÀ´¶¨ÒåÉú³É±¨±íµÄÀàÐÍ£¬±ÈÈçͼ±í¡¢Öù״ͼ¡¢±ý״ͼµÈ£»
Granularity£º¸Ã×Ö¶ÎÓÃÀ´¶¨ÒåÉú³É±¨±íµÄ¿ÅÁ£¶È£¬±ÈÈç 5 ·ÖÖÓ¡¢10 ·ÖÖÓ¡¢1 Сʱ¡¢1 Ìì¡¢1
ÐÇÆڵȣ»
Traffic Direction£º¸Ã×ֶζ¨ÒåÁ÷Á¿µÄ·½Ïò£¬ÊÇÈëÁ÷Á¿»¹ÊdzöÁ÷Á¿£»
Statistic£º¸Ã×ֶζ¨ÒåÁËͳ¼Æ·½·¨£¬±ÈÈ磺ÇóºÍ¡¢Çóƽ¾ùÖµ¡¢Çó×î´óÖµ¡¢Çó 95% µÈ£»
Scaling£º¸Ã×ֶζ¨ÒåÁËÁ÷Á¿µ¥Î»£¬±ÈÈ磺Mbps¡¢Megabytes¡¢Kilobytes µÈ¡£
ͼ 1. Application Traffic Analyzer
±¾ÎÄËùʹÓõı¨±í£¬ÒÔ 5 ·ÖÖÓΪ²ÉÑùµ¥Î»£¬Ã¿ÌìÉú³ÉÒ»Õŵ¥¶ÀµÄ±¨±í¡£¶¨ÒåµÄÖ÷Òª×Ö¶ÎÈçÏ£º
Time range£º9:00 am ¨C 19:00 pm Scaling£ºMbps Statistic£ºSum Traffic direction£ºinbound£¨ÓÉÓÚ Inbound Á÷Á¿Ô¶´óÓÚ Outbound Á÷Á¿£¬ËùÒÔÔÚÕâÀïÎÒÃÇÑ¡È¡½Ï´ó·½ÏòµÄÁ÷Á¿£© Function£ºdestinations£¨ÔÚÕâÀÎÒÃÇÒÔÄ¿µÄµØ IP À´ÅÅÐòËùÓÐµÄ inbound Á÷Á¿£© |
Êý¾ÝÔ¤´¦Àí
²¢²»ÊÇËùÓеÄÔʼÊý¾Ý¶¼ÄÜÖ±½ÓÓÃÀ´¹¹½¨Ô¤²âÄ£ÐÍ¡£Í¨¹ý¶Ô´ý½â¾öµÄÎÊÌâ½øÐÐÒ»¸öÃ÷È·ÇåÎúµÄ¶¨Ò壬À´È·¶¨ÔʼÊý¾ÝÊÇ·ñÄÜÖ±½ÓÖ§³Ö½â¾ö·½°¸µÄ¹¹½¨¡£Èç¹û²»ÄÜ£¬ÔòÐèÒª¶ÔһЩ×ֶνøÐд¦Àí£¬Éú³É¼ä½ÓÊý¾Ý½¨Ä£¡£ÕâÑù¼È¿ÉÒÔÌṩ×ã¹»µÄÐÅÏ¢Ö§³Ö£¬Ò²Äܱ£Ö¤Ô¤²â½á¹ûÊǿɺâÁ¿¡¢¿ÉÀí½âµÄ£¬´Ó¶ø±ãÓÚÆÀ¹À½â¾ö·½°¸µÄ½á¹û¡£
Êý¾Ý·ÖÎöºÍ¶¨Òå
´Ó IT ²¿ÃÅÄõ½µÄÔʼÊý¾Ý£¬ÔÚÔ¤´¦ÀíÇ°Ê×ÏÈÒª½øÐÐÊý¾Ý·ÖÎö¡£¸ù¾Ý½â¾ö·½°¸µÄÄ¿±ê¶¨Òå±íÖ®¼äµÄ¹Øϵ¡¢±íµÄ½á¹¹£¨Ä¿±ê±äÁ¿ºÍÒò±äÁ¿£©¡£
±¾ÎÄÖУ¬IT ²¿ÃÅÌṩÁË´Ó 2012 Äê 11 Ôµ½ 2013 Äê 1 ÔµÄÍøÂçÁ÷Á¿Êý¾Ý¡£ÕâЩÊý¾Ý°´ÕÕÿÌìµÄÍøÂçÁ÷Á¿¶ÀÁ¢ÖÆ±í£¬°ëÄê¹²¼Æ
92 ÕÅ±í£¨EXCEL ¸ñʽ£©£¬Ã¿Õűí¸ñʽͳһ¡£ÏÖÔÚÒÔ 2012 Äê 11 Ô 17 ÈÕΪÀý£¬½éÉÜÔʼ±íµÄ½á¹¹¡£
ͼ 2. Ôʼ±í½á¹¹
Èçͼ 2 Ëùʾ£ºÔʼ±íµÄÐбäÁ¿ÊÇÈÕÍøÂçÁ÷Á¿½øÈëÇ° 100 ÃûµÄ IP ¼¯ºÏ£¬ÆäÖаüÀ¨ÍøÂç»·¾³ÏµķþÎñÆ÷£¨Server£©ºÍ
PC Öն˻úÆ÷£¨Client£©¡£±íµÄÁбäÁ¿ÊÇÿ¸ö IP ÿ¸ô 5 ·ÖÖÓ£¨Ê±¼äµã£©¼Ç¼µÄÍøÂçÁ÷Á¿Öµ¡£´ÓÔç
9 µãµ½Íí 7 µã¹²¼Æ 119 ÁС£
±¾ÎĵÄÄ¿±êÊÇÒªÕÒµ½Ó°ÏìijÆóÒµÍøÂç×ÜÁ÷Á¿µÄÒòËØ¡£ÔʼÊý¾ÝÌṩµÄÐÅÏ¢ÓмǼʱ¼ä¡¢Server Á÷Á¿ºÍ Client
Á÷Á¿¡£¸ù¾ÝÊý¾Ý·ÖÎö½á¹û£¬ÎÒÃǶ¨ÒåÁËÓÃÓÚ½¨Ä£µÄÖÕ±í½á¹¹£¬Èçͼ 3 Ëùʾ¡£
ͼ 3. ÖÕ±í½á¹¹
ÎÒÃǶ¨ÒåµÄÄ¿±ê±äÁ¿ÊÇÍøÂç×ÜÁ÷Á¿ COS_Total£¬Òò±äÁ¿ÓмǼÈÕÆÚ Date£¬Ç° 10~70 ¸ö·þÎñÆ÷ÍøÂçÁ÷Á¿×ܺʹÓ
Top10Server_sum µ½ Top70Server_sum£¬Ç° 10~70 ¸öÖն˻úÆ÷ÍøÂçÁ÷Á¿×ܺʹÓ
Top10Client_sum µ½ Top70Client_sum¡£Ã¿Ò»ÕÅÔʼ±íµÄÐÅÏ¢×÷ΪÖÕ±íµÄÒ»¸öÐмǼ´æÔÚ¡£
Python ±à³Ì½Ó¿Ú£¬Êý¾ÝÔ¤´¦Àí×Ô¶¯»¯
´ÓÖÕ±íºÍÔʼ±íµÄ½á¹¹¿ÉÒÔ¿´³ö£¬Ôʼ±íµÄ±äÁ¿²»ÄÜÖ±½Ó×÷ΪÖÕ±íµÄ±äÁ¿¡£Õâ¾ÍÐèÒª°ÑÿÕÅÔʼ±íµÄʱ¼äµãÁ÷Á¿ÐÅϢת»»ÎªÈÕÁ÷Á¿ÐÅÏ¢¡£ÎÒÃÇÈÏΪÄܹ»Âú
95%Óû§ÍøÂçÁ÷Á¿ÐèÇóµÄÁ÷Á¿Öµ¿ÉÒÔ×÷ΪÆóÒµµ±ÌìµÄÍøÂçÁ÷Á¿×ܺÍÖµ¡£
ת»»µÄ˼·ÊÇ£º1£©Ã¿¸ö IP ÿÌìµÄÍøÂçÁ÷Á¿Öµ total_per_IP£¬µÈÓÚÉýÐòÅÅÁиà IP µ±ÌìËùÓÐʱ¼äµãÍøÂçÁ÷Á¿Öµºó£¬È¡µÚ
95%µÄÖµ¡£¸ù¾Ý total_per_IP ֵѡȡÅÅÃûÇ° 10~70 µÄ·þÎñÆ÷ºÍÖնˡ£2£©Ã¿ÌìÇ° 10~70
¸ö·þÎñÆ÷/Öն˲úÉúµÄÍøÂç×ÜÁ÷Á¿ topNClient/Server_sum£¬È¡Ç° 10~70 ¸ö·þÎñÆ÷/Öն˲úÉúµÄÍøÂçÁ÷Á¿¾ùÖµ¡£3£©ÍøÂç×ÜÁ÷Á¿Öµ
COS_Total£¬µÈÓÚ½«ËùÓÐ IP ÔÚÿ¸öʱ¼äµã²úÉúµÄÍøÂçÁ÷Á¿×ܺÍÉýÐòÅÅÁкó£¬È¡µÚ 95%µÄÖµ¡£¶¨ÒåÈçÏ£º
total_per_IP=Percentage(Sort(Time1,Time2,Time3,¡,Time119)ascending)95% topNClient/Server_sum=Mean(SumTime1,SumTime2,SumTime3,¡,SumTime119) COS_Total= Percentage(Sort(SumTime1,SumTime2,SumTime3,¡,SumTime119)ascending)95% |
ͳ¼Æ·ÖÎöÈí¼þ IBM SPSS Statistics ÔÚÓµÓеÄÇ¿´óµÄÊý¾Ý´¦ÀíÄÜÁ¦µÄͬʱ£¬Ò²ÌṩÁ˷ḻµÄ±à³Ì½Ó¿Ú£¨Python¡¢R¡¢.Net£©¡£±¾ÎÄÔËÓÃ
Statistics µÄ Compute¡¢Aggregate¡¢Transpose¡¢OMS¡¢Merge µÈ¹¦ÄܶÔÔʼÊý¾Ý½øÐвÙ×÷²¢ÕûºÏ£¬×îºóͨ¹ý±àд
Python ½Å±¾Åú´¦Àí´óÁ¿Êý¾Ý±í£¬ÊµÏÖÊý¾ÝÔ¤´¦Àí×Ô¶¯»¯¡£¹ØÓÚÈçºÎÔÚ Statistics ÖÐÔËÐÐ Python
½Å±¾£¬Çë²Î¼û Statistics ²úÆ·°ïÖúÎĵµ¡£
ÕâÀïÐèÒªÌáµ½µÄÊÇ£¬Ôʼ±íÖеÄûÓÐÇø·Ö·þÎñÆ÷ºÍ PC Öͦ赀 IP µØÖ·£¬Python ·â×°µÄ Netaddr
°üÄܹ»¸ù¾Ý¿Í»§É趨µÄ¹æÔò¶Ô IP ·ÖÀà¡£´¦Àí¹ý³ÌÈçÏÂͼ 4 Ëùʾ¡£
ͼ 4. IP ·ÖÀà½Å±¾
½¨Ä£¼°·ÖÎö
ÏßÐÔÄ£Ð͵Ľ¨Á¢
ͨ¹ý IBM SPSS Statistics ÌṩµÄÏßÐԻعé·ÖÎöÄ£¿é£¬ÉèÖýçÃæÈçÏÂͼ 5 Ëùʾ£¬¿ÉÒÔÕë¶Ô
3 ¸öÔµÄÊý¾Ý£¬Ñ°ÕÒ COS_Total Óë¸÷¸öÊäÈë±äÁ¿Ö®¼äµÄ¹Øϵ¡£
ͼ 5. ÏßÐԻعé·ÖÎö
ͨ¹ý±í 1 ºÍ±í 2 ¿ÉÒÔ¿´³ö¿ÉÒÔÀûÓà Top40Server_sum¡¢Top50Client_sum
½¨Á¢ÏßÐÔÄ£ÐÍÀ´Ô¤²â COS_Total£¬Ô¤²â׼ȷ¶È´ïµ½ 86.2%£¬ËµÃ÷ COS_Total Óë Top40Server_sum¡¢Top50Client_sum
µÄ¹Øϵ×îΪ½ôÃÜ£¬²¢¿ÉÒÔ½¨Á¢ÏßÐÔÄ£Ð͵ķ½³ÌÀ´Ô¤²â COS_Total¡£
COS_Total = 2.264+ 2.774 * Top40Server_sum + 2.976
* Top50Client_sum
±í 1. Ä£Ð͸ÅÒª
±í 2. ϵÊý
ÃÉÌØ¿¨Âå·ÂÕæ·ÖÎö
ÃÉÌØ¿¨Âå·ÂÕæ·ÖÎöÊÇ IBM SPSS Statistics 21 °æ±¾ºóÐÂÔö¼ÓµÄ¹¦ÄÜ£¬ÆäÔÀíÊǵ±ÎÊÌâ»ò¶ÔÏó±¾Éí¾ßÓиÅÂÊÌØÕ÷ʱ£¬¿ÉÒÔÓüÆËã»úÄ£ÄâµÄ·½·¨²úÉú³éÑù½á¹û£¬¸ù¾Ý³éÑù¼ÆËãͳ¼ÆÁ¿»òÕß²ÎÊýµÄÖµ¡£Ëæ×ÅÄ£Äâ´ÎÊýµÄÔö¶à£¬¿ÉÒÔͨ¹ý¶Ô¸÷´Îͳ¼ÆÁ¿»ò²ÎÊýµÄ¹À¼ÆÖµÇóƽ¾ùµÄ·½·¨µÃµ½Îȶ¨½áÂÛ£¬ÃÉÌØ¿¨Âå·ÖÎöÔÚ½ðÈÚ¡¢Ò½Ò©µÈ¶à¸öÐÐÒµÓÐ׏㷺µÄÓ¦Óá£
ÒòΪÔÚÕâÀïÖ»ÓÐ 3 ¸öÔµÄÍøÂçÁ÷Á¿Êý¾Ý£¬²¢ÇÒÓÐÔ¤²â COS_Total ÏßÐÔÄ£ÐÍ·½³Ì£¬Òò´ËÎÒÃÇ¿ÉÒÔ¸ù¾ÝÈý¸ö¸öÔÂÊý¾ÝµÄ·Ö²¼ÌØÕ÷£¬ÓÃÄ£Ä⹦ÄÜÉú³É´óÁ¿Ä£ÄâÊý¾Ý£¬²¢¸ù¾ÝÄ£ÄâÊý¾Ý·ÖÎö³ö
COS_Total µÄ·Ö²¼ÌØÕ÷£¬´Ó¶ø¶Ô¹«Ë¾µÄºÏÀí´ø¿íʹÓÃÌṩÒÀ¾Ý¡£
ÔÚ IBM SPSS Statistics 22 ÖÐÑ¡Ôñ·ÖÎö²Ëµ¥ÏµÄÄ£ÄâÄ£¿é£¬´ò¿ªÈçÏÂͼ 6 ½çÃ棬ѡÔñ¡°ÊäÈë·½³Ì¡±¡£
ͼ 6. Ä£ÄâÄ£¿é
ÔÚ¡°·½³Ì±à¼Æ÷¡±¶Ô»°¿òÖУ¨Í¼ 7£©£¬½«Ç°ÃæÓÃÀ´Ô¤²â COS_Total µÄÏßÐÔ·½³ÌÊäÈëµ½ÏÂÃæµÄ¡°Êý×Ö±í´ïʽ¡±ÖУ¬µ¥»÷¡°¼ÌÐø¡±°´Å¥È·ÈÏ¡£
ͼ 7. ·½³Ì±à¼Æ÷
ÔÚ¡°Ä£Ä⡱ҳÃ棬µ¥»÷¡°ÄâºÏÈ«²¿¡±°´Å¥£¬Statistics Èí¼þ¾Í»á¸ù¾ÝÒÑÓÐµÄ 3 ¸öÔÂÊý¾ÝÖÐµÄ Top40Server_sum
ºÍ Top50Client_sum ±äÁ¿×Ô¶¯µÄ¼ÆËãÆäÏàÓ¦µÄ·Ö²¼£¬¿ÉÒÔ·¢ÏÖ Top40Server_sum
·ûºÏ Weibull ·Ö²¼£¬¶ø Top50Client_sum ·ûºÏÕý̬·Ö²¼¡£µ¥»÷¡°ÔËÐС±°´Å¥£¬¾Í»á¸ù¾ÝÕâ¸öÁ½¸ö±äÁ¿µÄ·Ö²¼ºÍÒÑÓеÄÏßÐÔ·½³Ì£¬¶Ô
COS_Total µÄ¸ÅÂÊ·Ö²¼½øÐзÂÕæ¼ÆËã¡£
ͼ 8. Ä£Äâ¹¹½¨Æ÷
ÃÉÌØ¿¨Âå·ÂÕæ·ÖÎöµÃµ½µÄ COS_Total µÄ¸ÅÂÊ·Ö²¼ÈçÏÂͼ 9 Ëùʾ¡£Í¼ÖеĺáÖá±íʾ COS_Total
µÄÈ¡Öµ·¶Î§´Ó-100M µ½ 500M£¬×ÝÖá±íʾÁËÔÚÿһ¸ö COS_Total ÖµÉϵĸÅÂÊÃܶȣ¬ÏàÓ¦µÄ±íÖзֱð¸ø³öÁ˸²¸Ç
5% µÄ COS_Total Öµ£¬5%-95% µÄ COS_Total ÖµºÍ 95% µÄ COS_Total
Öµ¡£Òò´Ë˵Ã÷£¬¹«Ë¾²É¹º´ø¿íÈç¹ûÉ趨Ϊ 332.95M ʱ£¬¿ÉÒÔÂú×ã 95% µÄÇé¿öϵÄʹÓã¬Èç¹û²É¹º´ø¿íÉ趨Ϊ
54.52%£¬ÔòÖ»ÄÜÂú×ã 5% µÄÇé¿öʹÓá£
ͼ 9. ¸ÅÂÊÃܶÈ
ÒµÎñ¾ö²ß
ÆóÒµ´ø¿íÏÖ×´ÆÀ¹À
ͼ 10. Íø¹Ü±¨¸æ
´ÓÉÏÊöÍø¹Ü±¨¸æ£¨Í¼ 10£©¿ÉÒÔ¿´µ½£¬ÆóÒµ´ø¿íµÄʵ¼ÊʹÓÃÇé¿öÒÑÓò»Í¬ÑÕÉ«Çø·Ö¡£ÂÌÉ«±íʾÁ´Â·Õ¼ÓÃÂÊСÓÚ 50%£¬ËµÃ÷Á´Â·´¦ÓÚ½¡¿µ×´Ì¬¡£»ÆÉ«±íʾÁ´Â·Õ¼ÓÃÂÊ´¦ÓÚ
50%-70%£¬µ±´¦ÓÚÕâÖÖ״̬ʱ£¬ËµÃ÷ÍøÂç´¦ÓÚÓµÈû״̬£¬¶ª°üʱÓз¢Éú£¬ÐèÒª×ö´ø¿íµÄÉý¼¶×¼±¸ÁË¡£ºìÉ«±íʾÁ´Â·Õ¼ÓÃÂÊ´óÓÚ
70%£¬µ±´¦ÓÚÕâÖÖ״̬ʱ£¬ÒµÎñÐÔÄÜ»áÑÏÖØϽµ£¬ÎÞ·¨±£ÕÏÒµÎñµÄÕý³£Ê¹Óá£ÎÒÃÇ¿ÉÒԵóö½áÂÛ£¬ÆóÒµÐèÒª¾¡¿ìÉý¼¶´ø¿íÁË¡£ÄÇô£¬Éý¼¶µ½¶àÉÙºÏÊÊÄØ£¿
ÆóÒµ´ø¿íÉý¼¶¾ö²ß
¸ù¾ÝÎÒÃÇÇ°ÃæÔ¤²â·ÖÎöµÄ½á¹û£¬ÔÚ 95%µÄÇé¿öÏ£¬ÆóÒµ´ø¿íλÓÚ 332.95Mbps ÒÔÄÚ£¬ÕâºÍÍø¹Ü±¨¸æÖеĴø¿íʵ¼ÊʹÓÃÇé¿öÊÇÒ»Öµġ£ºÏÀíµÄ´ø¿íÉý¼¶·½Ê½£¬ÊǼÈÒª±£Ö¤Á¼ºÃµÄÓû§ÌåÑ飨´ø¿íʹÓÃÂÊ<70%£©£¬ÓÖÄܹ»¾¡Á¿½ÚÊ¡³É±¾¡£Òò´ËÎÒÃǽ¨Òé´ø¿íÉý¼¶µÄÉý¼¶·¶Î§ÊÇ
475.6Mbps£¨332.95/0.7£©~665.9Mbps£¨332.95/0.5£©¡£½«´ø¿íÉý¼¶µ½ 475.6Mbps
ÊÇÒ»¸öºÏÀíµÄ·½°¸£¬Ëü¿ÉÒÔÂú×ãÆóÒµ¾ø´ó¶àÊýÇé¿ö϶ÔÍøÂçµÄʹÓÃÒªÇó£¨ÂÌÉ«£©£¬¼´Ê¹È«Íø×ÊÔ´±»Õ¼ÓÃÒ²²»»á³öÏÖÐÔÄÜÑÏÖØϽµ£¨ºìÉ«£©µÄÎÊÌâ¡£µ±È»£¬Èç¹ûÆóÒµ¶ÔÍøÂçÐÔÄÜÒªÇóºÜ¸ß²¢ÇÒÔ¸ÒâͶÈë³É±¾£¬Ñ¡ÔñÉý¼¶µ½
665.9Mbps ºó£¬ÆóÒµµÄÍøÂç´¦Óڻ᳤ÆÚ´¦ÓÚ½¡¿µ×´Ì¬£¨ÂÌÉ«£©£¬´Ó¶ø¶Ô¹Ø¼üÒµÎñÐÔÄÜÓиü¿É¿¿µÄ±£Ö¤¡£ |