CN101123620A - Method for electronic data processing for concurrent request of a large number of services - Google Patents
Method for electronic data processing for concurrent request of a large number of services Download PDFInfo
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- CN101123620A CN101123620A CNA2007101314222A CN200710131422A CN101123620A CN 101123620 A CN101123620 A CN 101123620A CN A2007101314222 A CNA2007101314222 A CN A2007101314222A CN 200710131422 A CN200710131422 A CN 200710131422A CN 101123620 A CN101123620 A CN 101123620A
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Abstract
An electronic data processing method of concurrent request of a large scale services is disclosed. The system processing does not rely on a database, data recording and statistical query etc are carried out through a file mode, the file is written concurrently, and a file indexing operation is carried out rapidly. When an external system request is accessed, the request is received by a HTTP data acquisition module and is processed by a logic processing module. Then the processed data is transmitted to an external hairpin platform by a FTP data transmission module. The invention does not utilize the database, which greatly decreases system cost and improves system stability. A distributed Cache can integrate data and local map provides concurrent processing for the file. Socket pond carries out a rapid TCP/IP visit and a producer and consumer multithreading disposal mode greatly improves the service processing speed.
Description
Technical field
The present invention relates to the processing of electronic data, be specially a kind of method of electronic data processing of the concurrent request at a large number of services.
Background technology
At the bigger transaction of transaction data amount, the stability of platform is a most important index, requires this platform not come into contacts with database, and stronger fault tolerance is provided, and can tackle a large amount of concurrent requests fast simultaneously.The data that existing treating capacity is big all adopt database platform, and cost is higher.
Summary of the invention
The technical problem to be solved in the present invention is: at the concurrent request of a large number of services, provide a kind of stable large-scale fast electronic data platform.
Technical scheme of the present invention is: the method for the electronic data processing of the concurrent request of a large number of services, system handles does not rely on database, record data, query statistics etc. are undertaken by the mode of file, concurrent written document, carry out the file index operation fast, when the external system request inserts, obtain data module by HTTP and receive request, handle through logic processing module, the data that sent after data module will be handled by FTP are dealt into outside hair fastener platform again, are specially:
(1) obtain data module by HTTP: adopt the cluster strategy of Apache+WebLogic to carry out control and treatment, the Apache frame is in front end, and configuration Apache is distributed to request on the WebLogic cluster of rear end, and the request distribute weightings of configuration Apache;
(2) logic processing module: adopt the mode of multiple step format Cache to carry out the file preservation of WebLogic system, carry out the part mapping for identical file, write operation when realizing file, file read and adopt buffer memory to read;
(3) FTP sends data module: adopt the Socket mode to carry out remote encryption, carry out the connection pool management with pool mode, at first go to obtain available connection from the inside, pond, come and telecommunication.
The present invention adopts the multithreading tupe, the encapsulation producer, and consumer's thread carries out calling service, the producer thread acquisition target is put into shared queue, start a plurality of consumer's threads, consumer's thread obtains data from the shared queue the inside, carries out fast processing.
The present invention does not adopt database, has significantly reduced the cost of system, and has improved the stability of system.Distributed C ache can integral data, and local mapping provides the concurrent processing of file.Quick TCP/IP visit is carried out in the Socket pond, and the processing mode of production, consumer's multithreading has improved professional processing speed greatly.
Description of drawings
Fig. 1 is that hardware of the present invention is disposed schematic diagram.
Fig. 2 is a platform service process chart of the present invention
Fig. 3 is that platform of the present invention inserts process chart
Fig. 4 is that the present invention adopts an Apache and the figure report that WebLogic handles.
Fig. 5 is that the present invention adopts an Apache and the polymerization report that WebLogic handles.
Fig. 6 is that the present invention adopts an Apache and two figure reports that WebLogic handles.
Fig. 7 is that the present invention adopts an Apache and two polymerization reports that WebLogic handles.
Embodiment
System handles of the present invention does not rely on database, record data, and query statistics etc. are undertaken by the mode of file, concurrent written document.When the external system request inserts, obtain data module by HTTP and receive request, handle through logic processing module, the data that sent after data module will be handled by FTP are dealt into outside hair fastener platform again:
(1) HTTP obtains data module: adopt the cluster strategy of Apache+WebLogic to carry out control and treatment, the Apache frame is in front end, and configuration Apache is distributed to request on the WebLogic cluster of rear end, and the request distribute weightings of configuration Apache;
(2) logic processing module: adopt the mode of multiple step format Cache to carry out the file preservation of WebLogic system, carry out the part mapping for identical file, write operation when realizing file, file read and adopt buffer memory to read;
(3) FTP sends data module: adopt the Socket mode to carry out remote encryption, carry out the connection pool management with pool mode, at first go to obtain available connection from the inside, pond, come and telecommunication.
For improving the background process performance, adopt the multithreading tupe, the encapsulation producer, consumer's thread carries out calling service, and the producer thread acquisition target is put into shared queue, starts a plurality of consumer's threads, consumer's thread obtains data from the shared queue the inside, carries out fast processing.
Owing to there is not the database support, need preserve data and transaction situation by file mode, adopt the mode of multiple step format Cache to carry out the unified file preservation of two WebLogic systems, wherein because concurrent transaction is very many, there is frequent concurrent operations at this for same journal file.As a rule, can not carry out write operation simultaneously for identical file.The present invention is by carrying out part mapping, write operation when realizing file to identical file.Because file can be increasing, encapsulate the mode that reads file again in addition, carried out buffer memory and read, improved system greatly and read file, handled the speed of file.
The cluster strategy of Apache+WebLogic of the present invention is:
The Http Server that the Http front server adopts the Apache that increases income, be responsible for finishing following task:
1, carry out the weight configuration according to the performance situation of downstream Web machine, Apache reasonably asks distribution, realizes load balancing.
ProxyPass/balancer://proxy/
<Proxy?balancer://proxy>
BalancerMember?http://192.168.0.97:7001/loadfactor＝1
BalancerMember?http://192.168.0.99:7001/loadfactor＝3
</Proxy>
2, realize by configuration flexibly, can realize complicated distribution requirements.Such as for http://ucreceiver/HQLWebService and http://ucreceiver/HTLWebService, different context root correspondences different distribution policies, send on the Web1 and Web2 in downstream for/HQLWebService, and send on the Web3 and Web4 in downstream for/HTLWebService.
ProxyPass?/HQLWebService?balancer://proxy_HQLWebService/
<Proxy?balancer://proxy_HQLWebService>
The corresponding Web1 of BalancerMember http: // 192.168.0.26:7001/loadfactor=1--
The corresponding Web2 of BalancerMember http: // 192.168.0.99:5555/loadfactor=1--
</Proxy>
ProxyPass?/HTLWebService?balancer://proxy_HTLWebService/
<Proxy?balancer://proxy_HTLWebService>
The corresponding Web3 of BalancerMember http: // 192.168.0.97:6161/loadfactor=1--
The corresponding Web4 of BalancerMember http: // 192.168.0.99:7080/loadfactor=1--
</Proxy>
3, adopt the mode of request distribution, can be promoted for the support situation of system, the system requirements after the next satisfied business development from now on make things convenient for system to carry out dilatation.
Contrast two groups of test datas below:
Prepare three test machine: a DELL D610PC Server (CPU 1.6GHZ, internal memory 1G), Windows XPSP2 operating system is equipped with Apache2.2 and WebLogic9.0, as Apache request distribution;
Two All-China Federation of Taiwan Compatriots think E390PC Server (the two boxes of CPU 1.73GHZ, internal memory 1G), and Windows XP SP2 operating system is equipped with WebLogic9.0, handles as business transaction.
At first construct the test data use-case, create 19 groups of test datas, concurrent number is respectively 10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100, and 50 the simplest request calls are carried out in each connection.
Carry out the contrast of calling that unit is handled and multimachine (two) is handled respectively.
1. unit is handled and is called the result:
The figure report is as Fig. 4, wherein:
Sample data: 52250 transactions
Throughput: 7588.7778 transactions/minute
Mean value: 126/second (total run time is divided by the request number that sends to server).
Median: 15ms (an average request processing time).
Depart from: 103 transaction data deviation rates are bigger, and 0.197% polymerization that accounts for all request the insides is reported as Fig. 5:
Label: request type is the Http request.
#Samples: the number of samples 52250 that sends to server altogether.
Average:126 pen/second (total run time is divided by the request number that sends to server).
Median:15ms (server response time that half is arranged is lower than this value and second half is higher than this value).
90%line:32 pen/second (referring to that 90% this numerical value of request responding time ratio is also little).
Min:0ms (shortest time of server response).
Max:2344ms (maximum duration of server response).
Error%:0.00% (percentage of errors of request).
Throughput:126.5 pen/second (number of deals that the server per second is handled).
KB/sec:690.5KB/ second (byte number of request in the unit interval).
This data declaration of conclusion: 90%line is in the request that sends, and 90% subscriber response time is all also short than 32/second times of the numerical value that obtains, and is the significant data in the systematic function.This data declaration Apache can be good at supporting (100 of the concurrent connections of full test) for the concurrent number of system, and can respond fast.
2. two-shipper is handled and is called the result:
Figure is reported as Fig. 6:
Sample data: 52250 transactions
Throughput: 7751.2096 transactions/minute
Mean value: 129/second (total run time is divided by the request number that sends to server).
Median: 23ms (an average request processing time).
Depart from: 103 transaction data deviation rates are bigger, and 0.197% polymerization that accounts for all request the insides is reported as Fig. 7:
Label: request type is the Http request.
#Samples: the number of samples 52250 that sends to server altogether.
Average:129 pen/second (total run time is divided by the request number that sends to server).
Median:0ms (server response time that half is arranged is lower than this value and second half is higher than this value).
90%line:31 pen/second (referring to that 90% this numerical value of request responding time ratio is also little).
Min:0ms (shortest time of server response).
Max:2282ms (maximum duration of server response).
Error%:0.00% (percentage of errors of request).
Throughput:129.2 pen/second (number of deals that the server per second is handled).
KB/sec:0KB/ second (byte number of request in the unit interval).
Conclusion: carry out the parallel processing distribution of two machines, the transaction throughput of system obtains certain lifting.7588.7778 transactions in the time of by unit/minute rise to, 7751.2096 transactions/minute.2.09% performance boost is arranged.
Use the cluster strategy of Apache+WebLogic:
1, backstage Web is carried out cluster, can improve system survivability, under certain Web server generation hardware system rank failure condition, system still can support operation therein.Request can be automatically brought on the normal machine, and is unlikely to systemic breakdown.
2, backstage Web cluster strategy can not influence on-line system so that application can be carried out new function under the situation of not stopping process reach the standard grade, and promotes service quality.
The present invention also adopts the disk array strategy, can guarantee safety of data and consistency to a greater extent.Web server visit disk array guarantees the consistency of the data source of being visited.Data array need be RARI, and when guaranteeing hardware fault, data are not lost.
Logic processing module is carried out the part mapping to identical file, and write operation when realizing file is specially:
public?synchronized?void?recordCryptCount(String?dataIndex，String
currentRecordTime)throws?IOException{
RandomAccessFile?randomAccessFile＝new?RandomAccessFile(new
File(cryptOprFile)，″rw″)；
MappedByteBuffer mbbo=null; // carry out the statement of object
FileChannel?fco＝null；
try{
String?currentCount＝″001″；
String?lastRecordTime＝″″；
boolean?isFound＝false；
long?fileLen＝randomAccessFile.length()；
randomAccessFile.seek(0)；
while(randomAccessFile.getFilePointer()＜fileLen){
String?line＝randomAccessFile.readLine()；
if(line！＝null?&&?line.indexOf(dataIndex)！＝-1){
String[]str＝line.split(″\t″)；
if(str[0].equalsIgnoreCase(dataIndex)){
currentIndex＝randomAccessFile.getFilePointer()-
(IBossCryptLog.getRecordLen()+1)；
java.text.DecimalFormat?df＝
new?java.text.DecimalFormat(″000″)；
int?j＝Integer.parseInt(str[1])；
currentCount＝df.format(j+1)；
lastRecordTime＝str[2]；
isFound＝true；
break；
}
}
}
if(lastRecordTime.equalsIgnoreCase(currentRecordTime))
return；
if(！isFound){
currentIndex＝fileLen；
}
fco＝randomAccessFile.getChannel()；
mbbo＝fco.map(FileChannel.MapMode.READ_WRITE，
CryptBufferedRandomAccessFile.currentIndex，
IBossCryptLog.getRecordLen ()+1); // mapping local file object structure
byte[]oldCryptBytes＝new?byte[IBossCryptLog.getRecordLen()+1]；
Mbbo.get (oldCryptBytes); // former data are put into the Buffer the inside
String?line＝new?String(oldCryptBytes)；
IBossCryptLog?cryptLog＝null；
if(line＝＝null||line.trim().length()＝＝0)
cryptLog＝new?IBossCryptLog()；
else
cryptLog＝new?IBossCryptLog(line)；
cryptLog.setDATAINDEX(dataIndex)；
cryptLog.setFILECOUNT(currentCount)；
cryptLog.setLASTRECORDTIME(currentRecordTime)；
mbbo.clear()；
Mbbo.put ((cryptLog.toString ()+" n ") .getBytes ()); // new data is write back file
}catch(IOException?e){
e.printStackTrace()；
throw?e；
}catch(Exception?ex){
/**@todo?Handle?this?exception*/
}finally{
try{
if(fco！＝null)
fco.close()；
}catch(IOException?e){
//TODO?Auto-generated?catch?block
e.printStackTrace()；
throw?e；
}
randomAccessFile.close()；
}
}
The present invention sends The data Socket mode and carries out remote encryption, and its process is:
public?class?ConnectionToCryptMachine{
/**
* the root path of Ying Yonging
*/
public?static?String?INTF_WLS_HOME＝null；
Public static final int NOTCONNECTED=0; // connection status
Public static final int CONNECTED=1; // not-connected status
Protected int mystate; // state
Private String peerip; // encryption equipment IP address
Private int peerport; // encryption equipment port numbers
Private Socket mysocket; // client socket
DataInputStream?mydatainputstream；
DataOutputStream?mydataoutputstream；
Private Properties pro; // lasting property set
Private File config_file=null; // configuration file
/ * configuration encryption equipment parameter */
Private String crypt_comd; // encrypted command
Private String calculate_method_symbol; // cryptographic algorithm sign
Private String crpt_symbol; // encrypt/decrypt sign
//private String key_length; // key length
Private String edk_length_symbol; // key length sign
Private String key_index; // cipher key index number
//private String edk; // key was changed once in 1 year
Private String init_vector; // initial vector
//private Logger logger; // obtain the log record device
/**
* construct connecting object
*@param?ip
*@param?port
*/
public?ConnectionToCryptMachine(String?ip，int?port){
INTF_WLS_HOME＝System.getProperties().getProperty(″INTF_WLS_HOME″)；
String?configFileName＝new?StringBuffer()
.append(ConnectionToCryptMachine.INTF_WLS_HOME)
.append(File.separator)
.append(″conf″)
.append(File.separator)
.append(″XG_Config.propertities″)
.toString()；
config_file＝new?File(configFileName)；
mystate＝NOTCONNECTED；
peerip＝ip；
peerport＝port；
System.out.println(″ip＝″+peerip)；
System.out.println(″port＝″+peerport)；
// loading configuration file
try{
pro＝new?Properties()；
pro.load(new?FileInputStream(config_file))；
initConfig(pro)；
}catch(FileNotFoundException?e){
System.out.println(″not?found?the?config?file！″)；
e.printStackTrace()；
//logger.error(″dsfasdfs″)；
}catch(IOException?e){
System.out.println(″error?in?load?config?file″)；
e.printStackTrace()；
}catch(Exception?e){
e.printStackTrace()；
}
}
/**
* send data to encryption equipment
* @param senddata data to be sent
* the result after the @return encryption equipment is handled
*@throws?CryptMachineException
*@throws?Exception
*/
public?synchronized?String?cryptMachineHandlc(String?send_data)throws
CryptMachineException，Exception{
if(send_data＝＝null||″″.equals(send_data)){
throw?new?CryptMachineException(″To?CryptMachine?data?is?null！″)；
}
if(mystate＝＝NOTCONNECTED){
throw?new?CryptMachineException(″CryptMachine?connection?isnull！″)；
}
String?data＝this.getPackage(send_data)；
System.out.println(″data＝″+new?String(data))；
int?datalen＝data.length()；
byte[]sendData＝new?byte[datalen+2]；
System.out.println(datalen+2)；
sendData[0]＝(byte)(((datalen)/255)&?0xff)；
sendData[1]＝(byte)(((datalen)％255)&?0xff)；
System.out.println(byteToHex(sendData[0]))；
System.out.println(byteToHex(sendData[1]))；
System.out.println(sendData[1])；
for(int?j＝2；j＜sendData.length；j++){
sendData[j]＝data.getBytes()[j-2]；
}
System.out.println(″senddata.length?is″+sendData.length)；
System.out.println(″sendData＝″+new?String(sendData))；
String?recvstr＝″″；
byte[]byterecv＝new?byte[300]；
try{
try{
//mydataoutputstream.flush()；
mydataoutputstream.write(sendData)；
mydataoutputstream.flush()；
System.out.println(″client?wirte?data?success！！！！″)；
mydatainputstream.read(byterecv)；
System.out.println(″client?read?data?success！！！！″)；
if(byterecv＝＝null){
throw?new?CryptMachineException(
″error?in?synchronize?receive?from?cryptmachine?l！″)；
}
}catch(IOException?ioe){
ioe.printStackTrace()；
throw?new?CryptMachineException(
″IOExeception?for?this?EncryptMachie！″)；
}
}catch(Exception?e){
c.printStackTrace()；
throw?e；
}
StringBuffer?sb＝new?StringBuffer()；
for(int?i＝6；i＜38；i++){//byterecv.length
sb.append(byteToHex(byterecv[i]))；
//sb.append(Integer.toHexString(byterecv[i]))；
}
System.out.println (" * * * * * * * * * * * * * * data encrypted is:: "+
sb.toString().toUpperCase().trim())；
Return sb.toString () .toUpperCase () .trim (); // information after returning service end and encrypting
}
private?String?byteToHex(byte?b){
//Returns?hex?String?representation?of?byte?b
char?hexDigit[]＝{
’0’，’1’，’2’，’3’，’4’，’5’，’6’，’7’，
’8’，’9’，’a’，’b’，’c’，’d’，’e’，’f’
}；
char[]array＝{hexDigit[(b＞＞4)&?0x0f]，hexDigit[b?&?0x0f]}；
return?new?String(array)；
}
/**
* pack the encrypted characters string, return heuristicimal code
*@param?vipInfo
*@return
*@throws?CryptMachineException
*@throws?Exception
*/
private?String?getPackage(String?vipInfo)throws?CryptMachineException，
Exception{
The configuration of // encryption equipment is provided with combination
// encrypted command+cryptographic algorithm sign+encrypt/decrypt sign+key length sign+cipher key index number+initial vector
String?strVipInfo＝crypt_comd+calculate_method_symbol+
crpt_symbol+edk_length_symbol+
key_index+init_vector；
Stringstr?DataLength＝
getStrDataLength(String.valueOf(vipInfo.length()))；
System.out.println(″strVipInfo:″+strVipInfo.trim())；
System.out.println(″strDataLength:″+strDataLength.trim())；
System.out.println(″vipInfo:″+vipInfo.trim())；
System.out.println (" character string after the combination is: "+strVipInfo+strDataLength+vipInfo);
return(strVipInfo+strDataLength+vipInfo)；
}
/**
* will mend 0 before the character string, and get back four
*@param?str
*@return
*/
private?String?getStrDataLength(String?str){
str＝″0000″+str；
int?len＝str.length()；
str＝str.substring(len-4，len)；
System.out.println (" character string after the length combination of vip: "+str);
return?str.trim()；
}
/**
* set up and being connected of encryption equipment
*
*@throws?IOException
*/
public?synchronized?void?connect()throws?IOException{
disconnect()；
System.out.println(″＝＝＝＝＝＝＝＝＝＝＝in?the?connect＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝″)；
mysocket＝new?Socket(peerip，peerport)；
Mysocket.setSoTimeout (2000); // be provided with and call read () on the InputStream of Socket association therewith and will only block this time length, overtime will be unusual
Mysoeket.setSoLinger (true, 0); // enable SO_LINGER with appointment residence time (is unit with the second).The max-timeout value is specific to platform.This setting only influences socket and closes.
Mysocket.setTcpNoDelay (true); // enable TCP_NODELAY
mydatainputstream＝new?DataInputStream(mysocket.getInputStream())；
mydataoutputstream ＝ newDataOutputStream(mysocket.getOutputStream())；
mystate＝CONNECTED；
}
/**
* disconnect with encryption equipment and being connected
*
*/
public?synchronized?void?disconnect(){
mystate＝NOTCONNECTED；
try{
if(mydataoutputstream！＝null){
mydataoutputstream.close()；
}
}catch(Exception?e){
e.printStackTrace()；
}
try{
if(mydatainputstream！＝null){
mydatainputstream.close()；
}
}catch(Exception?e){
e.printStackTrace()；
}
try{
if(mysocket！＝null){
mysocket.close()；
}
}catch(Exception?e){
e.printStackTrace()；
}
mydataoutputstream＝null；
mydatainputstream＝null；
mysocket＝null；
}
public?String?getIP(){
return?peerip；
}
public?int?getPort(){
return?peerport；
}
// initialization encryption equipment configuration parameter
private?void?initConfig(Properties?p){
try{
crypt_comd＝p.getProperty(″crypt.command″).trim()；
calculate_method_symbol＝p.getProperty(
″crypt.calculate_method_symbol″).trim()；
crpt_symbol＝p.getProperty(″crypt.symbol″).trim()；
//key_length＝p.getProperty(″crypt.key_length″).trim()；
key_index＝p.getProperty(″crypt.key_index″).trim()；
edk_length_symbol＝
p.getProperty(″crypt.edk_length_symbol″).trim()；
//edk＝p.getProperty(″crypt.edk″).trim()；
init_vector＝p.getProperty(″crypt.init_vector″).trim()；
}catch(Exception?e){
e.printStackTrace()；
}
}
}
Claims (3)
1. the method for the electronic data processing of the concurrent request of a large number of services, it is characterized in that system handles does not rely on database, record data, query statistics etc. are undertaken by the mode of file, concurrent written document, carry out the file index operation fast, when the external system request inserts, obtain data module by HTTP and receive request, handle through logic processing module, the data that sent after data module will be handled by FTP are dealt into outside hair fastener platform again, are specially:
(1) HTTP obtains data module: adopt the cluster strategy of Apache+WebLogic to carry out control and treatment, the Apache frame is in front end, and configuration Apache is distributed to request on the WebLogic cluster of rear end, and the request distribute weightings of configuration Apache;
(2) logic processing module: adopt the mode of multiple step format Cache to carry out the file preservation of WebLogic system, carry out the part mapping for identical file, write operation when realizing file, file read and adopt buffer memory to read;
(3) FTP sends data module: adopt the Socket mode to carry out remote encryption, carry out the connection pool management with pool mode, at first go to obtain available connection from the inside, pond, come and telecommunication.
2. the method for the electronic data processing of the concurrent request of a large number of services according to claim 1, it is characterized in that adopting the multithreading tupe, the encapsulation producer, consumer's thread carries out calling service, the producer thread acquisition target is put into shared queue, start a plurality of consumer's threads, consumer's thread obtains data from the shared queue the inside, carries out fast processing.
3. the method for the electronic data processing of the concurrent request of a large number of services according to claim 1 is characterized in that using two WebLogic systems.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA2007101314222A CN101123620A (en) | 2007-08-28 | 2007-08-28 | Method for electronic data processing for concurrent request of a large number of services |
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|---|---|---|---|
| CNA2007101314222A CN101123620A (en) | 2007-08-28 | 2007-08-28 | Method for electronic data processing for concurrent request of a large number of services |
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ID=39085798
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| CN102082808A (en) * | 2009-11-30 | 2011-06-01 | 中国移动通信集团上海有限公司 | Distributed system, service distribution method and device as well as weight value management device |
| CN102148759A (en) * | 2011-04-01 | 2011-08-10 | 许旭 | Method for saving export bandwidth of backbone network by cache acceleration system |
| CN102510398A (en) * | 2011-10-26 | 2012-06-20 | 航天科工深圳（集团）有限公司 | Request concurrent processing method and device, and server |
| CN102760126A (en) * | 2011-04-26 | 2012-10-31 | 阿里巴巴集团控股有限公司 | Data synchronization method in distributive system, and distributive system |
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| CN101882983B (en) * | 2009-05-05 | 2012-12-26 | 上海摩波彼克半导体有限公司 | Cross-layer communication control method for realizing TCP transmission performance optimization in wireless communication network |
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| CN101815089B (en) * | 2010-02-22 | 2013-06-19 | 浪潮(北京)电子信息产业有限公司 | Command executing method and system of Web high-end disk array controller |
| CN102148759A (en) * | 2011-04-01 | 2011-08-10 | 许旭 | Method for saving export bandwidth of backbone network by cache acceleration system |
| CN102760126B (en) * | 2011-04-26 | 2015-04-01 | 阿里巴巴集团控股有限公司 | Data synchronization method in distributive system, and distributive system |
| CN102760126A (en) * | 2011-04-26 | 2012-10-31 | 阿里巴巴集团控股有限公司 | Data synchronization method in distributive system, and distributive system |
| CN102510398B (en) * | 2011-10-26 | 2015-01-21 | 航天科工深圳（集团）有限公司 | Request concurrent processing method and device, and server |
| CN102510398A (en) * | 2011-10-26 | 2012-06-20 | 航天科工深圳（集团）有限公司 | Request concurrent processing method and device, and server |
| CN104424326A (en) * | 2013-09-09 | 2015-03-18 | 华为技术有限公司 | Data processing method and device |
| CN104424326B (en) * | 2013-09-09 | 2018-06-15 | 华为技术有限公司 | A kind of data processing method and device |
| CN104506304A (en) * | 2014-11-20 | 2015-04-08 | 成都卫士通信息产业股份有限公司 | An adaptation control system and method for enhancing password device on-demand service capacity |
| CN104506304B (en) * | 2014-11-20 | 2018-04-24 | 成都卫士通信息产业股份有限公司 | A kind of adaptation control system and method for strengthening encryption device on-demand service ability |
| CN107783819A (en) * | 2017-10-30 | 2018-03-09 | 郑州云海信息技术有限公司 | A kind of storage method, device and the medium of virtual link relation |
| CN110162401A (en) * | 2019-05-24 | 2019-08-23 | 广州中望龙腾软件股份有限公司 | The parallel read method of DWG file, electronic equipment and storage medium |
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