Patent Publication Number: US-9419882-B2

Title: Network analyzing system, as well as network analyzing apparatus and network analyzing program, as well as data processing module and data processing program

Description:
TECHNICAL FIELD 
     The present invention relates to a network analyzing system, as well as a network analyzing apparatus and a network analyzing program, and additionally to a data processing module and a data processing program, and as one example can be applied to a system that carries out analysis relating to the usage situation and/or operational state of a network and monitors the network based on such analysis result. 
     BACKGROUND ART 
     It is known from the past that it is necessary to analyze the usage situation and/or operational state of a network and to monitor for abnormalities based on such analysis result. 
     In the past, a variety of algorithms for analyzing the usage situation and/or operational state of an IP network have been developed. More specifically, there are the technologies disclosed in Patent Literature 1 to 4 listed below, for example. 
     The algorithm disclosed in Patent Literature 1 calculates the appearance frequency of respective values in a data series (i.e., totals the number of errors detected for each IP address) for IP packets flowing on an IP network, and also totals the numbers of errors detected for each IP address and obtains IP addresses or routes that are the cause of a certain proportion of errors or higher. 
     The algorithm disclosed in Patent Literature 2 calculates statistics by carrying out statistical analysis on IP packets flowing on an IP network and detects abnormalities from a degree of deviation of such statistics in comparison with historical statistics. 
     In addition, the algorithm disclosed in Patent Literature 3 detects deterioration in the quality of a network via determinations made using an RF method (Random Forest method) on IP packets flowing on an IP network. The technology disclosed in Patent Literature 3 carries out learning in advance for a plurality of parameters by inputting normal state values as correct values (a teacher input) for determinations and detects quality deterioration from the parameters relating to the present IP network based on the results of such learning. 
     In addition, the algorithm disclosed in Patent Literature 4 carries out multi-resolution analysis on time series information (for example, transitions in the amount of traffic on an IP network), also carries out learning by inputting such resolution components into a learning apparatus that uses a neural network (neuro), and predicts time series information based on the results of such learning. 
     CITATION LIST 
     Patent Literature 
     Patent Literature 1: JP 2009-171252A 
     Patent Literature 2: JP 2006-148686A 
     Patent Literature 3: JP 2010-183220A 
     Patent Literature 4: JP 2010-204974A 
     SUMMARY OF INVENTION 
     Technical Problem 
     However, in the past, there has been the following problem when an ISP (Internet Service Provider) business or the like constructs a network analysis system that carries out analysis relating to the usage situation and/or operational state of its own network equipment using the existing technologies described above (for example, the technologies disclosed in Patent Literature 1 to Patent Literature 4). 
     As shown in Patent Literature 1 to 4, since complex processing is necessary for the processing algorithms used in a network analysis system and it is also necessary to carry out a large amount of processing in a short time (in particular, when monitoring a wide area network in real time), it has been necessary in the past to develop a system that is dedicated to the content to be analyzed. 
     For this reason, with an existing network analysis system, it has been difficult to flexibly change the specification at a later date (as examples, to change the procedure of the processing algorithm or to add processing steps) or to construct a system with a different specification by reusing the resources of a system that has already been constructed. 
     In view of the problem described above, there is demand for a network analysis system, as well as a network analysis apparatus and a network analysis program, and also a data processing module and a data processing program where it is easy to change the configuration of analysis processing relating to the usage situation and/or the operational state of a network. 
     Solution to Problem 
     The first present invention is characterized in that a network analysis system that carries out analysis related to a network, comprising, (1) one or a plurality of data processing modules; and a network analysis apparatus that accommodates the data processing modules and carries out an analysis process relating to the network using the data processing modules, (2) wherein the network analysis apparatus includes, (2-1) a data processing module accommodating unit accommodating the data processing modules, (2-2) a data-to-be-analyzed holding unit holding data-to-be-analyzed relating to the network, (2-3) a data processing definition information storing unit storing data processing definition information that defines steps that carry out the processing of the data-to-be-analyzed held in the data-to-be-analyzed holding unit using the one or a plurality of data processing modules, and (2-4) a data processing executing unit causing the data processing modules to carry out data processing based on the data processing definition information stored in the data processing definition information storing unit to obtain a data processing result, (3) and each data processing module includes, (3-1) a connection unit connecting to the network analysis apparatus, and (3-2) a data processing unit carrying out data processing in accordance with a request from the network analysis apparatus. 
     The second present invention is characterized in that a network analysis apparatus that accommodates one or a plurality of data processing modules and carries out an analysis process relating to a network using the data processing modules, comprising, (1) a data processing module accommodating unit accommodating the data processing modules, (2) a data-to-be-analyzed holding unit holding data-to-be-analyzed relating to the network, (3) a data processing definition information storing unit storing data processing definition information that defines steps that carry out the processing of the data-to-be-analyzed held in the data-to-be-analyzed holding unit using the one or a plurality of data processing modules, and (4) a data processing executing unit causing the data processing modules to carry out data processing based on the data processing definition information stored in the data processing definition information storing unit to obtain a data processing result. 
     The third present invention is characterized in that a network analysis program causing (1) a computer, which is installed in a network analysis apparatus that accommodates one or a plurality of data processing modules and carries out an analysis process relating to a network using the data processing modules, to function as (2) a data processing module accommodating unit accommodating the data processing modules, (2) a data-to-be-analyzed holding unit holding data-to-be-analyzed relating to the network, (3) a data processing definition information storing unit storing data processing definition information that defines steps that carry out the processing of the data-to-be-analyzed held in the data-to-be-analyzed holding unit using the one or a plurality of data processing modules, and (4) a data processing executing unit causing the data processing modules to carry out data processing based on the data processing definition information stored in the data processing definition information storing unit to obtain a data processing result. 
     The fourth present invention is characterized in that a data processing module comprising (1) a connection unit connecting to the network analysis apparatus, and (2) a data processing unit carrying out data processing in accordance with a request from the network analysis apparatus. 
     The fifth present invention is characterized in that a data processing program causing a computer to function as (1) a connection unit connecting to the network analysis apparatus, and (2) a data processing unit carrying out data processing in accordance with a request from the network analysis apparatus. 
     Advantageous Effects of Invention 
     According to the present invention, it is possible to provide a network analysis system capable of easily changing the configuration of analysis processing relating to the usage situation and/or the operational state of a network. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  illustrates a network analysis system according to an embodiment. 
         FIG. 2A  illustrates content of a processing rule according to the present embodiment. 
         FIG. 2B  illustrates a processing rule according to another embodiment. 
         FIG. 3  illustrates an example content of a processing rule management table according to the present embodiment. 
         FIG. 4  illustrates an engine management table according to the present embodiment. 
         FIG. 5  illustrates the functional configuration of an engine according to the present embodiment. 
         FIG. 6  is a sequence chart showing the operation when an engine is newly installed in the network analysis system according to the present embodiment. 
         FIG. 7A  illustrates transitions in a table when an engine is newly installed in the network analysis system according to the present embodiment. 
         FIG. 7B  illustrates an engine management table according to one embodiment. 
         FIG. 8  is a sequence chart showing the operation when an engine is to be uninstalled (when uninstallation is possible) in the network analysis system according to the present embodiment. 
         FIG. 9  is a sequence chart showing the operation when an engine is to be uninstalled (when uninstallation is not possible) in the network analysis system according to the present embodiment. 
         FIG. 10  is a sequence chart showing the operation when data processing is carried out for a first processing rule in the network analysis system according to the present embodiment. 
         FIG. 11A  illustrates the content of a data processing frame generated when data processing is carried out for the first processing rule in the network analysis system according to the present embodiment. 
         FIG. 11B  illustrates a data processing frame for carrying out a second processing operation according to one embodiment. 
         FIG. 11C  illustrates a data processing frame for carrying out a third processing operation according to one embodiment. 
         FIG. 11D  illustrates a data processing frame for completing processing of the data processing frame according to one embodiment. 
         FIG. 12  is a sequence chart showing the operation when data processing is carried out for a second processing rule in the network analysis system according to the present embodiment. 
         FIG. 13A  illustrates content of a data processing frame generated when data processing is carried out for the second processing rule in the network analysis system according to the present embodiment. 
         FIG. 13B  illustrates a data processing frame for carrying out a second processing operation according to one embodiment. 
         FIG. 13C  illustrates a data processing frame for carrying out a third processing operation according to one embodiment. 
         FIG. 13D  illustrates a data processing frame for completing processing of the data processing frame according to one embodiment. 
         FIG. 13E  illustrates a data processing frame having been processed according to one embodiment. 
         FIG. 13F  illustrates a data processing frame having been processed according to one embodiment. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the appended drawings. Note that, in this specification and the drawings, elements that have substantially the same function and structure are denoted with the same reference signs, and repeated explanation is omitted. 
     (A) Preferred Embodiment 
     Embodiments of a network analysis system, as well as a network analysis apparatus and a network analysis program, and also a data processing module and a data processing program according to the present invention will now be described in detail with reference to the attached drawings. Note that a data processing module according to the present embodiment is an engine. 
     (A-1) Configuration of Embodiment 
       FIG. 1  is a block diagram showing the functional configuration of a network analysis system  10  according to the present embodiment. 
     The network analysis system  10  according to the present embodiment carries out analysis (for example, analysis of a usage situation and/or an operational state) relating to networks based on traffic flowing in a router  400  disposed between an internal network N 1  and an external network N 2  and outputs an analysis result. Note that there are no limitations on the traffic to be analyzed by the network analysis system  10 . The network analysis system  10  then outputs the analysis result as necessary to an operating server (OPS)  300 . As examples, the internal network N 1  corresponds to a network of a communication carrier (for example, an ISP business) and the external network N 2  corresponds to any network large or small, such as an upstream network like a Tier-1 ISP connected to the communication carrier, a network called a Private Peer that is a similar scale to the network N 1 , or a downstream network such as a smaller ISP or a private network. The router  400  for which the network analysis system  10  acquires data on the traffic which is necessary for analysis is assumed to be a network apparatus for connecting the internal network N 1  to the external network N 2 . The OPS  300  corresponds for example to a terminal used by an operator who operates and monitors the internal network N 1 . 
     Next, the configuration of the router  400  will be described. 
     The router  400  includes an interface  410 , an interface  420 , a packet processing unit  430 , and an export processing unit  440 . 
     The interface  420  is assumed to be an interface for connecting to the internal network N 1 . The interface  410  is assumed to be an interface for connecting to the external network N 2 . Although there are no limitations on the types of interface for the internal network N 1  and the external network N 2 , as examples it is possible to use a 10-gigabit 
     Ethernet (registered trademark) interface or a gigabit Ethernet interface. 
     It is assumed that the packet processing unit  430  carries out processing (routing processing or the like) on packets transmitted and received by the interfaces  410 ,  420 . Note that the packet processing unit  430  can be provided with the same configuration as an existing router. Note that the network analysis system  10  will be described as carrying out analysis relating to traffic (IP packets) that are transmitted/received and observed at the interface  410 . 
     The export processing unit  440  functions as an exporter (agent) that gathers data that is necessary for analysis and transfers such data after processing as necessary in accordance with control from the network analysis system  10 . The export processing unit  440  is equipped with an output rule storage unit  441  that stores information defining rules (hereinafter referred to as “output rules”) relating to data outputted to the network analysis system  10 . The export processing unit  440  changes the defined content of the output rule storage unit  441  in accordance with control from the network analysis system  10 . The export processing unit  440  carries out the gathering of data in accordance with information stored in the output rule storage unit  441 , processes the information as necessary, and supplies the information to the network analysis system  10 . In the following description, at the network analysis system  10 , the data supplied from the router  400  (the export processing unit  440 ) is referred to as “report data”. Packets in which the report data transmitted from the router  400  (the export processing unit  440 ) has been inserted are also referred to as “report packets”. 
     Since it is possible to apply the processing configuration of an exporter (agent) in an existing technology such as Netflow (see Reference Literature 1 (IETF RFC 3954)), IPFIX (see Reference Literature 2 (IETF RFC 5101)), or sFLOW (see Reference Literature 3 (IETF RFC 3176)) to the specific processing configuration of the router  400 , detailed description thereof is omitted here. 
     Next, the configuration of the network analysis system  10  will be described. 
     The network analysis system  10  includes a network analysis apparatus  100  that functions as a platform of the system and engines  200  ( 200 - 1  to  200 - 6 ) that operate on the network analysis apparatus  100  (platform) and carry out data processing. Note that there is no limitation on the number of engines  200 . 
     The network analysis apparatus  100  processes the data (report data) relating to traffic that has been supplied from the router  400  using some or all of the engines  200  and principally carries out analysis processing relating to the usage situation and/or the operational state of networks (the internal network N 1  and the external network N 2 ). That is, in the network analysis system  10 , the respective engines  200  function as data processing modules for carrying out data processing of report data or the like. The network analysis apparatus  100  uses a combination of some or all of the engines  200  to carry out analysis of the usage situation and/or the operational state of networks. 
     The network analysis apparatus  100  includes an engine cooperative processing unit  110 , an engine shared driving unit  120 , a processing rule storage unit  130 , an output rule setting unit  140 , and a log accumulation unit  150 . 
     The network analysis apparatus  100  may be constructed by installing the network analysis program according to the present embodiment or the like into an apparatus including an execution configuration for programs (such as a CPU, ROM, RAM, EEPROM, and a hard disk drive) and an interface for connecting to a network. The functional configuration in such case can be as shown in  FIG. 1 . The network analysis apparatus  100  may also be partly or entirely constructed using hardware (for example, a dedicated chip or the like). 
     The engine cooperative processing unit  110  receives the report packets transmitted from the router  400  and extracts the report data. Note that as the processing configuration whereby the engine cooperative processing unit  110  receives the report packets and extracts the report data, it is possible for example to use the same configuration as a collector (manager) that corresponds to an exporter (agent) in the existing technologies in Reference Literature 1 to 3 mentioned above. 
     The engine cooperative processing unit  110  causes the engines  200  to carry out processing of the extracted report data in accordance with processing rules stored in the processing rule storage unit  130  for such report data. The engine cooperative processing unit  110  carries out communication via the engine shared driving unit  120  when inputting into and outputting out of the engines  200 , such as when controlling or requesting processing to the engines  200 . 
     The engine shared driving unit  120  carries out functions such as connecting the engines  200 , the engine cooperative processing unit  110 , and the log accumulation unit  150  and communication processing (switching processing) between the respective elements. That is, the engine shared driving unit  120  functions so as to accommodate the engines  200  inside the network analysis apparatus  100 . 
     The following description is given on the assumption that the engines  200 - 1  to  200 - 6  have been given the identifiers (hereinafter referred to as “engine IDs”) “1” to “6”. As examples, the identifier of the engine  200 - 1  is “1” and the identifier of the engine  200 - 2  is 
     In the processing rule storage unit  130 , data that defines rules (hereinafter referred to as “processing rules”) relating to processing steps or the like when the engine cooperative processing unit  110  carries out data processing using the engines  200  is stored. Such processing rules are described in detail later. 
     The processing rules stored in the processing rule storage unit  130  are managed in a processing rule management table  111  of the engine cooperative processing unit  110 . In the processing rule management table  111 , information relating to the respective processing rules (such as the format of report data to be inputted, the engines  200  used for processing, and the types of engines  200 ) is managed. The processing rule management table  111  is described in detail later. 
     The output rule setting unit  140  requests the router  400  (the export processing unit  440 ) to set the transmission content and conditions of the report data in accordance with information managed in the processing rule management table  111  so as to make it possible to acquire the report data required by respective processing rules. As the configuration with which the output rule setting unit  140  requests the router  400  (the export processing unit  440 ) to set transmission content and conditions of the report data, as one example it is possible to use the same configuration as a collector (manager) that corresponds to an exporter (agent) disclosed in the existing technologies of Reference Literature 1 to 3 mentioned above. 
     As described above, the report data transmitted from the router  400  (the export processing unit  440 ) is acquired by the engine cooperative processing unit  110 . That is, in the network analysis apparatus  100 , processing that holds the report data (data to be analyzed by the network analysis apparatus  100 ) from the router  400  (the export processing unit  440 ) is carried out by the output rule setting unit  140  and the engine cooperative processing unit  110 . 
     The log accumulation unit  150  is connected to the engine shared driving unit  120  and accumulates a log relating to processing by the respective engines  200 . Input data and/or output data, intermediate data of data processing, or the like are stored for each engine  200  in the log accumulation unit  150 . As one example, it is assumed here that the engine shared driving unit  120  supplies data inputted and outputted into and out of the respective engines  200  and data based on requests from the respective engines  200  in the log accumulation unit  150  and that the data supplied to the log accumulation unit  150  is accumulated having been sorted for the respective engines  200 . 
     Next, the specific content of the processing rules stored in the processing rule storage unit  130  will be described. Here, it is assumed that two rules R 1  and R 2  are stored in the processing rule storage unit  130 . 
       FIGS. 2A and 2B  are diagrams useful in explaining an example of the defined content of the processing rules stored in the processing rule storage unit  130 . 
       FIG. 2A  shows the content of the processing rule R 1  and  FIG. 2B  shows the content of the processing rule R 2 . 
     Although there are no limitations on the description format defining a processing rule, as shown in  FIGS. 2A and 2B , it is assumed here that processing rules are described in a C language-type script format. 
     In broad terms, a processing rule includes three steps, that is, a step of defining the report data to be used as input data (hereinafter referred to as the “input data definition step”) (step S 101  in  FIG. 2A  and step S 201  in  FIG. 2B ), a step of defining data processing that uses the engines  200  (hereinafter referred to as the “data processing definition step”) (step S 102  in  FIG. 2A  and step S 202  in  FIG. 2B ), and a step of defining the data outputted by such processing rule (hereinafter referred to as the “output data definition step”) (step S 103  in  FIG. 2A  and step S 203  in  FIG. 2B ). 
     First, the input data definition step (step S 101 , step S 201 ) will be described. In the present embodiment, it is assumed that the format of the input data (report data) to be used in the processing rule is one or both of “traffic data” such as pcap format where traffic observed at an interface is dumped (binary data of an IP packet sequence generated at specified intervals) and a “flow record” where traffic observed at an interface is extracted at a set sampling interval and outputted as flow information such as netflow/sflo/ipfix (statistical information of a specified item relating to IP packet sequence generated at specified intervals). Although the format of the input data (report data) may be defined with even more detailed classifications, the present embodiment is described using only the two types described above for ease of explanation. 
     In the input data definition step of the processing rule R 1  (step S 101 ), “input1=trafficdata;” is described showing that “input1” (the format of the first input data of the processing rule R 1 ) has the “trafficdata” format. 
     Meanwhile, in the input data definition step of the processing rule R 2  (step S 102 ), “input1=flow_record;” is described showing that “input1” (the format of the first input data of processing rule R 2 ) has the “flow_record” format. Note that in the input data definition step, it is also possible to make definitions relating to a plurality of input data with a description such as “input2= . . . ”, for example. 
     Next, the data processing definition step that configures a processing rule (step S 102 , step S 202 ) will be described. As shown in  FIG. 2A , the data processing definition step (step S 102 ) of the processing rule R 1  has three substeps S 102 - 1  to S 102 - 3 . Also, the data processing definition step (step S 202 ) of processing rule R 2  has three substeps S 202 - 1  to S 202 - 3 . 
     The data processing definition step defines processing to be carried out by the respective engines  200 , using functions (classes) whose name (class name) is “EngineN” (where N is an identifier (any of 1 to 6) of the engine in question). In the data processing definition step, if processing is to be carried out by an arbitrary engine  200  (the engine  200  whose identifier is “EngineN”) for arbitrary input data (“inputdata”) while designating an arbitrary parameter (“parameter”) (for example, a threshold when data processing is carried out) and data is to be outputted in an arbitrary data format (“output_type”), such processing can be expressed using the description “EngineN (inputdata, output_type, parameter). Although there are no limitations on the description format in the data processing definition step and it is possible for the system to be compatible with a plurality of description formats, for ease of explanation, the description here assumes that the network analysis apparatus  100  is compatible with the format mentioned above. Note that in the data processing definition step, in cases where it is unnecessary to clearly designate parameters aside from inputdata (i.e., output_type and parameter), description of such parameters may be omitted. Note also that in the following description, the parameters aside from inputdata are referred to as “additional parameters”. Also, although “output_type” and “parameter” are described as “output_type1” and “parameter1” in  FIG. 2A  for “output_type” and “parameter” for ease of the explanation, it is assumed that in reality, data (not shown) that defines the specific content for such parameters is held in the engine cooperative processing unit  110 . 
     For example, although “Engine1(input1,output_type1,parameter1)” is described in the step S 102 - 1  that composes the data processing definition step (S 102 ) of the processing rule R 1 , this means that “Engine1” (engine  200 - 1 ) is caused to carry out processing on “input1” (input data defined in step S 101 ) with the designated parameter “parameter1” to obtain output data with the output format “output_type1”. 
     Next, the content of the data processing definition step (step S 102 ) of the processing rule R 1  will be described. 
     The content of step S 102 - 1  is as described above. 
     Since “Analyze2=Engine2(analyze1, output_type2, parameter2);” is described in step S 102 - 2  that follows step S 102 - 1 , this refers to processing that causes “Engine2” (engine  200 - 2 ) to carry out data processing with “Analyze1” obtained in step S 102 - 1  as an input and has the result substituted into a variable called “Analyze2”. 
     Since “Analyze3=Engine3(analyze2, output_type3, parameter3);” is described in step S 102 - 3  that follows step S 102 - 2 , this refers to processing that causes “Engine3” (engine  200 - 3 ) to carry out data processing with “Analyze2” obtained in step S 102 - 2  as an input and has the result substituted into a variable called “Analyze3”. 
     That is, in the data processing definition step (step S 102 ) of the processing rule R 1 , a nested structure (syntax) where the engine  200 - 1  (Engine1) is first caused to carry out processing on the input data (input1), the engine  200 - 2  (Engine2) is caused to further process the result of such processing, and then the engine  200 - 3  (Engine3) is caused to further process the result of such processing is described. In other words, the data processing definition step (step S 102 ) of the processing rule R 1  has a structure (syntax) where the input data (input1) is serially processed in the order of the engine  200 - 1  (Engine1), the engine  200 - 2  (Engine2), and the engine  200 - 3  (Engine3). 
     Next, an example of the specific processing (the specific processing by the engines  200 - 1  to  200 - 3 ) of the data processing definition step (step S 102 ) of the processing rule R 1  will be described. 
     In the processing rule R 1 , it is assumed that traffic relating to real-time communication such as audio or video flowing in the router  400  is analyzed. More specifically, it is assumed that the processing rule R 1  carries out analysis that extracts packets during RTP/RTCP (Real-time Transport Protocol/RTP Control Protocol) communication (in particular, RTCP packets). 
     First, in step S 102 - 1 , traffic data (data of all of the IP packets) is inputted into the engine  200 - 1  (Engine1) as input data (input1) and data (Analyze1) produced by extracting only the RTCP packets is obtained. The data (Analyze1) of RTCP packets obtained by the engine  200 - 1  (Engine1) is inputted into the engine  200 - 2  (Engine2), a combination of IP addresses that appear at least a specified number of times (designated by Parameter2) is extracted from combinations of IP addresses (i.e., combinations of IP addresses of the transmission source and transmission destination of RTCP packets) of flows where it is believed, based on quality values (such as a delay or packet loss) included in the RTCP packets that the communication quality has significantly deteriorated, and data (Analyze2) that includes data on such combination of such IP addresses and data on parameter values relating to communication quality included in the RTCP packets relating to such combination (average values may be used if a plurality of parameter values exist) is obtained. The combination of IP addresses and data (Analyze2) on parameter values relating to such combination that have been obtained by the engine  200 - 2  (Engine2) are inputted into the engine  200 - 3  (Engine3), it is determined that there is a network abnormality if the number of times quality deterioration occurs within a certain period exceeds a threshold and such determination result and combination of IP addresses are obtained as Analyze3. The determination result (Analyze3) outputted from the engine  200 - 3  (Engine3) returns a pair of the IP addresses for which network quality deterioration has been determined within the certain period or returns “0” if there has been no deterioration in quality. In the present embodiment, by using the processing rule R 1 , it is possible, with the flow described above, to have data processing carried out on the input data (input1: trafficdata) serially by the engines  200 - 1  to  200 - 3  and to determine whether there are any network abnormalities. 
     Next, the content of the data processing definition step (step S 202 ) of the processing rule R 2  will be described. 
     Although the input data (input1) is serially processed by a plurality of engines with the processing rule R 1  as described above, processing is carried out in parallel with the processing rule R 2 . 
     More specifically, in step S 202 - 1  of the processing rule R 2 , processing of the input data (input1) is carried out by the engine  200 - 4  (Engine4) and the result of such processing is substituted into a variable called “Analyze1”. In step S 202 - 2  of the processing rule R 2 , processing of the input data (input1) is carried out by the engine  200 - 5  (Engine5) and the result of such processing is substituted into a variable called “Analyze2”. In addition, in step S 202 - 3  of the processing rule R 2 , processing of the input data (input1) is carried out by the engine  200 - 6  (Engine6) and the result of such processing is substituted into a variable called “Analyze3”. 
     Next, an example of the specific processing (the specific processing by the engines  200 - 4  to  200 - 6 ) of the data processing definition step (step S 202 ) of the processing rule R 2  will be described. 
     The engines  200 - 4  to  200 - 6  accumulate input data in the format of a flow record, carry out processing that uses respectively different algorithms to judge whether there are presently any network abnormalities based on data accumulated in the past and the most recently obtained data in flow record format, and obtain such determination results as Analyze1 to Analyze3. Here, as one example, it is assumed that the engine  200 - 4  determines that a network abnormality has occurred if an IP address or route that is the cause of at least a certain proportion (designated by parameter1) of errors has been obtained using the degree of change in trend in the same way as the technology disclosed by Patent Literature 1. It is assumed that the engine  200 - 5  determines whether there is a network abnormality (quality deterioration on the network) at present based on a determination using the RF method in the same way as the technology disclosed by Patent Literature 3. In addition, it is assumed that the engine  200 - 6  determines whether there is a network abnormality (quality deterioration on the network) at present using a learning machine that uses a neural network (neuro) in the same way as the technology disclosed by Patent Literature 4. 
     It is assumed that the determination results (Analyze1 to Analyze3) outputted from the engines  200 - 4  to  200 - 6  (Engine4 to Engine6) take the value “1” when it has been determined that there is a network abnormality and take the value “0” if it has been determined that there is no network abnormality. In the present embodiment, with the flow described above, with the processing rule R 2 , it is possible to have data processing carried out on the input data (input1: flow_record) in parallel by the engines  200 - 4  to  200 - 6  and to obtain determination results relating to network failures using respectively different algorithms 
     Next, the output data definition step (step S 103 , step S 203 ) that constructs a processing rule will be described. 
     In the output data definition step (step S 103 ) of the processing rule R 1 , as shown in  FIG. 2A , “Return analyze3;” is simply described, which shows that the variable called “analyze3” as a processing result of the processing rule R 1  is outputted as data on a return value. In the engine cooperative processing unit  110 , for each of the processing rules, processing that acquires data outputted as a return value and outputs such data as the analysis result of such processing rule is carried out by a function called “Return”. 
     In the output data definition step that constructs the processing rules in the present embodiment, it is assumed that “1” is outputted as the return value if the result of the analysis processing is that an abnormality relating to the usage situation and/or the operational state of the network has been detected and “0” is outputted as the return value if there is no abnormality (i.e., in the normal state). 
     Meanwhile, in the output data definition step (step S 103 ) of the processing rule R 2 , as shown in  FIG. 2A , “If ((analyze1+analyze2+analyze3)&gt;2) return 1; Else return 0;” is described in the form of syntax that uses an If statement. Here, as described above, “0” or “1” is substituted into each of “analyze1”, “analyze2”, and “analyze3”. With the syntax that uses an If statement described above, if “1” has been substituted into at least two out of the “analyze1”, “analyze2”, and “analyze3”, the If condition is satisfied and “1” is outputted as the return value of the processing rule R 2 . Meanwhile if the If condition is not satisfied (i.e., if the number of engines  200  that have outputted “1” is less than two), “0” is outputted as the return value of the processing rule R 2 . 
     As described above, the engines  200 - 4  to  200 - 6  determine whether there is a network-related failure using respectively different algorithms. Accordingly, it can be said that with the output data definition step of processing rule R 2  (step S 203 ), a final determination result determines that a network abnormality is present only when a network abnormality has been detected by at least two out of the engines  200 - 4  to  200 - 6  (i.e., when the engines  200  that have detected a network abnormality are in a majority). As described above, with the processing rule R 2 , the determination results of a plurality of engines  200  are totaled to make a final determination of whether there is a network abnormality. 
     As described above, the scripts of the respective processing rules are carried out by the network analysis apparatus  100 . If as a result of executing the scripts of the processing rules, “1” meaning that an abnormality has been detected has been acquired as a return value, the engine cooperative processing unit  110  carries out processing that notifies the OPS  300  that an abnormality has been detected by such processing rule (for example, notification processing that uses a Trap or the like of SNMP). When giving notification of the occurrence of a network abnormality, the engine cooperative processing unit  110  may give notification together with a message corresponding to each processing rule (for example, a message showing the cause of the abnormality). The engine cooperative processing unit  110  may manage the messages that notify the OPS  300  through management of the processing rule management table  111  with additional items, or such messages may be described in the output data definition step. 
     Note that there are no limitations on the method by which the engine cooperative processing unit  110  outputs the analysis results, and as examples, it is possible to internally accumulate the results as a log (history) or to output by displaying on a display or the like not at the OPS  300  but at the present apparatus. 
     In the OPS  300 , if there has been an error notification from the engine cooperative processing unit  110  (for example, if a Trap notification has been given via SNMP), a warning indicating the abnormality is issued to inform the operator that an abnormality has occurred on the network. Although there are no limitations on the method of having the OPS  300  issue a warning, it is possible to use various methods, such as outputting by displaying on a display, not shown, giving an audio output of an alarm sound using a speaker, not shown, or lighting a lamp, not shown. Although, there are no limitations on the specific configuration of the OPS  300 , it is possible for example to apply a network monitoring apparatus (SNMP manager) that is compatible with existing SNMP. 
     Next, the example content of the processing rule management table  111  held in the engine cooperative processing unit  110  will be described. 
       FIG. 3  is a diagram useful in explaining an example content of the processing rule management table  111 .  FIG. 3  shows the content of the processing rule management table  111  for a case where the processing rules R 1 , R 2  in  FIGS. 2A and 2B , described above, are stored in the processing rule storage unit  130 . 
     As shown in  FIG. 3 , information on items such as rule ID, used engines, interval, and input data format are registered in the processing rule management table  111 . In  FIG. 3 , information relating to one processing rule is managed on one row. 
     The “rule ID” item is an item showing the identifier of each processing rule. Here, a case where the rule ID of the processing rule R 1  is “1” and the rule ID of the processing rule R 2  is “2” is described. 
     The “used engines” item is an item used to manage the engines  200  used in the “data processing definition step” of such processing rule. As shown in  FIG. 3 , a value “1” or “0” is set for the engine ID of each engine in the “used engines” item. If the value corresponding to an engine ID is zero in the “used engines” item, this means that the engine  200  with such engine ID is not used by such processing rule. Meanwhile, if the value corresponding to an engine ID is one in the “used engines” item, this means that the engine  200  with such engine ID is used by such processing rule. As one example, for the processing rule R 1  (where rule ID:1), it is indicated that the engines  200 - 1  to  200 - 3  whose engine IDs are 1 to 3 are used. 
     The “interval” item shows the interval (gap) for carrying out the script of such processing rule. The interval may be shown in units of time or may be shown as a generated number of packets (the number of packets included in the report data supplied from the router  400 ). The “input data format” item shows the format of the input data defined in the input data definition step of such processing rule. 
     In  FIG. 3 , the interval of the processing rule R 1  (ruleID:1) is “10000 packets” and the input data format is “trafficdata”. Accordingly, it is shown that when the number of packets (the number of packets included in the report data supplied from the router  400 ) generated from the previous execution of the processing rule R 1  reaches 10,000, the engine cooperative processing unit  110  starts the execution of the processing rule R 1  with report data in the trafficdata format including such 10,000 packets of data as an input. 
     In  FIG. 3 , the interval of the processing rule R 2  (rule ID:2) is “10s” and the input data format is “flow_record”. Accordingly, it is shown that when 10 seconds have elapsed from the previous execution of the processing rule R 2 , the engine cooperative processing unit  110  starts the execution of processing rule R 2  with the report data in the flow_record format supplied during such 10 seconds as an input. 
     The content of the processing rule management table  111  may register content in accordance with user operations and may be updated by the engine cooperative processing unit  110  in accordance with the content of a processing rule added to the processing rule storage unit  130 . 
     The engine cooperative processing unit  110  is not limited to a unit that grasps the information of the respective items in the processing rule management table  111  for the processing rules. As one example, information on the respective items of the processing rule management table  111  may be stored together with data on the processing rules in the processing rule storage unit  130  and read into the engine cooperative processing unit  110 . The engine cooperative processing unit  110  may refer to the content of the script of the processing rule stored in the processing rule storage unit  130  and reflect the content in the processing rule management table  111 . As one example, if a new processing rule has been added to the processing rule storage unit  130 , the engine cooperative processing unit  110  may read the content of the input data definition step that configures such processing rule, grasp a confirmation (trafficdata or flow_record) of the format of the input data of such processing rule, and reflect such information in the “input data format” item. Also, for example, if a new processing rule has been added to the processing rule storage unit  130 , the engine cooperative processing unit  110  may read the content of the data processing definition step that configures such processing rule, grasp the engines  200  (engine IDs) to be used for such processing rule, and reflect such information in the “used engines item. 
     Next, an example content of an engine management table  112  held in the engine cooperative processing unit  110  will be described. 
       FIG. 4  is a diagram useful in explaining an example content of the engine management table  112 .  FIG. 4  shows the content of the engine management table  112  in a case where the engines  200 - 1  to  200 - 6  (engine ID: 1 to 6) are connected to the engine shared driving unit  120 . 
     As shown in  FIG. 4 , information on the items “engine ID”, “IF number”, “engine name” and “processing summary” are registered in the engine management table  112 . In  FIG. 4 , the information relating to one processing rule is managed on one row. 
     The “engine ID” item shows the engine ID (an ID used in the definition of a processing rule or the like) assigned to such engine  200 . 
     The “IF number” item shows the number of an interface (the identifier of a logical or physical interface) to which the engine  200  is installed on the engine shared driving unit  120 . 
     Although the engine IDs and the IF numbers of the respective engines  200  are described as separate items in  FIG. 4 , if the content matches, the engine IDs and the IF numbers may be collectively described in a single item. 
     The “engine name” item shows the name of such engine  200 . The “processing summary” item shows a summary of the processing of the engine  200 . Note that the “engine name” and “processing summary” items are not essential items for the engine management table  112  and may be omitted. 
     If an engine  200  has been newly installed (i.e., connected to the engine shared driving unit  120 ) or an engine  200  that has already been installed has been uninstalled (i.e., disconnected from the engine shared driving unit  120 ), the engine cooperative processing unit  110  updates the content of the engine management table  112 . Such processing will be described as part of the description of the operation given later. 
     Next, the internal configuration of the engines  200  ( 200 - 1  to  200 - 6 ) will be described. 
     Here, since the fundamental configurations (frameworks) of the respective engines  200  are all the same, only engines where the content of the data processing to be executed is different will be described. 
       FIG. 5  is a block diagram showing the functional configuration of the respective engines  200 . 
     The engines  200  may be constructed by installing a data processing program according to the present embodiment into hardware (a computer) that is separate to the network analysis apparatus  100  or may be constructed as one program (a data processing program according to the present embodiment) that operates on a computer that is the network analysis apparatus  100 . In either case, the functional configuration of the engines  200  can be as shown in  FIG. 5 . 
     An engine  200  includes an interface unit  210 , a data processing unit  220 , and an install processing unit  230 . 
     The interface unit  210  functions as an interface for connecting to the engine shared driving unit  120 . If the engine  200  is constructed using hardware (a computer) that is separate to the engine shared driving unit  120 , it is necessary for the interface unit  210  to be equipped with an interface for physically connecting to the network analysis apparatus  100  (the engine shared driving unit  120 ). Although there are no limitations on the interface if the engine  200  is connected to the engine shared driving unit  120  using hardware, as examples it is possible to use a LAN interface such as Ethernet or various interfaces such as a fiber channel. 
     The data processing unit  220  functions so as to carry out data processing based on a request from the engine cooperative processing unit  110 . The content of the specific data processing carried out by the data processing unit  220  differs according to the specification of the engine  200  in question. The data processing unit  220  may internally manage a work memory used when carrying out data processing and/or a detailed operation log, or part or all of such information may be stored in a region reserved in the log accumulation unit  150 . In such case, it is necessary to configure the respective engines  200  so as to be capable of reading and writing data accumulated in the log accumulation unit  150  via the engine shared driving unit  120 . 
     The install processing unit  230  carries out processing that connects to the network analysis apparatus  100  and installs the engine  200  and processing that disconnects (uninstalls) the engine  200  from a connected (installed) state to the network analysis apparatus  100 . As one example, the installation process and uninstallation process by the install processing unit  230  may be carried out in accordance with a user operation. If the engine  200  is configured with software by a program (the data processing program according to the present embodiment) the install processing unit  230  is configured as a subprogram that composes such program. When a subprogram corresponding to the install processing unit  230  has been executed by the user (for example, a specified command operation), installation or uninstallation processing is commenced. If the engine  200  is hardware that is separated to the network analysis apparatus  100 , the user may directly operate the engine  200  (the install processing unit  230 ) (for example, operation made via an interface such as a button, not shown), or may operate the engine  200  (the install processing unit  230 ) via the network analysis apparatus  100 . 
     When the installation or uninstallation process commences, the install processing unit  230  carries out processing in cooperation with the engine cooperative processing unit  110 . A specific sequence of the processing by the install processing unit  230  will be described as part of the description of the operation given later. 
     (A-2) Operation of the Present Embodiment 
     Next, the operation of the network analysis system  10  according to the present embodiment with the configuration described above will be described. 
     (A-2-1) Engine Installation 
     First, the operation when a new engine is installed into the network analysis system  10  will be described with reference to the sequence chart in  FIG. 6 . 
     Here,  FIG. 6  shows an operation where an engine  200 - 7  is newly installed in a state where the engines  200 - 1  to  200 - 6  have been installed on the network analysis apparatus  100 . In this description, it is assumed that as the initial state of the flowchart in  FIG. 6 , the contents of the processing rule management table  111  and the engine management table  112  are in the states shown in  FIGS. 3 and 4  respectively. 
     First, it is assumed that the engine  200 - 7  has been placed by a user operation in a state that can be accessed by the engine shared driving unit  120  and the install processing unit  230  of the engine  200 - 7  has been activated (S 301 ). If the engine  200  has a software configuration using a program (the data processing program according to the present embodiment), as one example, once a file of the program that configures the engine  200 - 7  has been expanded in a computer that configures the network analysis apparatus  100  and placed in an executable state, the engine  200 - 7  is placed in an accessible state for the engine shared driving unit  120 . Also, if the engine  200  is constructed by hardware (a computer) that is separate to the network analysis apparatus  100 , as one example, once the hardware (module) of the engine  200 - 7  has been connected to the network analysis apparatus  100  (for example, connection using a cable and an interface such as a socket), the engine  200 - 7  is placed in an accessible state for the engine shared driving unit  120 . 
     When the install processing unit  230  of the engine  200 - 7  is activated, notification of an install request is given from the install processing unit  230  via the engine shared driving unit  120  to the engine cooperative processing unit  110  (S 302 ). 
     When such notification of an install request is received, the engine cooperative processing unit  110  gives notification of a transmission request for management information (information to be registered in the engine management table  112 ) to the engine  200 - 7  (S 303 ). 
     When the transmission request of the management information has been received, the install processing unit  230  of the engine  200 - 7  sends management information of the engine  200 - 7  to the engine cooperative processing unit  110  (S 304 ). 
     When management information is received, the engine cooperative processing unit  110  assigns an engine ID to the engine  200 - 7 . The engine cooperative processing unit  110  then adds information relating to the engine  200 - 7  to the engine management table  112  based on the received management information and the assigned engine ID. In addition, the engine cooperative processing unit  110  adds the engine ID item of the engine  200 - 7  to the “used engines” item of the processing rule management table  111  (S 305 ). 
       FIGS. 7A and 7B  show the states of the processing rule management table  111  and the engine management table  112  after updating by the processing in step S 305  described above. 
     When assigning an engine ID to the engine  200  that has been newly installed, the engine cooperative processing unit  110  confirms the engine management table  112  and assigns an unused engine ID. Here, it is assumed that the engine cooperative processing unit  110  assigns the lowest number out of the unused engine IDs to the engine  200 - 7 . As described above, since the state of the engine management table  112  before step S 305  is the state shown in  FIG. 4  described above, the engine cooperative processing unit  110  assigns “7” as the engine ID to the engine  200 - 7 . Note that the engine ID assigned to the engine  200  that is newly installed may be a number in accordance with a user operation, or an ID or the like that is set in a fixed manner may be assigned in accordance with the type or the like of the engine  200 . The engine cooperative processing unit  110  additionally registers information on the engine  200 - 7  in the engine management table  112  with “7” as the engine ID of the engine  200 - 7  and the engine management table  112  becomes the state shown in  FIG. 7B . The engine cooperative processing unit  110  then adds an item (the item where the engine ID is “7”) corresponding to the engine  200 - 7  to the “used engines” item of the processing rule management table  111  and the processing rule management table  111  becomes the state shown in  FIG. 7A . In the processing rule management table  111 , since the engine  200 - 7  will not be used by any of the processing rules when the item corresponding to the engine  200 - 7  (the item where the engine ID is “7”) has just been added, the values “0” are set. 
     On completing the updating of the respective tables (the processing rule management table  111  and the engine management table  112 ), the engine cooperative processing unit  110  gives the engine  200 - 7  notification of the completion of installation and also notification of the assigned engine ID ( 7 ) (S 306 ). 
     After this, it becomes possible for the engine  200 - 7  to carry out data processing on the network analysis apparatus  100 . 
     (A-2-2) Engine Uninstallation 
     Next, an operation where an engine  200  that has already been installed (connected) is uninstalled from the network analysis system  10  will be described. 
     If there has been an uninstallation request from an engine  200  (the install processing unit  230 ), the engine cooperative processing unit  110  confirms the influence that would be caused by uninstalling the engine  200  and determines, based on such confirmation result, whether it is possible to uninstall the engine  200 . More specifically, if there has been an uninstallation request from the engine  200  (the install processing unit  230 ), the engine cooperative processing unit  110  refers to the processing rule management table  111 , determines that uninstalling the engine  200  will have no influence if there are no processing rules that use such engine  200 , and permits uninstallation of the engine  200 . Meanwhile, if there is a processing rule that uses such engine  200 , the engine cooperative processing unit  110  does not permit uninstallation of the engine  200 . 
     Here, an operation when the engine cooperative processing unit  110  determines that an uninstallation request from the engine  200  is possible will be described first with reference to  FIG. 8 . 
       FIG. 8  shows an operation that carries out uninstallation of the engine  200 - 7  in a state immediately after the engine  200 - 7  has been newly installed in  FIG. 6  described above. That is, in the flowchart in  FIG. 8 , it is assumed that the initial states of the processing rule management table  111  and the engine management table  112  are the states shown in  FIGS. 7A and 7B , described above. 
     First, it is assumed that the install processing unit  230  of the engine  200 - 7  is activated by a user operation in a state where the engine  200 - 7  has been installed on the network analysis apparatus  100  (S 401 ). 
     Once the install processing unit  230  of the engine  200 - 7  has been activated, notification of an uninstallation request is given from the install processing unit  230  via the engine shared driving unit  120  to the engine cooperative processing unit  110  (S 402 ). 
     Next, when notification of the uninstallation request has been received, the engine cooperative processing unit  110  confirms the content of the processing rule management table  111  and determines whether it is possible to uninstall the engine  200 - 7  (S 403 ). 
     As described above, the content of the processing rule management table  111  is the state in  FIG. 7A , described above. As shown in  FIG. 7A , the items corresponding to the engine  200 - 7  (the items where the engine ID is “7”) are set at the value “0” (i.e., the value showing that the engine is not used) for all of the processing rules. Accordingly, since the engine  200 - 7  is not used by any of the processing rules, the engine cooperative processing unit  110  determines that there will be no influence even if the engine  200 - 7  is uninstalled and that it is possible to uninstall the engine  200 - 7 . 
     On determining that the uninstallation of the engine  200 - 7  is possible, the engine cooperative processing unit  110  gives notification of a final confirmation (ACK) request for the uninstallation (S 404 ). 
     On receiving notification of the confirmation (ACK) request for the uninstallation, the install processing unit  230  of the engine  200 - 7  sends a confirmation (ACK) of the uninstallation (S 405 ). 
     On receiving notification of the confirmation (ACK) of the uninstallation, the engine cooperative processing unit  110  carries out the deletion of information relating to the engine  200 - 7  from the processing rule management table  111  and the engine management table  112  (S 406 ). 
     The engine cooperative processing unit  110  deletes information on the engine  200 - 7  (engine ID:7) from the engine management table  112  so that the engine management table  112  becomes the state shown in  FIG. 4  described above. The engine cooperative processing unit  110  also deletes items corresponding to the engine  200 - 7  (items where the engine ID is “7”) from the “used engines” item in the processing rule management table  111  so that the processing rule management table  111  becomes the state shown in  FIG. 3  described above. 
     The engine cooperative processing unit  110  transmits a notification that the uninstallation process is completed to the engine  200 - 7  (S 407 ). Through the operation in the sequence described above, the uninstallation process of the engine  200 - 7  in the network analysis system  10  ends, and it becomes possible to delete or remove the file for the engine  200 - 7 . 
     Next, the operation when the engine cooperative processing unit  110  determines that the uninstallation request from the engine  200  is not possible will be described using  FIG. 9 . The flowchart in  FIG. 9  is also described on the assumption that the initial states of the processing rule management table  111  and the engine management table  112  are the states shown in  FIGS. 7A and 7B , described above. 
     First, it is assumed that the install processing unit  230  of the engine  200 - 6  is activated by a user operation in a state where the engine  200 - 6  has been installed on the network analysis apparatus  100  (S 501 ). 
     Once the install processing unit  230  of the engine  200 - 6  has been activated, notification of an uninstallation request is given from the install processing unit  230  via the engine shared driving unit  120  to the engine cooperative processing unit  110  (S 502 ). 
     Next, when notification of the uninstallation request has been received, the engine cooperative processing unit  110  confirms the content of the processing rule management table  111  and determines whether it is possible to uninstall the engine  200 - 6  (S 503 ). 
     As described above, the content of the processing rule management table  111  is the state in  FIG. 7A , described above. As shown in  FIG. 7A , the value “1” (i.e., the value showing that the engine is used) is set on the row of the processing rule R 2  (the row where the rule ID is “2”) in the item corresponding to the engine  200 - 6 . Accordingly, since a processing rule that uses the engine  200 - 6  is present, the engine cooperative processing unit  110  determines that there will be an influence if the engine  200 - 6  is uninstalled and that it is not possible to uninstall the engine  200 - 6 . 
     On determining that the uninstallation of the engine  200 - 6  is not possible, the engine cooperative processing unit  110  transmits notification that uninstallation is not possible to the engine  200 - 6  (S 504 ) and cancels the uninstallation process. 
     (A-2-3) Data Processing Relating to a Processing Rule 
     Next, the specific operation (sequence) where the engine cooperative processing unit  110  causes the respective engines  200  to carry out data processing based on the script (data processing definition step) of a processing rule will be described. 
     First, the operation when the engine cooperative processing unit  110  causes the engines  200 - 1  to  200 - 3  to carry out data processing based on the data processing definition step of the processing rule R 1  (see  FIG. 2A  described above) will be described with reference to  FIGS. 10 and 11 . 
     First, the engine cooperative processing unit  110  carries out syntax analysis on the processing rule R 1  (see  FIG. 2A  described above) to generate a frame (hereinafter referred to as a “data processing frame”) F 101  of a specified format to have the engines  200 - 1  to  200 - 3  carry out data processing based on the analyzed syntax and supplies the data processing frame F 101  to the engine shared driving unit  120  (S 601 ). 
     As one example, the data processing frame F 101  generated by the engine cooperative processing unit  110  in step S 601  has a configuration such as that shown in  FIG. 11A . As shown in  FIGS. 11A-11D , the respective data processing frames are frames with fields for a processing designation header portion and a data portion. Note that although the description here assumes that a data processing frame carries out processing relating to one input data in one frame to simplify the description, it is also possible to carry out processing relating to one input data divided between a plurality of frames. 
     The data portion is a field in which input data that is to be processed in such data processing frame is inserted. The input data (input1) from the engine cooperative processing unit  110  is set in the data portion of the data processing frame F 101 . 
     The processing designation header portion is a field in which the processing order for when data processing for the data processing frame is to be carried out by the engines  200  and parameters (additional parameters) to be designated when data processing is carried out are described. As one example, as shown in  FIG. 11A , the processing designation header portion is shown by a list in which pairs of engine IDs and additional parameters are arranged into the processing order. 
     In the data processing definition step (step S 102 ) of the processing rule R 1 , as described above, a nested structure (syntax) where the engine  200 - 1  (Engine1) is caused to carry out processing first on the input data (input1), the result of such processing is further processed by the engine  200 - 2  (Engine2), and then the result of such processing is further processed by the engine  200 - 3  (Engine3) is described, so that serial processing is required. For this reason, to realize serial processing such as that described above using a simple description, the processing designation header portion is compatible with being described as a list in which pairs of an engine ID and additional parameters are arranged in accordance with the processing order. 
     As one example, as illustrated in  FIG. 11A , “1(output_type1,parameter1), 2(output_type2,parameter2), 3(output_type3,parameter3);” is written in the processing designation header portion of the data processing frame F 101 . The “1(output_type1,parameter1)” description at the front of the list of the processing designation header portion of the data processing frame F 101  shows that processing is carried out first for the data processing frame F 101  at the engine  200 - 1  whose engine ID is “1”. That is, the “1(output_type1,parameter1)” description has a content that corresponds to step S 102 - 1  shown in  FIG. 2A  described above. Also, “2(output_type2,parameter2)” which corresponds to step S 102 - 2  shown in  FIG. 2A  described above is described second in the list in the processing designation header portion of the data processing frame F 101 . In addition, “3(output_type3,parameter3)” which corresponds to step S 102 - 3  shown in  FIG. 2A  described above is written third in the list in the processing designation header portion of the data processing frame F 101 . In addition, “;” is described at the final end of the processing designation header portion of the data processing frame F 101  as a symbol showing the end of the list. 
     If a nested structure (syntax) such as that described above has been detected in the syntax analysis of the data processing definition step, as described above the engine cooperative processing unit  110  generates a list to be introduced into the processing designation header portion based on the content of the substeps that construct the data processing definition step. 
     Next, when the data processing frame F 101  with the construction described above has been handed over, the engine shared driving unit  120  refers to “1(output_type1,parameter1)” that is the first element in the list in the processing designation header portion that constructs the data processing frame F 101  and identifies that the transfer destination of the data processing frame F 101  is the engine  200 - 1  (engine ID:1). The engine shared driving unit  120  then hands over the data processing frame F 101  to the engine  200 - 1  (S 602 ). 
     The engine  200 - 1  then extracts the input data (input1) of the data portion of the data processing frame F 101  and the additional parameters (output_type1,parameter1) that are added to the first element in the list in the processing designation header portion. The engine  200 - 1  then carries out data processing using the additional parameters (output_type1,parameter1) on the extracted input data (input1) to obtain the data (Analyze1) after processing. Next, the engine  200 - 1  generates a data processing frame F 102  (see  FIG. 11B ) where, for the data processing frame F 101 , the data portion is replaced with the data (Analyze1) after processing and the first element “1(output_type1,parameter1)” is also deleted from the list in the processing designation header portion (S 603 ). 
     The engine  200 - 1  then hands over the data processing frame F 102  to the engine shared driving unit  120  (S 604 ). 
     Next, once the data processing frame F 102  has been handed over, the engine shared driving unit  120  refers to “2(output_type2,parameter2)” that is the first element in the list in the processing designation header portion that constructs the data processing frame F 102  and identifies that the transfer destination of the data processing frame F 102  is the engine  200 - 2  (engine ID:2). The engine shared driving unit  120  then hands over the data processing frame F 102  to the engine  200 - 2  (S 605 ). 
     The engine  200 - 2  then extracts the input data (Analyze1) of the data portion of the data processing frame F 102  and the additional parameters (output_type2,parameter2) that are added to the first element in the list in the processing designation header portion. The engine  200 - 2  then carries out data processing using the additional parameters (output_type2,parameter2) on the extracted input data (Analyze1) to obtain the data (Analyze2) after processing. Next, the engine  200 - 2  generates a data processing frame F 103  (see  FIG. 11C ) where, for the data processing frame F 102 , the data portion is replaced with the data (Analyze2) after processing and the first element “2(output_type2,parameter2)” has been deleted from the list in the processing designation header portion (S 606 ). 
     The engine  200 - 2  then hands over the data processing frame F 103  to the engine shared driving unit  120  (S 607 ). 
     Next, once the data processing frame F 103  has been handed over, the engine shared driving unit  120  refers to “3(output_type3,parameter3)” that is the first element in the list of the processing designation header portion that constructs the data processing frame F 103  and identifies that the transfer destination of the data processing frame F 103  is the engine  200 - 3  (engine ID:3). The engine shared driving unit  120  then hands over the data processing frame F 103  to the engine  200 - 3  (S 608 ). 
     The engine  200 - 3  then extracts the input data (Analyze2) of the data portion of the data processing frame F 103  and the additional parameters (output_type3,parameter3) that are added to the first element in the list of the processing designation header portion. The engine  200 - 3  then carries out data processing using the additional parameters (output_type3,parameter3) on the extracted input data (Analyze2) to obtain the data (Analyze3) after processing. Next, the engine  200 - 3  generates a data processing frame F 104  (see  FIG. 11D ) where, for the data processing frame F 103 , the data portion is replaced with the data (Analyze3) after processing and the first element “3(output_type3,parameter3)” has been deleted from the list in the processing designation header portion (S 609 ). 
     The engine  200 - 3  then hands over the data processing frame F 104  to the engine shared driving unit  120  (S 610 ). 
     Next, when the data processing frame F 104  has been handed over, the engine shared driving unit  120  refers to the processing designation header portion that constructs the data processing frame F 104 . At this time, since the list in the processing designation header portion that constructs the data processing frame F 104  is empty (a state where only “;” that is the symbol showing the end of the list is described), the engine shared driving unit  120  transmits the data processing frame F 104  not to an engine  200  but to the engine cooperative processing unit  110  (S 611 ). 
     As described above, it is assumed that if the list in the processing designation header portion that constructs a data processing frame is empty, the engine shared driving unit  120  transmits such data processing frame to the engine cooperative processing unit  110 . In this way, by distributing the data processing frame using the list in the processing designation header portion, it is possible to carry out processing efficiently without the processing returning to the engine cooperative processing unit  110  merely for interrupt processing every time processing by the respective engines  200  ends. Also, since it is sufficient as the processing of the engine shared driving unit  120  to carry out simple processing (switching processing) that determines the transmission destination by referring to the list in the processing designation header portion, it becomes easier to realize high-speed processing (for example, it becomes easier to increase the proportion of hardware used to construct the apparatus). 
     As described above, in the engine cooperative processing unit  110 , by merely generating the data processing frame F 101  in accordance with the data processing definition step of the processing rule R 1  and handing the data processing frame F 101  over to the engine shared driving unit  120 , it is possible to acquire the result (Analyze3) produced via the processing of the engines  200 - 1  to  200 - 3 . 
     Next, the operation when the engine cooperative processing unit  110  causes the engines  200 - 4  to  200 - 6  to carry out data processing based on the data processing definition step of the processing rule R 2  (see  FIG. 2B  described above) will be described with reference to  FIGS. 12 and 13A -13F. 
     First, the engine cooperative processing unit  110  carries out syntax analysis on the processing rule R 2  (see  FIG. 2B  described above) to generate data processing frames F 211 , F 221 , F 231  (see  FIG. 13A ,  FIG. 13B , and  FIG. 13C ) based on the analyzed syntax for the engines  200 - 4  to  200 - 6  and hands the data processing frames F 221 , F 221 , F 231  to the engine shared driving unit  120  (S 701  to S 703 ). 
     In the data processing definition step (step S 202 ) of the processing rule R 2 , unlike the processing rule R 1 , since there is no nested structure for having the plurality of engines  200  serially carry out data processing, the data processing frames F 211 , F 221 , and F 231  that separately request the engines  200 - 4  to  200 - 6  to carry out data processing are generated. 
     When the data processing frames F 211 , F 221 , and F 231  have been handed over, the engine shared driving unit  120  hands over the respective data processing frames to the transmission destination engines  200 - 4  to  200 - 6  (S 704  to S 706 ). 
     The engine  200 - 4  to which the data processing frame F 211  has been handed over processes the input data (input1) in the data portion of the data processing frame F 211  to obtain the data (Analyze1) after processing. For the data processing frame F 211 , the engine  200 - 4  then replaces the data portion with the data (Analyze1) after processing, generates a data processing frame F 212  (see  FIG. 13D ) from which the first element in the list in the processing designation header portion has been deleted (S 707 ), and hands over the data processing frame F 212  to the engine shared driving unit  120  (S 710 ). 
     The engine  200 - 5  to which the data processing frame F 221  has been handed over processes the input data (input1) in the data portion of the data processing frame F 221  to obtain the data (Analyze2) after processing. For the data processing frame F 221 , the engine  200 - 5  then replaces the data portion with the data (Analyze2) after processing, generates a data processing frame F 222  (see  FIG. 13E ) from which the first element in the list of the processing designation header portion has been deleted (S 708 ), and hands over the data processing frame F 222  to the engine shared driving unit  120  (S 711 ). 
     The engine  200 - 6  to which the data processing frame F 231  has been handed over processes the input data (input1) in the data portion of the data processing frame F 231  to obtain the data (Analyze3) after processing. For the data processing frame F 231 , the engine  200 - 6  then replaces the data portion with the data (Analyze3) after processing, generates a data processing frame F 232  (see  FIG. 13F ) from which the first element in the list of the processing designation header portion has been deleted (S 709 ), and hands over the data processing frame F 231  to the engine shared driving unit  120  (S 712 ). 
     When the data processing frames F 212 , F 222 , F 232  (in all of which the content of the processing designation header portion is empty) have been handed over, the engine shared driving unit  120  hands over each of the data processing frames F 212 , F 222 , F 232  to the engine cooperative processing unit  110  (S 713  to S 715 ). 
     As described above, at the engine cooperative processing unit  110 , in accordance with the data processing definition step of the processing rule R 2 , by merely generating the data processing frames F 211 , F 221 , and F 231  and handing over the data processing frames F 211 , F 221 , and F 231  to the engine shared driving unit  120 , it is possible to acquire the results (Analyze1, Analyze2, Analyze3) produced via the processing of the engines  200 - 4  to  200 - 6 . 
     (A-3) Effects of the Present Embodiment 
     The effects described below can be achieved by the present embodiment. 
     In the network analysis system  10 , the engines  200  are provided on the network analysis apparatus  100  and a data processing protocol (i.e., exchanges using data processing frames) between the network analysis apparatus  100  and the engine  200  is clearly established. By doing so, it becomes easy to replace and/or change the specification (upgrade) of the engines  200  in single engine units on the network analysis apparatus  100 . 
     Also, in the network analysis apparatus  100 , the processing rule management table  111  and the engine management table  112  are provided and the engines  200  to be used for each processing rule are managed. By doing so, even if an engine  200  is uninstalled, it is possible to maintain normal operation for the entire system. 
     In addition, since communication with the engine cooperative processing unit  110  and between the engines  200  can be carried out by just simple exchanges that use data processing frames, it is possible to realize higher-speed data processing. 
     In addition, in the network analysis system  10 , since it is possible to share the engines  200  between a plurality of processing rules, it becomes easy to construct the system efficiently. 
     (B) Other Embodiments 
     The present invention is not limited to the embodiment described above and can be subjected to modifications such as the examples described below. 
     (B-1) Although the log accumulation unit  150  simply accumulates log data in the embodiment described above, it is also possible to configure a database that is accessible from the OPS  300  or the like. As one example, it is possible to provide an interface which, when notification of the occurrence of a network abnormality has been given from the network analysis apparatus  100  to the OPS  300 , enables the user to use the OPS  300  to access the database (the log accumulation unit  150 ) and confirm the details of the network abnormality that has occurred. More specifically, as one example it is possible to separately provide an engine  200  that is capable of carrying out a search on the content of the database (the log accumulation unit  150 ).
 
(B-2) Although the network analysis apparatus  100  analyzes the traffic flowing through the router in the present embodiment, the analysis is not limited to a router and the traffic flowing in another network apparatus (for example, various types of server or a firewall) may be acquired and analyzed.
 
(B-3) Although data management where all of the engines  200  are different has been described in the above embodiment, it is possible to use a configuration where a plurality of engines  200  that carry out the same data processing are provided and load distribution is carried out. In this case, in the engine cooperative processing unit  110 , when generating the data processing frames, it is necessary to carry out processing that allocates processing with the same content to a plurality of engines  200  (for example, allocation according to a round robin method).
 
(B-4) Although the transmission and reception of data between the engine cooperative processing unit  110  and the respective engines  200  is carried out using data processing frames in the embodiment described above, so long as it is possible to carry out the transmission and reception of data, there are no limitations on the construction of the data.
 
(B-5) Although it is possible to confirm whether there is no processing rule that uses a specified engine  200  when there has been an uninstallation request for such engine  200  according to the embodiment described above, it is also possible to use a configuration that judges, when a new processing rule has been registered, whether such processing rule is executable by only the engines  200  that are already provided and defines, if the new processing rule is not executable, attributes and the like of the processing to be carried out and installs a suitable engine  200  from the OPS  300  or the like.
 
(B-6) Although one network analysis system  10  is connected to the OPS  300  in the embodiment described above, it is also possible to carry out control by connecting a plurality of network analysis systems  10  to the OPS  300 . With this configuration, it would be conceivable for the OPS  300  to identify the types of engines  200  provided in each network analysis system  10  based on the engine ID or the like, decide the load of each network analysis system  10  based on the processing rules that are executable for the respective network analysis systems  10  and have cooperative processing carried out.
 
(B-7) Although the embodiment described above has a configuration where the report data transmitted from the export processing unit  440  of the router  400  is inputted via the internal network N 1  into the network analysis system  10  as report packets, it is also possible to use a configuration where the export processing unit  440  and the network analysis system  10  are directly connected without the internal network N 1  in between.
 
(B-8) Although the embodiment described above is configured to acquire report data from the export processing unit  440  provided in the router  400 , it is also possible to use a configuration where a separate flow exporter (a network apparatus equipped with only the function of the export processing unit  440 ) is additionally provided in the network to acquire the report data.
 
(B-9) Although management of the information relating to the data processing definition information and the management of the data processing modules are carried out using the processing rule management table  111  and the engine management table  112  in table format in the embodiment described above, it is unnecessary for a configuration capable of executing the same function to be in table format and may be in another format such as database format.
 
     The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, whilst the present invention is not limited to the above examples, of course. A person skilled in the art may find various alternations and modifications within the scope of the appended claims, and it should be understood that they will naturally come under the technical scope of the present invention.