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A Unified Model of Internet Scale Alerting Services

A Unified Model of Internet Scale Alerting Services
A Unified Model of Internet Scale Alerting Services

A Uni?ed Model of Internet Scale Alerting Services

Annika Hinze,Daniel Faensen

Institute of Computer Science

Freie Universit¨a t Berlin,Germany

faensen,hinze@inf.fu-berlin.de

Abstract In the last years,alerting systems have gained strengthened attention.

Several systems have been implemented.For the evaluation and cooperation of these

systems,the following problems arise:The systems and their models are not com-

patible,and existing models are only appropriate for a subset of conceivable applica-

tion domains.Due to modeling differences,a simple integration of different alerting

systems is impossible.What is needed,is a uni?ed model that covers the whole vari-

ety of alerting service applications.This paper provides a uni?ed model for alerting

services that captures the special constraints of most application areas.The model

can serve as a basis for an evaluation of alerting service implementations.In ad-

dition to the uni?ed model,we de?ne a general pro?le structure by which clients

can specify their interest.This structure is independent of underlying pro?le de?-

nition languages.To eliminate drawbacks of the existing non-cooperating solitary

services we introduce a new technique,the Mediating Alerting Service(MediAS).

It establishes the cooperation of alerting services in an hierarchical and parallel way.

1Introduction

Electronic publication becomes more and more popular.Since the readers do not want to be forced to regularly search for information about new documents,there is strong need for alerting services.An alerting service keeps its clients informed about new doc-uments and events they are interested in.Currently,several implementations of alerting services exist for different applicational domains,such as Salamander[12],Siena[2],or Keryx[1].The underlying models of these services do not meet all requirements found in applications suitable for wide area networks,such as digital libraries.Additionally, the models for existing alerting services mainly cover the applications the services are designed for.In this paper,we provide a uni?ed model for alerting services that consid-ers the special constraints of different application domains.The interests of clients are de?ned as so-called pro?les.Since several pro?le de?nition languages are used in the dif-ferent services,we give a general structure of pro?les for alerting services,independent of the pro?le de?nition language.The large number of existing alerting services for a certain application domain has several drawbacks.The users have to de?ne their interest at different services in different ways.The available noti?cations are mostly bound to the supply of individual services,information from different suppliers is not combined.We therefore introduce and propose the use of a Mediating Alerting Service(MediAS),that connects several suppliers and clients.

The remainder of this paper is structured as follows:In Section2,we provide an overview of the structure and tasks of an alerting service.We introduce scenarios for the conceivable application domains of alerting services and name the problems with existing alerting services in detail.Section3introduces our architectural model for alerting ser-vices and Section4outlines our event-based model.In Section5,we propose the use of a mediating alerting service.Section6provides an overview of some related systems and models.Section7gives some directions for our future work.

2Event Noti?cation Service

In this section,we introduce the general structure and tasks of an alerting service.We

present a collection of possible scenarios in which Internet-scale event services are ap-

plicable.The main purpose of this collection is the motivation and validation of an event model that covers all applications.Based on the scenarios and the derived common re-

quirements for alerting services,we will point out the problems with existing alerting

services and their models.

Tasks of an Alerting Service Alerting services connect suppliers of information and inter-ested clients.In our example of scienti?c papers the suppliers are publishing houses and the clients are the interested scientists.Alerting services inform the clients about the oc-currences of events on objects of interest.Objects of interest are located at the supplier’s side.Events can be changes on existing objects or the creation of new objects,e.g.,the publication of a journal article.Clients de?ne their interest by personal pro?les.The infor-mation about the occurring events is?ltered according to these pro?les and noti?cations are sent to the interested users(clients).Fig.1depicts the data-?ow in a high-level ar-chitecture of an alerting service.Keep in mind that the data-?ow is independent from the delivery mode,such as push or pull.The tasks of an alerting service can be subdivided into the following steps:First,the observable event classes are to be determined and of-fered to the clients.Then,the client’s pro?les have to be de?ned and stored.The occurring events have to be observed and?ltered.Before creating noti?cations,the events are inte-grated in order to detect combinations of events(e.g.,two conferences happen to be at the same time).After duplicate recognition the messages can be buffered in order to enable ef?cient noti?cation(e.g.,by merging several messages into one noti?cation).According to a given

Figure1.Data-?ow in an Alerting Service

Scenarios We present a selection of application domains of alerting services to demon-

strate the need for a uni?ed and extended event model and a Mediating Alerting Service.

Stock ticker Selected stock values are pushed to registered clients.Delivery can be

immediate(to paying customers)or deferred.Clients can be off-line.In that case,noti-

?cations are lost without consequences.A client can be a PC with an analysis software that reacts on events like threshold crossing of a share value by notifying its user or by reacting autonomously.Cardinality of the relation between supplier and client is usually ,size of noti?cation messages is small(a few bytes)but they are sent with high frequency.Encryption can be required.Objects of interest are identi?able in advance,the clients subscribe to objects by selecting from a given list of objects(out of).

Digital Library In a digital library,users want to be noti?ed on new publications they

are interested in.They de?ne their interest by specifying certain bibliographical meta-

data(e.g.,a journal or an author)or by Information Retrieval-like https://www.wendangku.net/doc/139090467.html,rmation suppliers can be publishing houses or universities’technical report servers.The offered

documents reside on publisher’s side within a database,?le systems,or other repositories.

Within the pro?les,the clients have to specify the source.Noti?cations can include the

full document or a pointer to it(DOI,URL).To avoid an unnecessary high frequency of noti?cation deliveries,users can specify a time interval(e.g.,weekly)within which

noti?cations are collected and then delivered altogether.Since users do not know each

supplier and do not want to register at different suppliers’interfaces,a service covering many suppliers and giving uni?ed access to their repositories operates between clients and information sources.Departments or working groups may have overlapping user pro?les. Cardinality between suppliers and clients can be,noti?cations can be large(several MB).Frequency of noti?cations is low,delivery has to be guaranteed.Objects of interest are unknown at the time of pro?le de?nition and usually come into existence later.Clients can be interested in only parts of objects,e.g.,in a mathematical proof that is part of an article,which is part of a journal issue.

Software Update Registered users of software(programs,data)automatically get up-

dates pushed from their vendors via the Internet.To avoid too frequent delivery,users can specify that only every second update is really of interest.While noti?cation frequency is low,their size can become huge.It depends on previous events whether an update event is to be forwarded to the client.We call dependence of events on other events event patterns.

Remote monitoring and control A power station is equipped with a variety of probes

and sensors.Multiple devices of the same type ensure reliability by redundant measure-

ment.Measured values are pushed in real-time to the monitors.Monitoring is done at different places,several control rooms and by replicated software agents.A client can request information from certain probes or probe classes.Additionally,it can require to be noti?ed only if two or more probes deliver the same value or if a probe did not de-liver new measurements for a certain time interval.Cardinality of supplier to client can be out of,that means1of redundant clients has to handle an event.Reliable connections and real-time delivery is required.Noti?cation delivery in the case of at least two related event occurrences is another example of an event pattern.Events that indicate that nothing happened in a time interval are called passive events.

Other conceivable example scenarios are mobile computing,traveller information sys-tems and replication services.

Dimensions for Model Evaluation From the scenarios in the previous section,the follow-ing dimensions to classify and evaluate event models and alerting services emerge: Cardinality Associations between suppliers and clients cover the range from to .The Remote Monitoring and Control scenario shows that the notion of a out of cardinality is useful.

Noti?cation size Depending on application type,the size of a noti?cation can range from

a few bytes to several megabytes.By delivering pointers to objects instead of the

objects themselves,the size can be reduced signi?cantly.

Noti?cation frequency Can vary from high frequent(in the range of seconds)to,say, once a year or only once at all.

Guaranteed delivery In a digital library,for instance,it is necessary to guarantee deliv-ery of noti?cations even if clients are of?ine.

Real time Remote monitoring and control can require real time delivery of noti?cations. Passive events In some cases,it is useful to be noti?ed if during a speci?ed interval nothing happened,e.g.,if a server does not handle requests anymore.

Event pattern Clients register for events that depend on other events.

Composed objects Objects do not need to be atomic,but can consist of other objects.

Object repositories Clients can subscribe to repositories to get informed about the changes within that repository.To subscribe to information objects that do not exist at the time of the pro?le de?nition,clients refer to the repository the object will appear in.

Pro?le de?nition Clients can subscribe to concrete objects(e.g.,by referring to their identi?er),by specifying meta-data that describe the objects of interests or(in the case of digital libraries)using an IR-like query.

Scalability Can be achieved by redundant alerting services,duplicated parts of services or a hierarchy of services if pro?les of different clients are overlapping.

Encryption Scenarios that cover delivery of privacy data or data that are liable for costs can require encrypted delivery.Encryption is handled on protocol level.

Reliability and Acknowledgment Acknowledgments can be used to implement reliable delivery.These characteristics will not be considered in our model,since they have no in?uence within the modeling level used here.

Drawbacks of Existing Models In the following part,we show the drawbacks of the ex-isting models for alerting services regarding the requirements described above.

Terminology:The term alerting service itself bears the problem that on the one hand there exist several names for this kind of service(Alerting Service,Noti?cation Service, Pro?le Service,etc.),while on the other hand several different concepts are called no-ti?cation service(see Section6).Additionally,the different models for alerting systems use identical terms to describe different concepts.For example consider the term Chan-nel:In the CORBA model,an event channel is an intervening object that allows multiple suppliers to communicate with multiple consumers asynchronously[14].CDF[7]or Net-caster Channel[13]are similar to television broadcast channels.In contrast to CORBA, CDF Channel has an observer function for the channel objects.Further evaluation of the implementation of alerting services with channels can be found in[8].

States of non-existing objects:In most event-based models,an event is de?ned as a state transition of an object of interest at a particular time,where the state of an object is the current value of all its attributes(e.g.,[14,11]).The binding of events to the object of interest cannot be weakened in general as the events are strongly related to the objects (opposite to clock-time events).Consider the case of a scienti?c paper or article that is published.This object appears at a speci?c time,the state of the object is then the content of the paper and its meta-data such as author and title.But what is the state of the object before it exists?So the term of an event as a state transition of the object is not appropriate here.Rosenblum and Wolf[15]de?ne an event as an instantaneous effect of the termination of an invocation of an operation on an object.This de?nition associates the event with the invoker of the operation instead of with the object of interest.As a consequence,the invoker has to communicate with the observer in order to announce the event.But it cannot be generally presupposed that invokers actively announce events to observers,due to several reasons.

Composed Objects:The noti?cations sent to the clients are the messages that are seen as the physical representation of the events[2]that the clients are subscribed to.Since the events relate to identi?able objects of interest,the noti?cations contain or refer to these objects.However,clients are often not interested in whole documents or sites(they are interested in an article instead of the whole journal,or even in a single mathematical proof instead of the article),therefore,substructures need to be identi?able as objects.

How to register that nothing happened:“Send message if the value of share S does not change for a period of days.”Existing models of alerting services cannot handle this kind of pro?le,as neither an operation is performed on the object of interest,nor does the object of interest change its state.We are aware of the fact that this construct is contradictory to the intuitive notion of an event as something that happens.

Figure2.Architectural Model of an Alerting Service

3Architecture

In this section we introduce a general architectural model for alerting services that is used

for the identi?cation of components involved in the event model presented in Section4. The involved components and their relations are shown in Fig.2.Objects of interest are

so-called information objects that are located at the supplier’s side,optionally in an ob-

ject https://www.wendangku.net/doc/139090467.html,rmation objects can be persistent(e.g.,documents)or transient(e.g., measured values).The objects can be organized hierarchically.Changes of theses objects (creation,update,deletion)are induced by an invoker.Responsibility of the observer is the detection of changes of single objects or in the object repositories.For the observer change detection can be an active task or it is passively informed by the invoker.Any change is an event.A detailed de?nition of the term event will be given in Section4.1. Events are reported as materialized event messages to the?lter.The?lter has knowledge of the client’s pro?les and compares the event with the query part of the pro?les.If a pro?le and event match,the?lter delivers the event message to the noti?er.For the de-tection of event patterns,events are stored in the event repository.The noti?er in turn checks the schedule part of the pro?le.The event messages are buffered until the noti?ca-tions become due,they are then edited according to the format speci?ed by the client and delivered.The buffering is also needed for the noti?cation of of?ine clients to guarantee delivery.The client’s pro?les contain information about the events the client is interested in,a schedule,a noti?cation protocol,and a noti?cation format.A detailed description of the pro?le structure is given in Section4.1.For scalability and reliability the com-ponents of the alerting service can be duplicated.While invoker and object repository usually reside at the supplier’s side,not all information suppliers implement an observer. An alerting service that covers this type of suppliers could implement an observer as a wrapper for each supplier.The observer is enforced to keep various information on the repository if it is not noti?ed by the invoker and the supplier’s interface does not offer a search for changes since a speci?ed date.Alternatively,the observer can be moved to the supplier’s side and perform its tasks as an agent of the alerting service there.

4Uni?ed Event Model

In this section,we introduce our event-based model for alerting services.First,we de?ne the terms used within the model.Then,we formally describe the tasks of an alerting

service.Due to space limitations the event model is presented in a shortened version.An

extended version with all details can be found in[10].

4.1Terms and De?nitions

Object In correspondence to other models,we use objects to encapsulate the functional-

ity of model participants.In our model,an object can be any logical entity residing on a

hardware component within a network.Hardware and human beings can also participate but are represented by the software-based proxies.Each object is uniquely identi?able;for

simplicity reasons,we refer to the identi?er as a handle(e.g.,a URL).Considerations of

a naming model for alerting services can be found in[15].The objects,that are offered by suppliers,such as journals or news-pages,we call objects of interest.Objects have a state. The state of an object is the value of its attributes.A set of objects offered by a supplier is referred to as repository.A supplier can offer one or more repositories.Since repositories can also be seen as objects of interest,we consider a hierarchy of objects,whereas the items within the repositories are called information https://www.wendangku.net/doc/139090467.html,rmation objects can also be composed of other objects,e.g.,journals consist of articles.Therefore,objects need to carry information about their position within the hierarchy.

Event Based on the scenarios,we get a set of possible events regarding information ob-

jects:A new information object appears;existing information objects are changed;exist-

ing information objects are deleted;for a certain interval of time the information object remains unchanged.Similar to the model used for Event Action Systems[11]we divide events into two classes:time events and object events.Time events involve clock times, dates,and time intervals.Object events involve changes of non-temporal objects.We ad-ditionally distinguish active and passive events.Active events are state transitions of the repository at a particular time;they are observer-independent.State transitions can be ac-tions such as insertion,deletion,or change of a data-object.In the context of databases,as in digital libraries,the notion of state transition is in close relation to integrity constraints. Each transaction on the database underlies several constraints(e.g.,the key of a tuple has to be unique)and the operations are accepted only if the constraints are ful?lled.Allowed operations transfer the database from a valid state to another valid state.This process is called a state transition.As?nal consequence,both constraints and given set of values ensure an invariant state space.A state transition of a particular information object occurs if its attribute values are changed.Passive events involve counters and object properties at a speci?ed time.They have to be observed.Passive events model the fact that for a given time interval an object did not change.Examples are also given in Section2.

Pro?le A pro?le is the formally de?ned information need of a client.Each pro?le con-sists of two parts,a description of events the client is interested in(query-pro?le)and the conditions for the noti?cation(meta-pro?le).

Query-pro?le:In addition to primitive events(time and object events),they can spec-ify event patterns.Event patterns are Boolean combinations of events.For time events, we distinguish between points(),intervals(,,or)and frequencies(e.g.,weekly)in time(absolute).Time events can also be given in relation to another event,e.g.,“X weeks after the conference”(relative)or by using combina-tions.For time events,client and server need to de?ne a reference(e.g.,a common time zone).Passive events need to specify the objects and their attributes(see active events), and constraints as time or counters.For active events,clients have to de?ne the objects and the type of state transition to be observed on the object and possibly further attribute values they are interested in.Additionally,the repository of the objects has to be de?ned. Identi?cation of objects can be done by giving(1)the object handles,(2)metadata about

the objects,or(3)values of attributes of the objects.For example,the subscription to

subject-based Internet-channels is covered by(2).For composed objects,the level of the

concerned attribute within the hierarchy should also be given.Possible state transitions are the occurrence of a new object,the change of an object,or the removal of an object.

The change of an object can concern the structure(changing set of attributes,changing

range of attributes),or the values of the attributes.Additionally,clients can be interested in the changing number of values,or in different changes of the value itself.

The following items have to be de?ned within a meta-pro?le:

1.content of noti?cation(e.g.,object-handle,object itself,information about the ob-

ject/event and/or their numbers),

2.structure of noti?cation(number of events reported in the message,instructions for

the merging of noti?cations,ranking mechanism),

3.noti?cation protocol(e.g.,e-mail,desktop-icon,download),

4.time-policy for event detection(frequency of observations),

5.time-policy for noti?cation such as scheduled(e.g.,daily)or event-dependent(e.g.,

on events)or depending on event-attributes(“X weeks before the conference”). Noti?cation A noti?cation is a message reporting about events.Clients are noti?ed ac-cording to the time-policy given in their pro?les.Noti?cations created by observers have to be evaluated to discover patterns or duplicates.Before sending noti?cations,depend-ing on the pro?le,they have to be edited(e.g.,duplicate removal,merging,formating)in order to ensure that clients get only one noti?cation at the time.

4.2Model

The clients of an alerting service get information about the possible pro?le types from the service.Suppliers inform the service(and so the clients)about possible events by means of advertisements.An alert relation describes a connection between repositories of information objects,clients,and events the client wants to get noti?ed about.The alert relation is therefore a relation of a set of repositories,a set of clients,and a set of pro?les:Clients may register or unregister for certain events happening on certain repositories,for instance by subscribing to an event channel,such as CDF channels.The corresponding tuples,where denotes the repository, the client,and the pro?le regarding an event on,are inserted into,or deleted from,the relation.An event channel is a projection of the alert relation onto the repositories and the pro?les:.Here,we employ the notion of the relational algebra.Within a projection duplicate tuples are deleted.According to this model,a CORBA channel is only a communication medium and not covered by the de?nition of a channel given above.Another conclusion is,that clients that are interested in the same events at the same repository are subscribed for the same event channel,as in CDF channels or mailing lists.Events can happen at any time,they are caused by invokers that perform actions on the repository.Let be the time a state transition in repository has been caused by an invoker.An observer can learn of events in two ways.Either an observer is noti?ed by the invoker at time.Or the observer proceeds according to a time schedule

The observer registers all state changes on in the interval at time.The observer creates a message reporting the occurrence of the event and forwards it to the?lter.The pro?le?lter compares the reported events to the pro?les.With Carzaniga[2],denotes that an event matches a pro?le. Noti?cations to the following clients must be produced:, where is the set of alert relations affected by events

in at.A similar sequence is conceivable for passive events,as well as for the subsequent handling of event patterns and noti?cations.For the complete formalism, again,we have to refer to the extended paper version[10].

Several conclusions can be drawn from the model:The observers either have to be informed by the invokers or they have to be aware of the state of the repository(and the objects contained in the repository).In the latter case,observers,therefore,need to be initialized with the states of all existing objects in the repository.They can only detect changes with frequencies less or equal to the observation frequency.Otherwise,observers can miss events within their observation interval.If two events regarding the same object happen within the same observation interval,these events can weaken or intensify each other.For example,if the events that a value of an attribute increases and decreases hap-pen shortly one after another,these two events neutralize each other.For passive events,?lters initially have to know about the existence of objects,and,therefore,they have to be initialized with all existing objects.For the recognition of changed objects,different update strategies have to be considered(versions,in-place-update and shadow-update, see[5]).

5Mediating Alerting Service

In this section,we motivate and propose the use of a mediating alerting service.Consider the application domain of a digital library.For full coverage of scienti?c publications, users have to register at a variety of suppliers(cardinality),some even unknown to the user,with different interfaces for pro?le de?nition.Noti?cation format and protocol are heterogeneous,and many suppliers do not offer an alerting service.In addition,the noti?cations of different providers cannot be combined.As solution to the problems men-tioned above and pointed out in previous sections,and as an implementation of both the architectural and the event model,we propose a Mediating Alerting Service(MediAS).

In MediAS,multiple alerting services cooperate in a hierarchical and parallel manner. That means that alerting services are clients(or suppliers)for other alerting services.An alerting service can also cover multiple suppliers employing multiple observers.In turn, one observer can deliver event messages to multiple?lters.MediAS integrates the view to the information suppliers.Its observers serve as wrappers for the suppliers’interfaces. For suppliers that implement their own alerting services the observer acts as a client and is noti?ed of all changes in the suppliers’repositories.Other suppliers are queried regu-larly by the observer that wraps the suppliers’interfaces.Pro?les are stored in MediAS’repository.If pro?les of different clients are overlapping(as it is expected in a digital li-brary environment,e.g.,pro?les owned by library users of a working group or university department),several instances of MediAS can cooperate hierarchically,which improves scalability.A MediAS which is the client of a different MediAS submits an integration of its pro?les to its supplier.That ensures that the client MediAS will be noti?ed of all information objects its clients are interested in.

Problems arise when an alerting service is noti?ed by other alerting services whose coverages are overlapping.It can happen that noti?cations of the same event are delivered more than once.The MediAS must take this into account and?lter out duplicate events.

A similar problem can be caused by observers covering the same repository or suppliers providing similar objects(e.g.,two digital libraries that offer the same journals).In addi-tion to the problems that are well examined in the area of non-sequential processing when having parallel tasks,the duplication of the event repository forces replication to ensure reliable detection of event patterns.

6Related Work

Event services and event action systems are related systems to be considered for the def-inition of model and architecture.Event services support the asynchronous message ex-change between objects.They depend on an event-based infrastructure(such as JEDI[6]). Examples are event noti?cation services(such as SIENA[3,2],SIFT[17],or the CORBA Event Service[14]).Alerting aervices can be built upon event services.This is especially useful in the handling of asynchronous events.There is a class of infrastructures that we do not consider here.These infrastructures do not realize a noti?cation service,though they are published as such,e.g.,the Java Distributed Event Speci?cation.An investigation of these frameworks can be found,e.g.,in[2].Also,we do not consider local event-based procedures in operating systems,such as IPCs and interrupt handling.

Event Action Systems are software systems in which events occurring within the sys-tem trigger actions.The reaction is performed according to action speci?cations de?ned by the users.The triggered actions may generate other events,which trigger other actions, and so on.The actions are,in contrast to common event-based infrastructures,relevant to human beings rather than noti?cations to other software components[2].The alert-ing services considered here are closer related to event-action systems than to common event-based infrastructures.An example of an event-action system is Yeast[11].

Active databases[9,4]can serve as triggers for alerting services.The underlying model is based on ECA-rules(Event-Condition-Action),that can also be applied to alert-ing services,where the conditions are de?ned in the pro?les and the action is sending the noti?cation.They cover the repository,the observer,and the?lter facility,but the complex handling of scheduled noti?cation pro?les are beyond the means of active databases.A system-independent design framework for scalable event noti?cation services has been proposed by Rosenblum and Wolf[15].We have shown the restrictions of this model in Section2.Due to its independence of specialized applications,it serves as a basis for our model for alerting services.

The Simple Digital Library Interoperability Protocol(SDLIP)from Stanford Univer-sity[16]is designed for distributed information retrieval in a digital library environment. Alerting on new or changed objects is not focus of SDLIP.However,when starting an asynchronous search,a client can specify the address of an object that implements an in-terface which will receive the delivery.The server would submit new documents to that “receiver”.One only needs to make the query long-lasting.In our terminology a query is a query-pro?le.

7Conclusion and Outlook

In this paper,a general structure and architecture for an integrative and scalable alerting service has been de?ned.We proposed a general event-based model for alerting services. Moreover the paper introduced a general structure for pro?le de?nitions for noti?cation services and motivated the use of a Mediating Alerting Service(MediAS).

Expanded event-based model:Based on the requirements of scenarios for alerting services,we introduced an expanded model for Internet-scale alerting services.The mod-els covers various scenarios,whereas existing models for noti?cation services apply only for a restricted range of scenarios(as shown in Section2).The model offers a general terminology for the description of alerting service components.It extends the notion of events to cover states of non-existing objects.In addition,it introduces the notion of com-posed objects and the notion of passive events.It can be used as a basis for the comparison of different systems.

General pro?le structure:In this paper,we de?ned the general structure of pro?les independently from the pro?le de?nition language.Several languages and protocols have been proposed[1,16].One of our next steps will be the de?nition of a general pro?le de?nition language for bibliographic alerting services.

MediAS:We proposed the use of a mediating alerting service to overcome the draw-backs of the various existing implementations.Disadvantages of existing alerting services are,among others,the need for the clients to de?ne their pro?le many times in many dif-ferent ways,duplicate noti?cations cannot be avoided,and event patterns can be recog-nized only in a very restricted manner.In a MediAS,parts of the service can work dis-tributed in hierarchical or parallel order.Further research will support the decision which part of the service should be duplicated and in which order the cooperating services are to be arranged.MediAS is under development at the Freie Universit¨a t Berlin.

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美国常青藤名校的由来

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工业互联网发展综述报告

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工业互联网发展综述 (最新版报告请登陆我司官方网站联系) 公司网址: https://www.wendangku.net/doc/139090467.html, 1

目录 工业互联网发展综述 (4) 第一节工业互联网的相关概述 (4) 一、工业互联网的定义内涵 (4) 二、工业互联网的功能作用 (5) “互联网+”与供给侧结构性改革 (6) 1.互联网创新发展引发变革 (8) 2.互联网创新发展案例解析 (11) 3.利用互联网工具实现“价值流” (16) 三、工业互联网的五大应用 (17) 四、互联网对制造业的影响 (17) 第二节工业互联网相关概念分析 (19) 一、工业4.0 (19) 二、两化融合 (21) 三、中国制造2025 (22) 四、相关概念比较 (24) 第三节工业互联网的构成要素分析 (28) 一、智能设备 (28) 二、智能系统 (29) 三、智能决策 (30) 3)推理机 (32) 四、要素整合 (32) 2.产品性能改善模式 (33) 3.顾客培训模式 (34) 4.产品功能拓展模式 (34) 2

第四节实现工业互联网的关键要素分析 (35) 一、实现工业互联网的技术要素 (35) 二、实现工业互联网的管理要素 (47) 三、工业互联网的关键成功要素 (50) 3

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