Messagebased MVC Architecture for Distributed and Desktop Applications

Message-based MVC Architecture for Distributed and Desktop Applications Xiaohong Qiu Department of Electrical Engineering and Computer Science Syracuse University March 2, 2005 Xiaohong Qiu 1

Presentation Topics Background for My Research Architecture of Message-based MVC SVG Experiments Performance Analysis Collaboration Paradigms Conclusion and Future work March 2, 2005 Xiaohong Qiu 2

Background General area is technology support for Synchronous and Asynchronous Resource Sharing. § e-learning § e-science § e-business § e-entertainment (e. g. video/audio conferencing) (e. g. large-scale distributed computing) (e. g. virtual organizations) (e. g. online game) Grids manage and share (typically asynchronously) resources (people, computers, data, applications etc. ) or distributed services in a centralized fashion. Web Services define loosely coupled software components across internet interacting with messages. Peer-to-Peer Grids link services, resources and clients in dynamic decentralized fashion. The system consists of a sea of message-based Services (e. g. shared SVG as a Web Service) Services linked by publish/subscribe messaging infrastructure (e. g. Narada. Brokering) March 2, 2005 Xiaohong Qiu 3

Classic Grid Architecture Resources Netsolve Security Computing Collaboration Content Access Compositio n Middle Tier Brokers Service Providers Middle Tier becomes Web Services Clients March 2, 2005 A centralized organization Xiaohong Qiu 4

Peer to Peer Grids User Facing Web Service Interfaces Peers Brokers Event/Messag e Brokers Peers March 2, 2005 Brokers Service Facing Web Service Interfaces A democratic organization Xiaohong Qiu 5

Research on a generic model of building applications Application domains Distributed (Web) § Service Oriented Architecture and Web Services Desktop (client) § Model-View-Controller (MVC) paradigm Internet collaboration § Hierarchical Web Service pipeline model Motivations CPU speed (Moore’s law) and network bandwidth (Gilder’s law) continue to improve bring fundamental changes Internet and Web technologies have evolved into a global information infrastructure for sharing of resources Applications getting increasingly sophisticated § Internet collaboration enabling virtual enterprises § large-scale distributed computing Requires new application architecture that is adaptable to fast technology changes with properties March 2, 2005 Xiaohong Qiu 6

Summary of the situation The Internet has evolved into stability § § TCP/IP network stack dominating the communication protocol domain; IP forms the low-level sphere surrounding hardware network core Construction of distributed operating system over the Internet is not completed § § It keeps adding new functionalities to the general purpose platform One current effort focuses on building of messaging infrastructure tailored for disparate applications Evolution of application architectures § § § client-server model Multi-tier (e. g. three-tier) model A variety of distributed model (e. g. Java RMI, CORBA, COM/DCOM, J 2 EE, . NET) Grids Peer-to-peer Web Services and SOA Web application deployment shows diverse directions but have common features § § § User interfaces Services for the sharing of information and resources (e. g. through unicast and multicast of group communication) In the most general sense, collaboration is the core problem and service of Web applications, although “collaboration” usually refers to system with real-time synchronous and compelling time constraints Next generation of Web client should enable pervasive accessibility § § Ubiquitous availability to clients fro heterogeneous platforms (e. g. Windows, Linux, Unix, and Palm. OS) Uniform Web interface that provides a platform with aggregation of multiple services March 2, 2005 Xiaohong Qiu 7

Architecture of network system March 2, 2005 Xiaohong Qiu 8

Our approach Explicit messaging replacing implicit messaging of traditional event listener paradigms Key idea is to generalize MVC with model and view communicating by messages with the messaging providing control mechanism Message-based MVC (M-MVC) paradigm integrates distributed, Web, and desktop applications SMMV and MMMV for general collaboration paradigms Prototyping monolithic SVG collaborations § § Shared SVG browser Share online chess game Decomposed SVG experiments and detailed performance measurements to test viability of loose coupling services message-based Specifically investigate § § M-MVC and MVC M-MVC and Web Applications (Services) M-MVC and collaboration (SMMV and MMMV paradigms) M-MVC and messaging infrastructure (Narada. Brokering middleware) March 2, 2005 Xiaohong Qiu 9

Related Technologies Batik SVG browser (an open source project from Apache that supports SVG 1. 0) § A presentation style application is representative and complex in nature (we experiments with multiplayer-online game with high interactivity and compelling time constraints) § Similar applications includes Microsoft Power. Point, Adobe Illustrator, Macromedia Flash SVG (W 3 C specifications for Scalable Vector Graphics) § A language for describing 2 D vector and mixed vector/raster graphics in XML. DOM (W 3 C specifications for Document Object Model) § Programmatic interfaces for access and manipulate structured document object § All modern browsers (approximately) support the W 3 C DOM § DOM event model specifies event semantics and how to register event handlers and describe event flow through a tree structure March 2, 2005 Xiaohong Qiu 10

Model-View-Controller (MVC) model Model Controller Mouse event Keyboard events March 2, 2005 View Xiaohong Qiu Display 11

Double-linked multiple-stage Web Services pipeline model of Web applications Object Or WS March 2, 2005 Object’ Or WS’ Object’’ Or WS’’ Xiaohong Qiu Object Or View Object Or Display 12

Architecture of Message-based MVC M-MVC is a general approach for building applications with a message-based paradigm It emphasizes a universal modularized service model with messaging linkage Converges desktop application, Web application, and Internet collaboration MVC and Web Services are fundamental architectures for desktop and Web applications Web Service pipeline model provides the general collaboration architecture for distributed applications M-MVC is a uniform architecture integrating the above models M-MVC allows automatic collaboration, which simplifies the architecture design March 2, 2005 Xiaohong Qiu 13

Message-based MVC model March 2, 2005 Xiaohong Qiu 14

A comparison of MVC and pipeline model in a case of SVG application Model View Controller Decomposition of SVG Browser Semantic Model Events as messages Rendering as messages Controller High Level UI View Input port Output port Events as messages Rendering as messages Raw UI Display a. MVC Model Messages contain control information b. Three-stage pipeline Reformulation of SVG to message-based MVC in a Web Service Model March 2, 2005 Xiaohong Qiu 15

Monolithic SVG Experiments Collaborative SVG Browser Teacher-Students scenario Static Shared SVG contents Dynamic Share SVG contents § Hyperlink § Interactivity and animation (Java. Script binding) Collaborative SVG Chess game Two players-multiple observers scenario Complex interactivity with game intelligence March 2, 2005 Xiaohong Qiu 16

Collaborative SVG Chess Game Players March 2, 2005 Xiaohong Qiu Observers 17

Making SVG collaborative by sharing of intercepted events via messaging broker with Publish/Subscribe scheme Set up an event class (topic) Publish an event e ourc Res Facing Subscribe to the topic Broker to collaborative clients Port Facing e urc eso R Model Java. Script SVG DOM Facing Output port Rendering as messages Facing Application as Web Service User Port User rt Po Facing Input port Output port Rendering as messages Input port Event as messages GVT Renderer View Participating client Master client March 2, 2005 Xiaohong Qiu 18

Collaborative SVG Event processing chart Raw UI events (e. g. Mouse and key events) High Level UI events (e. g. SVG/DOM events) Semantic events Collaborative events (e. g. Application events such as “capture” in chess game) (e. g. Master Events which has context information of collaboration and information from previous stages) Classes of Events in SVG Around 60 detailed Events March 2, 2005 Xiaohong Qiu 19

Architecture of collaborative SVG browser on PC Data to other clients R Master client SVG browser 1 Session control Server Control to/from all SVG browsers in the collaborative session Control to/from XGSP I Data from master client R O Other client SVG browser 2 F Control to/from XGSP I Data from master client R O • • • Event (Message) Service Infrastructure XGSP Narada. Brokering F Other client SVG browser n F Control to/from XGSP I O This is monolithic SVG example Shows potential use of XGSP from Global. MMCS project to collaborative applications March 2, control 2005 Xiaohong Qiu 20

Architecture of multiplayer game with SVG Control to/from SVG WS 1, 2, …, n Rendering to SVG display 2 SVG WS n Internet Game Control to/from SVG display 1 Rendering from SVG WS 2 SVG display 2 Control to/from SVG display 2 • • • Control to/from XGSP, SVG display 2 Narada. Brokering SVG WS 1 Event (Message) Service Infrastructure XGSP Session control Server SVG display n SVG WS 1, 2, …, n This is decomposed SVG example March 2, 2005 Xiaohong Qiu 21

Decomposed SVG Experiments Convert a standalone application into distributed system by splitting Model and View. Where to split? How difficult to split? Is performance acceptable? March 2, 2005 Xiaohong Qiu 22

Three MVC approaches based on different communication mechanism and interactive pattern between model and view Broker View Control Pub/Sub Model a) classic (method-based) March 2, 2005 View Messages Model b) request/response (method-based or message-based) Xiaohong Qiu View Model c) publish/subscribe (message-based) 23

Method-based MVC vs. message-based MVC ic) u et n pa t en ev top s( Broker s cla S A register call back method B A nt ve ne ss cla Su b sc Se n de ha s bli pu rib e to ev en t cla ss ve nt B invoke call back method with event message based method based What we are doing when we move from classic MVC (monolithic model) to M-MVC (decomposed model) March 2, 2005 Xiaohong Qiu 24

Decomposition of SVG browser into stages of pipeline Decomposition Point View GVT tree’ Output (Renderer) (Graphics. Node changes ) Model DOM tree’ (after mutation) SVG parser (update image buffer) Java. Script GVT tree Input (UI events) (Graphics. Node events) DOM tree (before mutation) (DOM events) (access and manipulate DOM element) (e. g. Mouse and key events) We analyzed flow of events in Batik to see where best to decompose into Model and View. There was no clear separation in original code March 2, 2005 Xiaohong Qiu 25

Important principals One should split at points where the original method based linkage involved serializable Java objects. Serialization is needed before the method arguments can be transported and this is familiar from Java RMI. “Spaghetti” classes implied that additional state information would need to be transmitted if we split at points where classes spanned interfaces from different modules. Batik often involved large classes that implemented many different interfaces. These interfaces often came from different parts of the program and crossed the possible stages mentioned above. Message-based MVC paradigm tends to force a more restrictive programming model All data are shared explicitly and not implicitly via interfaces crossing splitting lines. March 2, 2005 Xiaohong Qiu 26

Implementation of Decomposed SVG Browser March 2, 2005 Xiaohong Qiu 27

Implicit State Broker su Broker bs h lis ub p cr ibe se n nt View sc rib h s bli pu de ve A A su b B se nd ev en t A e B Shared state Separated component/service model Conventional shared state model Implicit state needs to be serialized and integrated into the service model. March 2, 2005 Xiaohong Qiu 28

The changes bring up issues that cause a challenge to the system Timing becomes a compelling issue With the separation of client and Web Service server, original assumption and design principle break The time scope drastically increases from tens of microsecond level (e. g. a Java method call) to a few milliseconds level (network latency plus system overhead). Object serialization is a must have toolkit Messages, as a linkage vehicle, contains component information from both sides and keep context same Synchronization is a factor to consider for context consistency March 2, 2005 Xiaohong Qiu 29

Performance and Analysis Experiments with decomposed Batik SVG browser based on MMVC model. The decomposed Model and View interact with event-based message via messaging broker provided by Narada. Brokering. Many variables are set for testing scenarios, which including locations of Model, View and event broker runtime environment (e. g. OS and network connection) Analysis Relationship of user interactions and structure of mouse events Performance of fine-grained mouse events Factors (network latency and computation overhead, thread scheduling etc. ) that affect overall system performance March 2, 2005 Xiaohong Qiu 30

Definition of typical events of distributed applications Applications Macro. Event Micro. Event writing an email a key stroke writing one line of message a key stroke downloading a file n/a Distributed Simulation messaging passing (exchanging a message between components) n/a Internet TV Broadcast (Streaming Media) one-way buffering inter-frame delay multi-way buffering (interactivity) inter-frame delay loading a new URL a mouse click on a hyperlink drawing a new graphics component (e. g. a rectangle, a line, a path) a mouse movement moving a piece a mouse movement updating a region held in a single node message passing (exchanging a message between components) Email Instant Messenger Shared File System (P 2 P) Video/Audio Conferencing Shared Browser Shared Whiteboard Multiplayer Online Game (e. g. chess) Parallel Computing March 2, 2005 Xiaohong Qiu 31

Summary of typical distributed applications and characteristics Content Application type avg. min level of interactivity Rendering complexity network connectivity features Macro Event Micro Event bandwidth latency tolerance level reliabili ty connectivit y type Email text, image low min milli sec low minutes or above no point-topoint Instant Messenger text low sec milli sec low second no multicast Shared File System (P 2 P) byte stream n/a min n/a high minutes or above yes multicast Distributed Simulation byte message n/a sec n/a high 100’s millisecs yes point-topoint Internet TV/Broadcast image, sound high sec . 033 sec high second no broadcast Video/Audio Conferencing image, sound high sec . 033 sec high 100’s millisecs no multicast Shared Whiteboard text, image high sec milli sec low 10’s millisecs yes multicast Multiplayer Online Game text, image, sound high sec milli sec low 10’s millisecs yes multicast Parallel Computing byte message n/a large > 10 microsec high 10 microsecs yes point-topoint March 2, 2005 Xiaohong Qiu 32

Performance Testing and timing points Notification service (Narada. Brokering) View (Client) T 4 Output (Rendering) GVT tree’ T 3 DOM tree’ (mirrored) T 2 Event Processor Model (Service) Event Processor T 1 DOM tree’ (after mutation) Java. Script Broker Input (UI events) GVT tree DOM tree (mirrored) T 0 Event Processor T 0 Machine A Machine B DOM tree (before mutation) Machine C § T 0: A given user event such as a mouse click that is sent from View to Model. § T 1: A given user event such as a mouse click can generate multiple associated DOM change events transmitted from the Model to the View. T 1 is the arrival time at the View of the first of these. § T 2: This is the arrival of the last of these events from the Model and the start of the processing of the set of events in the GVT tree § T 3: This is the start of the rendering stage § T 4: This is the end of the rendering stage March 2, 2005 Xiaohong Qiu 33

Average Performance of Mouse Events Mousedown events Test scenarios Average of all mouse events (mousedown, mousemove, and mouseup) First return – Send time: T 1 -T 0 (milliseconds) Last return – Send time: T’ 1 T 0 (milliseconds) End Rendering T 4 -T 0 (microseconds) No distance NB location mean ± error Stdd ev mean ± error stdde v mean ± error stdd ev mean ± error stddev 1 Switch connects Desktop server 33. 6 ± 3. 0 14. 8 37. 9 ± 2. 1 18. 7 48. 9± 2. 7 23. 7 294. 0± 20. 0 173. 0 2 Switch connects Highend Desktop server 18. 0 ± 0. 57 2. 8 18. 9 ± 0. 89 9. 07 31. 0 ± 1. 7 17. 6 123. 0 ± 8. 9 91. 2 3 Office area Linux server 14. 9 ± 0. 65 2. 8 21. 0 ± 1. 3 10. 2 43. 9 ± 2. 6 20. 5 414. 0 ± 24. 0 185. 0 4 Within. City (Campus area) Linux cluster node server 20. 0 ± 1. 1 4. 8 29. 7 ± 1. 5 13. 6 49. 5 ± 3. 0 26. 3 334. 0 ± 22. 0 194. 0 5 Inter-City Solaris server 17. 0 ± 0. 91 4. 3 24. 8 ± 1. 6 12. 8 48. 4 ± 3. 0 23. 3 404. 0 ± 20. 0 160. 0 6 Inter-City Solaris server 20. 0 ± 1. 3 6. 4 29. 6 ± 1. 7 15. 3 50. 5 ± 3. 4 26. 0 337. 0 ± 22. 0 189. 0 34

Immediate bouncing back event Bouncing back event Test scenarios Average of all mouse events (mousedown, mousemove, and mouseup) Bounce back – Send time: (milliseconds) First return – Send time: T 1 -T 0 (milliseconds) Last return – Send time: T’ 1 T 0 (milliseconds) End Rendering T 4 -T 0 (milliseconds) mean ± error stdd ev mean ± error stddev No distance NB location mean ± error Stdde v mean ± error stdd ev 1 Switch connects Desktop server 36. 8 ± 2. 7 19. 0 52. 1 ± 2. 8 19. 4 68. 0 ± 3. 7 25. 9 405. 0 ± 23. 0 159. 0 2 Switch connects High-end Desktop server 20. 6 ± 1. 3 12. 3 29. 5 ± 1. 5 13. 8 49. 5 ± 3. 1 29. 4 158. 0 ± 12. 0 109. 0 3 Office area Linux server 24. 3 ± 1. 5 11. 0 36. 3 ± 1. 9 14. 2 54. 2 ± 2. 9 21. 9 364. 0 ± 22. 0 166. 0 4 Within-City (Campus area) Linux cluster node server 15. 4 ± 1. 1 7. 6 26. 9 ± 1. 6 11. 6 46. 7 ± 2. 9 20. 6 329. 0 ± 25. 0 179. 0 5 Inter-City Solaris server 18. 1 ± 1. 3 8. 8 31. 8 ± 2. 2 14. 5 54. 6 ± 4. 9 32. 8 351. 0 ± 27. 0 179. 0 6 Inter-City Solaris server 21. 7 ± 1. 4 9. 8 37. 8 ± 2. 7 19. 3 55. 6 ± 3. 4 23. 6 364. 0 ± 25. 0 176. 0 35

Basic NB performance in 2 hops and 4 hops Test 2 hops (View – Broker – View) 4 hops (View – Broker – Model – Broker – View) milliseconds No milliseconds mean ± error stddev 1 7. 65 ± 0. 61 3. 78 13. 4 ± 0. 98 6. 07 2 4. 46 ± 0. 41 2. 53 11. 4 ± 0. 66 4. 09 3 9. 16 ± 0. 60 3. 69 16. 9 ± 0. 79 4. 85 4 7. 89 ± 0. 61 3. 76 14. 1 ± 1. 1 6. 95 5 7. 96 ± 0. 60 3. 68 14. 0 ± 0. 74 4. 54 6 7. 96 ± 0. 60 3. 67 16. 8 ± 0. 72 4. 47 March 2, 2005 Xiaohong Qiu 36

Observations I This client to server and back transit time is only 20% of the total processing time in the local examples. The overhead of the Web service decomposition is not directly measured in tests shown these tables The changes in T 1 -T 0 in each row reflect the different network transit times as we move the server from local to organization locations. This overhead of Narada. Brokering itself is 5 -15 milliseconds depending on the operating mode of the Broker in simple stand-alone measurements. It consists forming message objects, serialization and network transit time with four hops (client to broker, broker to server, server to broker, broker to client). The contribution of Narada. Brokering to T 1 -T 0 is about 30 milliseconds in preliminary measurements due to the extra thread scheduling inside the operating system and interfacing with complex SVG application. We expect the main impact to be the algorithmic effect of breaking the code into two, the network and broker overhead, thread scheduling from OS. March 2, 2005 Xiaohong Qiu 37

Comparison of performance results to highlight the importance of the client Events per 5 ms bin All Events Mousedown Mouseup Mousemove Time T 1 -T 0 milliseconds NB on Model; Model and View on two desktop 1. 5 Ghz PCs; local switch network connection. March 2, 2005 NB on View; Model and View on two desktop PCs with “high-end” graphics Dell (3 Ghz Pentium) for View; 1. 5 Ghz Dell. Qiu for model; local switch network 38 Xiaohong connection.

Comparison of performance results with Local and remote NB locations Events per 5 ms bin All Events Mousedown Mouseup Mousemove Time T 1 -T 0 milliseconds NB on 8 -processor Solaris server NB on local 2 -processor Linux ripvanwinkle; Model and View on server; Model and View on two 1. 5 Ghz desktop PCs; remote Ghz desktop PCs; local switch network connection through routers. network connection. March 2, 2005 Xiaohong Qiu 39

Observations II One usually gets better performance moving the Narada. Brokering broker off the desktops; the better broker performance (there are no scheduling overheads) outweighs the increasing network overhead. The performance of NB on desktop server is not as good as that in fig 7. 5 with NB on “gridfarm 1” machine running Linux server. The results in fig. 7. 7 (“ripvanwinkle” with 100 miles round trip distance) generates similar pattern as in fig. 7. 5 (local connection) except with a slightly lower performance corresponding to the greater network delay for “ripvanwinkle”. Our results show that use of windows desktops to run Narada. Brokering is never good even when one uses a machine running the model and view with no network delay. Windows scheduling introduces delays of 10 -20 millisecond overhead that is much larger than the 1 -2 millisecond delays coming from network transit within the extended university campus and the similar intrinsic processing time needed by Narada. Brokering on a clean Linux/UNIX machine. We have not looked at a Windows server (which has a different scheduling algorithm from desktop Windows) for Narada. Brokering; this could be better than the desktop Windows used in tests. March 2, 2005 Xiaohong Qiu 40

This illustrates that this type of HPC engine can be used in Web Server mode with each node running different services. We are only using one node and so this is not a parallel computing application NB on one node of HPC Linux cluster; Model and View on two desktop PCs; routers network connection. A few events with. Xiaohong timing Qiu greater than 100 milliseconds are not March 2, 2005 41 shown on the plot

Comparison of performance results on 2 remote NB locations Events per 5 ms bin All Events Mousedown Mouseup Mousemove Time T 1 -T 0 milliseconds NB on 8 -processor Solaris server complexity; Model and View on two desktop PCs; remote network March 2, 2005 connection through routers. NB on 8 -processor Solaris server ripvanwinkle; Model and View on two desktop PCs; remote network Xiaohong Qiu 42 connection through routers.

Mean Mouseup Mean Mousemove Events Per 0. 5 ms Mean Mousedown 15 runs each split over 3 days Mean ms March 2, 2005 NB on Ripvanwinkle NB on View NB on Model Xiaohong Qiu 43

Standard Deviation Mouseup Events Per 0. 5 ms Standard Deviation Mousemove Standard Deviation Mousedown 15 runs each split over 3 days Mean ms March 2, 2005 NB on Ripvanwinkle NB on View NB on Model Xiaohong Qiu 44

Observations III Ripvanwinkle ALWAYS Better Means and Standard Deviations do not vary much from run to run Mouse Down has larger standard deviation when NB on Model Note Mouse Down has least model processing NB-Model and NB-View similar except for Mouse Down where NB-View better In an exploratory run with NB running over the local network on a Dell PC with Window XP (heavy loaded), we found very poor performance. For example, the mean of the mousedown event was 92 milliseconds compared to 16 milliseconds on ripvanwinkle March 2, 2005 Xiaohong Qiu 45

Summary of message-based MVC Provision of a universal paradigm with a service model converging desktop applications, Web applications, and Internet collaboration Web applications built on messages can achieve important features such as scalability The message-based approach is an indispensable part of the big picture of system design with a separate intermediate messaging layer Reduce deployment overhead of applications Increase portability of application by decoupling application architecture with underlying platforms It conforms to service oriented architecture with loosely coupled messages linkage, which we expect to have an increasingly important role for reusability, interoperability, and scalability March 2, 2005 Xiaohong Qiu 46

SMMV vs. MMMV as MVC interactive patterns Model 1 Model 2 Model m-1 Model m View 1 View 2 View n-1 View n Model View 1 View 2 View n-1 View n b) Multiple Model Multiple View a) Single Model Multiple View § SIMD– A single control unit dispatches instructions to each processing unit. § MIMD– Each processor is capable of executing a different program independent of the other processors. It enables asynchronous processing. § SMMV generalizes the concept of SIMD § MMMV generalizes the concept of MIMD § In practice, SMMV and MMMV patterns can be applied in both asynchronous and synchronous applications, thus form general collaboration paradigms. March 2, 2005 Xiaohong Qiu 47

Collaboration Paradigms Monolithic Collaboration All participating components are formed as replications of an existing application without explicit break up into a separate Model and View component as required by the Web service architecture. Works through interception of the events on a master application and allows messaging broker to multicast them to the collaborating clients. § CGL applications of Power. Point, Open. Office and data visualization Web Service Collaboration framework Shared input port ─ replicated Web Service § CGL applications including A/V conferencing, shared whiteboard, text chats and SVG chess Shared output port § CGL shared display application SMMV and MMMV collaboration model (integration of desktop and distributed models) SMMV ─ decomposed Model and View with multiple clients sharing a single Model component. § Instructor led learning MMMV ─ decomposed Model and View with multiple models each driving its own separate View. It enables ubiquity with the customization done from the Model at server side. – § Participatory learning March 2, 2005 Xiaohong Qiu 48

Monolithic collaboration Narada. Brokering SVG browser master client SVG browser master other client Identical programs receiving identical events Collaboration paradigms deployed with M-MVC model Narada. Brokering Model as Web Service Model as WS Broker Model as WS Narada. Brokering Broker View View master client other client other client March 2, 2005 SMMV MMMV Xiaohong Qiu 49

Summary of Contributions Proposing an “explicit Message-based MVC” paradigm (MMVC) as the general architecture of Web applications Demonstrating an approach of building “collaboration as a Web service” through monolithic SVG experiments. § As an example, we present architecture for three types of collaboration ─ monolithic, thin client, and interactive client. Bridging the gap between desktop and Web application by leveraging the existing desktop application with a Web service interface through “MMVC in a publish/subscribe scheme”. § As an experiment, we convert a desktop application into a distributed system by modifying the architecture from method-based MVC into message-based MVC. Proposing Multiple Model Multiple View and Single Model Multiple View collaboration as the general architecture of “collaboration as a Web service” model. Identifying some of the key factors that influence the performance of messagebased Web applications especially those with rich Web content and high client interactivity and complex rendering issues. March 2, 2005 Xiaohong Qiu 50

Questions Answered Can MVC be implemented in a message-based fashion? What principles are there to govern the decomposition of a given application into M-MVC components? What is the performance of the message-based MVC and what factors influence it? How does M-MVC depend on the operating system, the application, machines and network? What is the relationship of collaboration and Web services with M-MVC paradigm? What is the way to define state and state changes in collaborative applications? How easy is it to convert an existing application to message-based MVC? What are the architectural and implementation principles to be used in building applications from scratch in a message-based MVC paradigm? March 2, 2005 Xiaohong Qiu 51

Future Work Analyze performance in other cases (Linux clients, Windows servers) Optimize Performance with closer integration with Narada. Brokering and cleaner data structures What is best publish-subscribe architecture for M-MVC? Apply M-MVC to other applications (e. g. Open. Office) Use of Web Service specifications (WSRP, WS- Management) to define M-MVC Use of XGSP in Collaborative SMMV and MMMV March 2, 2005 Xiaohong Qiu 52

Reference Thesis for download http: //grids. ucs. indiana. edu/~xqiu/dissertation. html Thesis project http: //grids. ucs. indiana. edu/~xqiu/research. html Publications and Presentations http: //grids. ucs. indiana. edu/~xqiu/publication. html Narada. Brokering Open Source Messaging System http: //www. naradabrokering. org Information about Community Grids Lab project and publications http: //grids. ucs. indiana. edu/ptliupages/ March 2, 2005 Xiaohong Qiu 53