1. 1 AINA 2006 Wien, April 18-20 th 2006 DiVES: A DISTRIBUTED SUPPORT FOR NETWORKED VIRTUAL ENVIRONMENTS The IEEE 20th International Conference on Advanced Information Networking and Applications Antonio Bonotti, Luca Genovali, Laura Ricci Dipartimento di Informatica Università degli Studi di Pisa ricci @di.unipi.it

2. 2 AINA 2006 Wien, April 18-20 th 2006 PRESENTATION OUTLINE Distributed Virtual Environments: design choices DiVES (Distributed Virtual Environment Support): overall architecture DiVES communication supports: cell based vs. entity based routing Routing optimizations Experiments and Conclusions

3. 3 AINA 2006 Wien, April 18-20 th 2006 DISTRIBUTED VIRTUAL ENVIRONMENTS (DVE) Real-Time Distributed Virtual Environments : provide to geographically distributed end-users the illusion of being immersed in a unique shared virtual world real time interactions among users and/or among users and computer controlled entities Examples: distributed multiplayer games, military simulations Architectural models: central server, P2P, hybrid Multiplayer Games: a set of entities (avatars, monsters, tanks,…) populate a virtual world each entity communicates its state (change of position, colour), or virtual world modifications to other partecipants

4. 4 AINA 2006 Wien, April 18-20 th 2006 DVE: DESIGN CHALLANGES DVE applications raise many challanges mechanisms to guarantee the consistency of the virtual world synchronization, state replication real time requirements: the action performed by an entity must be visible to other entities within a bounded time scalability – consistency requires the exchange of a huge amount of information among end users – high bindwidth, CPU load – optimization required to minimize the exchanged information

5. 5 AINA 2006 Wien, April 18-20 th 2006 DVE: INTEREST MANAGEMENT Interest Management: reduce DVEs communication requirements. Area of Interest (IA) of an entity E = portion of the virtual world including entities that may interact with E – example: a player interacts with entities (players, monsters) located in its surrondings, e.g. in the same room. The definition of the IA of E depends upon the semantics of the application, e.g. the sight capability of E E is interested in receiving information from entities in its IA only Implementation: – Multicast groups – Publish-subscribe systems

6. 6 AINA 2006 Wien, April 18-20 th 2006 PUBLISH SUBSCRIBE SYSTEMS Support group communications Entities of the virtual world – deliver and publish events by notifications – express their interests in (pattern of) events by subscriptions (filters) Matching of subscriptions and notifications is implemented by a set of application level routers = brokers Broker Network = defines the broker interconnection structure Design choices – broker network topology – application level routing algorithms

7. 7 AINA 2006 Wien, April 18-20 th 2006 PUBLISH SUBSCRIBE SYSTEMS: FILTER BASED ROUTING example: the subscribed filter defines the area of interest of a player B1 B3 B4 B2 P1 F1 P1 10<x<20 20<y<30.... F2 P2 30<x<50 25<y<45. F1 F2 F1 B1 F2 B3 F1 B2 F2 B4 …. Area of Interest Routing table each subscription is flooded in the broker network notifications routing is guided by the subscriptions stored in the routing table P2 P1 P2

8. 8 AINA 2006 Wien, April 18-20 th 2006 DiVES: OVERALL ARCHITECTURE DiVES communication support is based on the publish-subscribe model DiVES overlay network =Acyclic P2P network of brokers – each player is connected to a single broker = terminal broker – internal brokers are connected to other brokers DiVES bootstrap: – a bootstrap broker BB can be located at a static IP address – BB manages a list L of the brokers currently available in the network – each broker/player entering a DiVES network connects to BB and receives L from BB chooses a single broker B in L and connects to B. B becomes the parent broker of BB.

9. 9 AINA 2006 Wien, April 18-20 th 2006 DiVES: OVERALL ARCHITECTURE The choice of the parent broker PB is guided by – number of connections opened by PB – latency estimated by ping DiVES defines a simple recovery mechanism Consistency: – local-lag is exploited to appoximate simultaneity of events dynamic adaptation of local lag to varying network conditions local lag value tailored to the communication group – dead reckoning

10. 10 AINA 2006 Wien, April 18-20 th 2006 DiVES PUBLISH SUBSCRIBE MODEL DiVES defines several routing algorithms Cell Based Routing – Coarse grain partition of the virtual world into a set af areas (cells) – Each area of interest is approximated by a set of cells Entity Based Routing – Finer grain area of interests: each filter corresponds to the area of interest of a player – generates a huge amount of filters. Several optimizations have been defined to reduce network traffic Approximated Area of Interest Advertisements Filter merging

11. 11 AINA 2006 Wien, April 18-20 th 2006 CELL BASED DiVES P the virtual world is partitioned into a set of cells Ip: each area of interest is included in a cell Filter = cell where P is located + surronding cells Filter Routing : P subscribes a filter when it enters a cell the filter is not modified as long as P moves within the same cell

12. 12 AINA 2006 Wien, April 18-20 th 2006 ENTITY BASED DiVES Filter = Area of interest of a player P each player notifies its position PO to the broker network the notification is delivered to each player whose area of interest includes PO P P1 P2 P3 P belongs to the areas of interests of P1,P2,P3 the movements of P are notified to P1,P2,P3 P1,P2,P3 do not belong to the area of interest of P

13. 13 AINA 2006 Wien, April 18-20 th 2006 ENTITY BASED DiVES: OPTIMIZATIONS Optimizations Goal: reduction of the network traffic due to filter propagation Predicted Notification Area (PNA) = Set of positions that can be reached by P in a time interval  t – starting from its current position – travelling along a straight line with a constant speed v Predicted Area of Interest (PAI) = Subspace of the virtual world including the area of interest corresponding to any point in the PNA Entity based routing optimization: – each player subscribes its PAI, rather than its exact area of interest Filter traffic can be tuned by defining a proper value of  t

14. 14 AINA 2006 Wien, April 18-20 th 2006 PREDICTED AREA OF INTEREST Y =Area of Interest Z = Predicted Notification Area (PNA) X = Predicted Area of Interest (PAI) P4 PNA B1 P1 B2 B3 B4 B5 … … P1 Y X B1 X B3 X … … … … … … … … … … P1 tt P3 P2

15. 15 AINA 2006 Wien, April 18-20 th 2006 ADVERTISEMENT BASED FILTER ROUTING Advertisement based routing each host periodically delivers a filter describing the set of notifications it is going to publish in the next future advertisements are flooded into the network each broker stores an advertisement table when a broker receives a filter F, it forwards F to the brokers including at least an advertisement intersecting F DiVES Advertisement based routing optimization advertisement = Predicted Notification Areas

16. 16 AINA 2006 Wien, April 18-20 th 2006 ADVERTISEMENT BASED ROUTING Y =Area of Interest P1 Z = Predicted Notification Area X = Predicted Area of Interest P4 PNA B1 P1 B2 B3 B4 B5 … … P1 Y X B1 X B3 X … … … … … … … … … … PNA(P4)  PAI(P1) =  B3 does not forward PAI(P1) to B4

17. 17 AINA 2006 Wien, April 18-20 th 2006 MERGING FILTERS P2 P1 P2 A broker can merge filters delivered from different players Example F = F1 U F2 Merging filters introduces another level of approximation DiVES merging based routing: Two filters are merged iff the resulting region does not exceed a given threshold F1 F2 F

18. 18 AINA 2006 Wien, April 18-20 th 2006 EXPERIMENTAL RESULTS: REMOTE TRAFFIC

19. 19 AINA 2006 Wien, April 18-20 th 2006 EXPERIMENTAL RESULTS: ROUTING TABLES

20. 20 AINA 2006 Wien, April 18-20 th 2006 CONCLUSIONS DiVES: exploits the publish-subscribe model Entity Based routing with predicted area of interest produces the minimum amount of remote traffic Best compromise between amount of remote traffic and routing tables size obtained in advertisement based routing Future work: – definition of cheating detection tools – refinement of consistency mechanisms – JXTA implementation of the broker network.