Million Entity Distributed Simulations Improving network load by eliminating broadcast interest groups Presented by: David Prody

State of the Art In 2005 the Institute for Defense Analysis conducted a million plus entity simulation. Joint Semi Autonomous Force (JSAF) was used as the driver for entities inside the simulation Scalable Parallel Processor (SPP) where use to provide the horsepower for the simulation These nodes where spread out across the country including several supercomputer sites –Maui High Performance Computing Center –Aeronautical Systems Center Major Shared Resource Center –High Performance Computing Modernization Program (DOD)

How they did it Tree of Meshes Routing –Groups of nodes used mesh overlays to communicate with other local nodes –One node in each local mesh was connected to backbone mesh connecting the 5 primary simulation sites Interest declaration –Modified Runtime Infrastructure version s (RTI-s) Simulation nodes specify what data they are interested in. Publish Subscribe model –Sender side quelch Original RTI-s used multicast to handle interest groups Smarter routers not only send out data to nodes that have requested it Limited “active entities” –Most entities (one million) where civilian “clutter) –Only 1000 combat entities total –No combat entities used emiiters (no radar or laser)

The Problem Simulation did not contain enough combat elements to effectively model theater wide combat. –More active entities are needed. –Modern combat vehicles make extensive use of EMF spectrum. Radar and laser is a major component of a modern battlefield –Precision guided weapons –Active Radar Tracking/Radar Countermeasures

Problem with Emitters Under the current RTI-s interest declaration protocol there is only one emitter interest group –If you an interested in any emission you must receive all emissions –This is not a scalable solution.

Proposed Solution Break up emitter interest group into geographic regions. –Simulations nodes will be allowed to specify specific geographic regions of interest and only receive emitter traffic from those regions –This forces receivers to compute the regions they are able to receive from before they can receive any traffic. –This implementation will be done the same as entity position interest groups are handled Battle space is broken in a grid and each grid point is given a unique identifier Receivers publish a list of grid square that they are interested in.

Test Bed Computer simulation based on the 2005 large simulation run and personal experience with battlespace simulations –100 nodes in Mesh network –Entities distributed evenly throughout nodes This is done for real simulations to prevent computational “hotspots” –Only Emitter traffic monitored –4 different distributions of emitter entities “locations” modeled Broadcast – This is the current method. Entity location is irrelevant because controlling node will broadcast to all nodes Random distribution – Entities in each node are randomly assigned a grid location Host Cluster – Entities in the same node have a high probability of being in the same grid. –This is closest to how real simulations work –Two different distributions where tried. The probability of entities grouping was changed »50% probability – half of the entities on the node where in the same grid »30% probability – 30 % of the entities on the node where in the same grid

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