Abstract: Methods and systems for providing dynamic dictionary-based compression and decompression are described herein. A computing device may receive, during a currently running session with a client device, a plurality of messages. The computing device may determine, based on the plurality of messages, one or more frames. The computing device may determine, based on the one or more frames, data samples. The computing device may compress the one or more frames based on a compression dictionary. The computing device may train, during the currently running session, the compression dictionary based on the determined data samples, to create a new compression dictionary. The computing device may determine, during the currently running session and based on receiving additional messages, one or more additional frames. In addition, the computing device may compress the one or more additional frames based on the new compression dictionary.

Abstract: Methods and systems for providing a network protocol for view replication over an unreliable network are described herein. A sender and a receiver may apply a branching time model to the history of views to replicate the views consistently. The sender may send a first data packet to receiver. The first data packet may comprise a first sequence number identifying the first data packet, a source version number, and a first set of one or more changes to be applied to a first state identified by the source version number. Based on a determination that an acknowledgment message indicating receipt of the first data packet is not received, the sender may send a second data packet to the client device. The content of the second data packet may be determined based on the first data packet.

Abstract: Methods and systems for providing scalable replication of object positions in virtual simulations are described herein. A computing device may determine a current position of an entity in a virtual simulation. The computing device may determine, based on the current position, a time derivative of the current position of the entity. The computing device may query a dictionary for the time derivative to obtain a particular index identifying a time derivative value that corresponds to the time derivative of the current position of the entity. The dictionary may comprise one or more time derivative value pairs associated with time derivatives of one or more previous positions of the entity. When the time derivative of the current position of the entity is in the dictionary, the computing device may encode the particular index. Further, the computing device may send the particular index to a client device.

Abstract: Methods, systems, computer-readable media, and apparatuses for performing, providing, managing, executing, and/or running a spatially-optimized simulation are presented. In one or more embodiments, the spatially-optimized simulation may comprise a plurality of worker modules performing the simulation, a plurality of entities being simulated among the plurality of worker modules, a plurality of bridge modules facilitating communication between workers and an administrative layer including a plurality of chunk modules, at least one receptionist module, and at least one oracle module. The spatially-optimized simulation may be configured to provide a distributed, persistent, fault-tolerate and spatially-optimized simulation environment. In some embodiments, load balancing and fault tolerance may be performed using transfer scores and/or tensile energies determined among the candidates for transferring simulation entities among workers.

Abstract: Methods and systems for providing a network protocol for view replication over an unreliable network are described herein. A sender and a receiver may apply a branching time model to the history of views to replicate the views consistently. The sender may send a first data packet to receiver. The first data packet may comprise a first sequence number identifying the first data packet, a source version number, and a first set of one or more changes to be applied to a first state identified by the source version number. Based on a determination that an acknowledgment message indicating receipt of the first data packet is not received, the sender may send a second data packet to the client device. The content of the second data packet may be determined based on the first data packet.

Abstract: Methods, systems, computer-readable media, and apparatuses for performing, providing, managing, executing, and/or running a distributed simulation are presented. In one or more embodiments, the distributed simulation may comprise a plurality of workers performing the simulation, and workers may send commands to other workers authoritative over entity components. A mapping of entity components to workers may be used to determine a bridge associated with a worker to which to send a command. A request to invoke the command may be transmitted to the worker via the bridge associated with the worker. The worker transmitting the command request may receive a response to the request to invoke the command, such as a success response or a failure response.

Abstract: Methods and systems for providing dynamic dictionary-based compression and decompression are described herein. A computing device may receive, during a currently running session with a client device, a plurality of messages. The computing device may determine, based on the plurality of messages, one or more frames. The computing device may determine, based on the one or more frames, data samples. The computing device may compress the one or more frames based on a compression dictionary. The computing device may train, during the currently running session, the compression dictionary based on the determined data samples, to create a new compression dictionary. The computing device may determine, during the currently running session and based on receiving additional messages, one or more additional frames. In addition, the computing device may compress the one or more additional frames based on the new compression dictionary.