Modeling and performance analysis using extended fuzzy-timing Petri nets for networked virtual environments

Abstract

Despite their attractive properties, networked virtual environments (net-VEs) are notoriously difficult to design, implement, and test due to the concurrency, real-time and networking features in these systems. Net-VEs demand high quality-of-service (QoS) requirements on the network to maintain natural and real-time interactions among users. The current practice for net-VE design is basically trial and error, empirical, and totally lacks formal methods. This paper proposes to apply a Petri net formal modeling technique to a net-VE-NICE (narrative immersive constructionist/collaborative environment), predict the net-VE performance based on simulation, and improve the net-VE performance. NICE is essentially a network of collaborative virtual reality systems called the CAVE-(CAVE automatic virtual environment). First, we introduce extended fuzzy-timing Petri net (EFTN) modeling and analysis techniques. Then, we present EFTN models of the CAVE, NICE, and transport layer protocol used in NICE: transmission control protocol (TCP). We show the possibility analysis based on the EFTN model for the CAVE. Then, by using these models and design/CPN as the simulation tool, we conducted various simulations to study real-time behavior, network effects and performance (latencies and jitters) of NICE. Our simulation results are consistent with experimental data.

On the Use of Petri Nets for the Computation of Completion Time Distribution for Short TCP Transfers

“…In [5] a TCP model, based on Colored Petri Nets, is used to compare the behavior of two different TCP versions (Reno and Tahoe) when they face different packet loss situations, and to evaluate the impact of packet loss on the throughput. In [24] a TCP model, based on Extended Fuzzy-Timing Petri Nets, is used to evaluate the impact of QoS parameters on virtual reality systems.…”

“…To appreciate the contribution of the present paper is intersting to observe that the analysis presented in [5] and [24] are performed by simulation. On the other hand, the models presented in [1,5,16] allow to obtain first order measures such as throughput, average buffer occupation, and packet loss probability.…”

A Minimum Cycle Time Analysis for Hierarchical Petri

“…To this end, Yim, Joo, and Lee [10], Murata, Yim, Yin and Wolfson [8] and Zhou, Murata and DeFanti [12] have shown how the Petri net minimum cycle time can be used to verify that the design of the system satisfies the user's requirements and maximize the performance of the system all the while saving as many resources as possible. The minimum cycle time process introduced in [7] represents the Petri net model in its incidence matrix A , finds x satisfying 0   x A T and y satisfying 0   y A , calculates the resource-time product, calculates the product of all the S-invariants and their resourcetime product, and returns the maximum of the products.…”

Fuzzy-Timing Petri Nets with Choice Probabilities for Response Time Analysis

“…Although reduction methods and simulation methods are introduced in [5] as analysis methods for Fuzzy Timing Petri net, they are essentially time consuming exhaustive methods.…”

“…Using the new temporal Petri net, they built a model of distributed multimedia synchronization and analysis methods [4]. The new temporal Petri net has also been used in modeling and performance analysis of networked virtual environments [5].…”