The performance of parallel discrete event simulation protocols is heavily dependent on the lookahead of the simulation model. Identifying and expressing correct lookahead for a model isn't easy, nor is it a well-defined process. In this paper, a global view of a PDES model as a set of data flows is presented. Using this view, we show how the lookahead of the model can be optimized, and we present various simplified implementations of this global view and the significant performance improvements generated when applied to real world models. 1 Introduction The complexity of many modern systems, ranging from wireless networking, internetworking, wargaming, to computer architecture design, defies analytical modeling techniques. A scalable simulation environment, with features such as object aggregation, varying levels of abstraction, and parallel model execution, is necessary to model these systems. Further, in some of these domains, there is a distinct need for real-time responsiveness...

We present a framework, called SWiMNet, for parallel simulation of wireless and mobile PCS networks, which allows realistic and detailed modeling of mobility, call traffic, and PCS network deployment. SWiMNet is based upon event precomputation and a combination of optimistic and conservative synchronization mechanisms. Event precomputation is the result of model independence within the global PCS network. Low percentage of blocked calls typical for PCS networks is exploited in the channel allocation simulation of precomputed events by means of an optimistic approach.

Abstract Rapid growth in wireless communication systems motivates the development of technology supporting the simulation of large-scale wireless systems. However, it is widely recognized that wireless communications do not have substantial "lookahead " needed by conservative synchronization protocols. This paper focuses on identifying and exploiting lookahead for such models. We find lookahead in three ways, exploiting characteristics of low power networks, the transceiver logic, and the way in which protocol stacks are typically constructed. We show how these observations allow a variety of conservative synchronization protocols to take advantage of lookahead, describe a synchronization we use, and empirically examine the performance this method offers on a large-scale simulation of a sensor network intended for homeland defense scenarios.

In this paper, we present a high fidelity and efficient emulation framework called TWINE, which combines the accuracy and realism of emulated and physical networks and the scalability and repeatability of simulation in an integrated testbed, for evaluation of real protocols and applications. Our measurements show that the TWINE emulation kernel has a memory footprint of less than 100KB, and occupies no more than 3.5 % CPU cycles. Thanks to such small overhead and the accurate modelling of physical layer events(at microseconds level), application throughput measured in TWINE is within 5 % of the measured throughput from an equivalent physical wireless LAN. A single commodity PC in TWINE can emulate at least four wireless hosts or simulate sixty nodes in real time at microseconds granularity. This paper also illustrates TWINE’s novel capabilities via two case studies: a protocol to maintain fairness in mesh networks and an adaptive streaming media application operating in heterogeneous wireless networks. The results from the case studies clearly show the benefit of the TWINE evaluation methodology, by identifying a mismatch between the performance of the protocol or application based on actual user experience versus its performance as measured using traditional network performance metrics such as application throughput. 1.

Accurate simulation of wireless networks requires realistic models of the channel propagation medium. The commonly used free space model is computationally efficient but ignores many losses that are common in wireless signal propagation. This paper describes the impact of the wireless channel models on the accuracy and execution time of large-scale simulation models. The paper also demonstrates the impact of using parallel execution in reducing the execution time of the model sufficiently such that a model with 10,000 wireless nodes can be simulated with 6 processors in less time than a network with half as many nodes using sequential execution.

It is well known that the critical path provides an absolute lower bound on the execution time of a conservative parallel discrete event simulation. It stands to reason that optimal execution time can only be achieved by immediately executing each event on the critical path. However, dynamically identifying the critical event is difficult, if not impossible. In this paper, we examine several heuristics that might help to determine the critical event, and conduct a performance study to determine the effectiveness of using these heuristics for preferential scheduling. 1. Introduction Ultimately, performance is the most important issue in parallel processing in general and parallel simulation in particular. There are two widely used families of parallel simulation algorithms: conservative [1] and optimistic [2]. Conservative techniques are so called because they only execute events that are known to be safe, while optimistic algorithms execute any available events, but must roll back to...

There has been rapid growth in wireless communication services. Efficient modeling tools are essential to the design and evaluation of wireless systems. Detail simulation of wireless networks requires long execution time and large amount of memory space. The problem is compounded by the fact that the wireless systems we are interested in are usually large in scale. In this proposal, we present our solution to this problem by the use of parallel discrete-event simulation techniques. We apply parallel computation in simulation of large-scale wireless ad hoc networks. Our research focuses on issues related to reducing synchronization overhead, ecient dynamic load balancing, and high performance modeling of wireless protocols. This proposal reports our previous work in these areas and provides further research directions.

this paper presents MAYA, a multi-paradigm network modeling framework including discrete event models, analytical models and physical network interfaces, together with its illustrative implementation using QualNet, fluid flow TCP model and physical network interface. MAYA framework allows users to interface simulated networks directly with physical networks, while attaining realtime constraints even for large-scale networks by incorporating above multi-paradigm network modeling techniques. It also gives user the flexibility to emulate applications on nodes in both real and simulated networks. Experiments are conducted to validate the interoperation of QualNet and fluid flow model, to examine the performance of MAYA as well as to evaluate the optimization techniques, namely interleaved execution of fluid flow model and causality-preserve realtime synchronization relaxation. Experimental results indicate that MAYA is a scalable and extensible solution to modeling of close interactions between real application and network dynamics