Michele Bracuto

MoVES: A framework for parallel and distributed simulation of wireless vehicular ad hoc networks

In this paper, we illustrate a Mobile Wireless Vehicular Environment Simulation (MoVES) framework for the parallel and distributed simulation of vehicular wireless ad hoc networks (VANETs). The proposed framework supports extensible, module-based and layered modeling, and scalable, accurate and efficient simulation of vehicular scenarios integrated with wireless communication and mobile services/applications. The vehicular layer includes models for vehicles, synthetic and trace-driven mobility, driver behavior, GPS-based street maps, intersection policies and traffic lights. The wireless communication layer currently includes models for physical propagation, and a network protocol stack including IEEE 802.11 Medium Access Control, up to the Application layer. MoVES provides a platform for microscopic modeling and simulation-based analysis of wireless vehicular scenarios and communication-based services and applications, like Intelligent Transportation Systems, communication-based monitoring/control and info-mobility services. The framework includes design solutions for scalable, accurate and efficient parallel and distributed simulation of complex, vehicular communication scenarios executed over cost-effective, commercial-off-the-shelf (COTS) simulation architectures. Dynamic model partition and adaptation-based load balancing solutions have been designed by exploiting common assumptions and model characteristics, in a user-transparent way. Test-bed performance evaluation for realistic scenarios has shown the effectiveness of MoVES in terms of simulation efficiency, scalability, adaptation and simulation accuracy.

Concurrent Replication of Parallel and Distributed Simulations

Parallel and distributed simulations enable the analysis of complex systems by concurrently exploiting the aggregate computation power and memory of clusters of execution units. In this paper we investigate a new direction for increasing both the speedup of a simulation process and the utilization of computation and communication resources. Many simulation-based investigations require to collect independent observations for a correct and significant statistical analysis of results. The execution of many independent parallel or distributed simulation runs may suffer the speedup reduction due to rollbacks under the optimistic approach, and due to idle CPU times originated by synchronization and communication bottlenecks under the conservative approach. We present a parallel and distributed simulation framework supporting concurrent replication of parallel and distributed simulations (CR-PADS), as an alternative to the execution of a linear sequence of multiple parallel or distributed simulation runs. Results obtained from tests executed under variable scenarios show that speedup and resource utilization gains could be obtained by adopting the proposed replication approach in addition to the pure parallel and distributed simulation.

A New Adaptive Middleware for Parallel and Distributed Simulation of Dynamically Interacting Systems

In this work we define and test a new framework obtained as the integration of two recently developed middlewares defined to support the parallel and distributed simulation of large scale, complex and dynamically interacting system models (like wireless and mobile network systems). In a distributed simulation of highly interacting system models, the main bottleneck may become the communication and synchronization required to maintain the causality constrains between distributed model components. We designed and implemented the ARTÌS middleware as a new framework incorporating a set of features that allow an adaptive optimization of the communication layer management in a distributed simulation scenario. ARTÌS has been integrated with GAIA, a dynamic mechanism for the runtime management and adaptive allocation of model entities in a distributed simulation. By adopting a runtime evaluation of causal bindings between model entities GAIA adapts the dynamic and time-persistent causal effects of model interactions to dynamic migration of model entities. Preliminary results demonstrate that the combined effect of ARTÌS management and GAIA heuristics leads to a significant reduction in the communication and synchronization overheads between the physical execution units. Simulation performance enhancements have been obtained also in worst-case modelling assumptions and simulation scenarios.

Distributed simulation of large-scale and detailed models

We present a new approach for the distributed simulation of large-scale and detailed models. Our approach increases the simulator speed jointly addressing two main problems of distributed simulation: the reduction of the communication overhead and the load-balancing in the execution cluster. The proposed method dynamically reconfigures the simulation, considering the performance of each part of the execution architecture. In this way, commercial-off-the-shelf hardware can be used for fast and cost-effective simulations. The performance evaluation, based on the 802.11 DCF protocol, demonstrates that this approach is feasible for the detailed simulation of very large-scale models such as wireless networks.

An adaptive load balancing middleware for distributed simulation

The simulation is useful to support the design and performance evaluation of complex systems, possibly composed by a massive number of interacting entities. For this reason, the simulation of such systems may need aggregate computation and memory resources obtained by clusters of parallel and distributed execution units. Shared computer clusters composed of available Commercial-Off-the-Shelf hardware are preferable to dedicated systems, mainly for cost reasons. The performance of distributed simulations is influenced by the heterogeneity of execution units and by their respective CPU load in background. Adaptive load balancing mechanisms could improve the resources utilization and the simulation process execution, by dynamically tuning the simulation load with an eye to the synchronization and communication overheads reduction. In this work it will be presented the GAIA+ framework: a new load balancing mechanism for distributed simulation. The framework has been evaluated by performing testbed simulations of a wireless ad hoc network model. Results confirm the effectiveness of the proposed solutions.

ARTÌS: A Parallel and Distributed Simulation Middleware for Performance Evaluation

This paper illustrates the motivation, the preliminary design and implementation issues, of a new distributed simulation middleware named Advanced RTI System (ARTIS). The aim of the ARTIS middleware is to support parallel and distributed simulations of complex systems characterized by heterogeneous and distributed model components. The ARTIS design is oriented to support the model components heterogeneity, distribution and reuse, and to increase the simulation performances, scalability and speedup, in parallel and distributed simulation scenarios. Another design issue of the ARTIS framework is the dynamic adaptation of the interprocess communication layer to the heterogeneous communication support of different simulation scenarios. In this paper we illustrate the guidelines and architecture that we considered in the design and implementation of the ARTIS middleware, and we sketch some case studies that demonstrated the ARTIS utility and motivation, e.g., a distributed simulation of massively populated wireless ad hoc and sensor networks.

Exploring the Effects of Hyper-Threading on Parallel Simulation

This paper illustrates the effects of the hyper-threading processor technology on the runtime performance of a parallel and distributed simulation middleware. A preliminary analysis of the middleware design and execution parameters is given to identify the tuning parameters and to evaluate the scalability of parallel simulation. A real testbed scenario has been illustrated, based on the ARTIS parallel and distributed simulation middleware. The experimental analysis has provided some interesting guidelines about the way to adapt the parallel and distributed simulation middleware to hyper-threading and to increase the execution speed of the simulation

Scalable and Efficient Parallel and Distributed Simulation of Complex, Dynamic and Mobile Systems

In this work we illustrate the design and implementation guidelines of a recently developed middleware defined to support the parallel and distributed simulation of large scale, complex and dynamically interacting system models. The distributed simulation of complex system models, may suffer the communication and synchronization required to maintain the causality constraints between distributed model components. We designed and implemented the ARTÌS middleware as a new framework by incorporating a set of features that allow adaptive optimization by exploiting many complex and dynamic model and distributed simulation characteristics. As an example, a dynamic migration mechanism for the run-time adaptive allocation of model entities has been designed and exploited for dynamic load and communication balancing. Optimizations have been introduced to obtain the maximum advantage from heterogeneous and asymmetric communication systems, from shared memory to LAN and Internet communication. Other optimizations have been introduced by the exploitation of concurrent replications of parallel and distributed simulations, in order to increase the resources utilization and to maximize the speedup of simulation processes. Solutions have been designed, implemented and tuned to obtain a significant reduction in the communication and synchronization overheads between the physical execution units, and an increased model scalability and simulation speedup, even in worst-case modeling assumptions and simulation scenarios.

Proximity detection in distributed simulation of wireless mobile systems

The distributed and the Grid Computing architectures for the simulation of massively populated wireless systems have recently been considered of interest, mainly for cost reasons. Solutions for generalized proximity detection for mobile objects is a relevant problem, with a big impact on the design and the implementation of parallel and distributed simulations of wireless mobile systems. In this paper, a set of solutions based on tailored data structures, new techniques and enhancements of the existing algorithms for generalized proximity detection are proposed and analyzed, to increase the efficiency of distributed simulations. The paper includes the analysis of computation complexity of the proposed solutions and the performance evaluation of a testbed distributed simulation of ad hoc network models. Recent works have shown that the performance of distributed simulation of dynamic complex systems could benefit from a runtime migration mechanism of model entities, which reduces the communication overheads. Such migration mechanisms may interfere with the generalized proximity detection implementations. The analysis performed in this paper illustrates the effects of many possible compositions of the proposed solutions, in a real testbed simulation framework.

Analysis of high performance communication and computation solutions for parallel and distributed simulation

This paper illustrates the definition and analysis of a collection of solutions adopted to increase the performance of communication and computation activities required by the implementation and execution of parallel and distributed simulation processes. Parallel and distributed simulation has been defined, and a real testbed simulation scenario has been illustrated, based on the ARTIS simulation framework. Three classes of solutions have been proposed to improve the performance of simulations executed over commodity off-the-shelf computation and communication architectures: multi-threaded software and Hyper-Threading support by the processor architectures, data marshalling solutions for shared-memory and network-based communications, and data structure optimization for simulation events’ management. All the proposed solutions have been evaluated on a testbed evaluation scenario, under variable configurations. Results obtained demonstrate that a performance improvement can be obtained by adopting and tuning the proposed solutions.