Proximity Detection in Distributed Simulation of Wireless Mobile Systems

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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.

Tecnología

Gabriele D’Angelo Lorenzo Donatiello Luciano Bononi Michele Bracuto Department of Computer Science University of Bologna Torremolinos, 03/10/2006 Proximity Detection in Distributed Simulation of Wireless Mobile Systems

Presentation outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Proximity Detection of Wireless Mobile Systems ,[object Object],[object Object],[object Object]

Proximity Detection of Wireless Mobile Systems ,[object Object],[object Object],[object Object],[object Object]

The all-pairs algorithm (brute force) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

External and internal squares 1/2 ,[object Object],[object Object],[object Object]

External and internal squares 2/2 ,[object Object],[object Object]

Grid-based data structure ,[object Object],[object Object],[object Object],[object Object]

Results caching ,[object Object],[object Object],[object Object],[object Object]

Simulated Mobile Hosts (SMHs) migration Wireless ad hoc network scenario: (evaluating migration of SMH x) X’s “transmission-event” must be notified to the 4 model entities executed over B After X’s migration, X’s “transmission-event” must be notified to one model entity executed over A A B network delay Physical Execution Units for the simulation model entities of SMHs executed over PEUs A and B Host X executed over PEU A “transmission-event” A B network delay Physical Execution Units for the simulation model entities of SMHs executed over PEUs A and B Same scenario after migration of X from A to B X X X SMH = Simulated Mobile Host PEU = Physical Execution Unit

The visual effect of the migration based mechanism Migration OFF Migration ON

Migration & results caching ,[object Object],[object Object],[object Object],[object Object]

Performance evaluation: Ad-Hoc wireless network model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Experimental environment and performance evaluation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Proximity detection: all-pairs with caching ON/OFF

Proximity detection: all-pairs with migration and caching ON/OFF

Conclusions and future work ,[object Object],[object Object],[object Object],[object Object],[object Object]

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eSAT Publishing House

WiFra is a new framework for the detailed simulation of very large-scale wireless networks. It is based on the parallel and distributed simulation approach and provides high scalability in terms of size of simulated networks and number of execution units running the simulation. In order to improve the performance of distributed simulation, additional techniques are proposed. Their aim is to reduce the communication overhead and to maintain a good level of load-balancing. Simulation architectures composed of low-cost Commercial-Off-The-Shelf (COTS) hardware are specifically supported by WiFra. The framework dynamically reconfigures the simulation, taking care of the performance of each part of the execution architecture and dealing with unpredictable fluctuations of the available computation power and communication load on the single execution units. A fine-grained model of the 802.11 DCF protocol has been used for the performance evaluation of the proposed framework. The results demonstrate that the distributed approach is suitable for the detailed simulation of very-large scale wireless networks.

Detailed Simulation of Large-Scale Wireless Networks

Gabriele D'Angelo

Milcom 2008 - Elisa Rondini

Elisa Rondini

IRJET - Analytical Study of Hierarchical Routing Protocols for Virtual Wi...

IRJET Journal

The Novel technique to modulate the nulls in the radiation pattern of IMT-Advanced base station (BS) towards the fixed satellite service is (FSS) affirmed in this paper. Designing a new algorithm to extract the nulls in the forbidding area and other base on MUSIC algorithm to estimate the direction of mobile user and control the handover technique is our major concern. A scenario of two mobile users (MS) moving around one FSS had been exclusively studied and simulated. Calculating the shortest separation distance after identifying the critical point and compare the result with the recent recommendation had shown how magnificent coexistence and spectrum sharing we can get.

Channel Overlapping Between IMT-Advanced Users and Fixed Satellite Service

EECJOURNAL

Similar a Proximity Detection in Distributed Simulation of Wireless Mobile Systems (20)