Mineo Takai

Directional virtual carrier sensing for directional antennas in mobile ad hoc networks

This paper presents a new carrier sensing mechanism called DVCS (Directional Virtual Carrier Sensing) for wireless communication using directional antennas. DVCS does not require specific antenna configurations or external devices. Instead it only needs information on AOA (Angle of Arrival) and antenna gain for each signal from the underlying physical device, both of which are commonly used for the adaptation of antenna pattern. DVCS also supports interoperability of directional and omni-directional antennas. In this study, the performance of DVCS for mobile ad hoc networks is evaluated using simulation with a realistic directional antenna model and the full IP protocol stack. The experimental results showed that compared with omni-directional communication, DVCS improved network capacity by a factor of 3 to 4 for a 100 node ad hoc network.

Effects of wireless physical layer modeling in mobile ad hoc networks

In most studies on mobile ad hoc networks (MANET), simulation models are used for the evaluation of devices and protocols. Typically, such simulations focus on the specific higher layer protocols that are being proposed, and tend to ignore details of models at other layers, particularly the interactions with physical layer models. In this paper, we present the set of factors at the physical layer that are relevant to the performance evaluations of higher layer protocols. Such factors include signal reception, path loss, fading, interference and noise computation, and preamble length. We start the discussion with the comparisions of physical layer models in ns-2 and GloMoSim, two commonly used simulators for MANET studies, and then quantify the impact of the preceding factors under typical scenarios used for the performance evaluation of wireless ad hoc routing protocols. Our experimental results show that the factors at the physical layer not only affect the absolute performance of a protocol, but because their impact on different protocols is non-uniform, it can even change the relative ranking among protocols for the same scenari

Exploiting medium access diversity in rate adaptive wireless LANs

Recent years have seen the growing popularity of multi-rate wireless network devices (e.g., 802.11a cards) that can exploit variations in channel conditions and improve overall network throughput. Concurrently, rate adaptation schemes have been developed that selectively increase data transmissions on a link when it offers good channel quality. In this paper, we propose a Medium Access Diversity (MAD) scheme that leverages the benefits of rate adaptation schemes by aggressively exploiting multiuser diversity. The basic mechanism of MAD is to obtain instantaneous channel condition information from multiple receivers and selectively transmit data to a receiver that improves the overall throughput of the network, while maintaining temporal fairness among multiple data flows. We identify and address the challenges in the design and implementation of MADs three phases: channel probing, data transmission, and receiver scheduling. We also use analytical models to examine the tradeoff between network performance improvement and overhead of channel probing, and derive an asymptotic performance bound for the receiver scheduling algorithms used by MAD. Results from the analysis and the extensive simulations demonstrate that, on average, MAD can improve the overall throughput of IEEE 802.11 wireless LANs by 50% as compared with the best existing rate adaptation scheme.

MAYA: Integrating hybrid network modeling to the physical world

The flourish of large-scale network applications across the Internet and or MANET has raised a challenge to network modeling environments that support experimentation and analysis of close interactions between real applications and network dynamics. To facilitate such experimentations, this paper presents MAYA, a multiparadigm 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 real-time constraints even for large-scale networks by incorporating above multiparadigm 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.

Performance evaluation of conservative algorithms in parallel simulation languages

Parallel discrete event simulation with conservative synchronization algorithms has been used as a high performance alternative to sequential simulation. In this paper, we examine the performance of a set of parallel conservative algorithms that have been implemented in the Maisie parallel simulation language. The algorithms include the asynchronous null message algorithm, the synchronous conditional event algorithm, and a new hybrid algorithm called Accelerated Null Message that combines features from the preceding algorithms. The performance of the algorithms is compared using the Ideal Simulation Protocol. This protocol provides a tight lower bound on the execution time of a simulation model on a given architecture and serves as a useful base to compare the synchronization overheads of the different algorithms. The performance of the algorithms is compared as a function of various model characteristics that include model connectivity, computation granularity, load balance, and lookahead.

Simulation of large-scale heterogeneous communication systems

Large-scale hybrid networks that include wireless, wired, and satellite-based communications are becoming common in both military and commercial situations. This paper describes a scalable simulation environment that effectively utilizes parallel execution to reduce the simulation time of detailed high-fidelity models of large communication networks. The paper also presents a set of case studies that evaluate the performance of large wireless networks with thousands of nodes and compares the impact of different lower layer protocols on the performance of typical applications.

Efficient wireless network simulations with detailed propagation models

Accurate simulation of wireless networks requires realistic models of the channel propagation medium. The widely used free space model is computationally efficient but ignores many attenuation components which affect wireless signal propagation. This paper describes the impact of the accuracy of the wireless channel model on the accuracy of the results and on the execution time of large-scale network models. It then introduces means to reduce the runtime execution when deploying such detailed propagation models.

Cooperative Vehicle Positioning via V2V Communications and Onboard Sensors

This paper presents a vehicular positioning system in which multiple vehicles cooperatively calibrate their positions and recognize surrounding vehicles with their GPS receivers and ranging sensors. The proposed system operates in a distributed manner and works even if all vehicles nearby do not or cannot participate in the system. Each vehicle acquires various pieces of positioning information with different degrees of accuracies depending on the sources and recency of information, and compiles them based on likelihood derived from estimated accuracies to minimize estimation errors. A simulation based performance evaluation given in the paper shows that the proposed system improves the estimation accuracy by 85% on average with respect to the standalone GPS receiver, and recognizes about 70% surrounding vehicles with an error of 1m.

Scalable simulation of large-scale wireless networks with bounded inaccuracies

Discrete event network simulators have emerged as popular tools for verification and performance evaluation for various wireless networks. Nevertheless, the desire to model such networks at high fidelity implies high computational costs, prohibiting most researchers from simulating wireless networks with thousands of nodes. There have been attempts on performance optimizations for large-scale wireless network simulation, but they have not appropriately modeled accumulation of weak interference, thereby suffering inaccuracies which may be magnified by upper layer protocols. This paper presents analysis of the effects of common optimization techniques for large-scale wireless network simulation on the overall network performance and also proposes modifications and novel techniques that introduce only limited inaccuracies or no additional inaccuracy at all. The study quantifies the effects of those optimizations on the simulation results for given thresholds and network parameters, and also identifies thresholds tolerable to most network studies. The experimental results show that these optimizations can improve the runtime performance of an already efficient wireless network simulator substantially, by a factor of up to 55 for wireless networks with 3200 nodes without compromising accuracy of the simulation results.

Detailed OFDM modeling in network simulation of mobile ad hoc networks

In mobile ad hoc network (MANET) studies, it is imperative to use highly detailed device models as they provide high layer protocols with good prediction of underlying wireless communication performance. However, such studies often utilize abstract models for execution speed and simplicity. This paper first shows that physical layer variables including path loss, shadowing, multipath, Doppler have significant effects on the predicted overall networking performance. It then proposes an approach to simulate details of wireless propagation and radio characteristics in networking studies while still maintaining a reasonable simulation execution time. Through our runtime performance studies with detailed OFDM Simulink/MATLAB models and QualNet network simulator, it is shown that the proposed approach can improve the simulation runtime performance by three to four orders of magnitudes without compromising the fidelity of simulation results.