Modeling and simulation best practices for wireless ad hoc networks

Perrone, L. Felipe; Yuan, Yougu

doi:10.1109/wsc.2003.1261484

Cited by 30 publications

(26 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…test beds or real life implementations) and analytical models are crucial for understanding the performance of mobile network protocols, simulation was selected as a method of study because it provides an environment which can allow repeatable scenario evaluation, isolation of parameters and wide variety of scenarios and network configuration evaluation on a reasonable scale, time and budget. Likewise a detailed complete analytical model for multihop networks with reasonable assumptions is coarse in nature (Perrone et al, 2003). Therefore, the above characteristics are extremely difficult, if not impossible, with real world experiments.…”

Section: Simulation Environment and Metricsmentioning

confidence: 99%

On the Performance of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

Mohammed¹,

Jabaka²

2010

Nig J Bas App Sci

View full text Add to dashboard Cite

Broadcasting is a commonly used operation in mobile ad hoc networks (MANETs), where a source node diffuses a message to all other nodes in the network. Flooding, a process in which each node retransmits every uniquely received packet exactly once is the simplest mechanism used for broadcasting in MANETs. Despite its simplicity, it can result in high redundant retransmission, contention and collision, a phenomenon collectively referred to as the broadcast storm problem. Counter-based broadcast scheme has been proposed to mitigate this inherent problem and it relies on counter threshold value for rebroadcast decision. Thus, the selection of an appropriate counter threshold-value is crucial to the performance of the scheme. However, previous studies have focused on determining an optimal counter threshold-value using a network setting with very low traffic load. In this paper, we investigate the effects of the counter threshold value on the performance of counterbased scheme in terms of number of retransmitting nodes, reachability and collision rate, using Ns-2 simulation under varying network density and traffic load. Simulation results have revealed that an optimal counter threshold for sparse networks is smaller than that of dense networks. Thus, while most previous studies have often used a single fixed value for the counter, this paper argues that the optimal counter threshold is network density dependent.

show abstract

Section: Simulation Environment and Metricsmentioning

confidence: 99%

On the Performance of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

Mohammed¹,

Jabaka²

2010

Nig J Bas App Sci

View full text Add to dashboard Cite

show abstract

“…A recent example is Gnutella, where strong emergence and unexpected/unexplored graphs have been discovered quite recently. 1 Although in these domains tools primarily designed for modeling of computer networks can occasionally be used to model and simulate, the norm is to have various levels of add-ons; this, however, is not exactly an easy marriage. The designers, being human, feel over-constrained by the limitations of having to keep tweaking and tracking lowlevel network parameters when their primary focus is on modeling more abstract concepts.…”

Section: Muaz Niazi and Amir Hussain University Of Stirlingmentioning

confidence: 99%

“…In turn, the larger and more complex the network, the harder it becomes to test and evaluate its design and eventual implementation. Modeling and simulation (M&S) serves a vital role in the design and development of distributed interacting systems because of their peculiar stochastic nature, especially if they involve systems with decentralized self-organizing capabilities [1,2]. Although networks have grown in both size as well as complexity, the tools to model and simulate them have not scaled at the same rate.…”

Section: Introductionmentioning

confidence: 99%

Agent-based tools for modeling and simulation of self-organization in peer-to-peer, ad hoc, and other complex networks

2009

View full text Add to dashboard Cite

Agent-based modeling and simulation tools provide a mature platform for development of complex simulations. They however, have not been applied much in the domain of mainstream modeling and simulation of computer networks. In this article, we evaluate how and if these tools can offer any value-addition in the modeling & simulation of complex networks such as pervasive computing, large-scale peer-to-peer systems, and networks involving considerable environment and human/animal/habitat interaction. Specifically, we demonstrate the effectiveness of NetLogo — a tool that has been widely used in the area of agent-based social simulation

show abstract

“…That is the complexity of the representation of real world entities and interactions, within the simulation. The importance of the level of detail is twofold: first of all, the correctness of the simulation results is deeply influenced by the amount of details involved in the representation of the simulated system (Perrone et al, 2003). In a performance evaluation, an inadequate amount of details in the model representation can lead to misleading or wrong results (Cavin et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Distributed simulation of large-scale and detailed models

D’Angelo¹,

Bracuto²

2009

IJSPM

View full text Add to dashboard Cite

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.Keywords: simulation; distributed simulation; load balancing; wireless networks.

show abstract

Modeling and simulation best practices for wireless ad hoc networks

Cited by 30 publications

References 12 publications

On the Performance of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

On the Performance of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

Agent-based tools for modeling and simulation of self-organization in peer-to-peer, ad hoc, and other complex networks

Distributed simulation of large-scale and detailed models

Contact Info

Product

Resources

About