The accuracy of wireless network packet simulation critically depends on the quality of wireless channel models. Path loss is the stationary component of the channel model affected by the shadowing in the environment. Existing path loss models are inaccurate, require excessive measurement or computational overhead, and/or often cannot be made to represent a given environment. This paper contributes a flexible path loss model that uses a novel approach for spatially coherent interpolation from available nearby channels to allow accurate and efficient modeling of path loss. We show that the proposed model, called Double Regression (DR), generates a correlated space, allowing both the sender and the receiver to move without abrupt change in path loss. Combining DR with a traditional temporal fading model, such as Rayleigh fading, provides an accurate and efficient channel model that we integrate with the NS-2 simulator. We use measurements to validate the accuracy of the model for a number of scenarios. We also show that there is substantial impact on simulation behavior when path loss is modeled accurately. Finally, we show that unlike statistical models, DR can make a simulation representative of a given environment by using a small number of seeding measurements. Thus, DR provides a cost-effective alternative to ray tracing or detailed site surveys.

In mobile ad hoc networks (MANETs), a layered approach to networks makes a routing protocol to be responsible on discovery of a path between two nodes. However, this approach has fundamental limitations in diversifying the strategies of routing in a network when various types of applications require different routing support. In this paper, we propose an application-driven path discovery mechanism. In the proposed architecture, a routing packet controller resides in each MANET node and each application can control path discovery process by installing rules in the routing packet controller. Several examples are described to show the feasibility of our approach.

Cross layer approach is a promising technology to satisfy applications' fastidious requirements and maximize the wireless channel usage in wireless ad hoc networks. Existing cross layer architecture either adopts a specific MAC for an application type or does not change the MAC behavior because the MAC is commonly used for all types of applications in a node. MAC virtualization is an appropriate method to associate the MAC behavior with a specific application's requirement without impacting on other types of application. In this paper, we propose a partial MAC virtualization to support cross layer design in wireless ad hoc networks. In the proposed scheme, a MAC scheme is divided into a set of controllable condition variables and common MAC executor. A MAC control manager generates a virtual MAC with a set of controllable condition variables and related state variables. This paper also proposes an interface through which an application or an agent of the application can control the MAC for its own purpose, which allows a cross-layer mechanism for each application in a node. We show the feasibility of the proposed scheme by an example and experiments.

The accuracy of wireless network packet simulation critically depends on the quality of the wireless channel models. These models directly affect the fundamental network characteristics, such as link quality, transmission range, and capture effect, as well as their dynamic variation in time and space. Path loss is the stationary component of the channel model affected by the shadowing in the environment. Existing path loss models are inaccurate, require very high measurement or computational overhead, and/or often cannot be made to represent a given environment. The paper contributes a flexible path loss model that uses a novel approach for spatially coherent interpolation from available nearby channels to allow accurate and efficient modeling of path loss. We show that the proposed model, called Double Regression (DR), generates a correlated space, allowing both the sender and the receiver to move without abrupt change in path loss. Combining DR with a traditional temporal fading model, such as Rayleigh fading, provides an accurate and efficient channel model that we integrate with the NS-2 simulator. We use measurements to validate the accuracy of the model for a number of scenarios. We also show that there is substantial impact on simulation behavior (e.g., up to 600% difference in throughput for simple scenarios) when path loss is modeled accurately.

Wireless mesh networks (WMNs) are promising networks in the future Internet environments due to their self-configuration and ease of deployment. Although streaming and real time applications are possible using current mobile devices, these applications still suffer from low quality. Because link failures are not reported in congested situations, the existing routing protocols do not capture these deteriorations. An extension of the AODV-MR that is adaptive to changes in link quality is proposed in order to detect deteriorated situations and to recover the path in WMNs. The path is recovered proactively by route discovery if the quality difference of the current link and other available links exceeds the threshold which is determined by the network status. The simulation results demonstrate that the proposed method is effective in multi-radio WMNs and achieve higher throughput, lower average jitter, and lower end-to-end delay.

Recent advancement in smart phones enables users to collaborate in mobile environments. Their diverse communication interfaces allow them to interact with nearby devices, enabling the sharing of computing capabilities and resources among collocated users. Given the personal nature of smart phones, the selection of trustworthy users must be incorporated to enable this sharing process. In this work, a context-aware trust decision scheme for mobile ad-hoc environments is presented. This scheme is decentralized as uses information acquired by mobile phones, while leveraging social theories to reflect real-life aspects properly. The proposed scheme is validated against required properties of trust decision schemes for mobile ad-hoc environments.

The ISM frequency bands (902~918 MHz (region 2 only), 2.4 GHz ~ 2.483 GHz, and 5.725~5.875 GHz) are unlicensed bands available for use by commercial technologies. In particular, the 2.4 GHz ~ 2.483 GHz band is very popular and is currently used by WiFi, Zigbee, Bluetooth, and RFID technologies. Moreover, microwave ovens, hand held phones, and other wireless devices operate in the same frequency range, often interfering with each other. The effects of the coexistence of different standards are complicated and significant. However, network simulators do not model the effect of interference from co-located devices using different technologies. In particular, they model external noise, including interference from technologies outside the primary network being simulated, as a flat Gaussian component. In this paper, we propose a methodology of modeling external interference, by considering the realistic characteristics interference generated by co-located wireless standards. The traditional view that noise is flat in space and time, is inaccurate when one considers interference from co-located technologies. The noise signals are generated from their sources, attenuate over distance and experience fading. In addition, external interference exists only when its sources are active. Based on these characteristics, we propose a realistic and configurable noise model that captures such behavior. We demonstrate that this model can be well-fitted to real noise data. Moreover, we also demonstrate the impact of the model on the performance of network protocols as estimated by simulation.

Wireless channels exhibit complex signal strength fluctuation over time due to signal propagation effects interacting with a dynamic environment. For accurate simulation of wireless networking protocols, it is important to model wireless channels accurately; without accurate models, simulation results have been shown to be significantly different from measured results. Accurate statistical models of the state of a particular channel can be constructed based on obtained experimental measurements. However, this approach cannot be easily exploited for dynamic simulations (e.g., those with mobility), because it is impossible to pre-measure all of the possible channels that arise during the simulation; for example, in a mobile ad hoc network the nodes move and a very large number of channels is encountered in the lifetime of the simulation. In this paper, we propose the use of interpolation between measured channels to produce models for other channels that have not been measured, significantly increasing the flexibility of this approach. Instead of obtaining measurement traces for every link, our method estimates the essential parameters for a new link by interpolation from nearby measured links. Thus, the flexibility of measurement based models is increased dramatically, providing a modeling approach that is both accurate and flexible. We validate the approach using representative experiments.