Efficient Routing for Wireless Mesh Networks Using a Backup Path

Wireless Mesh Network (WMN) has a proven record in providing viable solutions for some of the fundamental issues in wireless networks such as capacity and range limitations. WMN infrastructure includes clusters of Mobile Ad-Hoc Networks (MANETs) connected through a fixed backbone of mesh routers. The mesh network can be constrained severely due to various reasons, which could result in performance degradation such as a drop in throughput or long delays. Solutions to this problem often focus on multipath or multichannel extensions to the existing ad- hoc routing protocols. In this paper, we propose a novel solution by introducing an alternative path to the mesh backbone that traverses the MANET part of the WMN. The new routing solution allows the Mobile Nodes (MNs) to establish direct communication among peers without going through the backbone. The proposed alternative ad-hoc path is used only when the mesh backbone is severely constrained. We also propose, for the first time in WMNs, using MNs with two interfaces, one used in the mesh backbone communication and the other engaged in the ad-hoc network. A scheme is presented for making the MN aware of link quality measures by providing throughput values to the AODV protocol. We use piggybacking on route reply messages in AODV to avoid incurring additional costs. We implemented our solution in an OPNET simulator and evaluated its performance under a variety of conditions. Simulation results show that the alternative ad-hoc path provides higher throughput and lower delays. Delay analysis show that the throughput improvement does not impose additional costs

Service-Oriented Synthesis of Distributed and Concurrent Protocol Specifications

Several methods have been proposed for synthesizing computer communication protocol specifications from service specifications. Some protocol synthesis methods based on the finite state machine (FSM) model assume that primitives in the service specifications cannot be executed simultaneously. Others either handle only controlled primitive concurrency or have tight restrictions on the applicable FSM topologies. As a result, these synthesis methods are not applicable to an interesting variety of inherently concurrent applications, such as the Internet and mobile communication systems. This paper proposes a concurrent-based protocol synthesis method that eliminates the restrictions imposed by the earlier methods. The proposed method uses a synthesis method to obtain a sequential protocol specification (P-SPEC) from a given service specification (S-SPEC). The resulting P-SPEC is then remodeled to consider the concurrency behavior specified in the S-SPEC, while guaranteeing that P-SPEC provides the specified service

Investigating the impact of fault data completeness over time on predicting class fault-proneness

Context: The adequacy of fault-proneness prediction models in representing the relationship between the internal quality of classes and their fault-proneness relies on several factors. One of these factors is the completeness of the fault data. A fault-proneness prediction model that is built using fault data collected during testing or after a relatively short period of time after release may be inadequate and may not be reliable enough in predicting faulty classes. Objective: We empirically study the relationship between the time interval since a system is released and the performance of the fault-proneness prediction models constructed based on the fault data reported within the time interval. Method: We construct prediction models using fault data collected at several time intervals since a system has been released and study the performance of the models in representing the relationship between the internal quality of classes and their fault-proneness. In addition, we empirically explore the relationship between the performance of a prediction model and the percentage of increase in the number of classes detected faulty (PIF) over time. Results: Our results show evidence in favor of the expectation that predictions models that use more complete fault data, to a certain extent, more adequately represent the expected relationship between the internal quality of classes and their fault-proneness and have better performance. A threshold based on the PIF value can be used as an indicator for deciding when to stop collecting fault data. When reaching this threshold, collecting additional fault data will not significantly improve the prediction ability of the constructed model. Conclusion: When constructing fault-proneness prediction models, researchers and software engineers are advised to rely on systems that have relatively long maintenance histories. Researchers and software engineers can use the PIF value as an indicator for deciding when to stop collecting fault data