A cooperative scheme for the coexistence of the LTE and WiFi systems

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SODIM: Service Oriented Data Integration based on MapReduce

Data integration has become a backbone for many essential and widely used services. These services depend on integrating data from multiple sources in a fast and efficient way to be able to provide the accepted level of service performance it is committed to. As the size of data available on different environments increases, and systems are heterogeneous and autonomous, data integration becomes a crucial part of most modern systems. Data integration systems can benefit from innovative dynamic infrastructure solutions such as Clouds, with its more agility, lower cost, device independency, location independency, and scalability. This study consolidates the data integration system, Service Orientation, and distributed processing to develop a new data integration system called Service Oriented Data Integration based on MapReduce (SODIM) that improves the system performance, especially with large number of data sources, and that can efficiently be hosted on modern dynamic infrastructures as Clouds

VNetIntSim: An Integrated Simulation Platform to Model Transportation and Communication Networks

The paper introduces a Vehicular Network Integrated Simulator (VNetIntSim) that integrates transportation modelling with Vehicular Ad Hoc Network (VANET) modelling. Specifically, VNetIntSim integrates the OPNET software, a communication network simulator, and the INTEGRATION software, a microscopic traffic simulation software. The INTEGRATION software simulates the movement of travellers and vehicles, while the OPNET software models the data exchange through the communication system. Information is exchanged between the two simulators as needed. As a proof of concept, the VNetIntSim is used to quantify the impact of mobility parameters (traffic stream speed and density) on the communication system performance, and more specifically on the data routing (packet drops and route discovery time)

Software bug prediction using weighted majority voting techniques

Mining software repositories is a growing research field where rich data available in the different development software repositories, are analyzed and cross-linked to uncover useful information. Bug prediction is one of the potential benefits that can be gained through mining software repositories. Predicting potential defects early as they are introduced to the version control system would definitely help in saving time and effort during testing or maintenance phases. In this paper, defect prediction models that uses ensemble classification techniques have been proposed. The proposed models have been applied using different sets of software metrics as attributes of the classification techniques and tested on datasets of different sizes. The results show that change metrics outperform static code metrics and the combined model of change and static code metrics. Ensembles tend to be more accurate than their base classifiers. Defect prediction models using change metrics and ensemble classifiers have revealed the best performance, especially when the datasets used have imbalanced class distribution. Keywords: Modeling and prediction, Product metrics, Process metrics, Classifier design and evaluatio