Urban planning and intelligent transportation management are facing key challenges in today's ever more urbanized world. Providing the right tools to city planners is crucial to cope with these challenges. Data collected from citizens' mobile communication can be used as the foundation for such tools. These kinds of data can facilitate various analysis tasks, such as the extraction of human movement patterns or determining the urban dynamics of a city. City planners can closely monitor such patterns based on which strategic decisions can be taken to improve a city's infrastructure. In this paper, we introduce a novel visual analytics approach for pattern exploration and search in global system for mobile communications mobile networks. We define geospatial and matrix representations of data, which can be interactively navigated. The approach integrates data visualization with suitable data analysis algorithms, allowing to spatially and temporally compare mobile usage, identify regularities, as well as anomalies in daily mobility patterns across regions and user groups. As an extension to our visual analytics approach, we further introduce space-time prisms with uncertain markers to visually analyze the uncertainty of urban mobility patterns.

With mobile devices being today one of the main sources of Internet traffic, and the increasing amount of mobile services and applications, the importance of monitoring quality of service for this platform cannot be ignored. Such is the motivation behind the Adkintun Mobile project, attempting to characterize mobile QoS through passive monitoring of devices. The first phase of our project showed great results for our passive approach, however, we concluded that some active testing may be necessary for a more accurate characterization of service quality, but the device context is needed to best establish when to test. In this work we describe our efforts towards context-based active testing, including the development of our monitoring middleware, that through recording of status changes for different aspects of the system in the device, will allow us (and other developers) to clearly identify the context when QoS issues occur.

With the proliferation of web services on the Inter-net, it has become important for service providers to select the best services for their clients in accordance to their functional and non-functional requirements. Generally, QoS parameters are used to select the most performing web services, however, these parameters do not necessarily reflect the user's satisfaction. Therefore, it is necessary to estimate the quality of web services on the basis of user satisfaction, i.e., Quality of Experience(QoE). In this paper, we propose a novel method based on a fuzzy-rough hybrid expert system for estimating QoE of web services for web service selection. It also presents how different QoS parameters impact the QoE of web services. For this, we conducted subjective tests in controlled environment with real users to correlate QoS parameters to subjective QoE. Based on this subjective test, we derive membership functions and inference rules for the fuzzy system. Membership functions are derived using a probabilistic approach and inference rules are generated using Rough Set Theory (RST). We evaluated our system in a simulated environment in MATLAB. The simulation results show that the estimated web quality from our system has a high correlation with the subjective QoE obtained from the participants in controlled tests.

By applying formal description techniques and formal testing approaches, it is possible to validate the conformance of implementations to the requirements of communication protocols. However, and particularly in wireless communications systems, most of the testing work is devoted to the evaluation of their performance in a simulated environment without formal descriptions. The current work expands on our formal approach for black-box testing of network protocols implemented in the tool DataMonitor, and it demonstrates its applications for MANET routing protocols through passive testing on OLSR traces. With such application, we show how our formal approach can help express complex properties from data relations in messages and evaluated them on real traces. The results from our experiments with an OLSR implementation are provided.

There is currently a high level of consciousness of the importance and impact of formally testing communicating networks. By applying formal description techniques and formal testing approaches, we are able to validate the conformance of implementations to the requirements of communication protocols. In this context, passive testing techniques are used whenever the system under test cannot be interrupted or access to its interfaces is unavailable. Under such conditions, communication traces are extracted from points of observation and compared to the expected behavior formally specified as properties. Since most works on the subject come from a formal model context, they are optimized for testing the control part of the communication with a secondary focus on the data parts. In the current work, we provide a data-centric approach for black-box testing of network protocols. A formalism is provided to express complex properties in a bottom-up fashion starting from expected data relations in messages. A novel algorithm is provided for evaluation of properties in protocol traces. Experimental results on Session Initiation Protocol (SIP) traces for IP Multimedia Subsystem (IMS) services are provided.

Although the adoption of the IP Multimedia Subsystem (IMS) keeps growing, IMS applications are often integrated to the system without being formally tested. In this work, we are interested in the IMS Push over Cellular (PoC) service, an OMA standard. We propose a conformance passive testing approach to check that its implementation respects the main standard requirements. This approach is based on a set of formal invariants representing the most relevant expected properties to be tested. Two testing phases are applied: the verification of the invariants against the service specification and their testing on the PoC collected execution traces.