Obesity has been recognized to be among the principal causes of many chronic diseases such as diabetes, cholesterol, hypertension, and other cardiovascular diseases. Therefore, monitoring, controlling, and preventing obesity will mitigate the risks generated from the complications of these diseases. Comprehensive preventive measures are essential to control the spread of obesity, while healthcare systems should be organized on the basis of locally derived data to provide adequate and affordable care to the increasing groups of overweight and obese people. In this paper, we propose a hybrid model that relies on both data collected from sensors and participatory data collected from a social network community established to provide value-added obesity awareness, monitoring, and prevention. The model encompasses some key smart features including tracking food intake, lifestyle, and exercise activities, generating warnings and recommendations, and triggering interventions whenever needed. Our model also mines the collected data to produce statistical analysis that can be used by health authorities to have a clear picture of the health status of the population and might help in making rational and informed decisions. Moreover, we implement a prototype of our model as a set of Web services using the SOA paradigm and lightweight protocols. Promising results of our prototype are reported and analyzed.

Nowadays, mobile applications/devices have become the trends, especially, when they were gradually shifted from basic communication services to supporting more sophisticated service provisioning. Mobile applications are usually very light, are nowadays likely to be often connected to the Internet, and can be used quite easily. However, these applications exhibit some challenges related to limited resources they have access to, including limited processing power, memory, storage size, battery power, and intermittent network connection. In fact, these considerations have to be taken seriously into consideration when developing mobile applications especially if those applications will be used for critical services, for example, to collect and report vital health data over a long period of time. In this paper, we study the use of mobile applications for monitoring patient's vital. Mobile devices, through an application, are connected to body-strapped biosensors to collect and synchronize these parameters with information systems. This synchronization should be done in such a way that the cost of synchronization is kept low and urgent readings are delivered as soon as possible. To optimize the synchronization process and reduce its cost, we propose and validate cost-oriented algorithms. A case study is developed to illustrate the applicability and effectiveness of our innovative techniques in making continuous monitoring an efficient process.

Various and independent studies are showing that an exponential increase of chronic diseases (CDs) is exhausting governmental and private healthcare systems to an extent that some countries allocate half of their budget to healthcare systems. To benefit from the IT development, e-health monitoring and prevention approaches revealed to be among top promising solutions. In fact, well-implemented monitoring and prevention schemes have reported a decent reduction of CDs risk and have narrowed their effects, on both patients' health conditions and on government budget spent on healthcare. In this paper, we propose a framework to collect patients' data in real time, perform appropriate nonintrusive monitoring, and propose medical and/or life style engagements, whenever needed and appropriate. The framework, which relies on service-oriented architecture (SOA) and the Cloud, allows a seamless integration of different technologies, applications, and services. It also integrates mobile technologies to smoothly collect and communicate vital data from a patient's wearable biosensors while considering the mobile devices' limited capabilities and power drainage in addition to intermittent network disconnections. Then, data are stored in the Cloud and made available via SOA to allow easy access by physicians, paramedics, or any other authorized entity. A case study has been developed to evaluate the usability of the framework, and the preliminary results that have been analyzed are showing very promising results.

Despite the rapid growth of the mobile technology, mobile devices are still considered as resource constrained with limited battery. Same computations are awkward to be undertaken on these devices with limited processing capabilities. Other processes are costly in terms of battery consumption. Ideally, mobile applications will have the possibility to decide either to do a computation locally or remotely depending on the current device capabilities status. Making such decision is very challenging as many interrelated factors are to be considered (e.g. network connection, battery level, and processing capabilities). In this paper, we propose a framework that supports developers in implementing such smartness fitness within their mobile applications. This solution provides approaches in form of algorithms to instrument code of mobile applications to behave in smart way. Incorporating these algorithms will allow for on-the-fly decision of local versus remote computation using a calculated cost function. We conducted some experimental scenarios to evaluate the usability and effectiveness of our decision-based algorithms. The results we have obtained prove that for the same computation, depending on the size of data, the network status and the device status, the decision of the engine may differ.

Standard specifications of Web Services are mainly concerned with Web Service publishing and discovery. However, there is no standard regarding Web Service selection, which is very crucial for providers and clients. It will support clients in selecting Web Services based on required Quality of Web Service (QoWS) and support providers to remain competitive. Most of solutions on Web Service selection are very often based on a central component to make the selection decision, do not scale to the growing number of clients and Web Service providers, and/or lack trustworthiness. The objective of our approach is to support clients in selecting, and monitoring appropriate Web Services while increasing scalability, trust and reliability of Web Service selection. We propose a framework based on a federation of cooperative brokers. Each broker in the federation manages Web Services within its domain of expertise, and cooperates with its peers to select appropriate Web Services. We describe the federation management operations and our cooperative brokers QoS-aware selection algorithm. We propose certification and monitoring of Web Services as well as monitoring of brokers. The implementation and the experiments we have conducted evaluated the performance of our approach. The obtained results show that: the load is shared and distributed among brokers, a large number of client requests with different QoWS requirements were served, the architecture can scale up in order to include other brokers and/or other Web Services, and selection is guaranteed, trustworthy as it is supported by monitoring.

Mobility-aware Web services (MWS) should become nowadays an important research area as the number of powerful mobile devices proliferates and their usage for daily business transaction increases. Quality of Web Service (QoWS) assurance for MWS is very crucial for mobile users, however, it is highly affected by the available resources on mobile devices consuming these services and the performance of MWS. In this paper, we propose an architecture for MWS selection based on QoWS and resources requirements. The main purpose of the architecture is to support the client in selecting MWS based on desired QoWS as well as on its device resources availability. This architecture requires a concise description of QoWS and resources requirements. For this purpose, the architecture proposes a verification scheme to verify the conformity of claimed MWS QoWS and required device resources compared to the published one. A set of validation test cases are executed to measure, for each specific MWS operation: the required battery consumption, memory, CPU, and network throughput. The verification is used as input to a three-tier selection process in which selected MWS are those who passed the verification test cases. As proof of concept, a prototype has been implemented to evaluate the verification scheme and show its importance in selecting the best MWS while supporting the QoWS and the required device resource availability.

In this paper, we propose a preliminary approach for automating web service verification. We use Semantic Markup for Web Services (OWL-S) to describe web service behavior. We parse the OWL-S file and transform it automatically to a corresponding Markov chain diagram or Markov decision process, which are then transformed to a PRISM model to be used as input by PRISM, a probabilistic model checker, to verify automatically the web service behavior. We provide an implementation of the transformation algorithm through a developed software tool automating all the transformation and verification activities.

Quality of Web Service (QoWS) support for Mobility-aware Web services (MWS) is critical for mobile users since it relies on the available resources on mobile devices consuming these services. In this paper, we propose a selection model for MWS based on QoWS and device resources requirements. The main purpose of the model is to support the client in selecting MWS based on desired QoWS as well as on its device resources availability. We propose a verification scheme to verify the conformity of claimed MWS QoWS and required device resources compared to the published one. The verification is used to support selection of MWS. The implementation of our model is discussed and the importance of our verification scheme is highlighted.

Web Services are considered an attracting distributed approach of application/services integration over the Internet. As the number of Web Services is exponentially growing and expected to do so for the next decade, the need for categorizing and/or classifying Web Services is very crucial for their success and the success of the underlying SOA. Categorization aims at systematizing Web Services according to their functionalities and their Quality of Service attributes. Communities of Web Services have been used to connect Web Services based on their functionalities. In this paper, we augment the community approach by defining a new community to monitor Web Services operating in any Web Services community. This will be of prime importance for communities' creators/managers willing to protect and sustain their communities. This paper defines the overall architecture of the monitoring community and the basic services it offers to its various classes of customers.

This paper provides a brief description of a research project on using Ajax to enhance mobile Web applications for enterprise use. The project, known as MobileWeaver Ajax Framework, leverages enterprise SOA (Service Oriented Architecture) and the latest web technologies on mobile devices.