Towards critical event monitoring, detection and prediction for self-adaptive future Internet applications

The Future Internet (FI) will be composed of a multitude of diverse types of services that offer flexible, remote access to software features, content, computing resources, and middleware solutions through different cloud delivery models, such as IaaS, PaaS and SaaS. Ultimately, this means that loosely coupled Internet services will form a comprehensive base for developing value added applications in an agile way. Unlike traditional application development, which uses computing resources and software components under local administrative control, FI applications will thus strongly depend on third-party services. To maintain their quality of service, those applications therefore need to dynamically and autonomously adapt to an unprecedented level of changes that may occur during runtime. In this paper, we present our recent experiences on monitoring, detection, and prediction of critical events for both software services and multimedia applications. Based on these findings we introduce potential directions for future research on self-adaptive FI applications, bringing together those research directions

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Context aware programmable trackers for the next generation Internet

This work introduces and proposes the concept of context aware programmable trackers for the next generation Internet. The pro- posed solution gives ground for the development of advanced applications based on the P2P paradigm and will foster collaborative efforts among several network entities (e.g. P2P applications and ISPs). The proposed concept of context aware programmable trackers allows that several peer selection strategies might be supported by a P2P tracker entity able to improve the peer selection decisions according with pre-defined objectives and external inputs provided by specific services. The flexible, adaptive and enhanced peer selection semantics that might be achieved by the proposed solution will contribute for devising novel P2P based services and business models for the future Internet

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Architecture for satellite services over cryptographically heterogeneous networks with application into smart grid

The rapid growth in the demand for Future Internet services with many emerging group applications has driven the development of satellite, which is the preferred delivery mechanism due to its wide area coverage, multicasting capability and speed to deliver affordable future services. Nevertheless, security has been one of the obstacles for both satellite services as well as smart grid group applications, especially with logical/geographical/cryptographic domains spanning heterogeneous networks and regions. In this paper, adaptive security architecture is implemented to protect satellite services for smart grid group applications. The focus is on key management and policy provisioning. Leveraging Group Domain of Interpretation (GDOI) as the standard for smart grid centralized key/policy management architecture, a single Domain of Interpretation (DOI) is deployed and evaluated critically in terms of the added protocol signaling overhead on the satellite system for a fixed-network scenario. This also partially realizes the growing trend towards the use of TCP/IP technology for smart grid applications

Adaptive User Interfaces for Intelligent E-Learning: Issues and Trends

Adaptive User Interfaces have a long history rooted in the emergence of such eminent technologies as Artificial Intelligence, Soft Computing, Graphical User Interface, JAVA, Internet, and Mobile Services. More specifically, the advent and advancement of the Web and Mobile Learning Services has brought forward adaptivity as an immensely important issue for both efficacy and acceptability of such services. The success of such a learning process depends on the intelligent context-oriented presentation of the domain knowledge and its adaptivity in terms of complexity and granularity consistent to the learner’s cognitive level/progress. Researchers have always deemed adaptive user interfaces as a promising solution in this regard. However, the richness in the human behavior, technological opportunities, and contextual nature of information offers daunting challenges. These require creativity, cross-domain synergy, cross-cultural and cross-demographic understanding, and an adequate representation of mission and conception of the task. This paper provides a review of state-of-the-art in adaptive user interface research in Intelligent Multimedia Educational Systems and related areas with an emphasis on core issues and future directions

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Adaptive and context-aware service discovery for the Internet of Things

The Internet of Things (IoT) vision foresees a future Internet encompassing the realm of smart physical objects, which offer hosted functionality as services. The role of service discovery is crucial when providing application-level, end-to-end integration. In this paper, we propose trendy: a RESTful web services based Service Discovery protocol to tackle the challenges posed by constrained domains while offering the required interoperability. It provides a service selection technique to offer the appropriate service to the user application depending on the available context information of user and services. Furthermore, it employs a demand-based adaptive timer and caching mechanism to reduce the communication overhead and to decrease the service invocation delay. trendy’s grouping technique creates location-based teams of nodes to offer service composition. Our simulation results show that the employed techniques reduce the control packet overhead, service invocation delay and energy consumption. In addition, the grouping technique provides the foundation for group-based service mash-ups and localises control traffic to improve scalability