Smart, Autonomous and Reliable Internet of Things

AbstractThe dynamic rapidly changing and technology-rich digital environment enables the provision of added-value applications that exploit a multitude of devices contributing services and information. As the Internet of Things (IoT) techniques mature and become ubiquitous, emphasis is put upon approaches that allow things to become smarter, more reliable and more autonomous. In this paper we present challenges and enablers as technologies that will allow things to evolve and act in a more autonomous way, becoming more reliable and smarter. We describe decentralized management mechanisms targeting IoT-based systems in order to enable the exploitation of millions of devices, while we also present an architecture that allows things to learn based on others experiences. The proposed architectural approach also introduces situational knowledge acquisition and analysis techniques in order to make things aware of conditions and events affecting IoT-based systems behavior

Optimum Allocation of Distributed Service Workflows with Probabilistic Real-Time Guarantees

This paper addresses the problem of optimum allocation of distributed real-time workflows with probabilistic service guarantees over a set of physical resources. The discussion focuses on how such a problem may be mathematically formalized, in terms of both constraints and objective function to be optimized, which also accounts for possible business rules for regulating the deployment of the workflows. The presented formal problem constitutes a probabilistic admission control test that may be run by a provider in order to decide whether or not it is worth to admit new workflows into the system and to decide what the optimum allocation of the workflow to the available resources is. Various options are presented, which may be plugged into the formal problem description, depending on the specific needs of individual workflows. The presented problem has been implemented using GAMS and has been tested under various solvers. An illustrative numerical example and an analysis of the results of the implemented model under realistic settings are presented

Second Screen User Profiling and Multi-level Smart Recommendations in the context of Social TVs

In the context of Social TV, the increasing popularity of first and second screen users, interacting and posting content online, illustrates new business opportunities and related technical challenges, in order to enrich user experience on such environments. SAM (Socializing Around Media) project uses Social Media-connected infrastructure to deal with the aforementioned challenges, providing intelligent user context management models and mechanisms capturing social patterns, to apply collaborative filtering techniques and personalized recommendations towards this direction. This paper presents the Context Management mechanism of SAM, running in a Social TV environment to provide smart recommendations for first and second screen content. Work presented is evaluated using real movie rating dataset found online, to validate the SAM's approach in terms of effectiveness as well as efficiency.Comment: In: Wu TT., Gennari R., Huang YM., Xie H., Cao Y. (eds) Emerging Technologies for Education. SETE 201

Advance Reservations for Distributed Real-Time Workflows with Probabilistic Service Guarantees

This paper addresses the problem of optimum allocation of distributed real-time workflows with probabilistic service guarantees over a Grid of physical resources made available by a provider. The discussion focuses on how such a problem may be mathematically formalised, both in terms of constraints and objective function to be optimized, which also accounts for possible business rules for regulating the deployment of the workflows. The presented formal problem constitutes a probabilistic admission control test that may be run by a provider in order to decide whether or not it is worth to admit new workflows into the system, and to decide what the optimum allocation of the workflow to the available resources is. Various options are presented which may be plugged into the formal problem description, depending on the specific needs of individual workflows

An evaluation of time series forecasting models on water consumption data: A case study of Greece

In recent years, the increased urbanization and industrialization has led to a rising water demand and resources, thus increasing the gap between demand and supply. Proper water distribution and forecasting of water consumption are key factors in mitigating the imbalance of supply and demand by improving operations, planning and management of water resources. To this end, in this paper, several well-known forecasting algorithms are evaluated over time series, water consumption data from Greece, a country with diverse socio-economic and urbanization issues. The forecasting algorithms are evaluated on a real-world dataset provided by the Water Supply and Sewerage Company of Greece revealing key insights about each algorithm and its use

Ozone: An Insulating Layer Between Ontologies, Databases and Object Oriented Applications

Recent research shows that ontologies are a prominent tool for the semantic integration of heterogeneous data sources. However, in existing ontology-based systems the ontologies are tightly coupled with the rest of the system components. As a result, large parts of the system have to be developed in a logic programming language, typically used in describing ontologies, and adhere to the ontological knowledge model and representation. This eventually impedes the use of ontologies in industrial integrated systems. In this paper, we present an architecture that isolates the ontologybased components, waives the representation and programming language constraints and simplifies the knowledge model that components outside the ontology have to be aware of. The architecture makes it possible to access the ontological information and the federated data using exclusively object-oriented structures and interfaces. We show that it allows new databases to easily join the federation by implementing a standard database interface. The architecture has been implemented and evaluated in the field of information retrieval for e-commerce. We review the principal results and limitations of this case study

Elastic admission control for federated cloud services

This paper presents a technique for admission control of a set of horizontally scalable services, and their optimal placement, into a federated Cloud environment. In the proposed model, the focus is on hosting elastic services whose resource requirements may dynamically grow and shrink, depending on the dynamically varying number of users and patterns of requests. The request may also be partially accommodated in federated external providers, if needed or more convenient. In finding the optimum allocation, the presented mechanism uses a probabilistic optimization model, which takes into account eco-efficiency and cost, as well as affinity and anti-affinity rules possibly in place for the components that comprise the services. In addition to modelling and solving the exact optimization problem, we also introduce a heuristic solver that exhibits a reduced complexity and solving time. We show evaluation results for the proposed technique under various scenarios