Ioan Salomie

Optimizing the Semantic Web Service Composition Process Using Cuckoo Search

The behavior of biological individuals which efficiently deal with complex life problems represents an inspiration source in the design of meta-heuristics for solving optimization problems. The Cuckoo Search is such a meta-heuristic inspired by the behavior of cuckoos in search for the appropriate nest where to lay eggs. This paper investigates how the Cuckoo Search meta-heuristic can be adapted and enhanced to solve the problem of selecting the optimal solution in semantic Web service composition. To improve the performance of the cuckoo-inspired algorithm we define a 1-OPT heuristic which expands the search space in a controlled way so as to avoid the stagnation on local optimal solutions. The search space is modeled as an Enhanced Planning Graph, dynamically built for each user request. To identify the optimal solution encoded in the graph we define a fitness function which uses the QoS attributes and the semantic quality as selection criteria. The cuckoo-inspired method has been evaluated on a set of scenarios from the trip planning domain.

GAMES: Green Active Management of Energy in IT Service Centres

The vision of the recently started GAMES European Research project is a new generation of energy efficient IT Service Centres, designed taking into account both the characteristics of the applications running in the centre and context-aware adaptivity features that can be enabled both at the application level and within the IT and utility infrastructure. Adaptivity at the application level is based on the service-oriented paradigm, which allows a dynamic composition and recomposition of services to guarantee Quality of Service levels that have been established with the users. At the infrastructure level, adaptivity is being sought with the capacity of switching on and off dynamically the systems components, based on the state of the service centre. However, these two perspectives are usually considered separately, managing at different levels applications and infrastructure. In addition, while performance and cost are usually the main parameters being considered both during design and at run time, energy efficiency of the service centre is normally not an issue. However, given that the impact of service centres is becoming more and more important in the global energy consumption, and that energy resources, in particular in peak periods, are more and more constrained, an efficient use of energy in service centres has become an important goal. In the GAMES project, energy efficiency improvement goals are tackled based on exploiting adaptivity, on building a knowledge base for evaluating the impact of the applications on the service centre energy consumption, and exploiting the application characteristics for an improved use of resources.

Applying Green Metrics to optimise the energy-consumption footprint of IT service centres

This paper presents a novel approach to characterise applications with respect to their energy consumption by using a set of energy-related metrics, called Green Metrics. These indicators are based on energy consumption measurements, such as indices of computing resource usage, of environmental impact, of development costs required to (re)design an application in order to optimise its energy consumption footprint, and of organisational factors related to application management. Our approach is framed in the Green Active Management of Energy in IT Service Centres (GAMES) EU project, with a particular focus on green IT. In this paper, we define Green Metrics enabling to characterise an application in terms of the energy it consumes at run time. Such metrics are the basis for measuring the ‘Greenness’ of an application and to detect where it consumes and wastes energy. Hints are provided to improve applications design and execution. Using two application scenarios, we show how monitoring and evaluation of Green Metrics enables to improve energy efficiency.

Energy Aware Dynamic Resource Consolidation Algorithm for Virtualized Service Centers Based on Reinforcement Learning

In this paper we propose an energy aware dynamic consolidation algorithm for virtualized service centers based on reinforcement learning. The energy awareness is enacted by using the Energy Aware Context Model (EACM) to programmatically represent the current service center context situation by means of ontologies. We have defined the EACM model entropy metric for evaluating the service center greenness level. If the entropy value is above a predefined threshold, the service center is not in a green state. As a consequence, consolidation or dynamic power management actions are selected by means of reinforcement learning and executed to bring back the service center in an energy efficient state. The results are promising showing that the proposed energy aware consolidation algorithm decreases the energy consumption with about 26% from the total energy consumption of a service center.

Immune-inspired method for selecting the optimal solution in web service composition

This paper presents an immune-inspired algorithm applied in the context of Web service composition to select the optimal composition solution. Our approach models Web service composition as a multi-layered process which creates a planning-graph structure along with a matrix of semantic links. We have enhanced the classical planning graph with the new concepts of service cluster and semantic similarity link. The semantic similarity links are defined between services on different graph layers and are stored in a matrix of semantic links. To calculate the degree of the semantic match between services, we have adapted the information retrieval measures of recall, precision and F_Measure. The immune-inspired algorithm uses the enhanced planning graph and the matrix of semantic links to select the optimal composition solution employing the QoS attributes and the semantic quality as the selection criteria.

Fluent calculus-based Web service composition — From OWL-S to fluent calculus

Web service composition facilitates the creation of new services out of existing ones, for satisfying a complex functionality. Automatic Web service composition is considered as one of the most promising features that can be realized by Web services. This paper presents a novel approach for semantic Web service composition based on the fluent calculus. We show how the planning capabilities of the fluent calculus can be used to automatically generate a Web service composition. We have identified a mapping between an OWL-S process ontology and the fluent calculus concepts. We also present an algorithm to translate OWL-S service descriptions into an equivalent fluent calculus service specification. This specification is then forwarded as input to a flux planner to generate the plans that solve the composition goal. As a result, the solution for the requested functionality of the composed Web service is obtained. FLUX is used as the logic programming method to implement the mathematical formalism of the fluent calculus.

Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

Ant-Inspired Technique for Automatic Web Service Composition and Selection

This paper presents a technique for semantic Web service composition inspired by the behavior of ants. The proposed technique combines a service composition graph model with the ant colony optimization met heuristic to select the optimal composition solution. In our approach, we have considered as selection criteria the QoS attributes of the services and the semantic quality of the connections between the services involved in a composition solution.

Semantic Web Service Clustering for Efficient Discovery Using an Ant-Based Method

This paper presents an ant-inspired method for clustering semantic Web services. The method considers the degree of semantic similarity between services as the main clustering criterion. To measure the semantic similarity between two services we propose a matching method and a set of metrics. The proposed metrics evaluate the degree of match between the ontology concepts describing two services. We have tested the ant-inspired clustering method on the SAWSDL-TC benchmark and we have evaluated its performance using the Dunn Index, the Intra-Cluster Variance metric and an original metric we introduce in this paper.

RAP - a basic context awareness model

This paper addresses two fundamental research problems in the domain of context sensitive systems: the development of a generic context model that can be used to represent general purpose contexts in a computer interpretable way and the context model management. The context model is represented using a triple set consisting of context resources, actors and policies. The model is mapped onto real contexts by populating the sets with context specific elements. A context situation to which a context aware system must adapt is represented by a specific context model instance. To ease the context reasoning and adaptation processes, a core ontology is defined to represent the relationships between the context model concepts. The core ontology is extended with domain specific concepts as ontology sub-trees. For the context model management problem we propose an agent based solution using BDI agents.