The Experts below are selected from a list of 19752 Experts worldwide ranked by ideXlab platform
A. Yachir - One of the best experts on this subject based on the ideXlab platform.
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Energy-centered and QoS-aware Services selection for Internet of Things
IEEE Transactions on Automation Science and Engineering, 2016Co-Authors: M. S. Khanouche, Abdelghani Chibani, Yacine Amirat, M. Kerkar, A. YachirAbstract:An important challenge to be addressed in the domain of Internet of Things (IoT) is the development of efficient Services selection algorithms for an optimal management of both energy and Quality of Service (QoS) in the context of IoT Services composition. This issue becomes crucial in the case of large-scale IoT environments composed of thousands of distributed entities. In this paper, an energy-centered and QoS-aware Services selection algorithm (EQSA) is proposed for IoT Services composition. The proposed selection approach consists of preselecting the Services offering the QoS level required for user's satisfaction using a lexicographic optimization strategy and QoS constraints relaxation technique. In order to reduce the energy consumption of a composite Service without affecting the user's satisfaction, the most suitable Services among the preselected ones are then selected using the concept of relative dominance of Services in the sense of Pareto. The relative dominance of a Candidate Service depends on its energy profile and QoS attributes, and user's preferences. The proposed algorithm has been evaluated through several simulation scenarios. The obtained results show clearly the good performances of the EQSA algorithm in terms of selection time, energy efficiency, composition lifetime, and optimality and its added value in comparison with algorithms dealing separately with QoS and energy consumption.
Saeed Mansour - One of the best experts on this subject based on the ideXlab platform.
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to establish enterprise Service model from enterprise business model
IEEE International Conference on Services Computing, 2008Co-Authors: Pooyan Jamshidi, Mohsen Sharifi, Saeed MansourAbstract:One of the key activities that are needed to construct a quality Service-oriented solution is the identification of its architectural elements with the right granularity. The selection of an appropriate method for identification of Services from business models of an enterprise is thus quite crucial to the success of any Service-oriented solution for that enterprise. Existing methods for Service identification ignore required performance metrics and semantics integrity of business elements; more importantly, they focus on entity-based Services while ignoring process based ones. This paper proposes a new process for identification and specification of enterprise software Services and their architectural elements. A novel clustering technique, named elementary business process and business entity affinity analysis technique (EEAT), is introduced for identifying Candidate architectural elements. This technique identifies each Candidate Service with the right granularity, while satisfying low coupling, high cohesion, and low reuse cost principles for reusable software Services.
Ryszard Kowalczyk - One of the best experts on this subject based on the ideXlab platform.
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a decentralized Service discovery approach on peer to peer networks
IEEE Transactions on Services Computing, 2013Co-Authors: Qiang He, Yun Yang, Ryszard KowalczykAbstract:Service-Oriented Computing (SOC) is emerging as a paradigm for developing distributed applications. A critical issue of utilizing SOC is to have a scalable, reliable, and robust Service discovery mechanism. However, traditional Service discovery methods using centralized registries can easily suffer from problems such as performance bottleneck and vulnerability to failures in large scalable Service networks, thus functioning abnormally. To address these problems, this paper proposes a peer-to-peer-based decentralized Service discovery approach named Chord4S. Chord4S utilizes the data distribution and lookup capabilities of the popular Chord to distribute and discover Services in a decentralized manner. Data availability is further improved by distributing published descriptions of functionally equivalent Services to different successor nodes that are organized into virtual segments in the Chord4S circle. Based on the Service publication approach, Chord4S supports QoS-aware Service discovery. Chord4S also supports Service discovery with wildcard(s). In addition, the Chord routing protocol is extended to support efficient discovery of multiple Services with a single query. This enables late negotiation of Service Level Agreements (SLAs) between Service consumers and multiple Candidate Service providers. The experimental evaluation shows that Chord4S achieves higher data availability and provides efficient query with reasonable overhead.
Lei Wang - One of the best experts on this subject based on the ideXlab platform.
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two stage approach for reliable dynamic web Service composition
Knowledge Based Systems, 2016Co-Authors: Zhizhong Liu, Dianhui Chu, Zongpu Jia, Jiquan Shen, Lei WangAbstract:This paper proposes a two-stage method for reliable dynamic Web Service composition and improves the reliability of dynamic Web Service composition.In the first stage, the scale of Candidate Services is reduced and the Service composition problem is transformed to local Service selection problem.In the second stage, QoS of Candidate Services are predicted and used to select the optimal Services for tasks in the Service composition workflow.Culture Genetic Algorithm (CGA) is proposed to reduce Candidate Services and decompose the global QoS constraints into local QoS constraints.It proposes a Web Service QoS dynamic prediction method based on improvedÂ?case-based reasoning (CBR). Web Service composition is a key technology for creating value-added Services by integrating available Services. With the rapid development of Service Computing, Cloud Computing, Big Data, and the Internet of Things, mass Services with the same functionalities and different quality of Service (QoS) values are available on the Internet. Moreover, due to the uncertainties of Services' application environment, a Service's QoS is highly dynamic; these two factors cause reliable dynamic Web Service composition to be a challenge. To address this issue, this paper proposes a two-stage approach for reliable dynamic Web Service composition. In the first stage, the top K Web Service composition schemes based on each Service's historical QoS values are selected with the proposed algorithm named Culture Genetic Algorithm (CGA). Then, component Services in the top K schemes are filtered out and employed as the Candidate Services for dynamic Service composition. This operation can greatly reduce the number of available Services and filter out better Candidate Services for dynamic Service composition. Next, the global QoS constraints are decomposed into local QoS constraints with the CGA algorithm, and the global optimal problem of Service composition is transformed into a local optimal Service selection problem; this conversion increases the flexibility of dynamic Service composition and provides a chance to predict QoS values of Services before Service selection. In the second stage, before selecting the best Service for each task during the running of the Service composition workflow, QoS values of each Candidate Service are predicted based on the improved case-based reasoning, and the best Service is selected according to the predicted QoS values. Through QoS prediction, the reliability of the composite Web Service can be greatly enhanced. Finally, experimental results show that the proposed method is feasible and effective.
M. S. Khanouche - One of the best experts on this subject based on the ideXlab platform.
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Energy-centered and QoS-aware Services selection for Internet of Things
IEEE Transactions on Automation Science and Engineering, 2016Co-Authors: M. S. Khanouche, Abdelghani Chibani, Yacine Amirat, M. Kerkar, A. YachirAbstract:An important challenge to be addressed in the domain of Internet of Things (IoT) is the development of efficient Services selection algorithms for an optimal management of both energy and Quality of Service (QoS) in the context of IoT Services composition. This issue becomes crucial in the case of large-scale IoT environments composed of thousands of distributed entities. In this paper, an energy-centered and QoS-aware Services selection algorithm (EQSA) is proposed for IoT Services composition. The proposed selection approach consists of preselecting the Services offering the QoS level required for user's satisfaction using a lexicographic optimization strategy and QoS constraints relaxation technique. In order to reduce the energy consumption of a composite Service without affecting the user's satisfaction, the most suitable Services among the preselected ones are then selected using the concept of relative dominance of Services in the sense of Pareto. The relative dominance of a Candidate Service depends on its energy profile and QoS attributes, and user's preferences. The proposed algorithm has been evaluated through several simulation scenarios. The obtained results show clearly the good performances of the EQSA algorithm in terms of selection time, energy efficiency, composition lifetime, and optimality and its added value in comparison with algorithms dealing separately with QoS and energy consumption.
