QoS-Aware Multi-granularity Service Composition Based on Generalized Component Services

Wu, Quanwang; Zhu, Qingsheng; Jian, Xing

doi:10.1007/978-3-642-45005-1_33

Cited by 8 publications

(10 citation statements)

References 12 publications

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“…The first step of solving the QoS-aware service composition problem is to define a QoS model, a set of QoS aggregation rules and a utility function. Existing works have discussed these topics extensively, e.g., in [43], [44], [45]. However, the aggregation rules in existing works focus on conventional web services rather than complex event services, which need a different QoS aggregation schema.…”

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

“…The above GA-based approaches can only evaluate service composition plans with fixed sets of service tasks (abstract services) and cannot evaluate composition plans which are semantically equivalent but consists of different service tasks, i.e., service tasks on different granularity levels. A more recent work in [45] addresses this issue by presenting the concept of Generalized Component Services (GCS) and developing the GA encoding techniques and genetic operators based on GCS. Results in [45] indicate that up to 10% utility enhancement can be obtained by expanding the search space.…”

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

“…A more recent work in [45] addresses this issue by presenting the concept of Generalized Component Services (GCS) and developing the GA encoding techniques and genetic operators based on GCS. Results in [45] indicate that up to 10% utility enhancement can be obtained by expanding the search space. Composing events on different granularity levels is also a desired feature for complex event service composition.…”

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

“…Composing events on different granularity levels is also a desired feature for complex event service composition. However, the work described in [45] only caters for Input, Output, Precondition and Effect (IOPE) based service compositions, which creates composition plans as imperative workflows. Complex event service composition creates declarative event patterns (transformed from the requested event pattern with the same event semantics) as composition plans.…”

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

See 3 more Smart Citations

Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams

Kolozali

Bermúdez-Edo

Farajidavar

et al. 2019

IEEE Internet Things J.

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An increasing number of cities are confronted with challenges resulting from the rapid urbanisation and new demands that a rapidly growing digital economy imposes on current applications and information systems. Smart city applications enable city authorities to monitor, manage and provide plans for public resources and infrastructures in city environments, while offering citizens and businesses to develop and use intelligent services in cities. However, providing such smart city applications gives rise to several issues such as semantic heterogeneity and trustworthiness of data sources, and extracting up-to-date information in real time from large-scale dynamic data streams. In order to address these issues, we propose a novel framework with an efficient semantic data processing pipeline, allowing for real-time observation of the pulse of a city. The proposed framework enables efficient semantic integration of data streams and complex event processing on top of real-time data aggregation and quality analysis in a Semantic Web environment. To evaluate our system, we use real-time sensor observations that have been published via an open platform called Open Data Aarhus by the City of Aarhus. We examine the framework utilising Symbolic Aggregate Approximation to reduce the size of data streams, and perform quality analysis taking into account both single and multiple data streams. We also investigate the optimisation of the semantic data discovery and integration based on the proposed stream quality analysis and data aggregation techniques.

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Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

Section: Complex Event Processing and Qos-aware Event Service Composimentioning

confidence: 99%

See 2 more Smart Citations

Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams

Kolozali

Bermúdez-Edo

Farajidavar

et al. 2019

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…Indeed, non-functional properties, e.g. : Quality-of-Service (QoS) properties, can play a pivotal role in service composition (Wu, Zhu, & Jian, 2013).…”

Section: Introductionmentioning

confidence: 99%

QoS-Aware Stream Federation and Optimization Based on Service Composition

Gao

Ali

Curry

et al. 2016

International Journal on Semantic Web and Information Systems

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The proliferation of sensor devices and services along with the advances in event processing brings many new opportunities as well as challenges. It is now possible to provide, analyze and react upon real-time, complex events in urban environments. When existing event services do not provide such complex events directly, an event service composition maybe required. However, it is difficult to determine which event service candidates (or service compositions) best suit users' and applications' quality-of-service requirements. A sub-optimal service composition may lead to inaccurate event detection, lack of system robustness etc. In this paper, the authors address these issues by first providing a quality-of-service aggregation schema for complex event service compositions and then developing a genetic algorithm to efficiently create near-optimal event service compositions. The authors evaluate their approach with both real sensor data collected via Internet-of-Things services as well as synthesised datasets.

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QoS-Aware Complex Event Service Composition and Optimization Using Genetic Algorithms

Gao¹,

Curry²,

Ali³

et al. 2014

Service-Oriented Computing

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QoS-Aware Multi-granularity Service Composition Based on Generalized Component Services

Cited by 8 publications

References 12 publications

Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams

Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams

QoS-Aware Stream Federation and Optimization Based on Service Composition

QoS-Aware Complex Event Service Composition and Optimization Using Genetic Algorithms

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