ServiceStore: A Peer-to-Peer Framework for QoS-Aware Service Composition

Jin, Jun; Zhang, Yunlong; Cao, Ye; Pu, Xing; Li, Jiaxin

doi:10.1007/978-3-642-15672-4_17

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…Aiming at selecting a qualified web service for certain applications, efforts have been widely exerted in service location over P2P‐based systems . For example, in , they propose a distributed hash table‐based P2P service composition framework, called ServiceStore, for QoS‐aware service composition. In their ServiceStore, service selection and composition are distributed to the involved task brokers, requesting nodes, and service nodes.…”

Section: Discussionmentioning

confidence: 99%

A QoS‐aware service discovery method for elastic cloud computing in an unstructured peer‐to‐peer network

Lin

Dou

et al. 2013

Concurrency and Computation

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SUMMARY Traditionally, service discovery is often promoted by the centralized approach that typically suffers from single point of failure, poor reliability, poor scalability, to name a few. In view of this challenge, a QoS‐aware service discovery method is investigated for elastic cloud computing in an unstructured peer‐to‐peer network in this paper. Concretely speaking, the method is deployed by two phases, that is, service registering phase and service discovery phase. More specifically, for a peer node engaged in the unstructured peer‐to‐peer network, it firstly registers its functional and nonfunctional information to its neighbors in a flooding way. With the multiple registered information, the QoS‐aware service discovery is promoted in a probabilistic flooding way according to the network traffic. At last, extensive simulations are conducted to evaluate the feasibility of our method. Copyright © 2013 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 99%

A QoS‐aware service discovery method for elastic cloud computing in an unstructured peer‐to‐peer network

Lin

Dou

et al. 2013

Concurrency and Computation

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“…However, they decompose the global QoS constraint imposed on a given QoS property into the average values of that property associated with the services of each activity, which is not accurate and may discriminate a number of service candidates. A similar approach is presented by Jin et al [27]. The authors decompose global QoS constraints into local constraints using MILP, then they perform local selection.…”

Section: Related Workmentioning

confidence: 99%

Muti-Objective Service Composition in Ubqutious Environments With Service Dependencies

Mabrouk¹,

Georgantas²,

Issarny³

2016

STSC

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Service composition is a widely used method in ubiquitous computing that enables accomplishing complex tasks required by users based on elementary (hardware and software) services available in ubiquitous environments. To ensure that users experience the best Quality of Service (QoS) with respect to their quality needs, service composition has to be QoS-aware. Establishing QoS-aware service compositions entails efficient service selection taking into account the QoS requirements of users. A challenging issue towards this purpose is to consider service selection under global QoS requirements (i.e., requirements imposed by the user on the whole task), which is of high computational cost. This challenge is even more relevant when we consider the dynamics, limited computational resources and timeliness constraints of ubiquitous environments. To cope with the above challenge, we present QASSA, an efficient service selection algorithm that provides the appropriate ground for QoS-aware service composition in ubiquitous environments. QASSA formulates service selection under global QoS requirements as a set-based optimisation problem, and solves this problem by combining local and global selection techniques. In particular, it introduces a novel way of using clustering techniques to enable fine-grained management of trade-offs between QoS objectives. QASSA further considers: (i) dependencies between services, (ii) adaptation at run-time, and (iii) both centralised and distributed design fashions. Results of experimental studies performed using real QoS data are presented to illustrate the timeliness and optimality of QASSA.

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“…However, they decompose the global QoS constraint imposed on a given QoS property into the average values of that property associated with the services of each activity, which is not accurate and may discriminate a number of service candidates. A similar approach is presented by Jin et al [23]. The authors decompose global QoS constraints into local constraints using MILP, then they perform local selection.…”

Section: Related Workmentioning

confidence: 99%

Set-Based Bi-level Optimisation for QoS-Aware Service Composition in Ubiquitous Environments

Mabrouk

Georgantas

Issarny

2015

2015 IEEE International Conference on Web Services

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Service composition is a widely used method in ubiquitous computing that enables accomplishing complex tasks required by users based on elementary (hardware and software) services available in ubiquitous environments. To ensure that users experience the best Quality of Service (QoS) with respect to their quality needs, service composition has to be QoS-aware. Establishing QoS-aware service compositions entails efficient service selection taking into account the QoS requirements of users. A challenging issue towards this purpose is to consider service selection under global QoS requirements (i.e., requirements imposed by the user on the whole task), which is of high computational cost. This challenge is even more relevant when we consider the dynamics, limited computational resources and timeliness constraints of ubiquitous environments.To cope with the above challenge, in this paper we present QASSA, an efficient service selection algorithm that provides the appropriate ground for QoS-aware service composition in ubiquitous environments. The contribution of QASSA is three-fold. First, it formulates service selection under global QoS requirements as a setbased optimisation problem, benefiting from recent proposals in the domain of multi-objective optimisation. Second, QASSA resolves this problem in an efficient way using clustering techniques, namely the K-Means algorithm. Third, QASSA is devised in two versions, viz., centralised and distributed versions, so that it can be executed on top of centralised and decentralised infrastructures in ubiquitous environments. Results of experimental studies are presented to illustrate the timeliness and optimality of QASSA.

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ServiceStore: A Peer-to-Peer Framework for QoS-Aware Service Composition

Cited by 4 publications

References 7 publications

A QoS‐aware service discovery method for elastic cloud computing in an unstructured peer‐to‐peer network

A QoS‐aware service discovery method for elastic cloud computing in an unstructured peer‐to‐peer network

Muti-Objective Service Composition in Ubqutious Environments With Service Dependencies

Set-Based Bi-level Optimisation for QoS-Aware Service Composition in Ubiquitous Environments

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