Q-CAD: QoS and context aware discovery framework for mobile systems

Capra, Licia; Zachariadis, Stefanos; Mascolo, Cecilia

doi:10.1109/perser.2005.1506566

Cited by 23 publications

(17 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the proposed approaches in Q_CAD [11] and DINO [12] some frameworks are recommended for the selection of the optimum service regarding the context and QoS information. One considerable point About Q_CAD framework is that it does not support the dynamic adaptation process of service request at runtime.…”

Section: Related Workmentioning

confidence: 99%

A Framework for Optimizing the Response Quality of Services in Mobile Cloud Computing Systems

Zahedian¹,

Delavar²,

Aryan³

2014

IJCA

View full text Add to dashboard Cite

The subject of providing mobile users with an optimized service based on the Service Level Agreement (SLA) in cloud computing environment is one of the controversial issues, because there are a lot of challenging features in this environment such as the heterogeneity of cloud resources and also processing power of mobile phones.In this article, a framework called CSRAM is proposed for optimizing the response quality of services (QoS) in mobile cloud computing systems that tries to increase the precision and speed of the best service selection by offloading part of the computations to the cloud as well as using the context information of service provider in request adaptation process.In the proposed framework, it was tried to design a modular system and also to consider an appropriate algorithm for using in service request adaptation process. Finally, with regarding to seven effective environmental parameters as the inputs and also, with comparison between CSRAM framework and another applied framework, more flexibility was achieved in changing the environmental parameters of the problem, Reduction in the imposed computational load on user's mobile phone and also, increase in solution precision based on the reality.

show abstract

Section: Related Workmentioning

confidence: 99%

A Framework for Optimizing the Response Quality of Services in Mobile Cloud Computing Systems

Zahedian¹,

Delavar²,

Aryan³

2014

IJCA

View full text Add to dashboard Cite

show abstract

“…More closely related to our work are approaches that take into consideration mobility of devices, and thus services. In [5,11] (single) service discovery protocols have been proposed that aim to find the device capable of delivering the best quality of service, given the dynamicity of the current environment; the discovery protocol has also been extended to consider multi-hop networks [16]. We argue that, while important, QoS reasoning must come after colocation reasoning, especially for services that require more than just a few seconds to complete.…”

Section: Related Workmentioning

confidence: 99%

Reliable Discovery and Selection of Composite Services in Mobile Environments

Prete

Capra

2008

2008 12th International IEEE Enterprise Distributed Object Computing Conference

View full text Add to dashboard Cite

Service providers as we know them nowadays are the always-on "static" web service providers, that aim at Five9 availability (99.999%). Formal, or de-facto, standards, such as WSDL and BPEL, have become technology enablers for the easy discovery, use and coordination of such services. However, we envisage tomorrow's services to become increasingly pervasive, being deployed within buildings, transport systems, markets, as well as people portable devices. Such services will be, by their own nature, simple and fine grained; as a consequence, service composition will become crucial to deliver rich functionalities that satisfy end users requests. Composing services in mobile environments opens up significant challenges. In particular, the Five9 availability assumption no longer holds: the higher the dynamic nature of the environment, the higher the chances that services will move out-of-reach before the composition completes, causing the service as a whole to fail. We argue that, in order to enable the successful completion of compound services, the reliability of the composition must be measured and reasoned about. In order to do so, we propose to dynamically deploy a prediction model to estimate the duration of colocation between component services. These estimates are fed in input to a service composition semantics reasoner, which then autonomically selects those providers, within the current environment, that maximise the chances of successful compound service completion. We demonstrate the positive impact that the reliability reasoning has onto the ratio of successfully completed compound services in a typical human movement scenario.

show abstract

“…Solar [2] is a middleware platform that enables context-aware applications to locate environmental services based on the current context. Q-CAD [1] is a QoS and contextaware resource discovery framework for pervasive environments. Each application dynamically specifies in its profile context parameters to be taken into account when discovering resources, and also specifies a utility function to be maximized when binding the most suitable resources.…”

Section: Related Workmentioning

confidence: 99%

“…As users need to discover and interoperate with such services, service discovery represents a crucial functionality. In order to be effective, service discovery mechanisms need to cope 1 While visiting the ARLES project at INRIA. 2 This work is part of the IST UBISEC project and has been funded by the European Commission, FP6 contract number 506926, http://www.ubisec.org/.…”

Section: Introductionmentioning

confidence: 99%