Towards Trust-Aware and Self-adaptive Systems

Moyano, Francisco; Baudry, Benoît; López, Javier

doi:10.1007/978-3-642-38323-6_20

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Most approaches surveyed focus on the identification of a suitable alternative service as can be seen in the work of Cervantes et al [34]. He et al [14] however propose the adaptation of web service composition based on workflow patterns re-composition.…”

Section: Fig 4 Mape-k Architectural Model For Autonomic Computingmentioning

confidence: 99%

“…Taiani and Fabre [25] describe this as a key challenge in adaptive fault tolerant computing. Moyano et al [26] describe a system that monitors service failure and runtime environment triggers. These are changes in hardware and firmware, including the unpredictable arrival or disappearance of devices and software component.…”

Section: Factors That Influence Adaptationmentioning

confidence: 99%

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State of runtime adaptation in service‐oriented systems: what, where, when, how and right

Mutanu

Kotonya

2019

IET softw.

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Software as a Service reflects a "service-oriented" approach to software development that is based on the notion of composing applications by discovering and invoking network-available services to accomplish some task. However, as more business organizations adopt service-oriented solutions and the demands on them grow, the problem of ensuring that the software systems can adapt fast and effectively to changing business needs, changes in their runtime environment and failures in provided services has become an increasingly important research problem. Dynamic adaptation has been proposed as a way to address the problem. However, for adaptation to be effective several other factors need to be considered. This paper identifies the key factors that influence runtime adaptation in service-oriented systems, and examines how well they are addressed in 29 adaptation approaches intended to support service-oriented systems.

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Section: Fig 4 Mape-k Architectural Model For Autonomic Computingmentioning

confidence: 99%

Section: Factors That Influence Adaptationmentioning

confidence: 99%

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

Mutanu

Kotonya

2019

IET softw.

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“…As a result, trust established among agents promises to create more successful transactions. In fact, trust in a multi-agent environment is "a particular level of beliefs which an agent has about another agent or group of agents to perform a particular action" (Moyano et al, 2013;Bøegh, 2013).…”

Section: Introductionmentioning

confidence: 99%

An incorporated RUU model for multi-agent systems in e-commerce

Majd

Hobson

2020

JEIM

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PurposeThe purpose of this paper is to enhance trust in e-commerce multi-agent systems by presenting a model, called RUU, to select the most trustworthy provider agent based on learning from previous interactions and computing reliability, unreliability and uncertainty.Design/methodology/approachThe methodology comprises analyzing the most representative existing trust models, while a new concept was proposed and measured as unreliability. To make decision about the agents, RUU integrated reliability, unreliability and uncertainty components and used the TOPSIS multi-criteria decision method to select the most trustworthy provider agent. To evaluate the RUU model, the experimentation was carried out in two stages. First, the average accuracy of the model was investigated by simulating RUU in a multi-agent environment. Second, the performance of the model was compared with other related trust models.FindingsThe experimental results revealed that RUU model outperforms current models in providing accurate credibility measurements and computing an accurate trust mechanism for agents, also presenting a decision-making process to choose the most trustworthy provider agent.Research limitations/implicationsThe model presented based on different mathematical computations that take time to be calculated, which is a big limitation of computational models.Practical implicationsRUU enables an agent to make effective and sound decisions in light of the uncertainty that exists in e-commerce multi-agent environments.Originality/valueThis paper is beneficial to enhance the fulfilment of purchasing between provider and requester agents. In fact, the proposed model can ensure critical transactions performed securely in e-commerce multi-agent environments.

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What, Where, When, How and Right of Runtime Adaptation in Service-Oriented Systems

Mutanu

Kotonya

2018

Service-Oriented Computing – ICSOC 2017 Workshops

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Towards Trust-Aware and Self-adaptive Systems

Cited by 4 publications

References 11 publications

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

An incorporated RUU model for multi-agent systems in e-commerce

What, Where, When, How and Right of Runtime Adaptation in Service-Oriented Systems

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