A NFR-Based Framework for User-Centered Adaptation

Dalpiaz, Fabiano; Serral, Estefanía; Valderas, Pedro; Giorgini, Paolo; Pelechano, Vicente

doi:10.1007/978-3-642-34002-4_34

Cited by 8 publications

(9 citation statements)

References 20 publications

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“…Each older person has different preferences and contexts, which may depend on the community in which they live, their region, and the time it takes them to get used to their routine 22 . Here we use an approach in which a set of pairs is formed for each NFR and assigned a weight w (a real number in the interval [0,1]) 29 . Each pair indicates the prioritization (w) of the NFR.…”

Section: Associate Personal Contextmentioning

confidence: 99%

A Guide for Specifying Non-Functional Requirements in Ambient Assisted Living Systems

Coelho¹,

Alencar²

2022

JER

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The increase in life expectancy and the aging of the world's population is a reality every year, thanks to advances in technology in the medical field. Technologies such as Ambient Assisted Living (AAL) can provide services that enable seniors to live independently, safely and healthily. During system development, it is important to ensure a good specification of nonfunctional requirements (NFR). They are requirements that define how the system will behave in certain situations and can impact the final objective of the software if they are not considered during the analysis and development of the project. To meet and identify all needs and functions provided to system users, this article provides a guide for specifying non-functional requirements in Ambient Assisted Living, which helps the requirements engineer to specify the important requirements in the development of this system, capturing the requirements with techniques such as storytelling, reuse and legal requirements. Based on the systematic mapping, the main non-functional requirements for each subd o AAL subdomain were identified. An important finding is that the personal context of older people, legal requirements such as ISO/PRF TS 82304-2 and AAL Guidelines for Ethics, Data Privacy and Security directly affect the specification of non-functional requirements and the design of systems. This guide helps with that mapping, showing the requirements engineer what to consider when designing AAL systems.

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Section: Associate Personal Contextmentioning

confidence: 99%

A Guide for Specifying Non-Functional Requirements in Ambient Assisted Living Systems

Coelho¹,

Alencar²

2022

JER

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“…Differently from these approaches, we propose user-centric adaptation for the reconfiguration of multi-tenant services in cloud scenarios where users can come and go, and different service configurations and resources are shared depending on the cloud service model. Dalpiaz et al [2012] propose leveraging the preferences of nonfunctional requirements expressed by a single user as a key driver for adaptation. The collected preferences are used to adapt the selection of routine tasks to be performed in a pervasive infrastructure by a user.…”

Section: Related Workmentioning

confidence: 99%

User-Centric Adaptation Analysis of Multi-Tenant Services

García-Galán

Pasquale

Trinidad

et al. 2016

ACM Trans. Auton. Adapt. Syst.

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Multi-tenancy is a key pillar of cloud services. It allows different users to share computing and virtual resources transparently, meanwhile guaranteeing substantial cost savings. Due to the tradeoff between scalability and customization, one of the major drawbacks of multi-tenancy is limited configurability. Since users may often have conflicting configuration preferences, offering the best user experience is an open challenge for service providers. In addition, the users, their preferences, and the operational environment may change during the service operation, thus jeopardizing the satisfaction of user preferences. In this article, we present an approach to support user-centric adaptation of multi-tenant services. We describe how to engineer the activities of the Monitoring, Analysis, Planning, Execution (MAPE) loop to support user-centric adaptation, and we focus on adaptation analysis. Our analysis computes a service configuration that optimizes user satisfaction, complies with infrastructural constraints, and minimizes reconfiguration obtrusiveness when user- or service-related changes take place. To support our analysis, we model multi-tenant services and user preferences by using feature and preference models, respectively. We illustrate our approach by utilizing different cases of virtual desktops. Our results demonstrate the effectiveness of the analysis in improving user preferences satisfaction in negligible time.

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“…In our approach, we consider an explicit preference model. Dalpiaz et al [9] focus on user preferences over non-functional properties as a key driver for adaptation. However, this approach has its main focus on pervasive infrastructures and describes preferences through user routines.…”

Section: Related Workmentioning

confidence: 99%

User-centric adaptation of multi-tenant services: preference-based analysis for service reconfiguration

García-Galán

Pasquale

Trinidad

et al. 2014

Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

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Multi-tenancy is a key pillar of cloud services. It allows different tenants to share computing resources transparently and, at the same time, guarantees substantial cost savings for the providers. However, from a user perspective, one of the major drawbacks of multi-tenancy is lack of configurability. Depending on the isolation degree, the same service instance and even the same service configuration may be shared among multiple tenants (i.e. shared multi-tenant service). Moreover tenants usually have different -and in most of the cases -conflicting configuration preferences. To overcome this limitation, this paper introduces a novel approach to support user-centric adaptation in shared multi-tenant services. The adaptation objective aims to maximise tenants' satisfaction, even when tenants and their preferences change during the service life-time. This paper describes how to engineer the activities of the MAPE loop to support user-centric adaptation, and focuses on the analysis of tenants' preferences. In particular, we use a game theoretic analysis to identify a service configuration that maximises tenants' preferences satisfaction. We illustrate and motivate our approach by utilising a multi-tenant desktop scenario. Obtained experimental results demonstrate the feasibility of the proposed analysis.

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A NFR-Based Framework for User-Centered Adaptation

Cited by 8 publications

References 20 publications

A Guide for Specifying Non-Functional Requirements in Ambient Assisted Living Systems

A Guide for Specifying Non-Functional Requirements in Ambient Assisted Living Systems

User-Centric Adaptation Analysis of Multi-Tenant Services

User-centric adaptation of multi-tenant services: preference-based analysis for service reconfiguration

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