Self-adaptive software: development approach and automatic process for adaptation at runtime

Affonso, Frank José; Nakagawa, Elisa Yumi

doi:10.5335/rbca.2015.4224

Cited by 2 publications

(4 citation statements)

References 32 publications

(43 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, [10] presented reference architecture and an approach to the development and adaptation of software systems at runtime. The researchers-initiated Software Engineering for Self-adaptive Software which incorporates adaptations with no interruption in the execution.…”

Section: Related Workmentioning

confidence: 99%

“…As mentioned above, self-adaptive system make-sense about its runtime behavior and undertake necessary adjustment that changes it. However, the development of such system is somewhat complex because it has to constantly change structural and/or behavioral features at runtime in other to meet users or execution environment needs [10]. In view of this, a number of software engineering models, techniques, methods, and approaches have been designed and/or deployed.…”

Section: Self Adaptive Systemsmentioning

confidence: 99%

“…Also, [27] (as referenced in [10]) presented reference architecture for self-adaptive system; the suggested architecture is made-up of a core for adaptation (represented by dotted lines) and four complementary modules (the development, action plan, adaptation rule, and infrastructure modules) as shown in Figure 1 below. The adaptation module (see Figure 1) assists the adaptation activity of the software entities.…”

Section: Self Adaptive Systemsmentioning

confidence: 99%

“…Furthermore, [10], [26], and [6] adopted MAPE-K (Monitor, Analyze, Plan, Execute, and knowledge) control loop as a solution to manage the software adaptation at runtime. The researchers went one step further to summarize the control loop as shown in Figure 2, thus: The Monitor process has mechanisms that gather data from sensors and convert them to behavioral patterns and symptoms; (ii)…”

Section: Self Adaptive Systemsmentioning

confidence: 99%

See 3 more Smart Citations

An Embeddable Self-Reflective Self-Adaptive Software Model for Resource Management

Adenowo¹,

Yussuff²,

Oluyemi³

et al. 2019

ETRJ

View full text Add to dashboard Cite

With the growing complexity of today's world, there is rise in the design of smart and autonomous technologies. These technologies (or systems) are usually software-intensive and should have ability to self-manage, optimize resources, eliminate or reduce human intervention and still achieve quality and optimal output(s). Thus, technologies of this nature should self-reflect and self-adapt to internal and external factors to achieve its desired goal. Self-reflective, selfadaptive concepts are (or can be) used in a number of different areas including: robotics systems, autonomous computing, space systems, manufacturing, recommender systems, and e-commerce (for transactions monitoring), among others. These technologies basically have software component, which are usually underpinned by model(s). The main goal of this research, therefore, is to develop an embeddable software model (with self-reflective, selfadaptive properties) that shows real-time resource management. In developing our model, we particularly took into cognizance MAPE-K template for identification of self-* properties and performance requirements. We applied a Case Study within a particular domain (the education sector) to demonstrate the usability of this software model in managing human resource (a primary resource). The software model is able to reflect and modify its behavior at run-time in response to internal and external factors. Evaluation results show that the software model successfully self-manage the deployment of human resources; it was able to determine over/under-staffing, and redistribute (and/or identify recruitment needs for) human resource within the domain under consideration.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Self Adaptive Systemsmentioning

confidence: 99%