Dependable Risk-Aware Efficiency Improvement for Self-Organizing Emergent Systems

Hudson, Jonathan; Denzinger, Jörg; Kasinger, Holger; Bauer, Bernhard

doi:10.1109/saso.2011.12

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…The IoT domain shares a high overlap with the networking domain as IoT solutions are essentially localized networks. The trends of the IoT research in this phase is consistent with the themes of generic frameworks [1], [160], [172], [180], [297] and validation [129], [130].…”

Section: -2015 -The Last Decade -First Halfsupporting

confidence: 70%

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Wong¹,

Wagner²

2021

Preprint

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Championed by IBM's vision of autonomic computing paper in 2003, the autonomic computing research field has seen increased research activity over the last 20 years. Several conferences (SEAMS, SASO, ICAC) and workshops (SISSY) have been established and have contributed to the autonomic computing knowledge base in search of a new kind of system -a self-adaptive system (SAS). These systems are characterized by being context-aware and can act on that awareness. The actions carried out could be on the system or on the context (or environment). The underlying goal of a SAS is the sustained achievement of its goals despite changes in its environment. Despite a number of literature reviews on specific aspects of SASs ranging from their requirements to quality attributes, we lack a systematic understanding of the current state of the art. This paper contributes a systematic literature review into self-adaptive systems using the dblp computer science bibliography as a database. We filtered the records systematically in successive steps to arrive at 293 relevant papers. Each paper was critically analyzed and categorized into an attribute matrix. This matrix consisted of five categories, with each category having multiple attributes. The attributes of each paper, along with the summary of its contents formed the basis of the literature review that spanned 30 years . We characterize the maturation process of the research area from theoretical papers over practical implementations to more holistic and generic approaches, frameworks, and exemplars, applied to areas such as networking, web services, and robotics, with much of the recent work focusing on IoT and IaaS.

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Section: -2015 -The Last Decade -First Halfsupporting

confidence: 70%

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Wong¹,

Wagner²

2021

Preprint

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“…Many works take inspiration from nature [18] to use well-studied self-organisation mechanisms (famous examples to solve optimisation problem are ant colony optimisation [19], or particle swarm optimisation [35]). Also, some works propose generic (hence reusable) frameworks handling and constraining the self-organising aspects of the system [44], or generic external mechanism to adapt the functioning of the agents at runtime [32].…”

Section: Related Work and Discussionmentioning

confidence: 99%

Methodological Guidelines for Engineering Self-organization and Emergence

Noël

Zambonelli

2015

Lecture Notes in Computer Science

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The ASCENS project deals with the design and development of complex self-adaptive systems, where self-organization is one of the possible means by which to achieve self-adaptation. However, to support the development of self-organising systems, one has to extensively re-situate their engineering from a software architectures and requirements point of view. In particular, in this chapter, we highlight the importance of the decomposition in components to go from the problem to the engineered solution. This leads us to explain and rationalise the following architectural strategy: designing by following the problem organisation. We discuss architectural advantages for development and documentation, and its coherence with existing methodological approaches to self-organisation, and we illustrate the approach with an example on the area of swarm robotics

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“…There are several energy efficiency approaches reported in the literature on node localization. Hyperheuristic schemes are high level approaches with combinatorial optimization resolutions [14][15][16][17][18]. Hyperheuristics are used to resolve hard computational search problems.…”

Section: Literature Reviewmentioning

confidence: 99%

An Innovative Hyperheuristic, Gaussian Clustering Scheme for Energy‐Efficient Optimization in Wireless Sensor Networks

2021

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Energy stability on sensor nodes in wireless sensor networks (WSNs) is always an important challenge, especially during data capturing and transmission of packets. The recent advancement in distributed clustering algorithms in the extant literature proposed for energy efficiency showed refinements in deployment of sensor nodes, network duration stability, and throughput of information data that are channelled to the base station. However, much scope still exists for energy improvements in a heterogeneous WSN environment. This research study uses the Gaussian elimination method merged with distributed energy efficient clustering (referred to as DEEC-Gauss) to ensure energy efficient optimization in the wireless environment. The rationale behind the use of the novel DEEC-Gauss clustering algorithm is that it fills the gap in the literature as researchers have not been able to use this scheme before to carry out energy-efficient optimization in WSNs with 100 nodes, between 1,000 and 5000 rounds and still achieve a fast time output. In this study, using simulation, the performance of highly developed clustering algorithms, namely, DEEC, EDEEC_E, and DDEEC, was compared to the proposed Gaussian Elimination Clustering Algorithm (DEEC-Gauss). The results show that the proposed DEEC-Gauss Algorithm gives an average percentage of 4.2% improvement for the first node dead (FND), a further 2.8% improvement for the tenth node dead (TND), and the overall time of delivery was increased and optimized when compared with other contemporary algorithms.

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Dependable Risk-Aware Efficiency Improvement for Self-Organizing Emergent Systems

Cited by 6 publications

References 21 publications

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Methodological Guidelines for Engineering Self-organization and Emergence

An Innovative Hyperheuristic, Gaussian Clustering Scheme for Energy‐Efficient Optimization in Wireless Sensor Networks

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