Design Patterns for Self Adaptive Systems Engineering

Abuseta, Yousef; Swesi, Khaled

doi:10.5121/ijsea.2015.6402

Cited by 34 publications

(40 citation statements)

References 20 publications

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“…Although the field emerged from active networks [2], it is making its mark in software overlay networks [3] and distributed system design [4]. In the future, autonomic communications may further increase their hold through the flexibility offered by Software Defined Networks (SDN) [5].…”

Section: Introductionmentioning

confidence: 99%

Big Data for Autonomic Intercontinental Overlays

Brun

Wang

Gelenbe

2016

IEEE J. Select. Areas Commun.

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Abstract-This paper uses Big Data and Machine Learning for the real-time management of Internet scale Qualityof-Service Route Optimisation with an overlay network. Based on the collection of data sampled each 2 minutes over a large number of source-destinations pairs, we show that intercontinental Internet Protocol (IP) paths are far from optimal with respect to Quality of Service (QoS) metrics such as end-to-end round-trip delay. We therefore develop a machine learning based scheme that exploits large scale data collected from communicating node pairs in a multi-hop overlay network that uses IP between the overlay nodes, and selects paths that provide substantially better QoS than IP. Inspired from Cognitive Packet Network protocol, it uses Random Neural Networks with Reinforcement Learning based on the massive data that is collected, to select intermediate overlay hops. The routing scheme is illustrated on a 20-node intercontinental overlay network that collects some 2 × 10 6 measurements per week, and makes scalable distributed routing decisions. Experimental results show that this approach improves QoS significantly and efficiently.

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Section: Introductionmentioning

confidence: 99%

Big Data for Autonomic Intercontinental Overlays

Brun

Wang

Gelenbe

2016

IEEE J. Select. Areas Commun.

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“…Touchpoints exploit attributes or properties of the computing systems to sense running behavior. Abuseta [21] termed such attributes and properties as 'context attributes'. Sensors and effectors respectively offer the ability to obtain and set the value of context attributes at runtime [22].…”

Section: Related Workmentioning

confidence: 99%

“…Different architectures [1,3,7,13], models [4,8,16,17] and design patterns [2,21,23] exist for autonomic computing systems. A great deal of research [1,3,7,9,10] supports IBM's reference model for autonomic computing systems.…”

Section: Related Workmentioning

confidence: 99%

A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

2018

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Abstract:Autonomic computing embeds self-management features in software systems using external feedback control loops, i.e., autonomic managers. In existing models of autonomic computing, adaptive behaviors are defined at the design time, autonomic managers are statically configured, and the running system has a fixed set of self-* capabilities. An autonomic computing design should accommodate autonomic capability growth by allowing the dynamic configuration of self-* services, but this causes security and integrity issues. A secure, scalable and elastic autonomic computing system (SSE-ACS) paradigm is proposed to address the runtime inclusion of autonomic managers, ensuring secure communication between autonomic managers and managed resources. Applying the SSE-ACS concept, a layered approach for the dynamic adaptation of self-* services is presented with an online 'Autonomic_Cloud' working as the middleware between Autonomic Managers (offering the self-* services) and Autonomic Computing System (requiring the self-* services). A stock trading and forecasting system is used for simulation purposes. The security impact of the SSE-ACS paradigm is verified by testing possible attack cases over the autonomic computing system with single and multiple autonomic managers running on the same and different machines. The common vulnerability scoring system (CVSS metric) shows a decrease in the vulnerability severity score from high (8.8) for existing ACS to low (3.9) for SSE-ACS. Autonomic managers are introduced into the system at runtime from the Autonomic_Cloud to test the scalability and elasticity. With elastic AMs, the system optimizes the Central Processing Unit (CPU) share resulting in an improved execution time for business logic. For computing systems requiring the continuous support of self-management services, the proposed system achieves a significant improvement in security, scalability, elasticity, autonomic efficiency, and issue resolving time, compared to the state-of-the-art approaches.

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“…A combination of formal and semi-formal methods is also used in modeling of SAS [8] and the results have been very encouraging [6]. There have been a few studies where formal methods are used successfully in model checking [9] and domain specific languages [14] and design patterns [3] are proposed for development of SAS.…”

Section: Related Workmentioning

confidence: 99%

“…[2]. This aspect motivates the practitioners and researchers to use multiple existing approaches or develop new approaches [3] to handle uncertainties of the system [4].…”

Section: Introductionmentioning

confidence: 99%

Agent based Architecture for Modeling and Analysis of Self Adaptive Systems using Formal Methods

Mian¹,

Ahmad²

2018

ijacsa

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Abstract-Self-adaptive systems (SAS) can modify their behavior during execution; this modification is done because of change in internal or external environment. The need for selfadaptive software systems has increased tremendously in last decade due to ever changing user requirements, improvement in technology and need for building software that reacts to user preferences. To build this type of software we need well establish models that have the flexibility to adjust to the new requirements and make sure that the adaptation is efficient and reliable. Feedback loop has proven to be very effective in modeling and developing SAS, these loops help the system to sense, analyze, plan, test and execute the adaptive behavior at runtime. Formal methods are well defined, rigorous and reliable mathematical techniques that can be effectively used to reason and specify behavior of SAS at design and run-time. Agents can play an important role in modeling SAS because they can work independently, with other agents and with environment as well. Using agents to perform individual steps in feedback loop and formalizing these agents using Petri nets will not only increase the reliability, but also, the adaptation can be performed efficiently for taking decisions at run time with increased confidence. In this paper, we propose a multi-agent framework to model self-adaptive systems using agent based modeling. This framework will help the researchers in implementation of SAS, which is more dependable, reliable, autonomic and flexible because of use of multi-agent based formal approach.

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Design Patterns for Self Adaptive Systems Engineering

Abstract: ABSTRACT

Cited by 34 publications

References 20 publications

Big Data for Autonomic Intercontinental Overlays

Big Data for Autonomic Intercontinental Overlays

A Secure, Scalable and Elastic Autonomic Computing Systems Paradigm: Supporting Dynamic Adaptation of Self-* Services from an Autonomic Cloud

Agent based Architecture for Modeling and Analysis of Self Adaptive Systems using Formal Methods

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