The Vision of Autonomic Computing

By Jeffrey O. Kephart, David M. Chess. Computer, 2003

7,134 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/bff65e9da04d89e9248feb89110b1cc5fa1d99ca

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Citations in the corpus

A survey on engineering approaches for self-adaptive systems (2015, methodology): “The external approach separates the adaptation logic and managed resources [23] and connects them via sensors and effectors [2].”
Context-Aware Computing, Learning, and Big Data in Internet of Things: A Survey (2018, background): “Futuristic ideas for IoT are also emerging and deﬁned as self-conﬁgurable, self-optimized, self-protected, and self-healed IoT devices and systems [62], [63].”
Service-Oriented Computing: a Research Roadmap (2008, background): “The function of any autonomic capability is a control loop that collects details from the system and acts accordingly.(4,40,46) Although there can be numerous types of control loops in a system, they can be naturally divided into five categories: selfconfiguring, self-adapting, self-healing, self-op”
Using Magpie for Request Extraction and Workload Modelling (2004, background): “Magpie is a preliminary step towards systems that are robust, performance-aware and self-configuring (Autonomic Computing [12] is a well known articulation of this grand vision).”
AI for Next Generation Computing: Emerging Trends and Future Directions (2022, positive): “here are four stages to the IBM model of an autonomic system [1]: Monitor, analyse, plan, and execute are the four steps in he process, which will be supported by AI/ML models to improve the monitoring, analysing, planning and execution.”
Digital ecosystems in the clouds: Towards community cloud computing (2009, methodology): “The conceptualisation of the Community Cloud draws upon Cloud Computing [20], Grid Computing [9], Digital Ecosystems [48], Green Computing [63] and Autonomic Computing [12].”
Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber-physical convergence (2012, neutral): “A number of autonomic computing approaches propose ‘‘add-ons’’ to be integrated in existing frameworks such as the one from ‘‘à la IBM’’, that suggests coupling sophisticated control loops to existing systems to support selfmanagement [13].”
Software Engineering for Self-Adaptive Systems: A Second Research Roadmap (2010, methodology): “This means, for example, to add a V&V component to every phase of the MAPE-K loop [30].”
Dynamic Software Product Lines (2008, methodology): “In this aspect, the DSPL approach is less restrictive than other approaches to adaptive systems like autonomous computing [2] or self-adaptive systems [1], etc.”
A survey of autonomic communications (2006, methodology): “A high profile use of autonomic techniques is provided by IBM’s autonomic computing initiative [Kephart and Chess 2003].”
Internet of Things in Industries: A Survey (2014, background): “Future IoT systems should have characteristics including “self-configuration, self-optimization, self-protection, and selfhealing” [81], [82].”
Trust in multi-agent systems (2004, background): “…( Berners-Lee et al ., 2001), Web services ( McIlraith et al ., 2001), e-business ( Deitel et al ., 2001), m-commerce ( Vulkan , 1999; Sadeh , 2002), autonomic computing ( Kephart & Chess , 2003), the grid ( Foster & Kesselman , 1998), and pervasive computing environments ( Schmeck et al ., 2002).”
On the use of hybrid reinforcement learning for autonomic resource allocation (2007, background): “1, which depicts an IBM-proposed vision [7] of the general operation of Autonomic Computing systems.”
A survey of autonomic computing—degrees, models, and applications (2008, methodology): “The term autonomic computing was first used by IBM in 2001 to describe computing systems that are said to be self-managing [Kephart and Chess 2003].”
Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud (2013, neutral): “…intelligent and autonomic behavior with respect to participation in collaborative activities [32] supporting self-monitoring, self-healing, and self-management of the service environment in response to the dynamics of the business-to-business (B2B) and the business-to-customer (B2C) contexts [28].”