From Autonomic Computing to Autonomic Networking: An Architectural Perspective

Author(s):  
David Raymer ◽  
Sven van der Meer ◽  
John Strassner
Author(s):  
Prasant Sharma ◽  
Alka Agrawal

Be it industry or academia, Internet of the Things (IoT) has become buzzword today. Everyone is expecting a system of gadgets controlled by web without human intervention. The concept has opened many possibilities and a fear of failure too. All over the world the research is going on and few organizations have already started implementing the concept at a small level. But the available research is still immature and undirectional. The area is very young, the research too. Hence there is a need to develop an IoT architecture which is universally acceptable by various IoT objects as well as server.  To facilitate with the need, the paper presents a novel IOT architecture. In addition, the interaction of IoTobjects with each other has been discussed alongwith connection of a server’s infrastructure with another server’s infrastructure through API gateway.


2021 ◽  
Vol 10 (2) ◽  
pp. 27
Author(s):  
Roberto Casadei ◽  
Gianluca Aguzzi ◽  
Mirko Viroli

Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further opportunity lies in the collaboration of multiple agents or robots. Emerging macro-paradigms provide an approach to programming whole collectives towards global goals. Aggregate computing is one such paradigm, formally grounded in a calculus of computational fields enabling functional composition of collective behaviours that could be proved, under certain technical conditions, to be self-stabilising. In this work, we address the concept of collective autonomy, i.e., the form of autonomy that applies at the level of a group of individuals. As a contribution, we define an agent control architecture for aggregate multi-agent systems, discuss how the aggregate computing framework relates to both individual and collective autonomy, and show how it can be used to program collective autonomous behaviour. We exemplify the concepts through a simulated case study, and outline a research roadmap towards reliable aggregate autonomy.


2005 ◽  
Vol 33 (1) ◽  
pp. 2-5 ◽  
Author(s):  
David M. Chess
Keyword(s):  

Computer ◽  
2009 ◽  
Vol 42 (10) ◽  
pp. 37-43 ◽  
Author(s):  
Carlos Cetina ◽  
Pau Giner ◽  
Joan Fons ◽  
Vicente Pelechano

Author(s):  
George Cybenko ◽  
Vincent Berk ◽  
Ian Gregorio-de.souza ◽  
Chad Behre
Keyword(s):  

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