Autonomic Computing: An Overview Manish Parashar and Salim HaririIntroductionThe Autonomic Nervous SystemAshby’s Ultrastable SystemSlide 5Slide 6The Nervous System as a Subsystem of Ashby’s Ultrastable SystemSlide 8The Autonomic Computing ParadigmA Holistic View of Autonomic ComputingArchitecture of an Autonomic ElementSlide 12Autonomic Computing Systems and ApplicationsAutonomic Computing Research Issues and ChallengesThe Autonomic Computing LandscapeSlide 16ConclusionsAgnostic Question 1Agnostic Question 2Agnostic Question 3Agnostic Question 4Agnostic Question 5Agnostic Question 6Agnostic Question 7Agnostic Question 8Autonomic Computing: An Autonomic Computing: An OverviewOverviewManish Parashar and Salim HaririManish Parashar and Salim HaririPresenter: Alejandro SimonPresenter: Alejandro SimonAgnostic: Joseph CilliAgnostic: Joseph Cilli6/26/066/26/06 22/25/25IntroductionIntroductionAdvances in technology have resulted in Advances in technology have resulted in complex, heterogeneous and dynamic complex, heterogeneous and dynamic applications and systems.applications and systems.Growth in the information infrastructure Growth in the information infrastructure aggregates such systems.aggregates such systems.Applications, programming environments Applications, programming environments and information infrastructures have and information infrastructures have become brittle, unmanageable, insecure.become brittle, unmanageable, insecure.Autonomic computing is an alternate Autonomic computing is an alternate paradigm that deals with this issue.paradigm that deals with this issue.6/26/066/26/06 33/25/25The Autonomic Nervous The Autonomic Nervous SystemSystemThe most sophisticated example of The most sophisticated example of autonomic behavior. autonomic behavior. Regulates and maintains homeostasis: Regulates and maintains homeostasis: maintains structure and functions by maintains structure and functions by means of a multiplicity of dynamic means of a multiplicity of dynamic equilibriums that are rigorously controlled equilibriums that are rigorously controlled by interdependent regulation mechanisms. by interdependent regulation mechanisms. Not all parameters have the same urgency, Not all parameters have the same urgency, essential parameters are monitored more essential parameters are monitored more closely.closely.6/26/066/26/06 44/25/25Ashby’s Ultrastable SystemAshby’s Ultrastable SystemIn order for an In order for an organism to organism to survive, its survive, its essential essential variables (EVx) variables (EVx) must be kept must be kept within a within a viability zone. viability zone. Source: “Autonomic Computing: An Overview, ” M. Parashar, and S. Hariri, UPP 2004, Mont Saint-Michel, France, Editors: J.-P. Banâtre et al. LNCS, Springer Verlag, Vol. 3566, pp. 247 – 259, 2005.6/26/066/26/06 55/25/25Ashby’s Ultrastable SystemAshby’s Ultrastable SystemThe goal of an adaptive behavior is to The goal of an adaptive behavior is to ensure survivability of the system.ensure survivability of the system.If external or internal disturbances push the If external or internal disturbances push the system outside its equilibrium state, the system outside its equilibrium state, the system will work towards returning to system will work towards returning to equilibrium. equilibrium. The ultrastable system consists of two The ultrastable system consists of two closed loops, one controls small closed loops, one controls small disturbances, the other controls larger ones.disturbances, the other controls larger ones.6/26/066/26/06 66/25/25Ashby’s Ultrastable SystemAshby’s Ultrastable SystemSource: “Autonomic Computing: An Overview, ” M. Parashar, and S. Hariri, UPP 2004, Mont Saint-Michel, France, Editors: J.-P. Banâtre et al. LNCS, Springer Verlag, Vol. 3566, pp. 247 – 259, 2005.6/26/066/26/06 77/25/25The Nervous System as a The Nervous System as a Subsystem of Ashby’s Ultrastable Subsystem of Ashby’s Ultrastable SystemSystemNervous System consists of Peripheral Nervous System consists of Peripheral Nervous System (PNS), Central Nervous Nervous System (PNS), Central Nervous System (CNS)System (CNS)PNS: Sensory neurons connecting stimuli PNS: Sensory neurons connecting stimuli receptors to CNS. Motor neurons receptors to CNS. Motor neurons connecting CNS to muscles and glands.connecting CNS to muscles and glands.CNS: Sensory-somatic nervous system and CNS: Sensory-somatic nervous system and Autonomic Nervous System: Depicted as Autonomic Nervous System: Depicted as an Ashby’s Ultrastable Systeman Ashby’s Ultrastable System6/26/066/26/06 88/25/25The Nervous System as a The Nervous System as a Subsystem of Ashby’s Ultrastable Subsystem of Ashby’s Ultrastable SystemSystemSource: “Autonomic Computing: An Overview, ” M. Parashar, and S. Hariri, UPP 2004, Mont Saint-Michel, France, Editors: J.-P. Banâtre et al. LNCS, Springer Verlag, Vol. 3566, pp. 247 – 259, 2005.6/26/066/26/06 99/25/25The Autonomic Computing The Autonomic Computing ParadigmParadigmMust have a mechanism to adapt to changes in Must have a mechanism to adapt to changes in its Essential Variables (EVs) by changing its its Essential Variables (EVs) by changing its behavior to restore equilibrium. behavior to restore equilibrium. Equilibrium is impacted by internal environment Equilibrium is impacted by internal environment (excessive CPU usage), and external environment (excessive CPU usage), and external environment (external attack).(external attack).Requires sensor and motor channels to sense and Requires sensor and motor channels to sense and react to changes in environment by changing the react to changes in environment by changing the system and maintaining equilibrium.system and maintaining equilibrium.Stages: Sensing, Analyzing, Planning, Knowledge, Stages: Sensing, Analyzing, Planning, Knowledge, and Execution. and Execution.6/26/066/26/06 1010/25/25A Holistic View of Autonomic A Holistic View of Autonomic ComputingComputingExisting systems have been developed in an Existing systems have been developed in an ad-hoc manner and can optimize a few ad-hoc manner and can optimize a few attributes or functionalities. attributes or functionalities. Emerging systems and applications are Emerging systems and applications are dynamic, their requirements will change dynamic, their requirements will change during