xTune: A formal methodology for cross-layer tuning of mobile embedded systems

Resource-limited mobile embedded systems can benefit greatly from dynamic adaptation of system parameters. We propose a novel approach that employs iterative tuning using lightweight formal verification at runtime with feedback for dynamic adaptation. One objective of this approach is to enable trade-off analysis across multiple layers (e.g., application, middleware, OS) and predict the possible property violations as the system evolves dynamically over time. Specifically, an executable formal specification is developed for each layer of the mobile system under consideration. The formal specification is then analyzed using statistical property checking and statistical quantitative analysis, to determine the impact of various resource management policies for achieving desired timing/QoS properties. Integration of formal analysis with dynamic behavior from system execution results in a feedback loop that enables model refinement and further optimization of policies and parameters. We demonstrate the applicability of this approach to the adaptive provisioning of resource-limited distributed real-time systems using a mobile multimedia case study.

[1]  Mahesh Viswanathan,et al.  Model-Checking Markov Chains in the Presence of Uncertainties , 2006, TACAS.

[2]  MeseguerJosé Conditional rewriting logic as a unified model of concurrency , 1992 .

[3]  Joost-Pieter Katoen,et al.  The Ins and Outs of the Probabilistic Model Checker MRMC , 2009, 2009 Sixth International Conference on the Quantitative Evaluation of Systems.

[4]  Sandeep K. Shukla,et al.  A cross-layer approach for power-performance optimization in distributed mobile systems , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[5]  Soonhoi Ha,et al.  Dynamic voltage scheduling with buffers in low-power multimedia applications , 2004, TECS.

[6]  Douglas L. Jones,et al.  GRACE-1: cross-layer adaptation for multimedia quality and battery energy , 2006, IEEE Transactions on Mobile Computing.

[7]  Massoud Pedram,et al.  Dynamic power management in a mobile multimedia system with guaranteed quality-of-service , 2001, DAC '01.

[8]  Chun-Ying Huang,et al.  An empirical evaluation of VoIP playout buffer dimensioning in Skype, Google talk, and MSN Messenger , 2009, NOSSDAV '09.

[9]  Gianfranco Ciardo,et al.  Formal Verification of the NASA Runway Safety Monitor , 2005, Electron. Notes Theor. Comput. Sci..

[10]  Alessandro Aldini,et al.  Assessing the impact of dynamic power management on the functionality and the performance of battery-powered appliances , 2004, International Conference on Dependable Systems and Networks, 2004.

[11]  Sandeep K. Shukla,et al.  Using probabilistic model checking for dynamic power management , 2005, Formal Aspects of Computing.

[12]  Anil K. Bera,et al.  A test for normality of observations and regression residuals , 1987 .

[13]  Qi Han AutoSeC: An Integrated Middleware Framework for Dynamic Service Brokering , 2003 .

[14]  Nikil D. Dutt,et al.  Constraint Refinement for Online Verifiable Cross-Layer System Adaptation , 2008, 2008 Design, Automation and Test in Europe.

[15]  Soonhoi Ha,et al.  Hybrid Run-time Power Management Technique for Real-time Embedded System with Voltage Scalable Processor , 2001 .

[16]  Nalini Venkatasubramanian,et al.  Policy Construction and Validation for Energy Minimization in Cross Layered Systems : A Formal Method Approach , 2006 .

[17]  Mahesh Viswanathan,et al.  Statistical Model Checking of Black-Box Probabilistic Systems , 2004, CAV.

[18]  Håkan L. S. Younes,et al.  Numerical vs. statistical probabilistic model checking , 2006, International Journal on Software Tools for Technology Transfer.

[19]  Nikil D. Dutt,et al.  PBPAIR: an energy-efficient error-resilient encoding using probability based power aware intra refresh , 2006, MOCO.

[20]  Boudewijn R. Haverkort,et al.  Quantitative Evaluation in Embedded System Design: Predicting Battery Lifetime in Mobile Devices , 2008, 2008 Design, Automation and Test in Europe.

[21]  Marta Z. Kwiatkowska,et al.  Quantitative Analysis With the Probabilistic Model Checker PRISM , 2006, QAPL.

[22]  José Meseguer,et al.  A Rewriting Based Model for Probabilistic Distributed Object Systems , 2003, FMOODS.

[23]  José Meseguer,et al.  Conditioned Rewriting Logic as a United Model of Concurrency , 1992, Theor. Comput. Sci..

[24]  Nihal Pekergin,et al.  Statistical Model Checking Using Perfect Simulation , 2009, ATVA.

[25]  Peter Csaba Ölveczky,et al.  Semantics and pragmatics of Real-Time Maude , 2007, High. Order Symb. Comput..

[26]  Nikil D. Dutt,et al.  A Probabilistic Formal Analysis Approach to Cross Layer Optimization in Distributed Embedded Systems , 2007, FMOODS.

[27]  Nikil D. Dutt,et al.  Combining Formal Verification with Observed System Execution Behavior to Tune System Parameters , 2007, FORMATS.

[28]  E. Ziegel Introduction to the Practice of Statistics (2nd ed.) , 1994 .

[29]  Joost-Pieter Katoen,et al.  How Fast and Fat Is Your Probabilistic Model Checker? An Experimental Performance Comparison , 2007, Haifa Verification Conference.

[30]  R. Khan,et al.  Sequential Tests of Statistical Hypotheses. , 1972 .

[31]  Alan Jay Smith,et al.  Operating systems techniques for reducing processor energy consumption , 2001 .

[32]  Qi Han,et al.  AutoSeC : An Integrated Middleware Framework for Dynamic Service Brokering , 2003 .

[33]  Nagarajan Kandasamy,et al.  Online control for self-management in computing systems , 2004, Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..

[34]  G. Reinsel,et al.  Introduction to Mathematical Statistics (4th ed.). , 1980 .

[35]  Klara Nahrstedt,et al.  A control-based middleware framework for quality-of-service adaptations , 1999, IEEE J. Sel. Areas Commun..

[36]  Nikil D. Dutt,et al.  DYNAMO: A Cross-Layer Framework for End-to-End QoS and Energy Optimization in Mobile Handheld Devices , 2007, IEEE Journal on Selected Areas in Communications.

[37]  H. J. Arnold Introduction to the Practice of Statistics , 1990 .

[38]  Monica C. Jackson,et al.  Introduction to the Practice of Statistics , 2001 .

[39]  A. Wald Sequential Tests of Statistical Hypotheses , 1945 .

[40]  DAVID G. KENDALL,et al.  Introduction to Mathematical Statistics , 1947, Nature.

[41]  Narciso Martí-Oliet,et al.  All About Maude - A High-Performance Logical Framework, How to Specify, Program and Verify Systems in Rewriting Logic , 2007, All About Maude.

[42]  Kim Guldstrand Larsen,et al.  Specification and refinement of probabilistic processes , 1991, [1991] Proceedings Sixth Annual IEEE Symposium on Logic in Computer Science.

[43]  José Meseguer,et al.  PMaude: Rewrite-based Specification Language for Probabilistic Object Systems , 2006, QAPL.

[44]  Robert K. Brayton,et al.  Verifying Continuous Time Markov Chains , 1996, CAV.

[45]  Soonhoi Ha,et al.  Hybrid Run-time Power Management Technique for Real-time Embedded System with Voltage Scalable Processor , 2001, LCTES/OM.

[46]  Yifan Zhu,et al.  Feedback EDF scheduling exploiting hardware-assisted asynchronous dynamic voltage scaling , 2005, LCTES '05.

[47]  Christel Baier,et al.  Approximate Symbolic Model Checking of Continuous-Time Markov Chains , 1999, CONCUR.

[48]  Kevin Skadron,et al.  Control-theoretic dynamic frequency and voltage scaling for multimedia workloads , 2002, CASES '02.