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Realizing Compositional Scheduling through Virtualization Jaewoo Lee, Sisu Xi, Sanjian Chen, Linh T.X. Phan Chris Gill, Insup Lee, Chenyang Lu, Oleg Sokolsky
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Virtualization The benefits of virtualization Consolidate legacy systems Integrate large, complex systems Key challenges of virtualization for safety-critical systems Temporal isolation Real-time guarantee Hypervisor Legacy System Virtualization Platform Domains Legacy System 2
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Compositional Scheduling Compositional Scheduling Framework (CSF) Provides temporal isolation and real-time guarantee Computes the minimum-bandwidth resource model for the component The gap between CSF theory and system Realizing CSF though virtualization can bridge the gap Resource Model Parent component Child components Workload Periodic Tasks Component Scheduler Rate Monotonic Scheduler Scheduler Periodic Resource Model (period, budget) 3
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Contributions Compositional Scheduling Architecture (CSA) Confederation of compositional scheduling and virtualization Enhancement to periodic server design in CSA Extension to CSF for quantum-based platforms Performance evaluation of CSA Synthetic workloads and avionic workloads First open-source real-time virtualization with CSF Extensible with new domain-scheduling algorithms 4
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Overview of Our Work Compositional Scheduling Architecture (CSA) Component domain Periodic Resource Model (PRM) Periodic Server (PS) Task model: independent, CPU-intensive, periodic task Scheduling algorithm: rate monotonic App Domain Hypervisor RT-Xen Hardware Task Component Root Component Compositional Scheduling PSPRM S. Xi, J. Wilson, C. Lu, C. Gill, RT-Xen: Real-Time Virtualization Based on Hierarchical Scheduling, EMSOFT, 2011 Domain PS 5
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Theory Pessimism in CSF Interface considers the worst case: U PRM – U W ≥ 0 Interface overhead leads to underutilization of the component Resource model periodic server in CSA Periodic server does not fully utilize its budget Slacks : tasks do not always execute for WCETs Interface overhead Underutilization of periodic server long response times of real-time tasks Using idle times, we propose enhanced periodic servers 6 Interface Overhead
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Periodic Server Design Purely Time-driven Periodic Server (PTPS) If currently scheduled domain is idle, its budget is wasted Not work-conserving t Δ DHDH DLDL Budget time Task Release Task Complete Execution of tasks in D H Execution of tasks in D L Current Domain 7
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Periodic Server Design Work-Conserving Periodic Server (WCPS) If currently scheduled domain is idle, the hypervisor picks a lower-priority domain that has tasks to execute Early execution of the lower-priority domain during idle period does not affect schedulability t Δ DHDH DLDL Budget time Task Release Task Complete Execution of tasks in D H Execution of tasks in D L Current Domain 8
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Periodic Server Design Capacity Reclaiming Periodic Server (CRPS) If currently scheduled domain is idle, we can re-assign this idled budget to any other domain that has tasks to execute Early execution of the other domain during idle period does not affect schedulability t Δ DHDH DLDL Budget time Task Release Task Complete Execution of tasks in D H Execution of tasks in D L Current Domain 9
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CSF Extension for Quantum-based Platforms P: To find the minimum-bandwidth resource model for workload W. 10 Real-number-based resource model 3 tasks Task periodTask execution time of resource model B/P:
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CSF Extension for Quantum-based Platform infeasible bandwidth Real-number-based resource model Quantum-based resource model Necessary condition for schedulability To find the minimum-bandwidth resource model for workload W. the upper bound of the period to find min-BW resource model? 11 Non-decreasing P: of resource model B/P: 1 2
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CSF Extension for Quantum-based Platform the upper bound of the period to find min-BW resource model? infeasible bandwidth Non-decreasing Real-number-based resource model Quantum-based resource model Necessary condition for schedulability To find the minimum-bandwidth resource model for workload W. Min-BW resource model 12 P: B/P: 1 2 of resource model
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System Architecture Implemented in Xen 4.0 only re-compile Xen, keep Kernel untouched All source code available at RT-Xen website: https://sites.google.com/site/realtimexen/ https://sites.google.com/site/realtimexen/ Current Limitations: one VCPU per domain (single core) CPU intensive workload 13 Xen Scheduling Framework Real-Time Sub Framework PTPSWCPSCRPS
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Evaluation – Setup 14 VCPU Core 0 Core 1 Schedulers (PTPS, CRPS, WCPS) Dom0 App VCPU Dom1 VCPU Dom5 App Scheduling Algorithms (PTPS, CRPS, WCPS) Parameters for each Domain IDLE … Responsiveness: response time / deadline Deadline Miss Ratio Use Rate Monotonic within Domain …
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Evaluation – Synthetic workloads Randomly generate task sets, then compute interface Sources of idle time: interface overhead: U PRM – U W slacks: over-estimation of tasks’ execution time Range workload periods -> different interface overhead U W : 0.7, 0.8, 0.9, 1.0 Periods: [550ms, 650ms], [350ms, 850ms], [100ms, 1100ms] Range Execution Time Factor (ETF) -> different slacks For all tasks in highest three priorities domains: 100%, 50%, 10% Using period [550ms, 650ms], pick U w from 0.7, 0.8, 0.9, 1.0 15 typical overloaded situation most interface overhead uniform distribute [wcet*ETF, wcet] extremely overloaded situation
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Evaluation – Interface Overhead 16 100% 60% 0% CRPS ≥ WCPS ≥ PTPS deadline miss CDF Plot, Probability
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Evaluation – ETF 17 Sched ETF = 100 %ETF = 50 %ETF = 10 % median95 %maxmedian95 %maxmedian95 %max PTPS333333333 WCPS3330.5045330.399633 CRPS0.6192330.08600.32130.76080.05730.18070.4864 ( Response Time / Deadline ) for the Lowest Priority Domain PTPS: non work conservative, can not utilize slacks WCPS: consumes budget in parallel, still miss deadlines CRPS: ‘reclaim’ budget more aggressively, utilize slacks effectively
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Evaluation – ARINC-653 Workload 18 7 harmonic workloads, each represent a set of domains scheduled on a single processor, with each domain consisting of a set of periodic tasks A. Easwaran, I. Lee, O. Sokolsky, and S. Vestal, A Compositional Framework for Avionics (ARINC-653) Systems, Tech Report MS-CIS-09-04, 2009, University of Pennsylvania U PRM = U W if using real number parameters Overheads comes from rounding up the budget period is fixed CRPS > WCPS > PTPS Interface Overhead (8%) CDF Plot, Probability Response Time / Deadline
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Conclusion Compositional Scheduling Architecture (CSA) Enhanced version of the Pure Time-driven Periodic Server (PTPS) WCPS: work conserving, consume budget in parallel CRPS: aggressively reclaiming budget Extension of CSF for quantum-based platforms Extensive evaluation on synthetic and avionics workloads Open Source: RT-Xen Website: https://sites.google.com/site/realtimexen/ 19
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Questions? 20 RT-Xen https://sites.google.com/site/realtimexen/ or just Google RT-Xen *^_^*
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Backup : Interface overhead Interface considers the worst case: U PRM – U W ≥ 0 For example, a task T= (p = 3, e = 1) in a component Resource model (3, 1) cannot schedule T Resource model (3, 2) can schedule T 21 U PRM – U W =2/3 – 1/3 = 1/3 Interface Overhead 0 1 2 3 4 5 6 Task Release Task Deadline 0 1 2 3 4 5 6 Deadline miss Resource supply of resource model (3,1) Resource supply of resource model (3,2) 1 st period of the resource supply 2 nd period of the resource supply Supplied resource
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Backup : Simple rounding up does not work The minimum-bandwidth resource model CSF allow real number in budget. But, budget should be an integer multiple of the scheduling quantum in quantum-based platforms Ex: Optimal algorithm : (1,0.38) rounding up (1,1) Only integer : (1,1), (2,1), (3,2), (4,2),… Among feasible resource models, (5,2) is minimum bandwidth for quantum- based platforms
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Backup: Upper bound of the period P B/P infeasible bandwidth Non-decreasing Real-number-based resource model Quantum-based resource model Necessary condition for schedulability We can easily find the upper bound of the period for a given bandwidth 23 A given bandwidth The upper bound of the period for a given bandwidth
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Backup : Difference from reservation-based system CSA on RT-Xen virtualization Support different local scheduler for each domain ( by running different guest OS) Clean separation between local scheduler and global scheduler Local OS does not know other task or other domain inside the system Global scheduler does not know task information inside domain Reservation-based native system Local scheduler is a part of the operating system We cannot provide a component with a local scheduler No clean separation between local scheduler and global scheduler Malformed local scheduler can affect global scheduler or other local schedulers 24
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Backup : Related Work Crespo et al., “XtratuM”, EDDC ’10 A bare VMM with a fixed cyclic scheduling policy Cucinota et al., “Respecting Temporal Isolation...”, COMSAC ’09 KVM with a hard reservation behavior CSA is different from above two works Only CSA support compositional scheduling CSA is implemented on Xen, different architecture from KVM KVM is integrated into the manager domain 25
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CSF Extension for Quantum-based Platforms 26
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