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    μ΅œμ‹  ECUλ³΄λ“œλ₯Ό ν™œμš©ν•˜μ—¬ μ†Œν”„νŠΈμ—λŸ¬λ“€μ„ μ‹€μ‹œκ°„ λ³΅κ΅¬ν•˜λŠ” 기법

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    ν•™μœ„λ…Όλ¬Έ (석사) -- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : κ³΅κ³ΌλŒ€ν•™ 컴퓨터곡학뢀, 2020. 8. 이창건.This dissertation presents the fault-tolerant real-time scheduling using dynamic mode switch support of modern ECU hardware. This dissertation first describes the optimal capacity of the Periodic Resource which contains harmonic periodic task set using the exact time supply function.We show that the optimal capacity can be represented as sum of the each individual utilization of the task in the harmonic periodic task set for both normal state(i.e. no faults) and faulty state. Then, this dissertation proposes non-critical task overlapping technique by only using the idle time intervals of the Periodic Resource in order to overlap the non-critical tasks which ensures no additional capacity increase. Finally, this dissertation proposes the basic form of the Periodic Resources in order to efficiently use the dynamic mode switch support. Next, we also proposes the bin-packing heuristic algorithm that considers both making sub-taskset as a one Periodic Resource and Periodic Resource wide bin-packing which has the pseudo-polynomial time complexity. Experimental results show that the proposed algorithm performs better than the traditional partitioned fixed-priority scheduling approach and partitioned mixed-criticality scheduling approach. Also, the achievement is made up to 18% in terms of the total needed cores compared to traditional partitioned fixed-priority approach for making the given input task set schedulable.λ³Έ λ…Όλ¬Έμ—μ„œλŠ” 효율적인 μž¬κ΅¬μ„±κ°€λŠ₯ μ‹œμŠ€ν…œ μ‚¬μš©μ„ μœ„ν•œ κ³„μΈ΅κΈ°λ°˜ μ‹€μ‹œκ°„ 결함 감내 μŠ€μΌ€μ€„λ§ 기법을 μ œμ•ˆν•œλ‹€. λ³Έ μ—°κ΅¬λŠ” μ£ΌκΈ° μžμ› λͺ¨λΈμ„ 기반으둜, 졜적 μ£ΌκΈ° μžμ› μ„œλ²„μ˜ μš©λŸ‰μ„ μ£ΌκΈ° μžμ› λͺ¨λΈμ΄ κ°€μ§€λŠ” μ‹€μ‹œκ°„ μ£ΌκΈ° νƒœμŠ€ν¬ μ…‹μ˜ μœ ν‹ΈλΌμ΄μ œμ΄μ…˜μ˜ ν•©μœΌλ‘œ μ œμ‹œν•œλ‹€. λ³Έ 논문은 ν•΄λ‹Ή 졜적 μ„œλ²„ μš©λŸ‰μ„ μ‹œμŠ€ν…œμ΄ 정상 λ™μž‘ν• λ•Œμ™€ μ˜€λ™μž‘ ν• λ•Œ λͺ¨λ‘μ— λŒ€ν•΄μ„œ μ œμ‹œν•œλ‹€. λ‹€μŒμœΌλ‘œ, λΉ„μ€‘μš” νƒœμŠ€ν¬ 셋듀을 μ€‘μš” μ£ΌκΈ° μžμ› μ„œλ²„μ˜ μ—¬λΆ„ 곡백 μ‹œκ°„μ„ ν™œμš©ν•΄ μ„œλ²„ μš©λŸ‰μ˜ 증가 없이 λΉ„μ€‘μš” νƒœμŠ€ν¬λ₯Ό μ€‘μš” μ£ΌκΈ° μžμ› μ„œλ²„μ— ν• λ‹Ήν•˜λŠ” 방법둠을 μ œμ‹œν•œλ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ λ³Έ 논문은 μ£ΌκΈ° μžμ› μ„œλ²„ λ‹¨μœ„μ˜ νŒŒν‹°μ…˜ 기법과 μ£ΌκΈ° νƒœμŠ€ν¬λ₯Ό ν•˜λ‚˜μ˜ μ£ΌκΈ° μžμ› μ„œλ²„λ‘œ λ§Œλ“œλŠ” λΉˆνŒ¨ν‚Ή νœ΄λ¦¬μŠ€ν‹± μ•Œκ³ λ¦¬μ¦˜μ„ μ œμ‹œν•œλ‹€. μ‹€ν—˜ κ²°κ³Ό, λ³Έ λ…Όλ¬Έμ—μ„œ μ œμ‹œν•œ μ•Œκ³ λ¦¬μ¦˜μ€ 기쑴에 μ‚¬μš©λ˜μ—ˆλ˜ νŒŒν‹°μ…˜ 기반 μš°μ„ μˆœμœ„ μŠ€μΌ€μ€„λ§ μ•Œκ³ λ¦¬μ¦˜κ³Ό νŒŒν‹°μ…˜ 기반 μš°μ„ μˆœμœ„ 혼작 μ€‘μš”λ„ μ•Œκ³ λ¦¬μ¦˜λ³΄λ‹€ 더 μž‘μ€ 수의 μ½”μ–΄μ˜ 개수λ₯Ό λ„μΆœ ν•  수 μžˆμŒμ„ 보인닀. μ‹€ν—˜κ²°κ³Όλ₯Ό 기반으둜, λ³Έ μ—°κ΅¬μ—μ„œ μ œμ•ˆν•œ μ•Œκ³ λ¦¬μ¦˜μ„ μž¬κ΅¬μ„±κ°€λŠ₯ μ‹œμŠ€ν…œμ— ν™œμš©ν•œλ‹€λ©΄ κΈ°μ‘΄ 방법 λŒ€λΉ„ μ΅œλŒ€ 18%의 μ½”μ–΄μ ˆκ°νš¨κ³Όλ₯Ό κΈ°λŒ€ν• μˆ˜ μžˆλ‹€.1 Introduction 1 1.1 Motivation and Objective 1 1.2 Approach 2 1.3 Organization 6 2 System Model 7 3 Schedulability Analysis 10 3.1 Background 10 3.2 Optimal Capacity Analysis During Normal State 14 3.3 Optimal Capacity Analysis During Fault State 16 3.4 Periodic Resource Wide Schedulability Test 20 3.5 Non-Critical Task Overlapping 24 4 Proposed Approach 26 4.1 Minimum Harmonic Partitions of the Task Set 26 4.2 Proposed Heuristic Algorithm 28 4.2.1 Choosing Detection method 28 4.2.2 Packing Minimum Harmonic Partitions 29 4.2.3 Packing Free Tasks 30 4.2.4 Packing Non-Critical Tasks 31 4.3 Algorithm Description 32 5 Evaluation 35 5.1 Experimental Setup 35 5.2 Simulation Results 36 5.2.1 Free Task Bin-Packing 38 5.2.2 Minimum Harmonic Partitions Bin-Packing 40 5.2.3 Effect of Non-Critical Task Overlapping 43 5.2.4 Effect of State-Wise Computation 45 6 Related Works 46 6.1 Hierarchical Fault-Tolerant Real-Time Scheduling 46 6.2 Error Detection Method 46 7 Conclusion 48 References 50Maste
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