6 research outputs found
Optimizing Software Platforms with Cross-Layer Resource Control and Scheduling
νμλ
Όλ¬Έ (λ°μ¬)-- μμΈλνκ΅ μ΅ν©κ³ΌνκΈ°μ λνμ : μ΅ν©κ³ΌνλΆ(λμ§νΈμ 보μ΅ν©μ 곡), 2015. 2. νμ±μ.μννΈμ¨μ΄ νλ«νΌμ κ±°λν λ° λ³΅μ‘ν λ¬Έμ μ λμνκΈ° μν΄ νλ«νΌμ νμ°μ μΌλ‘ κ³μΈ΅μ μΈ μννΈμ¨μ΄ ꡬ쑰λ₯Ό μ±ννλ€. μ΄λ¬ν κ³μΈ΅ ꡬ쑰μμ μ±λ₯ μ΅μ νλ κ°λ³ κ³μΈ΅μμ ν κ³μΈ΅μ λ
립μ μΌλ‘ μνλλ©°, μΈμ ν κ³μΈ΅λ€μ μ νλ μ 보λ§μ μ΄μ©ν μ μκΈ° λλ¬Έμ μ μ²΄λ‘ μ μ±λ₯ μ΅μ νμ μΈ‘λ©΄μμ νκ³κ° μλ€. μ΄μ κ°μ΄ κ³μΈ΅μ μννΈμ¨μ΄ ꡬ쑰μ κΈ°μΈνλ μ±λ₯ μ΅μ νμ λ¬Έμ λ₯Ό ν΄κ²°νκΈ° μν΄ κ³ μλ κΈ°λ²μ΄ κ΅μ°¨κ³μΈ΅ μ΅μ νμ΄λ€. μ΄λ μ 체 μ±λ₯μ μν₯μ μ£Όλ κ° κ³μΈ΅μ μ 보λ₯Ό νμν κ³μΈ΅μ μ νμ μΌλ‘ μ λ¬νκ³ , μ΄λ₯Ό ν΅ν΄ μ μ²΄λ‘ μ μΈ μ±λ₯ μ΅μ νλ₯Ό λ¬μ±νλ κ²μ κ·Έ λͺ©μ μ΄ μλ€. λ°λΌμ μ΅κ·Όμλ κ΅μ°¨κ³μΈ΅μ μΈ μ΅μ νλ₯Ό ν΅νμ¬ νλ«νΌμ μ μ²΄λ‘ μ μ±λ₯μ ν₯μμν€λ €λ λ
Έλ ₯μ΄ κ²½μ£Όλκ³ μλ€. νΉν, μ€μΌμ€λ§μ μννΈμ¨μ΄ νλ«νΌμμ λ°μνλ λ€μν μ±λ₯ μ΅μ ν λ¬Έμ μ€μ μμ€ν
μ 체μ μν₯μ λΌμΉ μ μλ μ€μν λ¬Έμ μ΄λ€.
λ³Έ νμλ
Όλ¬Έμ κ³μΈ΅μ μννΈμ¨μ΄ νλ«νΌμμ λ°μν μ μλ λ κ°μ§ μ±λ₯ μ΅μ ν λ¬Έμ λ₯Ό κ΅μ°¨κ³μΈ΅ μμκ΄λ¦¬μ μ€μΌμ€λ§μ ν΅ν΄ ν΄κ²° ν μ μλ κΈ°λ²μ μ μνλ€. 첫째, λ³Έ μ°κ΅¬λ λ΄μ₯ν μ¬μ©μ λ¨λ§μμ μ¬μ©μ λ°μμ± μ΅μ νλ₯Ό μν κ΅μ°¨κ³μΈ΅ μμκ΄λ¦¬ κΈ°λ²μ μ μνλ€. μ μνλ κΈ°λ²μ ν¬κ² λ κ°μ§ κ΅¬μ± μμλ€λ‘ μ΄λ£¨μ΄μ§λ€. 첫째, Framework-assisted Task Characterization(FTC)μ μμ νλ μμν¬ κ³μΈ΅κ³Ό νμ Linux kernel κ³μΈ΅ μ¬μ΄μ κ΅μ°¨κ³μΈ΅μ μμκ΄λ¦¬ κΈ°λ²μ΄λ€. μμ κ³μΈ΅μμλ μ¬μ©μ μνΈμ νμ€ν¬ 체μΈμ΄ λ°νμμ κ²μΆλκ³ , νμ κ³μΈ΅μμλ μ΄ μ€ μ¬μ©μ λ°μμ±μ μν₯μ λΌμΉλ νμ€ν¬λ€μ μ°μ μμλ₯Ό λμ μΌλ‘ μ¦μ§νλ€. κ²°κ³Όμ μΌλ‘, μ΄ νμ€ν¬λ€μ λ€λ₯Έ νμ€ν¬μ μν΄ μ μ λΉνμ§ μκ³ μ€λ«λμ CPUλ₯Ό μ μ κ°λ₯ν΄μ§κΈ° λλ¬Έμ λ§€μ° μμ μ μ μ§μ°μκ°μ 보μ₯νλ€. λμ§Έ, Virtual Time-based Completely Fair Scheduler(VT-CFS)λ Linuxμ νμ€ν¬ μ€μΌμ€λ¬μΈ CFSλ₯Ό κ΅μ°¨κ³μΈ΅μ μΌλ‘ μ΅μ ννλ€. ꡬ체μ μΌλ‘, μ΄λ weighted fair queueing λ°©μμ μ€μΌμ€λ§μ νμ¬ λ³΄λ€ λμ μλ΅μ±μ 보μ₯νλ€. λν, μμ κ³μΈ΅ FTCλ‘λΆν° νλ³λ μ¬μ©μ μνΈμ νμ€ν¬λ€μ΄ λ°μ΄λ λ μ€ν μ§μ°μκ°μ μ€μΌμ€λ§ λ μ μλλ‘ κ·Έλ€μ virtual runtimeμ μ‘°μ νλ€.
λμ§Έ, λ³Έ μ°κ΅¬λ λ©ν°μ½μ΄ μ€μΌμ€λ§μ ν΅ν΄ λΉλ‘곡μ μ± μ΅μ ν λ¬μ±μ μν Progress Balancing κΈ°λ²μ μ μνλ€. μ΄λ νμ€ν¬μ μλμ μ§μ² μ λλ₯Ό virtual runtimeμΌλ‘ μ μνκ³ , μ΄λ₯Ό κ· λ±νκ² λΆνλΆμ° νλ μ§μ² κΈ°λ° λΆνλΆμ° κΈ°λ²μ΄λ€. ꡬ체μ μΌλ‘, Progress Balancingμ μμ€ν
λ΄ νμ€ν¬λ€μ CPU μ½μ΄μ κ°μλ§νΌμ νμ€ν¬ κ·Έλ£ΉμΌλ‘ λΆν νκ³ μλμ μΌλ‘ μ§μ²μ΄ λΉ λ₯Έ νμ€ν¬λ₯Ό λλ¦° μ½μ΄μ ν λΉνκ³ , λͺ¨λ μ½μ΄λ€ κ° λ‘λ μ°¨μ΄λ₯Ό λ°μ΄λ μν¨λ€. κ²°κ³Όμ μΌλ‘, νμ€ν¬ κ° virtual runtime μ°¨μ΄λ μμ μμλ‘ λ°μ΄λ λμ΄μ λΉλ‘곡μ μ±μ μ΅μ νλ₯Ό λ¬μ±νλ€.
λ³Έ μ°κ΅¬μμ μ μν κΈ°λ²λ€μ ν¨μ©μ±μ νκΈ° μν΄μ, λ³Έ μ°κ΅¬λ μ΄λ€μ΄ λ¬μ±νκ³ μ νλ μ±λ₯ μ§νμ λ°λΌ μ λ³λ λμ μμ€ν
μ κ° κΈ°λ²λ€μ ꡬννμλ€. FTCμ VT-CFSλ Android μ€λ§νΈν°μ ꡬνλμλ€. μ€ν κ²°κ³Ό, κΈ°μ‘΄ μμ€ν
λλΉ λ¬΄λ € 77.35% λ μ§§κ² μλ¨κ° μ¬μ©μ λ°μμκ°μ λ¨μΆν¨μΌλ‘μ¨ μ¬μ©μ λ°μμ±μ μ΅μ νλ₯Ό λ¬μ±νμλ€. μ΄ μ΅μ ν κ²°κ³Όλ FTCκ° μ μ μ§μ°μκ°μ 80.23%, VT-CFSκ° μ€ν μ§μ°μκ°μ 78.42% κ°μμμΌ°λ€λ μ¬μ€μ κΈ°μΈ νλ€. λν, Progress Balancingμ Linux κΈ°λ° μλ²μ ꡬνλμλ€. μ€ν κ²°κ³Ό, λͺ¨λ νμ€ν¬λ€μ virtual runtimeμ μ°¨μ΄κ° μμ μμλ‘ λ°μ΄λ λ¨μ νμΈνμλ€. μ΄λ¬ν virtual runtime μ°¨μ΄μ λ°μ΄λλ μλ² νκ²½μμ νΈμ€ν
λλ μ¬μ©μλ€μ λͺ¨λ 곡μ ν CPU μμμ 보μ₯ν μ μμμ λ»νλ€. μ΄λ¬ν κ²°κ³Όλ λ³Έ λ
Όλ¬Έμμ μ μνλ κ΅μ°¨κ³μΈ΅ μμκ΄λ¦¬μ μ€μΌμ€λ§ κΈ°λ²μ΄ λμ μμ€ν
μ ν¨κ³Όμ μΌλ‘ μ μ©λμ΄ λ³΄λ€ λμ μμ€μ μ±λ₯ μ΅μ νκ° κ°λ₯ν¨μ 보μ΄λ©°, λν κ³μν΄μ λ€κ°νλκ³ λ³΅μ‘νλλ μννΈμ¨μ΄ νλ«νΌμ μ μ²΄λ‘ μ μ±λ₯ μ΅μ νλ₯Ό μν μ€μ©μ μΈ μλ¨μμ λλ¬λΈλ€.Layering software platform is known to be a promising mean to deal with many problems incurred by its colossal and complex structure. In a layered structure, a performance optimization is performed locally at each individual layer independently from other layers, and restricted to use information provided from its adjacent layers. This leads many difficulties and challenges in achieving holistic system-wide performance optimization. A cross-layer optimization is an optimization paradigm which is proposed to solve such difficulties in layered software structure. It carefully delivers relevant information, which affects overall performance to other appropriate layers. Its objective is to lead a holistic performance optimization by violating the layering principle to a certain degree. Recently, due to its effectiveness, there have been a number of demands and efforts to improve an overall performance using the cross-layer optimization. In particular, task scheduling in a layered software platform is one of the most crucial problems which can affect an overall performance improvement of the platform.
This thesis proposes a cross-layer resource control and scheduling to solve two performance optimization problems in layered software platforms. First, we present a cross-layer resource control to optimize a user interactivity for embedded user equipment. The proposed one consists of two components. First, Framework-assisted Task Characterization (FTC) is a cross-layer scheme between Android application framework and its underlying operating systems kernel. At the upper level, it identifies user-interactive tasks using the notion of a user-interactive task chain. It then enables the lower level scheduler to selectively promote the priorities of tasks appearing in the task chain. This effectively reduces the preemption latency of a user-interactive task since it can occupy a CPU longer without being preempted. Second, Virtual Time-based Completely Fair Scheduler (VT-CFS) is a cross-layer refinement of CFS in terms of interactivity. Specifically, it schedules a task in a WFQ fashion and allows a task to be preempted at every smaller period. It also adjusts the virtual runtime of the user-interactive task identified by FTC to ensure that a dispatch latency of a user-interactive task is reduced to a small value.
Second, we present Progress Balancing in order to optimize a multicore proportional fairness in a server. It defines tasks relative progress as virtual runtimes and periodically balances them. Specifically, it partitions runnable tasks such that a core with larger virtual runtimes receives a larger load and the load difference among cores is bounded. As a result, the virtual runtime difference converges to the balancing period multiplied by some constant derived from the bounded load difference.
To show a viability and evaluate an effectiveness of the proposed schemes, we have applied them to the target software platform product line. We have implemented FTC and VT-CFS into Android smartphone and empirically evaluated them with well-known benchmark programs and real-world applications. Results show that the end-to-end response time was reduced by up to 77.35% compared to the legacy one. This improvement comes from the facts that the modified framework achieved 80.23% shorter preemption latency than the legacy framework and that the VT-CFS yielded 78.42% shorter dispatch latency for user-interactive tasks than CFS. We have also implemented Progress Balancing into a multicore Linux-installed server. Experimental results report that virtual runtime difference between tasks is bounded by a small constant by adopting our scheme. Such bounding virtual runtime differences implies that tenants hosted from our target server are able to guarantee a use of fair amount of CPU resources. As such qualitative and quantitative analyses indicate, our cross-layer resource control and scheduling schemes effectively improve the overall system performance of the existing software platforms.μ 1 μ₯ μλ‘ 1
μ 1 μ μ°κ΅¬ λκΈ° 3
μ 2 μ λ
Όλ¬Έμ κΈ°μ¬ 6
μ 3 μ λ
Όλ¬Έ κ΅¬μ± 10
μ 2 μ₯ κ΄λ ¨ μ°κ΅¬ 11
μ 1 μ κ΅μ°¨κ³μΈ΅ μ΅μ ν 11
μ 2 μ λΉλ‘곡μ μ€μΌμ€λ§ 15
2.1 Weighted Round Robin κΈ°λ° κΈ°λ²λ€ 15
2.2 Weighted Fair Queueing κΈ°λ° κΈ°λ²λ€ 19
μ 3 μ λ©ν°μ½μ΄ λΉλ‘곡μ μ± ν₯μμ μν μ€μΌμ€λ§ 22
3.1 κ°μ€μΉ(Weight) κΈ°λ° κΈ°λ²λ€ 23
3.2 μλ(Speed) κΈ°λ° κΈ°λ²λ€ 25
μ 3 μ₯ μμ€ν
λͺ¨λΈ 28
μ 1 μ κ³μΈ΅μ μν€ν
μ² 28
μ 2 μ Completely Fair Scheduler 31
μ 4 μ₯ κ΅μ°¨κ³μΈ΅ μμκ΄λ¦¬λ₯Ό ν΅ν μ¬μ©μ λ°μμ± μ΅μ ν 39
μ 1 μ λμ μμ€ν
μ μ 40
μ 2 μ μνμ νκΈ°λ²κ³Ό μ©μ΄ μ μ 49
μ 3 μ λ¬Έμ μ μ 52
μ 4 μ Framework-assisted Task Characterization 56
μ 5 μ Virtual Time-based CFS 61
μ 6 μ λμ μμ 66
μ 5 μ₯ Progress Balancingμ ν΅ν λΉλ‘곡μ μ± μ΅μ ν 68
μ 1 μ λμ μμ€ν
μ μ 69
μ 2 μ μνμ νκΈ°λ²κ³Ό μ©μ΄ μ μ 72
μ 3 μ λ¬Έμ μ μ 75
μ 4 μ Progress Balancing 80
4.1 PARTITION λ¨κ³ 83
4.2 THROTTLE λ¨κ³ 84
μ 5 μ λμ μμ 88
μ 6 μ₯ μ€ν λ° κ²μ¦ 93
μ 1 μ μ€ν νκ²½ 93
μ 2 μ μ±λ₯ μ§ν 94
μ 3 μ μ€νμ κ²μ¦ κ²°κ³Ό 97
3.1 μ¬μ©μ λ°μμ± μ΅μ ν 98
3.2 λΉλ‘곡μ μ± μ΅μ ν 105
μ 4 μ λΆμμ νκ° 113
μ 7 μ₯ κ²°λ‘ 121
μ°Έκ³ λ¬Έν 124
Abstract 133Docto
Virtual Runtime based Load Balancing Algorithm for Guaranteeing Fairness on Multicore Systems
Authors' final version리λ
μ€μ κΈ°λ³Έ μ€μΌμ€λ¬μΈ CFSλ ν΄λΌμ°λ μλ²μ κ°μ λκ·λͺ¨ μμ€ν
μμ λ리 μ¬μ©λκ³ μμ§λ§, μ΄λ μμ€ν
μ κ·λͺ¨κ° κ·Ήλλ‘ μ»€μ§μ λ°λΌ μμ€ν
μ΄ μꡬνλ μμ€μ 곡μ μ±μ 보μ₯νμ§ λͺ»νλ€. μ΄ λ
Όλ¬Έμ CFSμ λν μ¬λ κΉμ λΆμμ ν΅ν΄ 곡μ μ± λ³΄μ₯μ μ€ν¨μ μμΈμ κ·λͺ
νκ³ , μ΄λ₯Ό ν΄κ²°νκΈ° μν virtual runtime κΈ°λ°μ λ‘λ λ°Έλ°μ± μκ³ λ¦¬μ¦μ μ μνλ€. μ΄λ νμ€ν¬λ€μ virtual runtime μ°¨μ΄λ₯Ό λ°μ΄λμν€κΈ° μν΄ μ£ΌκΈ°μ μΌλ‘ νμ€ν¬ μ΄μ£Όλ₯Ό μννλ€. μ΄λ₯Ό μν΄ μκ³ λ¦¬μ¦μ μΈμ ν λ CPUμ load μ°¨μ΄κ° μ΅λ κ°μ€μΉ μ°¨μ΄ μ΄νκ° λλλ‘ λ°μ΄λ νκ³ , virtual runtimeμ΄ ν° νμ€ν¬λ€μ loadκ° ν° CPUμμ μνλκ² λ³΄μ₯νλ€. μ°λ¦¬λ μ μλ μκ³ λ¦¬μ¦μ 리λ
μ€ μ»€λ 2.6.38.8 μμ ꡬννκ³ μΌλ ¨μ μ€νμ μννμλ€. κ·Έ κ²°κ³Ό κΈ°μ‘΄ CFSμ κ²½μ° virtual runtime μ°¨μ΄λ μ νμ μΌλ‘ μ¦κ°νλλ° λ°ν΄ μ μλ κΈ°λ²μ 50.53 λ¨μ μκ°μΌλ‘ virtual runtime μ°¨μ΄λ₯Ό λ°μ΄λμν¬ μ μμΌλ©° κ³ μ 0.14%μ λ°νμ μ€λ²ν€λλ₯Ό μΌκΈ°μν΄μ 보μλ€.While the primary task scheduler of Linux, CFS, is widely adopted for the large-scale cloud system, it cannot provide a desired level of fairness when a system scales up to an extreme degree. This paper formally analyzes the behavior of CFS to precisely characterize the reason why it fails to achieve the fairness in multicore systems. Based on the analysis, we present a virtual runtime-based load balancing algorithm which directly bounds the maximum virtual runtime difference among tasks by periodically migrating tasks. In doing so, it bounds the load difference between two adjacent cores by the largest weight in the task set and makes the core with larger virtual runtimes receive a larger load and thus runs more slowly. We have implemented the algorithm into Linux kernel 2.6.38.8. Experimental results show that the maximal virtual runtime difference is 50.53 time units while incurring only 0.14% of run-time overhead comparing to CFS.OAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000004193/2SEQ:2PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000004193ADJUST_YN:YEMP_ID:A005174DEPT_CD:4541CITE_RATE:0FILENAME:(2011μΆκ³ μ°μλ°νλ
Όλ¬Έ) 11-12-12 μ 보과νν λ
Όλ¬Έμ§ CPL-νμΉμ£Ό - μ΅μ’
λ³Έ.pdfDEPT_NM:μ κΈ°Β·μ»΄ν¨ν°κ³΅νλΆEMAIL:[email protected]_YN:NCONFIRM:
DVFSμ κΈ°λ°ν μλλ‘μ΄λ μ€λ§νΈν°μ CPU μλͺ¨ μ λ ₯ μ κ° κΈ°λ²μ νκ³
Authors' final manuscriptOAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000004193/6SEQ:6PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000004193ADJUST_YN:NEMP_ID:A005174DEPT_CD:4541CITE_RATE:0FILENAME:12_μ 보과ννμ§_μ μ λ ₯.pdfDEPT_NM:μ κΈ°Β·μ»΄ν¨ν°κ³΅νλΆEMAIL:[email protected]_YN:NCONFIRM:
λ©ν°μ½μ΄ μμ€ν μμ 곡μ μ± ν₯μμ μν Virtual Runtime κΈ°λ° λ‘λ λ°Έλ°μ± λ©μ»€λμ¦
OAIID:oai:osos.snu.ac.kr:snu2011-01/102/0000004193/4SEQ:4PERF_CD:SNU2011-01EVAL_ITEM_CD:102USER_ID:0000004193ADJUST_YN:NEMP_ID:A005174DEPT_CD:4541CITE_RATE:0FILENAME:11-09-07 μ 보과νν - CFS λ‘λ λ°Έλ°μ±_μΆνμ©.pdfDEPT_NM:μ κΈ°Β·μ»΄ν¨ν°κ³΅νλΆEMAIL:[email protected]:
Framework-assisted Priority Boosting and Load Balancing for Improving Interactivity of Android Smartphones
Authors' final versionλ³Έ λ
Όλ¬Έμ KCC2012μμ μλλ‘μ΄λ κΈ°λ° μ€λ§νΈν°μ μ¬μ©μ μλ΅μ± ν₯μμ μν νλ μμν¬ μ§μ μ°μ μμ λΆμ€νΈ κΈ°λ²μ μ λͺ©μΌλ‘ λ°νλ λ
Όλ¬Έμ νμ₯ν κ²μμ΅κ·Ό μλλ‘μ΄λ νλ«νΌμ νμ¬ν μ€λ§νΈν°μ΄ λ리 보κΈλλ©΄μ μλλ‘μ΄λ νλ«νΌμ λν κ΄μ¬μ λμ± μ»€μ§κ³ μλ€. νμ§λ§ μλλ‘μ΄λ μ€λ§νΈν°μ μ’
μ’
μμ§μ μ¬μ©μ μλ΅μ±μ μ 곡νμ§ λͺ»νλ κ²μΌλ‘ μλ €μ Έ μλ€. μ΄λ μλλ‘μ΄λ μμμ λνν νμ€ν¬κ° λ€λ₯Έ νμ€ν¬μ ꡬλ³λμ§ μκ³ λμΌν μ°μ μμλ‘ μ€μΌμ€λ§ λκΈ° λλ¬Έμ μ¬μ©μ μ
λ ₯μ μ²λ¦¬νλ λμ μ¬λ¬ λ²μ μ μ μ λΉν΄ κΈ΄ μλ΅μκ°μ μ΄λν μ μκΈ° λλ¬Έμ΄λ€. μ΄ λ
Όλ¬Έμ μλλ‘μ΄λ μ€λ§νΈν°μ μ¬μ©μ μλ΅μ± ν₯μμ μν΄ νλ μμν¬ μ§μ μ°μ μμ λΆμ€νΈ κΈ°λ²κ³Ό λ‘λ λ°Έλ°μ± κΈ°λ²μ μ μνλ€. νλ μμν¬ μ§μ μ°μ μμκΈ°λ²μ νλ μμν¬ λ 벨μμ λνν νμ€ν¬λ₯Ό μλ³νκ³ μ΄λ₯Ό 컀λμκ² μ λ¬νλ©°, 컀λ λ 벨μμλ μλ³λ νμ€ν¬μ μ°μ μμλ₯Ό μ λ³μ μΌλ‘ λΆμ€νΈ μν΄μΌλ‘μ¨ μ¬μ©μ μ
λ ₯μ μ²λ¦¬ν λ§νΌ μΆ©λΆν μκ°μ 보μ₯ν΄ μ€λ€. λ‘λ λ°Έλ°μ± κΈ°λ²μ λΆμ€νΈ λ νμ€ν¬λ₯Ό μ¬μ ν λ°©ν΄νλ νμ€ν¬λ€μ λ€λ₯Έ μ€ν νλ‘ μ΄μ£Όμν΄μΌλ‘μ¨, λνν νμ€ν¬μ μλ΅μκ°μ μ΅μν νλ€. μ€ν κ²°κ³Ό λνν νμ€ν¬μ μλ΅μκ°μ΄ μ°μ μμ λΆμ€νΈ κΈ°λ²μ ν΅ν΄μλ κΈ°μ‘΄ μμ€ν
λ³΄λ€ μ΅λ 22% λ¨μΆλ¨μ 보μκ³ λ‘λ λ°Έλ°μ± κΈ°λ²μ ν΅ν΄μλ μ΅λ 43.31% λ¨μΆλ¨μ λ³΄μ¬ μ μλ κΈ°λ²μ ν¨μ©μ±μ μ
μ¦νμλ€.Smartphones on Android platform recently have been come into wide use. However, it is often reported that Android smartphones cannot provide enough interactivity because Android cannot distinguish interactive tasks and non-interactive tasks and they are scheduled with the same priority and preempted. Thus, it occurs poor response time. This paper proposes a framework assisted priority boosting and load balancing for improving interactivity of Android smartphones. The framework assisted priority boosting technique distinguishes the interactive task in the framework level and send the task ID to the kernel. The kernel ensures enough time to process user input by boosting the priority of distinguished task. The load balancing technique minimizes response time of boosted task by migrating tasks disturbing boosted task to other run-queue. The experiment results demonstrate the priority boosting technique reduces response time up to 22% and the load balancing technique along with priority boosting reduces response time up to 43.31% compared to the previous techniques.OAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000004193/8SEQ:8PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000004193ADJUST_YN:YEMP_ID:A005174DEPT_CD:4541CITE_RATE:0FILENAME:(CSTV12-07-09-15).pdfDEPT_NM:μ κΈ°Β·μ»΄ν¨ν°κ³΅νλΆEMAIL:[email protected]_YN:NCONFIRM:
μλλ‘μ΄λ κΈ°λ° μ€λ§νΈν°μ μ¬μ©μ μλ΅μ± ν₯μμ μν νλ μμν¬ μ§μ μ°μ μμ λΆμ€νΈ κΈ°λ²
Authors' final versionOAIID:oai:osos.snu.ac.kr:snu2012-01/102/0000004193/9SEQ:9PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:0000004193ADJUST_YN:NEMP_ID:A005174DEPT_CD:4541CITE_RATE:0FILENAME:12-06-27 μ 보과νν - Android_Interactivity.pdfDEPT_NM:μ κΈ°Β·μ»΄ν¨ν°κ³΅νλΆEMAIL:[email protected]: