1NUS.SOC.CS5248Ooi Wei Tsang

Course Matters

NUS.SOC.CS5248Ooi Wei Tsang

2

Make-Up LectureThis Saturday, 23 OctoberTR7, 1-3pm

Topic: “CPU scheduling”

3NUS.SOC.CS5248Ooi Wei Tsang

Multimedia Storage Issues

NUS.SOC.CS5248Ooi Wei Tsang

4

Media vs. Documents

NUS.SOC.CS5248Ooi Wei Tsang

5

Media vs. Documents large file sizewrite once, read many sequential accessperiodic accessdeadlines

NUS.SOC.CS5248Ooi Wei Tsang

6

Average Service Time?

7NUS.SOC.CS5248Ooi Wei Tsang

OS Review: Disk

NUS.SOC.CS5248Ooi Wei Tsang

8

Disk

head, spindle, track, sector, cylinder

NUS.SOC.CS5248Ooi Wei Tsang

9

Latency components

seek time, rotational time and transfer time

NUS.SOC.CS5248Ooi Wei Tsang

10

Disk Scheduler

disksched

I/O Request

read/write command

11NUS.SOC.CS5248Ooi Wei Tsang

OS Review: Disk Scheduling Algorithm

NUS.SOC.CS5248Ooi Wei Tsang

12

FCFS

98 183 37 122 14 124 65 67

NUS.SOC.CS5248Ooi Wei Tsang

13

SSTF

98 183 37 122 14 124 65 67

NUS.SOC.CS5248Ooi Wei Tsang

14

SCAN (Elevator)

98 183 37 122 14 124 65 67

NUS.SOC.CS5248Ooi Wei Tsang

15

C-SCAN

98 183 37 122 14 124 65 67

NUS.SOC.CS5248Ooi Wei Tsang

16

EDF

98 183 37 122 14 124 65 6730 10 13 5 24 33 21 39

NUS.SOC.CS5248Ooi Wei Tsang

17

EDF-SCAN

98 183 37 122 14 124 65 6730 10 13 5 24 33 21 39

NUS.SOC.CS5248Ooi Wei Tsang

18

Other SchemesFD-SCAN

SSEDO

SSEDV

19NUS.SOC.CS5248Ooi Wei Tsang

Data Placement

NUS.SOC.CS5248Ooi Wei Tsang

20

Contiguous

NUS.SOC.CS5248Ooi Wei Tsang

21

Fragmented

NUS.SOC.CS5248Ooi Wei Tsang

22

Striping (RAID-0)

NUS.SOC.CS5248Ooi Wei Tsang

23

Mirroring (RAID-1)

NUS.SOC.CS5248Ooi Wei Tsang

24

Parity (RAID-5)

NUS.SOC.CS5248Ooi Wei Tsang

25

Parity

NUS.SOC.CS5248Ooi Wei Tsang

26

Summary of ConcernsHigh ThroughputFault TolerantLoad balancing

NUS.SOC.CS5248Ooi Wei Tsang

27

This LectureConsider striping only (RAID-0)

28NUS.SOC.CS5248Ooi Wei Tsang

Efficient Striping Techniques for Multimedia File Servers P. Shenoy, H. VinNOSSDAV 97

NUS.SOC.CS5248Ooi Wei Tsang

29

Design Parametersunit of striping (block size)degree of striping (num of disks)

NUS.SOC.CS5248Ooi Wei Tsang

30

Stripe Unit

NUS.SOC.CS5248Ooi Wei Tsang

31

ModelDisk serves clients in rounds

Time to read media from disk should be smaller than round time

Concern: minimize service time of most heavily loaded disk

NUS.SOC.CS5248Ooi Wei Tsang

32

Effects of Block Size

Block Size

servicetime

NUS.SOC.CS5248Ooi Wei Tsang

33

ProblemFind block size such that the

service time for the most heavily loaded disk is minimize

NUS.SOC.CS5248Ooi Wei Tsang

34

Analysis Model: A Planservice time of the busiest disk

as a function of block sizeexpected num of blocks

accessed on the busiest diskexpected num of blocks

accessed on any disk

NUS.SOC.CS5248Ooi Wei Tsang

35

AssumptionsNon-redundant arrayVBRAnalyze read operation only

NUS.SOC.CS5248Ooi Wei Tsang

36

Variables DeclarationNd : Number of Disks

Nc : Number of Clients

B : Block size

NUS.SOC.CS5248Ooi Wei Tsang

37

Variables DeclarationNb(i,j): Number of blocks client i

access from disk j

Pa(i,m): Probability of i access m blocks in a round

NUS.SOC.CS5248Ooi Wei Tsang

38

AnalysisSuppose i request m blocks

NUS.SOC.CS5248Ooi Wei Tsang

39

Reading 1 blockProb(Nb(i,j)=1)

Nd : Number of DisksNc : Number of ClientsB : Block sizeNb(i,j): Number of blocks client

i access from disk jPa(i,m): Probability of i access

m blocks in a round

NUS.SOC.CS5248Ooi Wei Tsang

40

Reading k blockProb(Nb(i,j)=k)

Nd : Number of DisksNc : Number of ClientsB : Block sizeNb(i,j): Number of blocks client

i access from disk jPa(i,m): Probability of i access

m blocks in a round

NUS.SOC.CS5248Ooi Wei Tsang

41

Blocks Read From a Disk Nb(*,j) =

Nd : Number of DisksNc : Number of ClientsB : Block sizeNb(i,j): Number of blocks client

i access from disk jPa(i,m): Probability of i access

m blocks in a round

NUS.SOC.CS5248Ooi Wei Tsang

42

Busiest DiskNmax =

Nd : Number of DisksNc : Number of ClientsB : Block sizeNb(i,j): Number of blocks client

i access from disk jPa(i,m): Probability of i access

m blocks in a round

NUS.SOC.CS5248Ooi Wei Tsang

43

Access TimeT = Nmax(ts + tr + Btt)

Depends on:block size Bdisk characteristic ts,tr,tt

server design Nd

workload characteristic Nc, Nb(i,j)_

Nd : Number of DisksNc : Number of ClientsB : Block sizeNb(i,j): Number of blocks client

i access from disk jPa(i,m): Probability of i access

m blocks in a round

NUS.SOC.CS5248Ooi Wei Tsang

44

Model Verification

NUS.SOC.CS5248Ooi Wei Tsang

45

Imbalance and Overhead

NUS.SOC.CS5248Ooi Wei Tsang

46

Effects of Block Size

NUS.SOC.CS5248Ooi Wei Tsang

47

Effects of Clients

NUS.SOC.CS5248Ooi Wei Tsang

48

Effects of Num of Disks

NUS.SOC.CS5248Ooi Wei Tsang

49

Choosing Block Size Given Nc, assume rest is fixed find B that minimize T

if T < duration of a round incr Nc and try again

NUS.SOC.CS5248Ooi Wei Tsang

50

There is more.. redundant arrayfinding optimum degree of striping

51NUS.SOC.CS5248Ooi Wei Tsang

Cello: A Disk Scheduling Framework for Next Generation Operating Systems P. Shenoy, H. VinSIGMETRICS 98

NUS.SOC.CS5248Ooi Wei Tsang

52

ProblemHow to co-exist with other

applications?

NUS.SOC.CS5248Ooi Wei Tsang

53

Classes of ApplicationsReal-time

hard/soft periodic/aperiodic

Best-effort interactive troughput-intensive

NUS.SOC.CS5248Ooi Wei Tsang

54

Attempt 1Priority-based schedulerAlways schedule real-time tasks

ahead of best-effort tasks

NUS.SOC.CS5248Ooi Wei Tsang

55

Attempt 2Partition time slots into real-time

and best-effort

NUS.SOC.CS5248Ooi Wei Tsang

56

Attempt 3Assign weight to application class,

based on their priorityService based on weight

NUS.SOC.CS5248Ooi Wei Tsang

57

Attempt 3: CelloTwo-level scheduling

NUS.SOC.CS5248Ooi Wei Tsang

58

Class Independent Scheduler

NUS.SOC.CS5248Ooi Wei Tsang

59

Allocating Disk BandwidthAllocate in proportion to timeAllocate in proportion to bytes

NUS.SOC.CS5248Ooi Wei Tsang

60

Proportionate Time-Allocation

NUS.SOC.CS5248Ooi Wei Tsang

61

VariablesP : Interval of a period I : Idle time so farUi : Allocated time for class iwi : Weightage of class i

NUS.SOC.CS5248Ooi Wei Tsang

62

Proportional Time Allocation

NUS.SOC.CS5248Ooi Wei Tsang

63

Example

Weights 1:1:2P = 100I = 30

10 20 16 14

NUS.SOC.CS5248Ooi Wei Tsang

64

NUS.SOC.CS5248Ooi Wei Tsang

65

r

next

prev

NUS.SOC.CS5248Ooi Wei Tsang

66

Need to Make Sure..Does not exceed share for class i

NUS.SOC.CS5248Ooi Wei Tsang

67

Need to Make Sure..Total service time does not exceed

available time

NUS.SOC.CS5248Ooi Wei Tsang

68

Update and Repeat

next

prev

NUS.SOC.CS5248Ooi Wei Tsang

69

Being Work ConservingWork conserving: “don’t work only

if no work to do”

NUS.SOC.CS5248Ooi Wei Tsang

70

What if..a class have no pending request?

put in no_work group

a class violates one of the constraints? put in too_much_work group

NUS.SOC.CS5248Ooi Wei Tsang

71

Improving UtilizationWhen disk is idle, distribute service

time among classes in too_much_work group

Pick a request from this class and put into scheduled queue

NUS.SOC.CS5248Ooi Wei Tsang

72

Free Time Utilization

NUS.SOC.CS5248Ooi Wei Tsang

73

Class Specific SchedulerHow to pick (r, prev, next)?

Must not affect tasks in queue Idea: Compute slack time

NUS.SOC.CS5248Ooi Wei Tsang

74

Slack Time li Latest time must begin

servicing request iei Earliest time may begin

servicing request idi Deadline for request isi Slack time for i = li – ei

ti Time to service request i

NUS.SOC.CS5248Ooi Wei Tsang

75

Slack Time

i

i

NUS.SOC.CS5248Ooi Wei Tsang

76

Class 1: Interactive Best Effort

next

prev

NUS.SOC.CS5248Ooi Wei Tsang

77

Class 2: High Throughput Best Effort

next

prev

NUS.SOC.CS5248Ooi Wei Tsang

78

Class 3: Real Time Application

next

prev

NUS.SOC.CS5248Ooi Wei Tsang

79

Evaluationsresponsetime

# video

NUS.SOC.CS5248Ooi Wei Tsang

80

Evaluations%time

time

NUS.SOC.CS5248Ooi Wei Tsang

81

Cello SummaryOS disk schedulerSupport multiple classesProtect classes from each otherWork conservingUse two-level scheduling