論文 / 著書情報
Article / Book Information
Title

A Power Saving Storage Method That Considers Individual Disk
Rotation

AuthorSatoshi Hikida, Hieu Hanh Le, Haruo Yokota

Journal/Book name

Database Systems for Advanced Applications Lecture Notes in
Computer Science, Volume 7239/2012, , pp. 138-149

発行日 / Issue date2012, 4

DOI

http://dx.doi.org/10.1007/978-3-642-29035-0̲10

権利情報 / Copyright

The original publication is available at www.springerlink.com.

Note

このファイルは著者（最終）版です。
This file is author (final) version.

Powered by T2R2 (Science Tokyo Research Repository)

A Power Saving Storage Method That Considers
Individual Disk Rotation
Satoshi Hikida, Hieu Hanh Le, and Haruo Yokota
Department of Computer Science, Tokyo Institute of Technology
2-12-1 Ookayama, Meguro-ku, Tokyo 152-8552, Japan{hikida,hanhlh}@de.cs.titech.ac.jp, yokota@cs.titech.ac.jp

Abstract. Reducing the power consumption of storage systems is now considered a major issue, alongside the maintenance of system reliability, availability, and performance. In this paper, we propose a method named as the Replicaassisted Power Saving Disk Array (RAPoSDA) to reduce the electrical consumption of storage systems. RAPoSDA utilizes a primary backup configuration toensure system reliability and it dynamically controls the timing and targeting of
disk access based on individual disk rotation states. We evaluated the effectiveness of RAPoSDA by developing a simulator that we used for comparing the performance and power consumption of RAPoSDA with Massive Arrays of Inactive
Disks (MAID), which is a well-known power reduction disk array. The experimental results demonstrated that RAPoSDA provided superior power reduction
and a shorter average response time compared with MAID.

Keywords: storage, power saving, performance, large scale, reliability

1Introduction

Ongoing increases in the total electricity consumed by data centers present significant
problems that must be solved to reduce the running cost of centers and to keep the global
environment green. A governmental report estimated that the electricity consumptionof US data centers in 2011 would be double that of 2006 [11].
Servers and storage systems are the two main data center components that consume
electricity. They tend to grow at a numerically faster rate, because of the increasing
requirements for processing load and the targets of processes. The amount of data stored
in storage systems is increasing particularly rapidly, because of the explosive increase in
the volume of data generated by the Internet. The IDC reports that the growing amountof digital data created and replicated will surpass 1.8 zettabytes in 2011 [7]. Many
services are leveraged by cloud computing, which is becoming widespread in our daily
life and business, including social network services, data sharing services, and movie
sharing services. These services require large-scale storage, which is characterized bywriting new data and reading recent data, while only a few read old data. In this paper,
we focus on a power saving method for large-scale storage systems that involve timeskewed data access.
Many methods have been proposed to reduce the power consumption of storage
systems. A typical approach is to spin down some of the hard disk drives in a storage

2

Satoshi Hikida, Hieu Hanh Le, and Haruo Yokota

system, because rotation of the platters in a disk drive accounts for most of the electricity consumption by a storage system. Thus, the electricity consumption of a disk isdecreased by spinning it down.
A well-known system that uses this approach is MAID (Massive Arrays of Inactive Disks) [3]. MAID keeps a small number of disk drives rotating at all times, which
are used as a cache (known as cache disks), and this allows other disk drives to spin
down (known as data disks). The MAID approach is effective for reducing power consumption when data access is time skewed, because numerous data disk drives store
infrequently accessed old data and this allows disk rotation to be suspended. However,
the original version of MAID did not consider system reliability. Thus, data stored on adisk are lost if one of data disks fails in the MAID system.
If we introduce a simple replica-based fault-tolerant configuration into MAID, synchronization between replicas during update operations would reduce the effect of saving power consumption because an increased number of write operations on disks elevates the number of spinning disks. In contrast, if we choose to improve timing when
applying replica updates, we can reduce power consumption and maintain system reliability. In this paper, we propose a Replica-assisted Power Saving Disk Array (RAPoSDA) as a method for dynamically controlling the timing of disk write operations byconsidering the rotation status of disks storing replicas.
RAPoSDA employs a duplicated write cache memory to maintain reliable data andit waits for a suitable time to write to an appropriate disk, thereby avoiding unnecessary
disk spin-ups. We assume that there is an independent power supply (UPS) for the
duplicate cache memory to ensure tolerance of power shortages or a UPS failure. Dataon data disks are replicated in RAPoSDA as a primary backup configuration to ensure
system reliability. RAPoSDA also has cache disks that provide large read cache spaces,
as found with MAID, but they do not need to be replicated. Cache disks are an optionalfeature in RAPoSDA if there is sufficient cache memory.
The main contribution of this approach is the introduction of careful control overtiming and targeting of disk access by replicas, which is achieved by dynamically checking the rotation status of individual disk drives. To ensure system reliability and reduce
power consumption, RAID-based low power consumption storage systems [9, 8] andpower proportional disk arrays using replicas [14, 13, 1] have also been proposed. However, those other methods do not check the rotation status of each disk drive.
A simulation was more appropriate than empirical experiments and disks when evaluating the performance and power consumption of a storage system with changing configurations, including various sizes of cache memory, disk capacity, number of disks,and particularly with large numbers of disks. Therefore, we developed a dedicated simulator to compare RAPoSDA with MAID and a simple disk array with no power saving
mechanism. We also prepared synthetic workloads with skewed data access based ona Zipf distribution and different ratios of read/write requests. The experimental results
using the simulator indicated that RAPoSDA provided superior power reduction and ashorter average response time compared with MAID.
The remainder of this paper is organized as follows. Section 2 describes the power
consumption model of a disk drive and a general approach to power reduction for astorage system with disk drives. Section 3 describes the details of our proposed stor-

A Power Saving Storage Method That Considers Individual Disk Rotation3

age system, RAPoSDA. Section 4 outlines the simulator we developed to evaluate theperformance and power consumption of a storage system. A detailed discussion of ourevaluation of RAPoSDA and MAID in terms of power saving and performance is reported in Section 5. Section 6 presents a number of related studies. Finally, Section 7
provides the conclusions of this paper.

2

Disk Drive Power Consumption Model

A disk drive is mainly composed of mechanical and control parts. The mechanical parthas four components: platters, a spindle motor, read and write heads, and an actuatorto move the heads over the platters. The controller is a component of the control partthat performs read and write operations to comply with requests. Of these components,
the spindle motor, actuator, and controller consume the most electricity in a disk drive,
depending on its state.
A disk drive has three states, as shown in Table 1. It consumes the most power
when it is in an active state, because the spindle motor, actuator, and controller are all
working. It consumes the least in the standby state, because all components are notworking, whereas only the spindle motor is working in the idle state. The standby statetransfers to the active state after a read or write request. The idle state transfers to thestandby state via spin-down, and vice versa via spin-up.
Compared with the active state, a disk drive consumes larger amounts of electricity
when it spins up or down, especially at the beginning of spin-up. This means that frequent spin-ups and spin-downs to provide short standby states are not good for powersaving. Thus it is important to keep unaccessed disk drives in a standby state for as longas possible. The duration of a standby state where a spin-up and spin-down requiring
energy consumption does not exceed that of the idle state is known as the break-eventime. A power saving is produced only if the duration of the standby state is longer thanthe break-even time.
Table 1. Disk-drive Status and Corresponding Power Consumption

State
ActiveIdle
Standby3

I/O
In operation
No operation
No operation

RPM
max rotation
max rotation0

Head location Poweron diskLarge
on disk
Middleoff disk
Small

RAPoSDAOne approach for reducing power consumption in a storage system with multiple harddisk drives is to divide the disk drives into two groups. Disk drives in one group are

4Satoshi Hikida, Hieu Hanh Le, and Haruo Yokota

Fig. 1. Configuration of RAPoSDA

mainly kept in the standby state for longer than the break-even time, while disk drives
in the other group are kept in active or idle states by access localization.
MAID (Massive Arrays of Inactive Disks) [3] is a well-known system that takes
this approach. MAID ensures that a small number of disk drive are always kept in idle
or active state as cache disks, while the remaining large number of disks are kept ina standby state as data disks. All read and write requests are initially dealt with by
the cache disks and a replacement algorithm is used to keep the hit ratio high. Thisapproach is effective in reducing the power consumption of a storage system. However,
the original MAID method had problems of reliability, which is a major requirementfor data centers. There is no means of recovering data in the event of a data disk failure.
Direct importation of replicas into MAID might make it more reliable, but it would havedetrimental effects on power consumption because the increased disk access required
for replicas might violate the break-even time restriction.
To solve this problem, we propose a method for controlling the timing and targetingof replica disk access by dynamically checking the rotation status of individual disk
drives. This reduces the power consumption and maintains system reliability. To implement the method, we propose the RAPoSDA storage system configuration.

3.1

RAPoSDA Configuration

In RAPoSDA, we adopt the chained declustering [6] method for data placement on data
disks as a primary backup configuration that tolerates disk failures. When writing data
onto data disks, RAPoSDA tries to select a disk that is currently rotating or one that has
been longer in the standby state than the break-even time. This means that RAPoSDA
has to maintain data elsewhere when waiting for the write timing. We use a write cachememory to temporarily maintain data. It is important to maintain reliability when thedata are in the volatile cache memory, so we provide the cache memory with a primary
backup configuration that corresponds to the data disks. As with MAID, RAPoSDA canuse some disks as cache disks to provide larger read cache spaces. Figure 1 shows theconfiguration of RAPoSDA.

A Power Saving Storage Method That Considers Individual Disk Rotation

5

Fig. 2. Data Flow in RAPoSDA During Write Requests

Data Disks Chained declustering is a simple but effective strategy for data placementthat provides good reliability and accessibility when the backup data is logically locatedin the disk next to the primary. We assume that a data disk spins down and moves to a
standby state if the time without access is longer than a predefined threshold time.
Cache Disks When the size of cache memories is not sufficient for comparing thetotal capacity of a disk array, cache disks are effectively used for enlarging the readcache space. However, cache disks are optional in RAPoSDA if there is sufficient cachememory and access localization. The cache contents are copies, so they do not need tobe replicated. In contrast to data disks, we assume that cache disks do not spin down.
Therefore, a large number of cache disks is not appropriate for reducing power consumption.
Cache Memory RAPoSDA has two layers of cache memories that correspond to theprimary and backup data disks, while one cache memory is shared by more than one
disk drive. Each layer is connected to an individual power supply (UPS) to ensure thetolerance of power shortages or UPS failures.
3.2

Handling Write Requests

Write requests are processed in RAPoSDA as shown in Figure 2. Data are initially written into both the primary and backup layer of the cache memory. The written data aregathered in a corresponding buffer location in the cache memory of each individual
disk that is responsible for storing the data. Buffered data are written onto their corresponding data disks when the amount of buffered data on the cache memory exceeds
a predefined threshold. The rotation status of the data disk is investigated at this point.
The data disk will spin up if it is in a standby state. When the disk enters an active state,
all data on the location that corresponds to the disk in the cache memory are written todisks and then deleted from the cache memory. When a buffer overflow occurs in the
primary layer corresponding to Pi , all data in the backup layer buffer for Bi−1 are alsotransferred onto the data disk. However, if the buffer overflow occurs in Bi , the data

6

Satoshi Hikida, Hieu Hanh Le, and Haruo Yokota

Fig. 3. Data Flow in RAPoSDA During Read Requests

in Pi+1 are also transferred. Therefore, the amount of data in the primary layer of thecache memory is different from that in the backup layer.
This collective writing process reduces the frequency of spin-ups and spin-downs.
Data are also copied to the cache disks to ensure quick responses for future read requests
when there is time-skewed access. The remaining data disks with data still in the buffer
stay in a standby state beyond the break-even time.
3.3

Handling Read Requests

As shown in Figure 3, read requests initially check the existence of data in the cachememory, followed by cache disks. The cache memory has primary and backup layers,and both layers are searched for data. If the target data are in the cache memory or cachedisks, the data are returned without accessing the data disks. If the data do not exist in
the cache memory or cache disk, the data are read from a data disk.
Chained declustering is the method used for primary backup data placement on data
disks, so RAPoSDA selects an appropriate disk from the two disks that correspond to
the primary and backup for data. This selection is also important for reducing power
consumption while still maintaining the break-even restriction. We propose the following set of rules for selecting the disk.
– If only one data disk is active, select the one that is active.
– If both data disks are active, select the disk with the largest memory buffer capacity.
– If both data disks are in standby, select the disk with the longer standby duration
period.
Data read from data disks are also copied to cache disks to ensure a rapid response in
future read requests when there is time-skewed access.

4

Disk Array Simulator

A number of simulators, such as DiskSim [4], have been proposed for evaluating theperformance of storage systems. However, many cannot measure power consumption,
including DiskSim. Dempsey [15] used an expansion of DiskSim with a function for

A Power Saving Storage Method That Considers Individual Disk Rotation

7

Fig. 4. Simulator Configuration

measuring power consumption, but it needed to measure the power of the actual disk
drives in advance and there was a limitation on the number of hard disks that could be
used in a simulation. Thus, we developed a new simulator to evaluate the performanceand power consumption of RAPoSDA and MAID.
The developed simulator is shown in Figure 4. It simulates behavior of each disk
drive in the target storage system with a given workload, including the response timeand power consumption, and it can flexibly change its configuration and workload.
The simulator initially sets up the parameters for the workload and the configuration of the cache memories, cache disks, and data disks. Clients inside the simulator
then generate requests at times assigned by the workload. The Storage Manager dispatches the requests to the cache memories, cache disks, and data disks, based on information from the Data Layout Manager. Logs of the operation status for each device
are collected by the Log Collector and analyzed by the Analyzer after finishing thesimulation.

5

Evaluation

We used the simulator described in the previous section to compare the performance andpower consumption of RAPoSDA, MAID, and a Normal system that was composed ofa simple disk array with no power saving mechanism. In this paper, we mainly focus
on the effect of read/write ratio for their performance and power consumption. We also
evaluated other aspects, including their scalability. The evaluation results on the scalability indicate the superiority of RAPoSDA to MAID. Because of the page limits, wewill report the details of the scalability evaluation in the other chance.
The original MAID proposed by [3] had no cache memory. However, many practicalstorage systems have cache memories and the cache memories in RAPoSDA play avery important role in reducing power consumption. To ensure a fair comparison, we8Satoshi Hikida, Hieu Hanh Le, and Haruo Yokota

Fig. 5. Parameters for the Hard Disk
Drive Used in the Simulation
parameter
value
Capacity (TB)
2
Number of platters
5
RPM
7200
Disk cache size (MB)32
Data transfer rate (MB/s) 134
Active power (Watt)
11.1
Idle power (Watt)
7.5
Standby power (Watt)
0.8
Spin-down energy (Joule) 35.0
Spin-up energy (Joule)450.0
Spin-down time (sec)0.7
Spin-up time (sec)
15.0

Fig. 6. Parameters of the Synthetic Workload

Workload parameter
value
Time
5 hours
read:write
7:3, 5:5, 3:7
Number of files
1,000,000 (32KB/file)
Amount of file size
64GB (Primary × Backup)
Number of requests
λ× 3600 × Time
Distribution of access
Zipf distribution
Request arrival distribution Poisson process
Zipf factor
1.2
Mean arrival rate (λ)
25 (request/sec)

introduced cache memory into MAID and evaluated the effect of cache memory withthe three storage systems.
To ensure reliability, we also modified MAID so it had two replicas on the data disks
to match RAPoSDA. However, MAID had no replica in the cache memory and cachedisks because the data in the cache was only a copy. To prevent data loss from the cacheduring failures, the cache memory and cache disk in MAID used the ‘write through’protocol. To handle replicas in the data disks, MAID randomly selected disks for the
replicas. Normal also used replicas and it provided a faster response than the othermethod. RAPoSDA determined the access disk based on the rotation state of individual
disks.
The hard disk drive model used in our simulator was based on the Hitachi Deskstar
7K2000[12] produced by Hitachi Global Storage Technologies. Table 5 shows the parameters of the model. Furthermore, We prepared a synthetic workload for the evaluation. The workload parameters used in this experiment are listed in Table 6. In theworkload, the access skew was based on Zipf distribution and the request arrival rate
was based on a Poisson distribution. A workload was generated with three different
types of read:write ratio, 7:3, 5:5, and 3:7.
In this evaluation, we set the simulation parameter as follows. The number of data
disks was 64 with six cache disks and the total capacity of the cache memory was thenumber of data disks × 1/4 GB.
5.1

Power Consumption and Power Reduction Rate

Figure 7 shows the power consumption of Normal, MAID, and RAPoSDA, and thepower reduction ratio of MAID and RAPoSDA when compared with Normal. This figure shows that Normal was the highest power consumer and that the power consumption of Normal increased with an increase in the write frequency. In contrast, MAID
and RAPoSDA decreased power consumption with an increased write frequency. This

A Power Saving Storage Method That Considers Individual Disk Rotation
Normalh] 2.5
w
K
[ 2.0
onti
p 1.5
um
sn 1.0oC
er 0.5
w
o
P 0.0

MAID

RAPoSDA

100

9MAID RAPoSDA

]
%
[ 80
no
it
cu 60
de
R 40
er
w
o 20
P

7:3

5:5
Read:Write

3:7

0

7:3

5:5

Read:Write

3:7

Fig. 7. Power Consumption of Each Storage System and the Power Reduction Ratios of RAPoSDA and MAID versus Normal

16000
14000

pu12000-nip10000
Sf 8000
or6000
be 4000m
u 2000N
0MAID RAPoSDA

7:3

5:5

Read:Write

16000
14000

3:7

n
12000
ow
-dn10000
ip
Sf 8000
or 6000
eb 4000m
u 2000N 0

MAID RAPoSDA

7:3

5:5

Read:Write

3:7

Fig. 8. Spin-up and Spin-down Counts with MAID and RAPoSDA

shows that MAID and RAPoSDA achieve significant power savings. The power reduction ratio of RAPoSDA was higher than MAID with all read/write ratios. This matched
our assumption of time-skewed data access with high write requests.
The disk drive power consumption depended on the rotation state and the numberof spin-ups or spin-downs. If spin-ups and spin-downs occurred frequently, the power
consumption may exceed that with no disk spin-downs. Control of excessive spin-ups
and spin-downs is very important for power saving in the storage system.
Figure 8 shows the number of disk spin-ups and spin-downs with MAID and RAPoSDA (Normal had no spin-downs). The graph shows that the trend for MAID wasdecreasing a number of spin-ups and spin-downs with a decreasing read frequency,
while the trend for RAPoSDA was an increasing spin-up and spin-down count. Fromthe perspective of the write cache size, MAID had a larger write cache than RAPoSDA
because MAID used the cache disks for reads and writes, whereas RAPoSDA only usedthem for reads and this led to a smaller write cache memory compared with cache disks.
This led to the possibility of a higher hit ratio of write requests for MAID and a smaller
number of spin-ups and spin-downs with a frequent write workload.
However, the power reduction ratio shown in Figure 7 indicates that RAPoSDA
gave a greater power reduction ratio compared with MAID. This shows that the group
writing method of RAPoSDA provided a beneficial effect in maintaining the break-eventime for individual data disks, even though the total counts of spin-ups and spin-downs
with RAPoSDA exceeded those with MAID.

10

Satoshi Hikida, Hieu Hanh Le, and Haruo Yokota
NormalMAID

RAPoSDA

0.004

7:3
teri
0.004
:W
ade 5:5
R
0.004
3:7

3.308

1.296
0.893

2.911

2.302
0.559
Average Response Time [sec]Fig. 9. Average Response Time with Normal, MAID, and RAPoSDA

5.2 Average Response Time
Figure 9 shows the average response time for each storage system. The graph shows that
Normal had the fastest response time but Normal consumed the most amount of power,
because the disks were always spinning. The average response time of RAPoSDA wasfaster than that of MAID. When the average response time of MAID changed from2.302 sec to 3.308 sec, the corresponding values for RAPoSDA fell in the range 0.559
sec to 1.296 sec.
Based on the previous discussion of hit ratios for the write cache, it seemed possiblethat the average response time of MAID was shorter than that of RAPoSDA, because thecache hit was effective in reducing the response time. However, Figure 9 demonstrates
that RAPoSDA was also superior to MAID in terms of the average response time. Oneof the main reasons for this was the cache protocol. MAID adopted a write throughprotocol for cache memories and cache disks to prevent data loss because of failures.

6

Related Studies

This section briefly reviews related systems other than MAID.
In DRPM [5], the power consumption of disk drives can be expressed as a functionof the rotation speed (RPM). To achieve good performance and low power consumption, DRPM utilizes multispeed disk drives that can dynamically change the rotation
speed of the disk depending on the system’s workload. Similarly, Hibernator [16] exploited this concept to implement power saving and performance controlled by a RAID
configuration of multispeed disk drives.
The reduction of power consumption by network servers, such as Web servers andProxy servers, was investigated by Carrera [2]. According to that report, multispeed
hard disk drives are necessary to reduce power consumption and maintain server response performance. However, dynamic changes in the frequency of disk drive rotations
present many technical challenges. As a result, such hard disk drives are not currently
popular in practical use.
PARAID [14] is a powerful power saving technique for targeting RAID-based storage [10]. The controller skews the access to a small number of disk drives. It then createsinaccessible disks and spins down these disks to reduce power consumption. GRAID[9] places an emphasis on ensuring reliability and power savings based on RAID10 diskarrays. Using information at the log disk that is added into the normal disk to store logs,

A Power Saving Storage Method That Considers Individual Disk Rotation

11

the system only needs to update the mirror disks periodically, so the system can spin
down all the mirror disks to a low-power mode for most of the time and save energy.
EERAID [8] is a power saving method that is focused in the RAID controller layer.
EERAID reduces the power consumption using dynamic I/O scheduling and a cachemanagement policy.
SIERRA[13] and RABBIT[1] are distributed storage systems that implement power
proportionality through leveraging cluster-based data placement with data replication.
These methods achieve proportional relation between power consumption and system
performance by dividing all storing nodes into groups and controlling which groups areto be active to serve certain workloads.

7

Conclusions

Large-scale, high-performance, reliable, and low-power storage systems are required
to construct better data centers for cloud computing. In this paper, we proposed RAPoSDA (Replica-assisted Power Saving Disk Array) for use with such storage systems.
RAPoSDA carefully controls the timing and targeting of disk access by dynamicallychecking the rotation status of individual disk drives. We compared the performanceand power saving effects of RAPoSDA with modified MAID in simulations with different ratios of read/write requests in the workloads. The original version of MAID had
no cache memory and no replication mechanism, so we added them to MAID to makea fair comparison.
The experimental results showed that RAPoSDA and the modified MAID provide
reduced power consumption compared with a simple disk array with no power saving
mechanism. However, RAPoSDA was superior to the modified MAID. From the performance perspective, the simulation results showed that the average response time of
RAPoSDA was shorter than that of the modified MAID. Thus, consideration of individual disk rotation is an effective method for reducing the power consumption of storage
systems, while maintaining good performance.
In future work, we will consider distributed file systems such as Hadoop Distributed
File System (HDFS) and Google File System (GFS) which accepts more than two replicas, as power saving storage systems. We also aim to develop an experimental systemwith actual disk drives and evaluate the system using actual workloads.

Acknowledgment
This work is partly supported by Grants-in-Aid for Scientific Research from Japan Science and Technology Agency (A) (#22240005).

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