p-Jigsaw: A Cluster-based Web Server

with Cooperative Caching Supports

p-Jigsaw: A Cluster-based Web Server

with Cooperative Caching Supports

Ge Chen, Cho-Li Wang, Francis C.M. Lau(Presented by Cho-Li Wang)

The Systems Research GroupDepartment of Computer Science and Information Systems

The University of Hong Kong

2

What’s a cluster ?What’s a cluster ?

A cluster is a type of parallel or distributed processing system, which consists of a collection of interconnected stand-alone/complete computers cooperatively working together as a single, integrated computing resource – IEEE TFCC.

3

Rich Man’s ClusterRich Man’s Cluster Computational Plant (C-Plant

cluster) Rank: 30 at TOP500 (11/2001) 1536 Compaq DS10L 1U servers

(466 MHz Alpha 21264 (EV6) microprocessor, 256 MB ECC SDRAM)

Each node contains a 64-bit, 33 MHz Myrinet network interface card (1.28 Gbps/s) connected to a 64-port Mesh64 switch.

48 cabinets, each of which contains 32 nodes

(48x32=1536)

4

Poor Man’s ClusterPoor Man’s Cluster HKU Linux Cluster 32 733 MHz Pentium III PCs,

392MB Memory Hierarchical Ethernet-based

network : four 24-port Fast Ethernet switches + one 8-port Gigabit Ethernet backbone switch)

Additional 80-port Cisco Catalyst 2980G Fast Ethernet Switch

6

Cluster Computer ArchitectureCluster Computer Architecture

High-Speed LAN (Fast/Gigabit Ethernet, SCI, Myrinet)

Availability Infrastructure

Single System Image Infrastructure

Programming Environment

(Java, C, MPI, HPF)

Web WindowsUser Interface

Other Subsystems(Database, Web server

OLTP, etc.)

OS

Node

OS

Node

OS

Node

OS

Node

7

Talk OutlineTalk Outline Motivation -- The Need for Speed Cluster-based Solutions System Architecture of p-Jigsaw Performance Evaluation Conclusion and Future Work Other SRG Projects

8

The ChallengesThe Challenges Netscape Web site in November 1996: 120 million hits

per day Microsoft Corp. Web site received more than 100 M

hits per day. (1,200 hits per second) Olympic Winter Games 1998 (Japan): 634.7M (16 days),

peak day 57M, peak minute 110K Winbledon July 1999, 942 M hits (14 days), peak day

125M, peak minute 430K Olympic Games 2000 : peak day 502.6 M, peak minute

600K hits. (10K hits per second)

9

The Need for SpeedThe Need for Speed Internet user popularity is growing very fast

According to United States Internet Council’s report, regular Internet user has increased from less then 9M in 1993 to more than 300M in the summer of 2000, and is still growing fast

Broadband becomes popularAccording IDG’s report, 57% of the workers in U.S access Internet via broadband in office. The figure will be more than 90% by 2005. Home broadband user will also increase from less than 9M now to over 55M by 2005

HTTP requests account for larger portion of Internet traffic now

One study shows that HTTP activity has grown to account for 75%~80% of all Internet traffic

11

The Need for SpeedThe Need for Speed The Need for Speed

Growing user numberFaster last-mile connection speed Increasing portion of HTTP requests accounts for all Internet traffic

Require a more powerful Web server architecture

Cluster-Based SolutionCluster-Based Solution

Cluster -- A Low-cost yet efficient parallel computing

architecture

15

Dispatcher-basedDispatcher-based

Dispatcher

A network component of the Web-server system acts as a dispatcher which routes the requests to one of the Web servers to fulfill the load balancing. Each Web server works individually.

InternetInternet

client

Layer 4 switching with level 2 address translation :

One-IP, IBM eNetwork, WebMux, LVS in DR mode

Layer 4 switching with level 3 address translation : Cisco LocalDirector, Alteon ACEDirector, F5 Big/IP, LVS in NAT mode.

Layer 7 switching (Content-based): LARD, IBM Web Accelerator, Zeus Load Balancer (ZLB)

17

p-Jigsaw -- Goalsp-Jigsaw -- Goals High Efficiency:

Explore aggregate power of cluster resources (CPU, memory, disk, network bandwidth).Explore in-memory Web caching on cluster-based Web servers

High Scalability Maintain high cache hit rate and high throughput as cluster size growsEliminate potential bottleneck in the overall design

High PortabilityMulti-platform supportHeterogeneous cluster

18

Main Features of p-Jigsaw Web serversMain Features of p-Jigsaw Web servers

Global Object Space (GOS) Hot Objects Caching Cooperative Object Caching Distributed Cache Replacement Algorithms

19

Global Object SpaceGlobal Object Space(All Web objects in system are visible and accessible to every (All Web objects in system are visible and accessible to every

node through GOS)node through GOS)

OSOSOSOS

JVMJVMJVMJVM

p-Jigsawp-Jigsawp-Jigsawp-Jigsaw

OSOSOSOS

JVMJVMJVMJVM

p-Jigsawp-Jigsawp-Jigsawp-Jigsaw

OSOSOSOS

JVMJVMJVMJVM

p-Jigsawp-Jigsawp-Jigsawp-Jigsaw

OSOSOSOS

JVMJVMJVMJVM

p-Jigsawp-Jigsawp-Jigsawp-Jigsaw

Server NodeServer Node Server NodeServer Node Server NodeServer Node Server NodeServer Node

High-Speed LAN

Global Object SpaceGlobal Object Space

Memory Cache Memory Cache Memory Cache Memory Cache

Hot Object Cache

23

Incoming Request: http://p-Jigsaw.org/node4/dir2/pic1.jpg

Hard

diskH

ard disk

Hot Object CacheHot Object Cache

Node 1Node 1

1111

Local Object Table for Node 1Local Object Table for Node 1Object URLObject URL AGACAGAC LACLAC HNHN

//node3/dir31/fig311.jpgnode3/dir31/fig311.jpg 1500015000 100100 33

//node1/dir12/fig121node1/dir12/fig121 1100011000 5050 11

…… …… …… ……2222

Node 2Node 2 Node 3Node 3Node 4Node 4

Global Object Table for Node 1Global Object Table for Node 1Object URLObject URL HNHN AGACAGAC CCNNCCNN

//node4/dir2node4/dir2 44…… …… …… ……

//node1/dir12/fig121.bmpnode1/dir12/fig121.bmp 11 1100011000 2-3-42-3-4

Hard

diskH

ard disk

Hot Object CacheHot Object Cache

Hard

diskH

ard disk

Hot Object CacheHot Object Cache

Hard

diskH

ard disk

Hot Object CacheHot Object Cache

Mis

Mis

s!s!

3333

Global Object Table for Node 4Global Object Table for Node 4Object URLObject URL HNHN AGACAGAC CCNNCCNN

…… …… …… ……

//node4/dir12/pic1.jpgnode4/dir12/pic1.jpg 44 1500015000 2-3-42-3-4

4444

6666

HN HN : Home Node: Home NodeAGAC AGAC : Approximated Global Access Counter : Approximated Global Access CounterCCNN CCNN : Cache Copy Node Number: Cache Copy Node NumberLAC LAC : Local Access Counter: Local Access Counter

Redirect the request to node 4Redirect the request to node 4(Home node of the requested page)(Home node of the requested page)Search on GOT1 (Hashing)Search on GOT1 (Hashing)

Cached copy is forwarded from node 2,3, Cached copy is forwarded from node 2,3, or 4, depends on the server workloador 4, depends on the server workload

Cached copy is forwarded from node 2,3, Cached copy is forwarded from node 2,3, or 4, depends on the server workloador 4, depends on the server workload

5555

Cached in node 1

24

Distributed Cache ReplacementDistributed Cache Replacement Two LFU-based Algorithms are Implemented:

LFU-Aging: AGAC/ 2 ; every △ tWeighted-LFU: AGAC/ (file size)Global LRU (GLRU) is implemented for comparison

Try to cache the “hottest objects” in global object space Cached object’s life time is set according to HTTP

timestamp. Cache consistency is maintained by invalidation scheme.

25

Update of Access CountersUpdate of Access Counters

GOS

GOT for Node 1

Object URL/Partial URL AGAC HN

/node3/dir31/doc3.html 3

/node4/dir41 4

/node1/dir11/doc1.html 105 1

… … …

LOT for Node 1

Object URL LAC AGAC HN

/node3/dir32/pic3.jpg 45 200 3

/node1/dir11/doc1.html 24 105 1

… … …

GOT for Node 3

Object URL AGAC HN

/node3/dir31/doc3.html 50 3

/node3/dir32/pic3.jpg 200 3

… … …

1 2 3 4

HOC HOC HOC HOC

45+200 = 245

245

2450

LAC is periodically sent back to objects’ HN to maintain an approximate global access counter for every cached object

27

Experiment SetupExperiment Setup 32-node PC cluster. Each node

consists of a 733MHz Pentium III PC running Linux 2.2.4.

The nodes are connected with an 80-port Cisco Catalyst 2980G Fast Ethernet Switch.

A NFS server (2-way SMP) with Gigabit Ethernet link to the switch.

16 nodes acts as clients, and the rest as Web servers.

Each of the server nodes has 392MB physical memory installed

32-node PC cluster

28

Requests Throught ( With 64MB HOC at each node)

0

100

200

300

400

500

600

2 Nodes 4 Nodes 8 Nodes 16 Nodes

Req

uest

s/S

econ

d

Weighted-LFU with CC LFU-Aging with CCGLRU with CC Weighted-LFU without CCLFU-Aging without CC Without GOS Support

Experiment ResultsExperiment Results

Effects of Scaling the Cluster Size

4.56

2.02

29

Experiment ResultsExperiment Results

Effects of Scaling the Cache SizeRequests Throughput (16 nodes)

0

100

200

300

400

500

600

1.8% 3.6% 7.2% 14.4%

Relative Cache Size

Weighted-LFUwith CC

LFU-Agingwith CC

GLRU with CC

Weighted-LFUwithout CC

LFU-Agingwithout CC

Aggregated Cache size for 16 nodes = 1.8% (8 MB per node), 3.6%, 7.2%, and 14.4% (64 MB per node) of the size of the data set

31

Analysis of Requests Handle PatternsAnalysis of Requests Handle Patterns Local Cache Object (in local memory)

The server that receives the request has the requested object in its local hot object cache.

Peer Node Cache Object (in remote memory)The server that receives the request does not have the requested object in its local hot object cache. The object is fetched from either the home node or a or other peer nodes.

Disk Object (local or remote disk)The requested object is not in the global object space, and has to be fetched from the file server. This has the longest serving time.

32

Weighted-LFU with CC(64MB HOC Size at Each Node)

0

0.2

0.4

0.6

0.8

1

4 Nodes 8 Nodes 16 Nodes

Local Cache Object Peer Node Object Disk Object

Analysis of Requests Handle PatternsAnalysis of Requests Handle Patterns

~60%

LFU-based algorithms show high local cache hit rates. With 64 MB cache per node, the local cache hit rate is around 60% for both Weighted-LFU and LFU-Aging,

33

Weighted-LFU with CC(8MB HOC Size at Each Node)

0

0.2

0.4

0.6

0.8

1

4 Nodes 8 Nodes 16 Nodes

Local Cache Object Peer Node Object Disk Object

Analysis of Requests Handle PatternsAnalysis of Requests Handle Patterns

~6.7%

~35.2%~50%

~25%

With small cache size (8MB), the cooperative cache can improve the global cache hit rate and reduce the costly file server disk access, which is a common bottleneck

for a website.

36

ConclusionsConclusions Use of cluster wide physical memory as object

cache can lead to improved performance and scalability of Web server systems

With relatively small amount of memory dedicated for object content caching, we are able to achieve a high hit rate with the cooperative caching

Favor replicating more hot objects rather than squeezing more different objects into the global object space.

37

Future WorkFuture Work

The HKU “Hub2World” ProjectBuild a giant proxy cache server on a large PC cluster with HKU’s 300-node Gideon cluster based on p-Jigsaw

Cache hot objects on 150 GB in-memory cache (0.5GB x 300) + 12 Terabytes disk space (40GB x 300)

Design of new caching algorithms

Other SRG ProjectsOther SRG Projects

Welcome to download our software packages and test them on your clusters.

URL: http://www.srg.csis.hku.hk/

39

Current SRG ClustersCurrent SRG Clusters

40

JESSICA2 – A Distributed JVMJESSICA2 – A Distributed JVM

JVM JVM JVM JVM JVM

Thread Migration

Global Object Space

JVM

A Multithreaded Java Program

41

JUMP Software DSMJUMP Software DSM Allows programmers to assume a globally shared virtual

memory, even they execute program on nodes that do not physically share memory

The DSM system will maintain the memory consistency among different machines. Data faulting, location, and movement are handled by the DSM.

Proc 1

Mem 1

Proc N

Mem N

Proc N-1

Mem N-1

Proc 2

Mem 2

Network

Globally Shared Virtual Memory

42

HKU DP-II on Gigabit EthernetHKU DP-II on Gigabit Ethernet

050

100

150200

4 256 512 768 1024 1280 1500Message (Bytes)

La

ten

cy

(us

)

DP-II, back to back on Gigabit EthernetDP-II, through switch on Gigabit EthernetTCP/IP Latency

Single-trip Latency Test(Min: 16.3 µs)

Bandwidth Test(Max: 79.5 MB/s)

0

20

40

60

80

1 480 992 1504

Message size(Byte)B

an

dw

idth

(M

B/s

) DP-II TCP/IP

RWCP GigaE PM : 48.3 us round-trip latency and 56.7 MB/s on Essential Gigabit Ethernet NIC Pentium II 400 MHz.

RWCP GigaE PM II : 44.6 us round trip time. 98.2 MB/s bandwidth on Packet Engines G-NIC II for connecting Compaq XP-1000 (Alpha 21264 at 500 MHz.),.

43

SPARKLE ProjectSPARKLE Project A Dynamic Software Architecture for Pervasive

Computing – “Computing in Small”

Won’t Fit

Application

Applications distributed as monolithic blocks

Our component-based solution

Facets

44

SPARKLE ProjectSPARKLE Project

Facet Servers

Execution Servers

Computational Grid

Co-operativeCaching

(User Mobility)

Intelligent proxies

Facet Query

Facet Retrieval

Service Providers

Delegation/ Mobiie

code

Peer-to-Peer Interaction

Clients (Linux + JVM)

Overview of the proposed software architecture

45

ClusterProbe : Cluster Monitoring ToolClusterProbe : Cluster Monitoring Tool

Q&AQ&A

For more information, please visithttp://www.csis.hku.hk/~clwang