CLOUD ENABLING TECHNOLOGIES.pptx

IT19741
Cloud and Big Data
Analytics
Dr G Geetha
Dean innovation and Professor CSE
Women Scientist, Qualified Patent agent

UNIT-I CLOUD
ENABLING
TECHNOLOGIES
Technologies for Network-Based Systems -
System Models for Distributed and Cloud
Computing - Implementation Levels of
Virtualization - Virtualization Structures/Tools
and Mechanisms - Virtualization of CPU,
Memory, and I/O Devices - Virtual Clusters
and Resource Management - Virtualization for
Data-Center Automation.

1.1 Technologies for Network-Based Systems
1. Multicore CPUs and Multithreading Technologies
2. GPU Computing to Exascale and Beyond
3. Memory, Storage, and Wide-Area Networking
4. Virtual Machines and Virtualization Middleware
5. Data Center Virtualization for Cloud Computing

4
Copyright © 2012, Elsevier Inc. All rights reserved. 1 - 4
Data Deluge Enabling New Challenges
(Courtesy of Judy Qiu, Indiana University, 2011)

5
From Desktop/HPC/Grids to Internet Clouds
in 30 Years
• HPC moving from centralized supercomputers to geographically distributed
desktops, desksides, clusters, and grids to clouds over last 30 years
• R/D efforts on HPC, clusters, Grids, P2P, and virtual machines has laid the
foundation of cloud computing that has been greatly advocated since 2007
• Location of computing infrastructure in areas with lower costs in hardware,
software, datasets, space, and power requirements – moving from desktop
computing to datacenter-based clouds

6
Interactions among 4 technical challenges :Data Deluge, Cloud
Technology, eScience,and Multicore/Parallel Computing
(Courtesy of Judy Qiu, Indiana University, 2011)

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Clouds and Internet of Things
HPC: High-Performance
Computing
HTC: High-Throughput Computing
P2P: Peer to Peer
MPP: Massively Parallel
Processors
Source: K. Hwang, G. Fox, and J. Dongarra,Distributed and Cloud Computing,
Morgan Kaufmann, 2012.

8
Computing Paradigm Distinctions
• Centralized Computing
• All computer resources are centralized in one physical system.
• Parallel Computing
• All processors are either tightly coupled with central shard memory or loosely coupled with
distributed memory
• Distributed Computing
• Field of CS/CE that studies distributed systems. A distributed system consists of multiple
autonomous computers, each with its own private memory, communicating over a network.
• Cloud Computing
• An Internet cloud of resources that may be either centralized or decentralized. The cloud
apples to parallel or distributed computing or both. Clouds may be built from physical or
virtualized resources.

9
Technology Convergence toward HPC for Science and HTC for
Business: Utility Computing
(Courtesy of Raj Buyya, University of Melbourne, 2011)
Copyright © 2012, Elsevier Inc. All rights reserved.

10
2011 Gartner “IT Hype Cycle” for Emerging Technologies
2007
2008
2009
2010
2011

11
33 year Improvement in Processor and Network Technologies
Technologies for Network-based Systems

14
Multi-threading Processors
• Four-issue superscalar (e.g. Sun Ultrasparc I)
• Implements instruction level parallelism (ILP) within a single processor.
• Executes more than one instruction during a clock cycle by sending multiple
instructions to redundant functional units.
• Fine-grain multithreaded processor
• Switch threads after each cycle
• Interleave instruction execution
• If one thread stalls, others are executed
• Coarse-grain multithreaded processor
• Executes a single thread until it reaches certain situations
• Simultaneous multithread processor (SMT)
• Instructions from more than one thread can execute in any given pipeline stage
at a time.

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5 Micro-architectures of CPUs
Each row represents the issue slots for a single execution cycle:
• A filled box indicates that the processor found an instruction to execute in that
issue slot on that cycle;
• An empty box denotes an unused slot.

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33 year Improvement in Memory and Disk Technologies

17
Architecture of A Many-Core Multiprocessor GPU
interacting with a CPU Processor

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GPU Performance
Bottom – CPU - 0.8 Gflops/W/Core (2011)
Middle – GPU - 5 Gflops/W/Core (2011)
Top - EF – Exascale computing (10^18 Flops)

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Interconnection Networks
• SAN (storage area network) - connects servers with disk arrays
• LAN (local area network) – connects clients, hosts, and servers
• NAS (network attached storage) – connects clients with large storage
systems

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Datacenter and Server Cost Distribution

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Virtual Machines
• Eliminate real machine constraint
• Increases portability and flexibility
• Virtual machine adds software to a physical machine to give it the
appearance of a different platform or multiple platforms.
• Benefits
• Cross platform compatibility
• Increase Security
• Enhance Performance
• Simplify software migration

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Initial Hardware Model
 All applications access hardware resources (i.e. memory, i/o)
through system calls to operating system (privileged
instructions)
 Advantages
 Design is decoupled (i.e. OS people can develop OS
separate of Hardware people developing hardware)
 Hardware and software can be upgraded without notifying
the Application programs
 Disadvantage
 Application compiled on one ISA will not run on another
ISA.
 Applications compiled for Mac use different operating
system calls then application designed for windows.
 ISA’s must support old software
 Can often be inhibiting in terms of performance
 Since software is developed separately from hardware…
Software is not necessarily optimized for hardware.

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Virtual Machine Basics
• Virtual software placed between underlying
machine and conventional software
• Conventional software sees different ISA from the
one supported by the hardware
• Virtualization process involves:
• Mapping of virtual resources (registers and
memory) to real hardware resources
• Using real machine instructions to carry out the
actions specified by the virtual machine
instructions

1.2 System Models for Distributed and Cloud
Computing
1. Clusters of Cooperative Computers
2. Grid Computing Infrastructures
3. Peer-to-Peer Network Families
4. Cloud Computing over the Internet .

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System Models for Distributed and Cloud
Computing

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A Typical Cluster Architecture

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A Typical Computational Grid

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Peer-to-Peer (P2P) Network
• A distributed system architecture
• Each computer in the network can act as a client or server for other netwpork
computers.
• No centralized control
• Typically many nodes, but unreliable and heterogeneous
• Nodes are symmetric in function
• Take advantage of distributed, shared resources (bandwidth, CPU, storage) on
peer-nodes Fault-tolerant, self-organizing Operate in dynamic environment,
frequent join and leave is the norm

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Overlay network - computer network built on top of another network.
• Nodes in the overlay can be thought of as being connected by virtual or logical links, each of which
corresponds to a path, perhaps through many physical links, in the underlying network.
• For example, distributed systems such as cloud computing, peer-to-peer networks, and client-server
applications are overlay networks because their nodes run on top of the Internet.

33

34
The Cloud
• Historical roots in today’s Internet apps
• Search, email, social networks
• File storage (Live Mesh, Mobile Me, Flicker, …)
• A cloud infrastructure provides a framework to manage
scalable, reliable, on-demand access to applications
• A cloud is the “invisible” backend to many of our mobile
applications
• A model of computation and data storage based on “pay
as you go” access to “unlimited” remote data center
capabilities

35
Basic Concept of Internet Clouds
• Cloud computing is the use of computing resources (hardware and software) that are
delivered as a service over a network (typically the Internet).
• The name comes from the use of a cloud-shaped symbol as an abstraction for the
complex infrastructure it contains in system diagrams.
• Cloud computing entrusts remote services with a user's data, software and computation.

36
The Next Revolution in IT
Cloud Computing
 Classical Computing
 Buy & Own
 Hardware, System
Software, Applications
often to meet peak needs.
 Install, Configure, Test, Verify,
Evaluate
 Manage
 ..
 Finally, use it
 $$$$....$(High CapEx)
 Cloud Computing
 Subscribe
 Use
 $ - pay for what you use,
based on QoS
Every
18
months?
(Courtesy of Raj Buyya, 2012)

37
Cloud Service Models (1)
Infrastructure as a service (IaaS)
• Most basic cloud service model
• Cloud providers offer computers, as physical or more often as virtual machines,
and other resources.
• Virtual machines are run as guests by a hypervisor, such as Xen or KVM.
• Cloud users deploy their applications by then installing operating system images
on the machines as well as their application software.
• Cloud providers typically bill IaaS services on a utility computing basis, that is,
cost will reflect the amount of resources allocated and consumed.
• Examples of IaaS include: Amazon Cloud Formation (and underlying services
such as Amazon EC2), Rackspace Cloud, Terre mark, and Google Compute
Engine.

38
Platform as a service (PaaS)
• Cloud providers deliver a computing platform typically including operating system,
programming language execution environment, database, and web server.
• Application developers develop and run their software on a cloud platform without
the cost and complexity of buying and managing the underlying hardware and
software layers.
• Examples of PaaS include: Amazon Elastic Beanstalk, Cloud Foundry, Heroku,
Force.com, EngineYard, Mendix, Google App Engine, Microsoft Azure and
OrangeScape.

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Software as a service (SaaS)
• Cloud providers install and operate application software in the cloud and cloud
users access the software from cloud clients.
• The pricing model for SaaS applications is typically a monthly or yearly flat fee
per user, so price is scalable and adjustable if users are added or removed at
any point.
• Examples of SaaS include: Google Apps, innkeypos, Quickbooks Online,
Limelight Video Platform, Salesforce.com, and Microsoft Office 365.

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Service-oriented architecture (SOA)
• SOA is an evolution of distributed computing based on the request/reply design
paradigm for synchronous and asynchronous applications.
• An application's business logic or individual functions are modularized and
presented as services for consumer/client applications.
• Key to these services - their loosely coupled nature;
• i.e., the service interface is independent of the implementation.
• Application developers or system integrators can build applications by composing
one or more services without knowing the services' underlying implementations.
• For example, a service can be implemented either in .Net or J2EE, and the
application consuming the service can be on a different platform or language.

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SOA key characteristics:
• SOA services have self-describing interfaces in platform-independent XML documents.
• Web Services Description Language (WSDL) is the standard used to describe the services.
• SOA services communicate with messages formally defined via XML Schema (also called
XSD).
• Communication among consumers and providers or services typically happens in
heterogeneous environments, with little or no knowledge about the provider.
• Messages between services can be viewed as key business documents processed in an
enterprise.
• SOA services are maintained in the enterprise by a registry that acts as a directory listing.
• Applications can look up the services in the registry and invoke the service.
• Universal Description, Definition, and Integration (UDDI) is the standard used for service
registry.
• Each SOA service has a quality of service (QoS) associated with it.
• Some of the key QoS elements are security requirements, such as authentication and
authorization, reliable messaging, and policies regarding who can invoke services.

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Layered Architecture for Web Services

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Cloud Computing Challenges:
Dealing with too many issues (Courtesy of R. Buyya)
Billing
Utility & Risk
Management
Scalability
Reliability
Software Eng.
Complexity
Programming Env.
& Application Dev.

44
The Internet of Things (IoT)
Internet of
Things
Smart Earth
Smart
Earth:
An
IBM
Dream

45
Opportunities of IoT in 3 Dimensions
(courtesy of Wikipedia, 2010)

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Virtualization for Datacenter Automation
to serve millions of clients, simultaneously
• Server Consolidation in Virtualized Datacenter
• Virtual Storage Provisioning and Deprovisioning
• Cloud Operating Systems for Virtual Datacenters
• Trust Management in virtualized Datacenters

1.3 Implementation Levels of Virtualization
1. Levels of Virtualization Implementation
2. VMM Design Requirements and Providers
3. Virtualization Support at the OS Level
4. Middleware Support for Virtualization

48
Difference between Traditional Computer and Virtual machines
(Courtesy of VMWare, 2008)

49
Virtual Machine, Guest Operating System,
and VMM (Virtual Machine Monitor) :
The Virtualization layer is the middleware between the underlying hardware and
virtual machines represented in the system, also known as virtual machine
monitor (VMM) or hypervisor.

50
(Courtesy of VMWare, 2008)

51
Virtualization Ranging from Hardware to Applications in
Five Abstraction Levels

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Virtualization at ISA (Instruction Set Architecture) level
Emulating a given ISA by the ISA of the host machine.
• e.g, MIPS binary code can run on an x-86-based host machine with the help of ISA emulation.
• Typical systems: Bochs, Crusoe, Quemu, BIRD, Dynamo
Advantage:
• It can run a large amount of legacy binary codes written for various processors on any given
new hardware host machines
• best application flexibility
Shortcoming & limitation:
• One source instruction may require tens or hundreds of native target instructions to perform its
function, which is relatively slow.
• V-ISA requires adding a processor-specific software translation layer in the complier.

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Virtualization at Hardware Abstraction level
Virtualization is performed right on top of the hardware.
• It generates virtual hardware environments for VMs, and manages the underlying
hardware through virtualization.
• Typical systems: VMware, Virtual PC, Denali, Xen
Advantage:
• Has higher performance and good application isolation
• Very expensive to implement (complexity)

54
Virtualization at OS Level

55
Virtualization at Operating System (OS) level
It is an abstraction layer between traditional OS and user applications.
• This virtualization creates isolated containers on a single physical server and the OS-instance
to utilize the hardware and software in datacenters.
• Typical systems: Jail / Virtual Environment / Ensim's VPS / FVM
Advantage:
• Has minimal starup/shutdown cost, low resource requirement, and high scalability;
synchronize VM and host state changes.
• All VMs at the operating system level must have the same kind of guest OS
• Poor application flexibility and isolation.i

56
Virtualization for Linux and Windows NT Platforms

57

58
Advantages of OS Extension for Virtualization
1. VMs at OS level has minimum startup/shutdown costs
2. OS-level VM can easily synchronize with its
environment
Disadvantage of OS Extension for Virtualization
All VMs in the same OS container must have the same or similar guest OS,
which restrict application flexibility of different VMs on the same physical
machine.

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Library Support level
It creates execution environments for running alien programs on a platform
rather than creating VM to run the entire operating system.
• It is done by API call interception and remapping.
• Typical systems: Wine, WAB, LxRun , VisualMainWin
Advantage:
• It has very low implementation effort
• poor application flexibility and isolation

60
Virtualization with Middleware/Library Support

61
The vCUBE for Virtualization of GPGPU

62
User-Application level
It virtualizes an application as a virtual machine.
• This layer sits as an application program on top of an operating system and
exports an abstraction of a VM that can run programs written and compiled to a
particular abstract machine definition.
• Typical systems: JVM , NET CLI , Panot
Advantage:
• has the best application isolation
• low performance, low application flexibility and high implementation complexity.

63
More Xs mean higher merit

1.4 Virtualization Structures/Tools and
Mechanisms
• Hypervisor and Xen Architecture
• Binary Translation with Full Virtualization
• Para-Virtualization with Compiler Support

65
Hypervisor
A hypervisor is a hardware virtualization technique allowing multiple operating systems, called
guests to run on a host machine. This is also called the Virtual Machine Monitor (VMM).
Type 1: bare metal hypervisor
• sits on the bare metal computer hardware like the CPU, memory, etc.
• All guest operating systems are a layer above the hypervisor.
• The original CP/CMS hypervisor developed by IBM was of this kind.
Type 2: hosted hypervisor
• Run over a host operating system.
• Hypervisor is the second layer over the hardware.
• Guest operating systems run a layer over the hypervisor.
• The OS is usually unaware of the virtualization

66
Major VMM and Hypervisor Providers

67
The XEN Architecture (1)

68

69

70
Full virtualization
It is the first software solution for server virtualization and
uses binary translation and direct approach techniques. In
full virtualization, guest OS is completely isolated by the
virtual machine from the virtualization layer and hardware.
• Para virtualization
Paravirtualization is the category of CPU virtualization
which uses hypercalls for operations to handle
instructions at compile time. In paravirtualization, guest
OS is not completely isolated but it is partially isolated by
the virtual machine from the virtualization layer and
hardware. VMware and Xen are some examples of
paravirtualization.
Full Virtualization vs. Para-Virtualization

71
Binary
Translation
of Guest OS
Requests
using a
VMM:

72

73
Full virtualization
• Does not need to modify guest OS, and critical instructions are emulated by software through the
use of binary translation.
• VMware Workstation applies full virtualization, which uses binary translation to automatically modify
x86 software on-the-fly to replace critical instructions.
• Advantage: no need to modify OS.
• Disadvantage: binary translation slows down the performance.
Para virtualization
• Reduces the overhead, but cost of maintaining a para virtualized OS is high.
• The improvement depends on the workload.
• Para virtualization must modify guest OS, non-virtualizable instructions are replaced by hypercalls
that communicate directly with the hypervisor or VMM.
• Para virtualization is supported by Xen, Denali and VMware ESX.
Full Virtualization vs. Para-Virtualization

74
Full Virtualization

75
Para- Virtualization with Compiler Support.
The KVM builds offers kernel-based VM on the Linux
platform, based on para-virtualization

76
VMWare ESX Server for Para-Virtualization

77

1.5 Virtualization of CPU, Memory, and I/O
Devices
• Hardware Support for Virtualization
• CPU Virtualization
• Memory Virtualization
• I/O Virtualization
• Virtualization in Multi-Core Processors

79

80
CPU, Memory and I/O Virtualization
• CPU virtualization demands hardware-assisted traps of sensitive
instructions by the VMM
• Memory virtualization demands special hardware support (shadow page
tables by VMWare or extended page table by Intel) to help translate virtual
address into physical address and machine memory in two stages.
• I/O virtualization is the most difficult one to realize due to the complexity if
I/O service routines and the emulation needed between the guest OS and
host OS.

81
Multi-Core Virtualization:
VCPU vs. traditional CPU
Figure 3.16 Four VCPUs are exposed to the software, only three cores are actually present. VCPUs V0, V1, and V3 have
been transparently migrated, while VCPU V2 has been transparently suspended. (Courtesy of Wells, et al., “Dynamic
Heterogeneity and the Need for Multicore Virtualization”, ACM SIGOPS Operating Systems Review, ACM Press, 2009 [68] )

1.6 Virtual Clusters and Resource
Management
• Physical versus Virtual Clusters
• Live VM Migration Steps and Performance Effects
• Migration of Memory, Files, and Network Resources
• Dynamic Deployment of Virtual Clusters

83
Virtual Cores vs. Physical Processor Cores
Physical cores Virtual cores
The actual physical cores present in the
processor.
There can be more virtual cores
visible to a single OS than there are
physical cores.
More burden on the software to write
applications which can run directly on
the cores.
Design of software becomes easier as
the hardware assists the software in
dynamic resource utilization.
Hardware provides no assistance to the
software and is hence simpler.
Hardware provides assistance to the
software and is hence more complex.
Poor resource management. Better resource management.
The lowest level of system software has
to be modified.
The lowest level of system software
need not be modified.

84
(Courtesy of Marty and Hill, 2007)

85
Virtual Clusters in Many Cores
Space Sharing of VMs -- Virtual Hierarchy
(Courtesy of Marty and Hill, 2007)

86
• The virtual cluster nodes can be either physical or virtual machines. Multiple VMs running with
different OSs can be deployed on the same physical node.
• A VM runs with a guest OS, which is often different from the host OS, that manages the
resources in the physical machine, where the VM is implemented.
• The purpose of using VMs is to consolidate multiple functionalities on the same server. This will
greatly enhance the server utilization and application flexibility.
• VMs can be colonized (replicated) in multiple servers for the purpose of promoting distributed
parallelism, fault tolerance, and disaster recovery.
• The size (number of nodes) of a virtual cluster can grow or shrink dynamically, similarly to the
way an overlay network varies in size in a P2P network.
• The failure of any physical nodes may disable some VMs installed on the failing nodes. But the
failure of VMs will not pull down the host system.
Virtual Cluster Characteristics

87
Virtual Clusters vs. Physical Clusters

88

89
Live Migration of Virtual Machines

90
Live Migration of Virtual Machines

91

92
Virtual Cluster Projects

93

94
Cluster-on-Demand (COD Project) at Duke University

95

96
VIOLIN Project at Purdue University

97

1.7 Virtualization for Data-Center Automation
• Server Consolidation in Data Centers
Server consolidation is the process of migrating network services and applications
from multiple computers to a singular computer. This consolidation can include
multiple physical computers to multiple virtual computers on one host computer
• Virtual Storage Management
Virtual Storage Management provides end-to-end view of the storage assigned to
client logical partition.
• Cloud OS for Virtualized Data Centers
vSphere is primarily intended to offer virtualization support and resource
management of data-center resources in building private clouds.
• Trust Management in Virtualized Data Centers
assures secure data access through trustworthy cloud service provider

99
Parallax for VM Storage Management

100
Cloud OS for Building Private Clouds

101

102
Eucalyptus : An Open-Source OS for Setting
Up and Managing Private Clouds

103

104
Trusted Zones for VM Insulation
Tenant #2
APP
OS
APP
OS
Virtual Infrastructure
Physical Infrastructure
Cloud Provider
APP
OS
APP
OS
Virtual Infrastructure
Tenant #1
Insulate
information
from cloud
providers’
employees
Insulate
information
from other
tenants
Insulate
infrastructure from
Malware, Trojans
and cybercriminals
Segregate and
control user
access
Control and
isolate VM in
the virtual
infrastructure
Federate
identities with
public clouds
Identity
federation
Virtual
network
security
Access
Mgmt
Cybercrime
intelligence
Strong
authentication
Data loss
prevention
Encryption
& key mgmt
Tokenization
Enable end to end view of security events
and compliance across infrastructures
Security Info. &
Event Mgmt GRC
Anti-malware
(Courtesy of L. Nick, EMC 2008)

1.7 Virtualization for Data-Center Automation
• Server Consolidation in Data Centers
• Virtual Storage Management
• Cloud OS for Virtualized Data Centers
• Trust Management in Virtualized Data Centers

Test
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