n. xiong@ gsu slide 1 chapter 02 cloud computing systems n. xiong georgia state university
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N. Xiong@ GSU Slide 1
Chapter 02
Cloud Computing Systems
N. Xiong
Georgia State University
N. Xiong@ GSU Slide 2
Chapter 02
Review and Introduction
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Chapter 02
Scalable Computing Towards Massive Parallelism
Enabling Technologies for Distributed Computing
Distributed Computing System Models
Performance, Security, and Energy-Efficiency
References and Homework Problems
Chapter 02 Main Contents
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Chapter 02
Levels of Parallelism Bit-level parallelism (BLP) instruction-level parallelism (ILP) Data-level parallelism (DLP) task-level parallelism (TLP) job-level parallelism (JLP)
Scalable Computing Towards Massive Parallelism
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Chapter 02
Key issues of the age of Internet computing Efficiency measured in building blocks and execution model to exploit
massive parallelism as in HPC. This may include data access and storage model for HTC and energy efficiency.
Dependability in terms of reliability and self-management from the chip to system and application levels. The purpose is to provide high-throughput service with QoS assurance even under failure conditions.
Adaptation in programming model which can support billions of job requests over massive datasets, virtualized cloud resources, and flexible application service model.
Scalable Computing Towards Massive Parallelism
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Chapter 02
The Platform Evolution
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Chapter 02
Distributed Computing Families
peer-to-peer (P2P) Grid computing Cloud computing
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Chapter 02
The Top-500 supercomputer performance
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Chapter 02
Architectural evolution of the Top-500 supercomputers
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Chapter 02
Top Five Supercomputers
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Chapter 02
Killer Applications of HPC and HTC Systems
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Chapter 02
Enabling Technologies for Distributed Parallelism
Network technologies for distributed computing
Software technologies for distributed computing
Hardware technologies for distributed computing
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Chapter 02
System Components and Wide-Area Networking
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Chapter 02
Multicore Architecture
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Chapter 02
Memory, SSD, and Disk Arrays
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Chapter 02
Virtual Machines and Virtualization Middleware
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Chapter 02
Virtualization Operations
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Chapter 02
Trends in Distributed Operating Systems
Three approaches build a network OS over a large number of
heterogeneous OS platforms develop middleware to offer limited degree
of resource sharing develop a distributed OS to achieve higher
use or system transparency
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Chapter 02
Amoeba vs. DCE
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Chapter 02
Parallel and Distributed Programming Environments
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Chapter 02
Grid Standards and Toolkits for scientific and Engineering Applications
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Chapter 02
Distributed Computing System Models
A large number of autonomous computer nodes
Interconnected by system-area networks (SAN), local-are networks (LAN), or wide-area networks (WAN)
A hierarchical manner
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Chapter 02
System Classification
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Chapter 02
New Challenges
new network-efficient processors Scalable memory and storage schemes distributed OS middleware for machine virtualization new programming model effective resource management application program development
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Chapter 02
Cluster Architecture
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Chapter 02
Cluster Design Issues
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Chapter 02
Grid Computing Infrastructures
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Chapter 02
Grid Families
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Chapter 02
Service-Oriented Architectures (SOA)
Three kernel standards: Web Service Description Language (WSDL) Simple Object Access Protocol (SOAP) Universal Description Discovery and
Integration (UDDI)
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Chapter 02
Service-Oriented Architectures (SOA)
General layered architecture for distributed entities
Layered architecture for web services and grids
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Chapter 02
Integrating Several Entities Together
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Chapter 02
P2P Networks
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Chapter 02
Peer-to-Peer Network Families
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Chapter 02
P2P Computing Challenges
Data locality, network proximity, and interoperability
routing efficiency and self-organization Fault Tolerance, failure management,
and load balancing Security, privacy, and copyright
violations
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Chapter 02
Virtualized Cloud Computing Infrastructure
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Chapter 02
Internet Clouds Cloud platform offers a scalable computing paradigm built
around the datacenters. Cloud resources are dynamically provisioned by datacenters
upon user demand. Cloud system provides computing power, storage space, and
flexible platforms for upgraded web-scale application services.
Cloud computing relies heavily on the virtualization of all sorts of resources.
Cloud computing defines a new paradigm for collective computing, data consumption and delivery of information services over the Internet.
Clouds stress the cost of ownership reduction in mega datacenters.
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Chapter 02
Basic Cloud Models
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Chapter 02
Representative Cloud Providers
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Chapter 02
Performance, Security, and Energy-Efficiency
System Performance and Scalability Analysis
System Availability and Application Flexibility
Security Threats and Defense Technologies
Energy-Efficiency in Distributed Computing
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Chapter 02
Performance Metrics
CPU speed in MIPS network bandwidth in Mbps Job response time network latency quality of service (QoS)
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Chapter 02
Dimensions of Scalability
Size Scalability Software Scalability Application scalability Technology Scalability
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Chapter 02
Scalability vs. OS Image Count
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Chapter 02
Amdahl’s Law and Some Improvement
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Chapter 02
System Availability
A system is highly available if long mean time to failure (MTTF) short mean time to repair (MTTR)
System Availability = MTTF / ( MTTF + MTTR )
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Chapter 02
System Availability
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Chapter 02
Security Threats and Defense Technologies
Threats To Systems and Networks Security Responsibilities System Defense Technologies Copyright Protection Data Protection Infrastructure
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Chapter 02
Threats To Systems and Networks
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Chapter 02
Security Responsibilities
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Chapter 02
System Defense Technologies
Three generations prevent or avoid intrusions, such as access
control policies or tokens detects intrusions timely to exercise
remedial actions, like firewalls, Intrusion Detection Systems (IDS), PKI service
intelligent responses
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Chapter 02
Energy-Efficiency in Distributed Computing
Energy consumption of unused servers
Reducing energy in active servers Application layer Middleware layer Resource layer Network layer
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Chapter 02
Energy Consumption of Unused Servers
15% of the full-time servers in a company is idling
in the world, around 4.7 million servers are not doing any useful work
globally $3.8 billion in energy costs alone and $24.7 billion in the total cost of running non-productive servers
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Chapter 02
Reducing Energy in Active Servers
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Chapter 02
Application layer
Challenge: how to design sophisticated multilevel and
multi-domain energy management applications without hurting performance
First step Find out the relationship between
performance and energy consumption
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Chapter 02
Middleware layer
A bridge between the application layer and the resource layer
Susceptible for applying energy-efficient techniques particularly in task scheduling
Need a new cost function covering both makespan and energy consumption
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Chapter 02
Resource Layer
Resource include: computing nodes storage units
Some approaches: Dynamic power management (DPM) dynamic voltage-frequency scaling (DVFS)
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Chapter 02
Resource Layer
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Chapter 02
Network Layer
Two major challenges: The models should represent the networks
comprehensively as they should give a full understanding of interactions between time, space and energy;
New energy-efficient routing algorithms need to be developed. New energy-efficient protocols should be developed against network attacks.
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Chapter 02
Some References and Further Reading
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Chapter 02
Homework Problems
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Chapter 02
Homework Problems