Grid Computing and Alternative Distributed Computing Solutions

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Grid ComputingandAlternative Distributed
Computing Solutions

• Noman Islam
• k060991_at_nu.edu.pk
• Oct, 2007
• NU-FAST, Karachi

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Introduction

• The defining characteristic of a grid 1
• The essence of grid computing lies in the
  efficient and optimal utilization of a wide range
  of heterogeneous, loosely coupled resources in an
  organization tied to sophisticated workload
  management capabilities or information
  virtualization

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A Three Point Check List for Grids 4

• Coordinates resources that are not subject to
  centralized control
• A Grid integrates and coordinates resources and
  users that live within different control domains
• Uses standard, open, general-purpose protocols
  and interfaces
• built from multi-purpose protocols and interfaces
  that address such fundamental issues as
  authentication, authorization, resource
  discovery, and resource access

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A Three Point Check List for Grids 4

• Deliver nontrivial qualities of service
• Allows its constituent resources to be used in a
  coordinated fashion to deliver various qualities
  of service to meet complex user demands, so that
  the utility of the combined system is
  significantly greater than that of the sum of its
  parts

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Grid Fills a Crucial Gap 1
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Introduction to Cluster Computing

• A group of tightly coupled computers that work
  together closely so that in many respects they
  can be viewed as though they are a single
  computer
• They are often connected to each other through
  fast LAN
• Cluster Categories
• High-availability (HA) clusters
• Load-balancing clusters
• High-performance computing (HPC) cluster

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An example of Cluster
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Grid Vs Cluster Computing

• The key difference between grids and traditional
  clusters are that grids connect collections of
  computers which do not fully trust each other, or
  which are geographically dispersed
• Grid computing is optimized for workloads which
  consist of many independent jobs or packets of
  work, which do not have to share data between the
  jobs during the computation process. Grids serve
  to manage the allocation of jobs to computers
  which will perform the work independently of the
  rest of the grid cluster. Resources such as
  storage may be shared by all the nodes, but
  intermediate results of one job do not affect
  other jobs in progress on other nodes of the grid.

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Grid Vs Cluster Computing

• Grids consist of heterogeneous resources
  (integrates storage, networking, and computation
  resources) where as clusters have computational
  resources
• Clusters usually contain a single type of
  processor and operating system grids can contain
  machines from different vendors running various
  operating systems

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Grid Vs Cluster Computing

• Grids are dynamic by their nature. Clusters
  typically contain a static number of processors
  and resources resources come and go on the grid.
  Resources are provisioned onto and removed from
  the grid on an ongoing basis
• Grids are inherently distributed over a local,
  metropolitan, or wide-area network. Usually,
  clusters are physically contained in the same
  complex in a single location grids can be (and
  are) located everywhere. Cluster interconnect
  technology delivers extremely low network latency

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Grid Vs Cluster Computing

• Grids offer increased scalability. Physical
  proximity and network latency limit the ability
  of clusters to scale out due to their dynamic
  nature, grids offer the promise of high
  scalability
• But Cluster and grid computing are becoming
  completely complementary. Many grids incorporate
  clusters among the resources they manage. Indeed,
  a grid user may be unaware that his workload is
  in fact being executed on a remote cluster. And
  while there are differences between grids and
  clusters, these differences afford them an
  important relationship because there will always
  be a place for clusters -- certain problems will
  always require a tight coupling of processors

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Grid Vs Cluster Computing

• As networking capability and bandwidth advances,
  problems that were previously the exclusive
  domain of cluster computing will be solvable by
  grid computing. It is vital to comprehend the
  balance between the inherent scalability of grids
  and the performance advantages of tightly coupled
  interconnections that clusters offer

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Introduction to P2P

• P2P is a class of applications that takes
  advantage of resources-storage, cycles, content,
  human presence - available at the edges of the
  Internet
• A pure peer-to-peer network does not have the
  notion of clients or servers, but only equal peer
  nodes that simultaneously function as both
  "clients" and "servers" to the other nodes on the
  network.

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Grid Vs P2P

• Grid were motivated by the requirements of
  professional communities needing to access remote
  resources, federate datasets, and/or pool
  computers for large-scale simulations and data
  analyses. It was initially developed to address
  the needs of scientific collaborations,
  commercial interest is growing
• P2P has been popularized by grass roots,
  mass-culture file-sharing and highly parallel
  computing applications that scale in some
  instances to hundreds of thousands of nodes

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Grid Vs P2P

• Grid integrate resources that are more powerful,
  more diverse, and better connected than the
  typical P2P
• Grid resource - cluster, storage system,
  database, or scientific instrument administered
  in an organized fashion according to some well
  defined policy.
• P2P often deal with intermittent participation
  and highly variable behavior.
• Major resources are home computers.

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Grid Vs P2P

• Grid often involves only modest numbers of
  participants. The amount of activity can be
  large.
• Early Grid implementations did NOT address
  scalability and self management as priorities
• P2P has far larger communities

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Grid Vs P2P

• In Grid, works have been done associated with
  creating and operating persistent, multipurpose
  infrastructure services for authentication,
  authorization, discovery, resource access, data
  movement...Less effort has been devoted to
  managing participation in the absence of trust
• P2P offers much scalability, fault tolerance,
  self-configuration, automatic problem
  determination. P2P system have tended to focus on
  the integration of simple resources (individual
  computers) by protocols. The persistence
  properties of such infrastructures are not
  specifically engineered but are rather emergent
  properties

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Grid Vs P2P

• P2P system lacks a central point of management
  this makes it ideal for providing anonymity. Grid
  environments, on the other hand, usually have
  some form of centralized management and security
  (for instance, in resource management or workload
  scheduling).
• Lack of centralization means
• More scalable
• More tolerant of single-point failures than grid
  computing systems. (Although grids are much more
  resilient than tightly coupled distributed
  systems, a grid inevitably includes some key
  elements that can become single points of
  failure)
• The key to building grid computing systems is
  finding a balance between decentralization and
  manageability -- not an easy chore

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Grid Vs P2P

• Also, while an important characteristic of grid
  computing is that resources are dynamic, in P2P
  systems the resources are much more dynamic in
  nature and generally are more fleeting than
  resources on a grid
• A final distinction between the two systems is
  standards -- the general lack of standards in the
  P2P world contrasts with the host of standards in
  the grid universe. And, thanks to entities like
  the Global Grid Forum, the grid universe has a
  mechanism for refining existing standards and
  creating new ones

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Common Object Request Broker Architecture
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Grid Vs CORBA

• CORBA
• OGSA and CORBA, both are based on the concept of
  service-oriented architecture (SOA)
• CORBA assumes object orientation (after all, it
  is part of the name), but grid computing does not
• There are also issues of interoperability among
  different platforms in CORBA

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Distributed Computing Environment

• The Distributed Computing Environment (DCE) is a
  software system developed in the early 1990s by a
  consortium that included Apollo Computer (later
  part of Hewlett-Packard), IBM, Digital Equipment
  Corporation, and others. The DCE supplies a
  framework and toolkit for developing
  client/server applications. The framework
  includes a remote procedure call (RPC) mechanism
  known as DCE/RPC, a naming (directory) service, a
  time service, an authentication service, an
  authorization service and a distributed file
  system (DFS) known as DCE/DFS

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Grid Vs DCE

• Not so much an architecture but an environment,
  DCE facilitates distributed computing grid
  computing (in the form of OGSA) is more of an
  end-to-end architecture designed to encapsulate
  many of the intricacies of the mechanics of
  distributed computing

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Conclusion

• We have examined Grid Computing and its
  importance at Enterprise Level
• Also an analysis of the similarities and
  differences between grid computing and four major
  distributed computing systems
• Based on the benefits of these paradigms, we can
  expect these approaches to eventually converge

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References

• 1 Perspectives on grid Grid computing --
  Next-generation distributed computing, Matt
  Haynos, Program Director, Grid Marketing and
  Strategy, IBM, http//users.cs.cf.ac.uk/David.W.Wa
  lker/IGDS/GridCourse.htm
• 2 Grid Vs Peer-to-Peer, Yin Chen,
  http//freewebs.com/yinchenagain/doc/p2p.pdf
• 3 Wikpedia, the Free Encyclopedia,
  http//www.wikipedia.org
• 4 What is the Grid? A Three Point Check List,
  Ian Foster, 2002