1) - )Modem is an acronym for DEModulate / MODulate
Know modems as of the leading means of linking computers and communication systems different, and the modem is a small device comes with two kinds:
the first type is a card integrates into the computer through port serial connection (serial port) in the motherboard, and quickly comes 56 kilometers bytes per second, which is a reasonable speed has the potential to meet the needs of the user to surf the Internet and other,
second type of modems is the external modem and the advantage of this modem multiple choices and price relatively high, where he works such as a fax machine,in which you can send a fax and receive any fax message without the condition that the computer is working, also there are types of modems operate tool integrated with the phone, where it can play the role of devices automatic reply (Answering Machine)
and there are other types of this kind can see and monitor the status and quality of contact with providing greater speed of communication, and the characteristics of this device that can work revealing the figures, any it could be on the way to know your numbers related. All modems are two ports (LAN) is a special phone line compass, which is used by the device when an external connection request or receive a call, the other port is (phone) and its work is to provide a home phone can be connected or connecting other devices.
The role of network card is the following matters:
1 - ) preparing data transmitted over the network.
( 2 - Send data on the network.
( 3 - control the flow of data between the computer and the dispatch center.
4 - ) translate electrical signals from the wire network bytes understood by thecomputer's processor, and when you want to send data, it translates digital computer signals into electrical pulses can wire network to carry.
Every network card has a unique network address, and this address determined by the IEEE committee and this committee allocates a range of addresses for each plant manufacturers of network cards. The publication entitled card on the network, allowing for Baltkhatab devices with each other and routing data to the intended destination.
Network card contains all of the physical parts Hardware and software parts Firmware Software, and this part be stored inside the compiler ROM memory and be responsible for directing and carrying out the tasks entrusted to the card.
The network card organizing the transmission of data on the network and by doing the following steps:
1 - ) the transfer of data from the computer to the card.
2 - )temporarily store data on the card as a prelude to broadcast to the wire.
3 - ) an understanding on the conditions for the transfer of data between the card sending and receiving card.
4 - ) control the flow of data on the network.
Criteria that must be agreed upon by the cards in order to contact them are:
1 - ) the maximum size of data sets that will be sent.
2 - )The amount of data that will be sent prior to obtaining confirmation of arrival.
3 - ) the time interval between sending data packets.
4 - ) period of time to wait before getting to confirm the arrival of the data.
5 - ) the amount of data that can each card received before overflowing Overflow.
6 - ) speed data transfer.
After that is the agreement on these standards is the exchange of data between cards
3 - ) central Transport (Transmission Media)
Which is the medium used to connect computers to each other and which is the transfer of data.?
Among transportation types:
1 - ) wired circles
Scheduled wire (Twisted Pairs): a telephone wire and need a modem.
Coaxial wire (Coaxial): They are similar to your router to your TV cable and need a network card.
Optical fiber (Fiber Optics): a thin glass tube in which data is transferred at the speed of light and is used in wide area networks.
2 - ) Wireless circles:
Transport using radio waves.
Transport using the microwave.
Transport via satellite
History:
The term grid computing
originated in the early 1990s as a metaphor for making computer power as easy
to access as an electric power grid. The power grid metaphor for accessible
computing quickly became canonical when Ian Foster and Carl Kesselman published
their seminal work, "The Grid: Blueprint for a new computing
infrastructure" (2004).
CPU scavenging and volunteer
computing were popularized beginning in 1997 by distributed.net and later in
1999 by SETI@home to harness the power of networked PCs worldwide, in order to
solve CPU-intensive research problems.[citation needed]
The ideas of the grid
(including those from distributed computing, object-oriented programming, and
Web services) were brought together by Ian Foster, Carl Kesselman, and Steve
Tuecke, widely regarded as the "fathers of the grid".[6] They led the
effort to create the Globus Toolkit incorporating not just computation
management but also storage management, security provisioning, data movement,
monitoring, and a toolkit for developing additional services based on the same
infrastructure, including agreement negotiation, notification mechanisms,
trigger services, and information aggregation. While the Globus Toolkit remains
the de facto standard for building grid solutions, a number of other tools have
been built that answer some subset of services needed to create an enterprise
or global grid.
In 2007 the term cloud
computing came into popularity, which is conceptually similar to the canonical
Foster definition of grid computing (in terms of computing resources being
consumed as electricity is from the power grid). Indeed, grid computing is
often (but not always) associated with the delivery of cloud computing systems
as exemplified by the AppLogic system from 3tera.
Grids are a form of distributed
computing whereby a “super virtual computer” is composed of many networked
loosely coupled computers acting together to perform very large tasks. This
technology has been applied to computationally intensive scientific, mathematical,
and academic problems through volunteer computing, and it is used in commercial
enterprises for such diverse applications as drug discovery, economic
forecasting, seismic analysis, and back office data processing in support for
e-commerce and Web services
What isthedefinitionof grid computing?
Grid computing is the
federation of computer resources from multiple administrative domains to reach a common goal. The grid can be thought of as a distributed system with non-interactive workloads that involve a large number of files
What is
grid computing from the point of view of infrastructure?
A grid computer is multiple
number of same class of computers clustered together. A grid computer is
connected through a super fast network and share the devices like disk drives,
mass storage, printers and RAM Grid Computing is a cost efficient solution with
respect to Super Computing Operating system has capability of parallelism
Buyya/Venugopal[25] define grid
as "a type of parallel and distributed system that enables the sharing,
selection, and aggregation of geographically distributed autonomous resources
dynamically at runtime depending on their availability, capability,
performance, cost, and users' quality-of-service requirements".
One of the main strategies of
grid computing is to use middleware to divide and apportion pieces of a program
among several computers, sometimes up to many thousands. Grid computing
involves computation in a distributed fashion, which may also involve the
aggregation of large-scale cluster computing-based systems.
What
distinguishes grid computing from conventional high performance computing
systems such as cluster computing
is that grids tend to be more loosely coupled,
heterogeneous, and geographically dispersed.[1] Although a
single grid can be dedicated to a particular application, commonly a grid is
used for a variety of purposes. Grids are often constructed with
general-purpose grid middleware software libraries.
The size of a grid may vary from small—confined to a
network of computer workstations within a corporation, for example—to large,
public collaborations across many companies and networks. "The notion of a
confined grid may also be known as an intra-nodes cooperation whilst the notion
of a larger, wider grid may thus refer to an inter-nodes cooperation
How Grid
Computing Works?
Grid computing offers a model
for solving massive computational problems by making use of the unused
resources (CPU cycles and/or disk storage) of large numbers of disparate
computers, often desktop computers, treated as a virtual cluster embedded in a
distributed telecommunications infrastructure. Grid computing’s focus on the
ability to support computation across administrative domains sets it apart from
traditional computer clusters or traditional distributed computing.
Grids offer a way to solve
problems like protein folding, financial modelling, earthquake simulation, and
climate/weather modeling. Grids offer a way of using the information technology
resources optimally inside an organization. They also provide a means for offering
information technology as a utility bureau for commercial and non-commercial
clients, with those clients paying only for what they use, as with electricity
or water.
Grid computing can solve
problems which are too big for any single supercomputer, whilst retaining the
flexibility to work on multiple smaller problems. Thus Grid computing provides
a multi-user environment which uses secure authorization techniques to allow
remote users to control computing resources.
Grid computing involves sharing
heterogeneous resources (based on different platforms, hardware/software
architectures), located in different places belonging to different
administrative domains over a network using open standards. In short, it
involves virtualizing computing resources.
Grid computing is often
confused with cluster computing. The key difference is that a cluster is a
single set of nodes sitting in one location, while a Grid is composed of many
clusters and other kinds of resources (e.g. networks, storage facilities).
Grid computing environment is
created to address resource needs. The use of that resource(s) (eg. CPU cycles,
disk storage, data, software programs, peripherals) is usually characterized by
its availability outside of the context of the local administrative domain.
One characteristic that
currently distinguishes Grid computing from distributed computing is the
abstraction of a ‘distributed resource’ into a Grid resource. One result of
abstraction is that it allows resource substitution to be more easily
accomplished. Some of the overhead associated with this flexibility is
reflected in the middleware layer and the temporal latency associated with the
access of a Grid (or any distributed) resource. This overhead, especially the
temporal latency, must be evaluated in terms of the impact on computational
performance when a Grid resource is employed
Key Components :
•Portal/user interface
•Security •Grid Security Inf\rastructure (GSI)
•Broker
•Monitoring and Discovery Service (MDS)
•Scheduler
•Data management Grid Access to
Secondary Storage (GASS)
•Job and resource management
Grid
Resource Allocation Manager (
Grid
Architecture:
the bottom “Fabric” layer
represents different distributed resources from different administrative
domains, such as supercomputers or parallel computing clusters, storage
systems, scientific instruments and data resources. Those resources are managed
by domain-specific resource managers and users access them via the non-standard
interfaces of the resource managers or directly via the Operating System API.
On a computing resource, the local resource manager, known as the local
scheduler or batch scheduler, is responsible for allocating computing elements
to users’ jobs, launching them and monitoring their executions. Some well-known
local schedulers include Sun Grid Engine (SGE), Platform Load Sharing Facility
(LSF), Portable Batch System (PBS) and IBM Load Leveler . System administrators
of these systems may also deploy a resource monitoring system, such as
Ganglia,to report resource load/failure status.
From bottom-up, the second layer, the “Connectivity” layer provides the core
capabilities of the grid architecture for sharing individual resources, namely,
the security infrastructure and the networking protocol. The security
infrastructure is the middleware solutions to the grid security issues we
mentioned before, and it is the core of the grid architecture. Currently, the
standard solution is the Grid Security Infrastructure (GSI), which uses public
key cryptography as the basis for its functionality. The networking
capabilities make use of the widely deployed standard protocols, such as HTTP,
TCP/IP, etc., and recently, web service communication protocols, such as SOAP,
also become part of this layer as the grid architecture moves to service
oriented architectures.
The third layer, the “Resource” layer, provides interfaces for single resource
sharing, which include remote computational resource access, data sharing and
replication and resource monitoring and auditing. From this layer, users are
able to access individual resources using standard grid interfaces. Middleware
solutions in the “Resource” layer and the “Connectivity” layer address those
grid issues we mentioned in the last section and provide a standard and uniform
interface to build higher level services to access multiple resources
collaboratively. The middlewares in these two layers serve as the software glue
between the grid resources and the applications. The open source Globus Toolkit
is the de facto standard for providing these middlewares. We have a dedicated
section next to introduce it.
While the “Resource” layer is focused on interactions with a single resource,
the next layer in the architecture contains protocols and services that are not
associated with any one specific resource but rather capture interactions
across collections of resources . For this reason, the next layer of the
architecture is referred to as the layer, the fourth layer in above Figure.
Typical services include resource co-allocation, application scheduling on
multiple resources, application workflow execution and monitoring, data
discovery and retrievals. The work described in this dissertation belongs to
this layer. Software developed in this layer varies according to the application
needs of the upper “Applications” layer and it is hard to provide a general
solution that fits the various types of applications.
Softwares in the “Applications” layer provide an end-user environment to use a
grid for domain applications, for example, a portal interface to submit
computation job or transfer files from web browser; an interface or tool to
develop grid applications. The middleware functionalities in this layer also
depend on the requirements of applications and users, and they are developed
together with services in the layer.
To build a grid, the development and deployment of a number of middlewares are
required, including those for the standard services, such as security,
information, data and resource allocation services, and those services for
application development, execution management, resource aggregation, and
scheduling. Again, choosing which middleware to develop and/or to deploy
depends on the requirements of both the applications and users, and there is no
standard configuration for setting up a general-purpose grid.
:The difference between grid computing
and cloud computing
is hard to grasp because they
are not always mutually exclusive. In fact, they are both used to economize
computing by maximising existing resources. Additionally, both architectures
use abstraction extensively, and both have distinct elements which interact
with each other.
However, the difference between
the two lies in the way the tasks are computed in each respective environment.
In a computational grid, one large job is divided into many small portions and
executed on multiple machines. This characteristic is fundamental to a grid;
not so in a cloud.
The cloud computing is intended
to allow the user to avail of various services without investing in the
underlying architecture. While grid computing also offers a similar facility
for computing power, cloud computing isn’t restricted to just that. A cloud can
offer many different services, from web hosting, right down to word processing.
In fact, a computing cloud can combine services to present a user with a
homogenous optimized result.
There are many computing
architectures often mistaken for each other because of certain shared
characteristics. Again, each architecture is not mutually exclusive, however
they are indeed distinct conceptually
The difference between grid computing and Virtualization?
Grid Computing
Grid Computing involves a
network of computers that are utilized together to gain large supercomputing
type computing resources. Using this network of computers large and complex
computing operations can be performed. In grid computing these network of
computers may be present in different locations.
A famous Grid
Computing project is Folding@Home.
The project involves utilizing unused computing powers of thousands of
computers to perform a complex scientific problem. The goal of the project is
"to understand protein folding, misfolding, and related diseases".
Virtualization
Virtualization introduces a
layer between Hardware and operating system. During the sixties mainframe
started supporting many users using virtual machines. These virtual machines
simulated behavior of an operating system for each user. VMWare launched a product
called VMware Workstation in 1999 that allows multiple operating systems to run
on personal computers.
The virtualization
forms the foundation of cloud technology. Using virtualization, users can
access servers or storage without knowing specific server or storage details.
The virtualization layer will execute user request for computing resources by
accessing appropriate resources.
Typically server
utilization in data centers can be as low as 10%.
Virtualization can help in
significantly improving server utilization.
: advantage
of grid computing
•is that it reduces the time taken to complete
tasks, without increasing costs.
•Computers on a grid are not
necessarily in the same geographical location, and can be spread out over
multiple countries and organizations, or even belong to individuals.
:Disadvantages
of Grid Computing
Grid computing has great
potential, but there are still absent features waiting for implementation.
Furthermore, there are still particular disadvantages of grid computing that
must not be overlooked.
As expected, the first
disadvantage concerns the relative immaturity of the concept. This is
especially noticeable when talking about the missing features, non-defined standards
and software. On the subject of software, some applications require
modifications in order to use all the benefits of grid computing. It is also
important to mention that applications which are not designed to use an MPI
(Message Passing Interface) will have to revert to an SMP (Symmetric
Multi-Processing).
The biggest disadvantage of
grid computing though, concerns processes and their results. More specifically,
the results of all processes are sent first on all nodes within the grid, and
then collaboratively assessed. Before the final assessment is made, it is not
possible to define or to declare a final outcome. This is particularly a
problem when talking about time sensitive projects. Furthermore, another
important disadvantage of grid computing is that it relies heavily on dispersed
data management (which is a very important concept in cloud computing) and
connectivity (connectivity errors may occur unexpectedly).
Furthermore, grid computing requires an advanced
infrastructure: small servers, fast connections between the servers and
finally, in order to maximize the potential of that infrastructure, it requires
the use of quality tools, software and skilled technicians to manage the grid.
In other words, when all these components are put together, it is obvious that
this technology is costly. In certain occasions, it is not possible to change
how data is displayed on screen. Naturally, as it is a case with every
computing network, it is important to pay a maximum attention to security
issues.
Finally, there is also a
problem with people who don't want to share their resources, despite the fact
that everybody involved with the resource sharing would benefit.
Why need
Grid Computing?
Core networking technology now
accelerates at a much faster rate than advances in microprocessor speeds
Exploiting under utilized
resources
Parallel CPU capacity
Virtual resources and virtual
organizations for collaboration
Access to additional resources
Not just computer scientists
scientists “hit the wall” when
faced with situations:
The amount of data they need is
huge and the data is stored in different institutions.
The amount of similar
calculations the scientist has to do is huge.
Other areas:
Government
Business
Education
Industrial design
Some
application :
•The Southern California
Earthquake Center uses Globus software to visualize earthquake simulation
data.
Scientists in the Earth System Grid (ESG) are producing,
archiving, and providing access to climate data that advances our understanding
of global climate change. ESG uses Globus software for security, data movement,
and system monitoring
•Computational
scientists at Brown University are using the Globus Toolkit and MPICH-G2 to
simulate the flow of blood through human arteries.
•Globus Toolkit-driven
Grid computing is central to management of large datasets generated by
colliders such as those at CERN. This simulation shows two
colliding lead ions just after impact, with quarks in red, blue, and green and
hadrons in white.
Other Grid Applications
There are many smaller computational grids that exist
all over the globe. Typically applications like weather forecasting, protein
folding and earthquake simulation are prime candidates for a grid
infrastructure. Grids have also been used to render large-scale animation projects,
like movies.
There are many uses for computational grids, which are
beginning to surface more since the volume of data that is generated, and as a
result analyzed at a later stage, grows exponentially every day.
Software implementations and middleware
•Globus Toolkit
•Sun Grid Engine
•ProActive
•UNICORE
•SDSC Storage resource broker (data grid)
•gLite (EGEE)
•NInf GridRPC
•IceGrid
•Java CoG Kit
Overview of Security Issues
Grid computing
has distinct security issues compared to traditional computing systems, be it
stand-alone, or networked architecture. The major security problems with grid
computing include:
·Impact on Local Host: Grid computing involves running an alien
code in the host system. This external code can hamper jobs running locally,
and compromise local data security.
·Vulnerable Hosts: Clients using the grid remain in danger
from the local hosts. The major vulnerabilities include the local hosts
shutting down resulting in denial of service, viruses, or other malware in the
local host affecting the entire process, and local hosts compromising client
data integrity and confidentiality.
·Interception: One major security risk with grid
computing is an attacker intercepting the resources and data in the grid. The
attack can take various forms such as a distributed denial-of-service (DDOS)
attack and the like.
·Packet Losses: Interruption of nodes during the routing
process to send packets from source to destination decreases total packet
delivery and loss or corruption of data
The extent
of security risks when using smart grid depends on the intellectual property
put in the hosted environment
Solutions:
A monitoring agency with the
following roles can resolve most of the grid computing security concerns with
grid systems:
•Monitoring resource usage.
•Institution of a trust
management system to create, manage, and negotiate trust among the different
units in the grid.
•Establishing an authorization
system to authorize user access specific resources.
The user running an application
on a remote machine in the grid-computing network requires assurance of the
machine retaining its integrity, to ensure that proprietary application remains
safe. The local host requires a similar assurance regarding the client data and
processes that run on the host. While the safeguards of a traditional system
aim at protecting the system and data from its users, the security orientation
of grid systems need to go a step ahead and also protect applications and data
from the system where the computation takes place.
Grid computing security
requires strong authentication and restrictions on local execution from remote
systems. Some of the ways include:
•Secure grid communication
using public key cryptography.
•Authentication or verifying
identity of the participant. Traditional systems authenticate
clients to protect the server, grid systems require mutual authentication to ensure protection
against attackers.
•Single sign on or delegation
capacity, to reduce the number of times
a user needs to enter password
•Firewalls.
•SSL Layers.
•Filtering and auditing of
data.
•Erasure of data after use.
•Advanced measures for security
in grid computing such as hardware based Virtual Private Network (VPN), which
involves moving grid processors into the VPN at the start of a session and out
at its conclusion, and restricting client-side access to the grid to named
users.
The business gains resulting
from grid computing already outweigh the security risks, and as security
problems with grid computing find even more resolution with further advancement
of technology, grid computing is poised to become commonplace.
conclusion
Despite
the described disadvantages of grid computing, this technology has many
benefits and it seems likely that it will be used more and more in different
computational grid projects, especially for biomedical, industrial and
financial research, but also in chemistry and medicine. One of the most famous
exponents of grid computing is the European Organization for Nuclear Research
(CERN), as they use (among others) the concept for the Large Hadron Collider
(LHC).
Some grid computingprojectsaround the world*: 1)European Union DataGrid www.eu-datagrid.org
EUphysicalandenvironmentalapplicationsand information-vital
. Grid Physics Network Griphyn.org American National Foundationfor Science(NSF)physicalanalysis ofexperimentaldataandwide-ranging
. Information Power Grid www.ipg.nasa.gov U.S. Agency forAviationandSpaceSciencesResearchSupportAviation
. Singapore BioGrid www.nic.nus.edu.sg / biogrid Singaporean
governmentresearchinformatics-Vital
Important
events:
The Fourth International
workshop on Grid Computing (GridCom-2012)(
