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Distributed Systems

COMPARISON BETWEEN CLOUD AND GRID COMPUTING: REVIEW PAPER

Profile image of Hamza AldabbasHamza Aldabbas

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https://doi.org/10.5121/IJCCSA.2012.2401
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Abstract

Cloud computing is the most recent announced technology that has been launched on the network world. Clouds are considered as a new generation of Grid computing. Clouds consist of data centres which are owned by the same institute. The homogeneity within each data centre in the infrastructure is the main feature for the cloud computing compared to grid computing. This paper provides a definition for the cloud, it discusses many aspects of Cloud Computing, and describes architectures for the cloud (by looking at Amazon's application (GrepTheWeb)) and how its cost definition differs from that of Grid computing. This paper focuses on comparing Cloud Computing to previous generations such as Grid Computing, by reviewing some Security and Policy Issues in Cloud and Grid Computing. At the end, this paper describes the similarities and differences between the Grid and Cloud approaches.

Figures (15)
Table reference as extracted from [14 ] .
Table reference as extracted from [14 ] .
International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
Clouds computing could be comprised of several heterogeneous components/systems such as grids computing, cluster, super computers etc. (Figure 1). This aggregation is used by millions of users. Consider, for example the case of Microsoft’s Live, where the system has around 300 million users. Added to this, there are almost 330.000 application developers of Amazon EC2. Cloud Architecture consists of software applications, which use Internet-accessible on-demand services. Therefore, these applications are considered as an essential computing infrastructure that is used when it is required (such as processing a user request) and to perform a specific job by giving up unwanted resources. Also drawing the needed resources on-demand (like compute servers or storage).
Clouds computing could be comprised of several heterogeneous components/systems such as grids computing, cluster, super computers etc. (Figure 1). This aggregation is used by millions of users. Consider, for example the case of Microsoft’s Live, where the system has around 300 million users. Added to this, there are almost 330.000 application developers of Amazon EC2. Cloud Architecture consists of software applications, which use Internet-accessible on-demand services. Therefore, these applications are considered as an essential computing infrastructure that is used when it is required (such as processing a user request) and to perform a specific job by giving up unwanted resources. Also drawing the needed resources on-demand (like compute servers or storage).
Figure 2: High-level market-oriented Cloud architecture. Source: [17]. The figure below illustrates a high level architecture for supporting market-oriented resource allocation in Data Centres and Clouds.
Figure 2: High-level market-oriented Cloud architecture. Source: [17]. The figure below illustrates a high level architecture for supporting market-oriented resource allocation in Data Centres and Clouds.
Figure3 depicts a high-level illustration of GrepTheWeb architecture. GrepTheWeb has two inputs the first one is the output of the Search Results Service, which is a list of links that are zipped in a single file. The second input is a regular expression. The output is a filtered subset of document links stored and gzipped into a single file. Developers can get the status of their jobs by calling GetStatus() to see whether the execution is completed or not as long as the overall process is asynchronous.
Figure3 depicts a high-level illustration of GrepTheWeb architecture. GrepTheWeb has two inputs the first one is the output of the Search Results Service, which is a list of links that are zipped in a single file. The second input is a regular expression. The output is a filtered subset of document links stored and gzipped into a single file. Developers can get the status of their jobs by calling GetStatus() to see whether the execution is completed or not as long as the overall process is asynchronous.
Figure 5 illustrates the workflow of GrepTheWeb. It does its processing in four stages as appeared down. The first stage ( launch phase ) has the responsibility to validate and initiate the processing of a GrepTheWeb request, instantiate Amazon EC2 instances, launch the Hadoop cluster on them and start all the job processes. The second phase (monitor phase) do several significant jobs such as monitoring the EC2 cluster, maps, reduces, and checking for success and failure. The third phase (shutdown phase) to shut down Amazon EC2 instances and Hadoop processes, whilst deleting Amazon SimpleDB transient data in the Final phase (cleanup phase). 2. A lunch message is added to the queue as soon as startGerp request is received.
Figure 5 illustrates the workflow of GrepTheWeb. It does its processing in four stages as appeared down. The first stage ( launch phase ) has the responsibility to validate and initiate the processing of a GrepTheWeb request, instantiate Amazon EC2 instances, launch the Hadoop cluster on them and start all the job processes. The second phase (monitor phase) do several significant jobs such as monitoring the EC2 cluster, maps, reduces, and checking for success and failure. The third phase (shutdown phase) to shut down Amazon EC2 instances and Hadoop processes, whilst deleting Amazon SimpleDB transient data in the Final phase (cleanup phase). 2. A lunch message is added to the queue as soon as startGerp request is received.
Figure 6: GrepTheWeb Architecture - Zoom Level 3 Source: [11] International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
Figure 6: GrepTheWeb Architecture - Zoom Level 3 Source: [11] International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
Table 2: Guide to where costs go in the data centre. In this section the discussion focuses on cost models in some Components in Cloud architecture such as those in table2. The important question about the cost of cloud is Where does the cost go in today’s cloud service data centres?. The table below provides a rough guide to associated costs [2].
Table 2: Guide to where costs go in the data centre. In this section the discussion focuses on cost models in some Components in Cloud architecture such as those in table2. The important question about the cost of cloud is Where does the cost go in today’s cloud service data centres?. The table below provides a rough guide to associated costs [2].
Figure 7: Map Reduce Operation (in GrepTheW eb) Source: [11] International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
Figure 7: Map Reduce Operation (in GrepTheW eb) Source: [11] International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
4.3 Power cost. International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
4.3 Power cost. International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
The popularity of different paradigms varies with time. The web search popularity, as measured by the Google search trends during the last 12 months, for terms “cluster computing”, “Grid computing”, and “Cloud computing” is shown in Figure 2. From the Google trends, it can be observed that cluster computing was a popular term during 1990s, from early 2000 Grid computing become popular, and recently Cloud computing started gaining popularity [17].
The popularity of different paradigms varies with time. The web search popularity, as measured by the Google search trends during the last 12 months, for terms “cluster computing”, “Grid computing”, and “Cloud computing” is shown in Figure 2. From the Google trends, it can be observed that cluster computing was a popular term during 1990s, from early 2000 Grid computing become popular, and recently Cloud computing started gaining popularity [17].
Table reference as extracted from [14]
Table reference as extracted from [14]
International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
International Journal on Cloud Computing: Services and Architecture (IJCCSA),Vol.2, No.4, August 2012
Figure 15 : Grid application in a cloud environment Source:[5] There are two solutions to deal with increased processing power, additional low-level services can be deployed automatically, and to deal with increased number of users, additional high-level services can be instantiated to serve the interface [5]. Firstly, solution is based on incorporating an index service to register grid services. Secondly, load balancing can be used to achieve this approach at interface nodes. For example, a master-worker is implemented as multiple workers who need only to register themselves with the index service to become available to the master. The figure below shows a scenario compatible with the master- worker Paradigm.
Figure 15 : Grid application in a cloud environment Source:[5] There are two solutions to deal with increased processing power, additional low-level services can be deployed automatically, and to deal with increased number of users, additional high-level services can be instantiated to serve the interface [5]. Firstly, solution is based on incorporating an index service to register grid services. Secondly, load balancing can be used to achieve this approach at interface nodes. For example, a master-worker is implemented as multiple workers who need only to register themselves with the index service to become available to the master. The figure below shows a scenario compatible with the master- worker Paradigm.

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