Utility Computing

Top PDF Utility Computing:

Fault-Tolerant Dynamic Deduplication for Utility Computing

Fault-Tolerant Dynamic Deduplication for Utility Computing

Abstract— Utility computing is an increasingly important paradigm, whereby computing resources are provided on- demand as utilities. An important component of utility computing is storage; data volumes are growing rapidly, and mechanisms to mitigate this growth need to be developed. Data deduplication is a promising technique for drastically reducing the amount of data stored in such system systems; however, current approaches are static in nature, using an amount of redundancy fixed at design time. This is inappropriate for truly dynamic modern systems. We propose a real-time adaptive deduplication system for Cloud and Utility computing that monitors in real-time for changing system, user, and environmental behaviour in order to fulfill a balance between changing storage efficiency, performance, and fault tolerance requirements. We evaluate our system through simulation, with experimental results showing that our system is both efficient and scalable. We also perform experimentation to evaluate the fault tolerance of the system by measuring Mean Time to Repair (MTTR), and using these values to calculate availability of the system. The results show that higher replication levels result in higher system availability; however, the number of files in the system also effects recovery time. We show that the tradeoff between replication levels and recovery time when the system overloads needs further investigation.
Show more

9 Read more

A2HA—automatic and adaptive host allocation in utility computing for bag-of-tasks

A2HA—automatic and adaptive host allocation in utility computing for bag-of-tasks

Computing clouds have become more and more used to solve e-science problems, such as scheduling workflows of astronomy applications [17] comprised of large numbers of small tasks. This approach was compared, with encourag- ing results regarding virtual clusters, in different environ- ments: combinations of virtual machines and virtual clusters deployed on the Nimbus science cloud vs. a single local ma- chine and a local Grid-based cluster. In Hill’s work [14], the calculations of MPI-driven ocean climate models are performed on Amazon EC2 using 12 processes, each one running on a virtual machine inside a virtual cluster. They study the cost-effectiveness of the two main classes of ar- chitectures provided by EC2 w.r.t. this type of applications (m1-standard, i.e., single-core and c1-high-cpu, i.e., multi- core virtual Opteron/Xeon processors). They have similar price-performance ratio even though the claims of almost five-fold performance increase in c1-high-cpu are not met experimentally. The authors conclude that it is feasible to run such applications on EC2, despite significant overhead penalties regarding bandwidth and latency of memory and I/O. A virtual cluster created on-demand can perform on par with low-cost cluster systems, but comparatively with high- end supercomputers, performance is much lower.
Show more

15 Read more

Beyond Clouds -- Towards Real Utility Computing

Beyond Clouds -- Towards Real Utility Computing

in typical (unstructured) numerical grid algorithms (such as blood-flow simulation etc.), the communication relationship between the parallel processes is not symmetrical, meaning that t[r]

13 Read more

An Efficient Energy Consumption Minimizing Based on Genetic and Power Aware Scheduling in Cloud Computing

An Efficient Energy Consumption Minimizing Based on Genetic and Power Aware Scheduling in Cloud Computing

parallel applications on heterogeneous cloud computing systems,” 2017 because the cost-driven public cloud services emerge, budget constraint is one in all the primary style problems in large-scale scientific applications dead on heterogeneous cloud computing systems. Minimizing the schedule length whereas satisfying the budget constraint of AN application is one among the foremost necessary quality of service needs for cloud suppliers. [5] H. Arabnejad, et., al., “Low-time complexity budget deadline constrained workflow scheduling on heterogeneous resources,” 2016The execution of scientific applications, under the utility computing model, is constrained to Quality of Service (QoS) parameters. Commonly, applications have time and price constraints such all tasks of an application have to be compelled to be finished at intervals a user-specified point and Budget.
Show more

5 Read more

A Comparison between Cluster, Grid, and Cloud Computing

A Comparison between Cluster, Grid, and Cloud Computing

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction [14]. The term “cloud computing” itself likely comes from network diagrams in which cloud shape are used to describe certain types of networks, either the Internet or internal networks [15]. It’s the Internet-based computing in which everything (like hardware, software, and platform) is provided as services on demand [16]. Cloud computing has also been called utility computing or IT-on- demand.
Show more

6 Read more

MOBILE CLOUD COMPUTING AN EFFICIENT TECHNIQUE FOR MOBILE USERS

MOBILE CLOUD COMPUTING AN EFFICIENT TECHNIQUE FOR MOBILE USERS

„„Cloud computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the data enters that provide those services‟‟ [6]. A cluster of computer hardware and software that offer the services to the general public (probably for a price) makes up a „public cloud‟. Computing is therefore offered as a utility much like electricity, water, gas etc. where you only pay per use. For example, Amazon‟s Elastic cloud, Microsoft‟s Azure platform, Google‟s App Engine and Salesforce are some public clouds that are available today. However, cloud computing does not include „private clouds‟ which refer to data centres internal to an organization. Therefore, cloud computing can be defined as the aggregation of computing as a utility and software as a service. Virtualization of resources is a key requirement for a cloud provider—for it is needed by statistical multiplexing that is required for scalability of the cloud, and also to create the illusion of infinite resources to the cloud user. Ambrust et al. Holds the view that „„different utility computing offerings will be distinguished based on the level of abstraction presented to the programmer and the level of management of the resources‟‟. To take an example from the existing cloud providers, an instance of Amazon‟s EC2 is very much like a physical machine and gives the cloud user almost full control of the software stack with a thin API. This gives the user a lot of flexibility in coding; however it also means that Amazon has little automatic scalability and failover features. In contrast, Google‟s App Engine enforces an API on the user but offers impressive automatic scalability and failover options. Microsoft‟s Azure platform is something in between the aforementioned providers by giving the user some choice in the language and offers somewhat automatic scaling and failover functions. Each of the aforementioned providers has different options for virtualizing computation, storage and communication.
Show more

10 Read more

Security and Privacy Issues in Cloud Computing Environment: A Survey Paper

Security and Privacy Issues in Cloud Computing Environment: A Survey Paper

As seen in the table above, it all started with Grid Computing which solves large problems with parallel computing in the late 1980s, then Utility and software as a Service which are two complementary trends; as Utility computing can only be successful on the market if a critical mass of applications is able to run on it and SaaS needs a flexible, scalable and easily accessible infrastructure on which it can run. So to meet market demand, the next in evolution by nature is the integration of the two trends into a new holistic approach which offers the following functionality;
Show more

10 Read more

ADAPTIVE COLOR FILTER ARRAY INTERPOLATION ALGORITHM BASED ON HUE TRANSITION AND 
EDGE DIRECTION

ADAPTIVE COLOR FILTER ARRAY INTERPOLATION ALGORITHM BASED ON HUE TRANSITION AND EDGE DIRECTION

until the early 2000 and the upcoming of Web 2.0.Indeed, Computing is being transformed to a model consisting of services that are commoditized and delivered in a manner similar to traditional utilities [3] such as water. As for Utility Computing, it is not a new paradigm of computing infrastructure; fairly, it is a business model in which computing resources, such as computation and storage, are wrapped as metered services similar to a physical public utility, such as electricity and public switched telephone network. Utility computing is typically implemented using other computing infrastructure. In a cloud business model, a customer will pay the provider on a consumption basis, very much like the utility companies charge for basic utilities such as electricity, gas, and water, and the model relies on economies of scale in order to drive prices down for users and profits up for providers. Whether they are software, hardware, platform, or storage providers, they deliver their offerings over the Internet. There are no wrapped boxes containing discs or hardware for you to buy and set up yourself. Thus, the computing world is rapidly transforming towards developing software for millions to consume as a service, rather than to run on their individual computer.
Show more

9 Read more

Study of the Implementation of Cloud Computing: Applications and Challenges

Study of the Implementation of Cloud Computing: Applications and Challenges

specific Private cloud. One of the best examples of a private cloud is Eucalyptus Systems [3].Public Cloud: Public cloud describes cloud computing in the traditional mainstream sense, whereby resources are dynamically provisioned on a fine- grained, self-service basis over the Internet, via web applications/web services, from an off-site third-party provider who shares resources and bills on a fine-grained utility computing basis. It is typically based on a pay-per-use model, similar to a prepaid electricity metering system which is flexible enough to cater for spikes in demand for cloud optimization [1]. Public clouds are less secure than the other cloud models because it places an additional burden of ensuring all applications and data accessed on the public cloud are not subjected to malicious attacks. Examples of a public cloud include Microsoft Azure, Google App Engine. Hybrid Cloud: Hybrid cloud is a private cloud linked to one or more external cloud services, centrally managed, provisioned as a single unit, and circumscribed by a secure network [2]. It provides virtual IT solutions through a mix of both public and private clouds. Hybrid Cloud provides more secure control of the data and applications and allows various parties to access information over the Internet. It also has an open architecture that allows interfaces with other management systems. Hybrid cloud can describe configuration combining a local device, such as a Plug computer with cloud services. It can also describe configurations combining virtual and physical, collocated assets -for example, a mostly virtualized environment that requires physical servers, routers, or other hardware such as a network appliance acting as a firewall or spam filter. An example of a Hybrid Cloud includes Amazon Web Services (AWS).Community Cloud: Infrastructure shared by several organizations for a shared cause and may be managed by them or a third party service provider and rarely offered cloud model. These clouds are normally based on an agreement between related business organizations such as banking or educational organizations. A cloud environment operating according to this model may exist locally or remotely. An example of a Community Cloud includes Face book.
Show more

7 Read more

Cloud Computing   Theory and Practice  Marinescu, Dan C pdf

Cloud Computing Theory and Practice Marinescu, Dan C pdf

Virtualization has been used successfully since the late 1950s. A virtual memory based on paging was first implemented on the Atlas computer at the University of Manchester in the United Kingdom in 1959. In a cloud computing environment a VMM runs on the physical hardware and exports hardware- level abstractions to one or more guest operating systems. A guest OS interacts with the virtual hardware in the same way it would interact with the physical hardware, but under the watchful eye of the VMM which traps all privileged operations and mediates the interactions of the guest OS with the hardware. For example, a VMM can control I/O operations to two virtual disks implemented as two different sets of tracks on a physical disk. New services can be added without the need to modify an operating system. User convenience is a necessary condition for the success of the utility computing paradigms. One of the multiple facets of user convenience is the ability to run remotely using the system software and libraries required by the application. User convenience is a major advantage of a VM architecture over a traditional operating system. For example, a user of the Amazon Web Services (AWS) could submit an Amazon Machine Image (AMI) containing the applications, libraries, data, and associated configuration settings. The user could choose the operating system for the application, then start, terminate, and monitor as many instances of the AMI as needed, using the Web Service APIs and the performance monitoring and management tools provided by the AWS.
Show more

415 Read more

Research, Implementations and Issues on Cloud Computing

Research, Implementations and Issues on Cloud Computing

“Virtual Computing Laboratory (VCL)- http://vcl.ncsu.edu is an award-winning open source implementation of a secure production-level on-demand utility computing and services oriented technology or wide-area accessto solutions based on virtualized resources, including computational, storage and software resources. There are VCL pilots with a number of University of North Carolina campuses, North Carolina Community College System, as wellas with a number of out-of-state universities–many of which are members of the IBM Virtual Computing Initiative”. Figure 5 illustrates NC State Cloud based onVCL technology. Access to NC State Cloudreservations and management is either throughaweb portal, or through an API. Authentication, resource availability, image and other informationare kept in a database. Resources (realand virtual) are controlled by one or more management nodes. These nodes can be within the same cloud, or among different clouds, and theyallow extensive sharing of the resources provided licensing and other constraints are honored. NC State undifferentiated resources arecurrently about 1000 IBM Blade Center blades. About 40% to 50% of them are serving high performance computing needs, the rest are in the individual seat mode. Its differentiated servicesare teaching lab computers that are adopted into VCL when they are not in use (e.g., at night).In addition, VCL can attach other differentiated and undifferentiated resources such as Sunblades, Dell clusters, and similar. More detailed information about VCL user services, functions, security and concepts can be found in [6, 44].
Show more

7 Read more

A comparative study of grid & cloud computing

A comparative study of grid & cloud computing

The main idea behind cloud computing is to make applications available on flexible execution environments located in , 2011). It is a complete new technology. It is the development of parallel computing, grid computing. It is the evolution of virtualization, utility computing, Service(SaaS), Infracture-as-a-Service(IaaS), Service(PaaS) and Data-as-a-Service(DaaS) “Cloud is a Parallel and Distributed computing system of a collection of inter-connected and virtualized computer based on service level agreements (SLA).
Show more

5 Read more

A Survey Of Scheduling Mechanisms In Cloud

A Survey Of Scheduling Mechanisms In Cloud

NIST consolidated and defines cloud computing as: “a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., network, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction”. Cloud computing has emerged as a new paradigm leveraging distributed computing in delivering infrastructure, platform, and software as services. These services are made available to the customers or consumers based on subscription in a pay-as-you-go model. The main characteristics of Cloud are
Show more

5 Read more

Evaluation of the Application Benefit of Meteorological High Performance Computing Resources

Evaluation of the Application Benefit of Meteorological High Performance Computing Resources

sources for unified scheduling for the national and regional numerical model business, scientific research work to provide technical services (In accordance with the known application requirements and resource supply capacity, pre-se- lected system ready in the data environment, to achieve the application of re- source scheduling operation). To achieve the system computing and storage re- source usage, the main application of the resource occupancy will be monitored and evaluated. Carrying out some technical researches [12] [13] of parallel algo- rithm optimization, heterogeneous parallel acceleration and so on. But overall, the soft power of application is still relatively weak, to be further strengthened.
Show more

8 Read more

Customer Satisfaction Aware Scheduling For Utility Maximization in Cloud Computing

Customer Satisfaction Aware Scheduling For Utility Maximization in Cloud Computing

ABSTRACT----- we take customer satisfaction into consideration to address the problem how to configure their cloud service platforms to obtain the maximum profit becomes increasingly the focus that they pay attention to. Customer satisfaction affects the profit of cloud service providers in two ways. On one hand, the cloud configuration affects the quality of service which is an important factor affecting customer satisfaction. On the other hand, the customer satisfaction affects the request arrival rate of a cloud service provider. This paper adopts the thought in Business Administration, and firstly defines the customer satisfaction level of cloud computing. Based on the definition of customer satisfaction, a profit maximization model is build in which the effect of customer satisfaction on quality of service (QoS) and price of service (PoS) is considered.
Show more

6 Read more

Edge detection, Fuzzy Logic system, hardware implementation.

Edge detection, Fuzzy Logic system, hardware implementation.

Normally the edge extraction mechanisms are implemented executing the corresponding software realisation on a processor. Nevertheless in applications that demand constrained response times (real time applications) the specific hardware implementation is required. The main drawback of implementing the edge detection techniques in hardware is the high complexity of the existing algorithms. For that reason this paper presents a technique that offers reasonable results for detecting edges in images and simultaneously it allows low cost hardware realisations and high processing speed. The method is based on applying soft computing techniques such as fuzzy logic and Lukasiewicz algebra operator. The utility of this technique is related to the simplicity of the operations for edge calculation that makes it very suitable for hardware implementation.
Show more

6 Read more

Novel review of security issue in security model of cloud computing facing environment

Novel review of security issue in security model of cloud computing facing environment

services. That can be supported and released with least management interaction. The ability for end user to users to utilize part of the resources acquired quickly and easily. Cloud computing in order self service. The capability for an end user to sign up and receive services without late .the application service to end user internet. The cloud service termed as Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS).the cloud provider everywhere the software service mentioned to cloud service. for Example Microsoft Azure, Amazon and Google, IBM, Google Apps Engine Etc .it is Cloud is a pool of virtualized computer resource networks, it can host a different workload and its style back- end jobs, interactive facing application workload with physical machines. It self recovery and highly scaled deployed workload and recovery from any software and hardware failures. It is real time to enable rebalancing of allocations [1-5].
Show more

7 Read more

NEED OF PRIVACY PRESERVATION IN CLOUD DATABASES

NEED OF PRIVACY PRESERVATION IN CLOUD DATABASES

Imagine that a client has developed a web based search service that is available to the world for use through WEB2. Cloud computing will enable the developer to host this service remotely and can deal with the scale variability efficiently. As the business grows or shrinks, developer can acquire or release the resources easily and relatively inexpensively. On the other hand, implementation and maintenance of the data services that are scalable and adaptable to such dynamic conditions becomes a challenge. Especially when the data services are the compositions of the other possibly third party services (e.g., Google search or Yahoo Image search), these services becomes the data processing graphs that use the third party services as building blocks and invoke them during their execution. Running these data services under different QoS (Quality of Service) constraints as per the client’s requirements further makes the system complex [7] .
Show more

8 Read more

MOBILE CLOUD COMPUTING: A SURVEY OF EMERGING ISSUES AND FUTURE TRENDS

MOBILE CLOUD COMPUTING: A SURVEY OF EMERGING ISSUES AND FUTURE TRENDS

In mobile cloud computing, there are two categories of cloud services: cloud contents and computing power. Cloud content are provided in the form of centralized storage centers or sharing online content ,for example live video streams from other mobile devices. There are a number of online file storage services that are available on cloud server which augment the storage potentials by providing off-device storage services. Examples of cloud storage services include Amazon S3 [20] and Drop Box [21].Mobile users outsource data storage by maintaining data storage on cloud server nodes. Smart Box [22] is online file storage and management model which provides constructive approach for online cloud based storage and access management system.
Show more

6 Read more

An Efficient Anomaly Detection Framework for Cloud Computing Environment

An Efficient Anomaly Detection Framework for Cloud Computing Environment

manifold structure of the original data set. And then, an anomaly detection algorithm is designed to cluster the data set with reduced dimensionality into clusters and consider the data instance that does not belong to any cluster as an anomaly point. A series of experiments are conducted on a cloud computing environment that is deployed using OpenStack and experimental results show that the proposed anomaly detection framework is better than other anomaly detection methods that are designed for cloud computing environment in terms of precision, recall, false alarm rate, and runtime.
Show more

11 Read more

Show all 10000 documents...