Cloud Computing Literature Review

On-demand Self-Service: It is defined as based on the user requirement the computing resources should be made available

Cloud computing is an internet based computing which provides various applications and services like storage, servers, infrastructure, networking with low cost, on-demand self service, pay as you go model, location independent resource pooling, reasonable price , rapid elasticity etc. Cloud computing is one way to increase the capacity add capabilities without investing in new infrastructures like computer hardware involves storage memory, licensing for new software, training for a person and in a dynamic way.

Cloud computing is an emerging model where users can gain access to their applications from anywhere through their connected devices. A simplified user interface makes the infrastructure supporting the applications transparent to users. The applications reside in massively-scalable data centers where compute resources can be dynamically provisioned and shared to achieve significant economies of scale. A strong service management platform results in near-zero incremental management costs when more IT resources are added to the cloud. The proliferation of smart mobile devices, high speed wireless connectivity, and rich browser-based Web 2.0 interfaces has made the network-based cloud computing model not only practical but

Cloud Computing is an innovating new IT service that enables multiple services like storage, web hosting and computing under the same roof. Many companies are moving their services to this technology with the flexibility of “pay as you go” model where a customer pays only for the services used leading to cost saving for them. It also helps in terminating the need for large infrastructure maintenance and development. Multiple Virtual Machines (VMs) having varying resource locations can be operated together by a physical machine through utilization of hardware virtualization by Clouds [1]. There can be an imbalance in a PM due to a varying load of each VM due to over load of resource demand and it can affect the performance of VMs on the PM

The Important of Cloud Computing is increasing and it is receiving a growing attention in Scientific & Industrial Communities. Cloud computing is one of the top 10 most important technologies and has a greater possibility in successive years by companies and organizations. Cloud computing implement everywhere, favourable, on demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications and servers) that can be immediately supply and released with minimal management effort.

ABSTRACT: Elasticity is defined as the ability of the system to adapt to workload increase or decrease the computing resources allocated in a dynamic way and on demand.In this survey, they have researched upon various problem in using cloud computing in today's world limitations that occur to use Elasticity in Scientific Application.They have also taken some of the limitations and problem that can be solved in today period.

The current scenario in cloud computing has evolved from traditional need of cloud platforms as a single platform of data storage and virtual machines to Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Due to growth in availability of number of cloud providers in the market, providers are facing intense pressure of competition for providing best prices and complement it with the best Quality of Service(QoS). QoS is dependent on various factors like latency, acceptance rate as well as reliability. Cloud providers must meet all these requirements and keeping the running costs as low as possible. The pattern of access to these services varies depending on the time of access.

Cloud based application workloads are very dynamic [1] and distinctive in nature, and the resources of the Cloud environments should exploit their native properties such as rapid elasticity, resource sharing, instant scaling etc, in such a way to handle the incoming workloads in an efficient way. Cloud datacenters are facing more commercial and interactive workloads at higher frequencies unlike the traditional

The scarcity of computing resources can lead to slowdown or delay in processing job requests. In some cases, it leads to the rejection of job request. However, the emergence of Cloud computing gives the illusion of infinite computing resources. These resources are made available on demand and can be provisioned rapidly and automatically in any amount of quantity to process users’ job requests. In the Cloud, it is possible to add up resources for provisioning when there is an increase in application load (Scale up). On the other hand, when there is a decrease in application load, resources can be released. (Scale down). This feature of the Cloud that dynamically scales the amount of the resources it provides to clients as their workloads increase or decrease is called elasticity [41]. In this work, the number of resources in the private Cloud are considered to be static (not elastic). However, based on the characteristics of the incoming jobs of users, extra public Cloud compute resources can be rented or released [1][42].

For cloud computing systems to function optimally, the individual components of the network of computing resources must function optimally. Thus, the importance of keeping track of the performance of these components is apparent. In addition to this, the providers of the cloud service need to

Abstract: Cloud Computing as a new enterprise model has become popular to provide on-demand services to user as needed. Cloud Computing is essentially powerful computing paradigm to deliver services over the network. Computing at the scale of the Cloud system allows users to access the enormous resources on-demand. However, a user demand on resources can be various in different time and maintaining sufficient resources to meet peak resource requirements all the time can be costly. Therefore, dynamic scalability which can also be called as elasticity is a critical key point to the success of Cloud Computing environment. Dynamic resizing is a feature which allows server to resize the virtual machine to fill the new requirement of resources in a cloud environment. Though there are enormous applications hosted on cloud now a days, but the next big thing which will be focused on will be the elasticity. In this paper, an effort has been put to explain the cloud elasticity concept and how it will benefit the Cloud implementers in reducing operation cost and also to improve the system’s performance as a whole.

Cloud computing interestingly offers several types of services which can be provisioned by cloud providers. The offered cloud services by providers are apparently categorized into three main ones according to the National Institute of Standards and Technology (NIST) [1] and they are as follows:

Cloud computing was founded on already-existing computing technologies, such as distributed computing (Clusters, Grids), Internet technologies (Web Services, Service Oriented Architectures, Web 2.0), virtualization and systems management (autonomic computing, data centre automation) [11]. Specifically, with the advent of Cloud computing, the benefits of these technologies have been combined and further improved. Cloud basically presents a suitable environment for convenient, on-demand network access to a pool of configurable computing resources that can be mutually accessed and provisioned with insignificant administration effort or service provider interaction [1]. The optimal provisioning of these compute resources to meet certain predefined performance criteria is a complex problem which has attracted much research attention [12][13]. This problem comprise the steps involved in the allocation of suitable computing resources to tasks with the aim of optimizing certain objectives. Some objective functions include but not limited to; maximizing task throughput, minimizing the time of task completion and maximizing the utilization of resources.

Clouds are large scale, complex systems. This makes the management of resources a challenging job. The heterogeneous distributed system requires intelligent strategies to provision resources. These strategies can be automated for efficient performance. Resources provided must be secure, cost-efficient and reliable. Therefore effective management of Clouds providing services in software platforms becomes fundamental. This paper identifies issues on autonomic resource provisioning and provides innovative management techniques which supports SaaS applications on Clouds. A conceptual architecture with early results is provided to emphasis the benefits of autonomic management of Clouds.

Resource Pooling is characterised by provider’s computing resources that combined to maintain numerous users utilising a multi-tenant model, with various physical and virtual resources actively allocated and reallocated accordingly to user demand. A user does not have to monitor or be aware of the location of facilities such as storage, processing, memory, network bandwidth but can indicate general position of it as country, state or datacenter. Rapid Elasticity brings capabilities that can be resiliently procured and extricated to measure promptly outward and inward well proportioned with request. To the user the facilities provided for procuring often appear to be unrestricted and can be suitable in any amount at any stage. The last significant aspect is Measured Service of cloud systems. It monitor and optimize resource use automatically by controlling a metering capability suitable to the type of service, such as active user accounts, bandwidth storage, and processing.