A Concept Of Computing Resources On Internet

Published Date: 02 Nov 2017

Sudeep Srivastava

Email: [email protected], [email protected]

Sun Software Remedies, SSR, Gali No 9 Ghaziabad, Uttar Pradesh

Abstract: Cloud computing has beendeveloped as a new model for hosting and transporting services over the Internet. Cloud computing is beautiful to industry owners as it eliminates the necessity for employers to plan ahead for provisioning, and allows enterprises to start from the small and increase supplies only when there is a rise in service demand. However, despite the fact that cloud computing offers huge openingsto the IT industry, the growth of cloud computing technology is currently at its beginning, as many issues are still to be addressed. In this paper, ananalysis of cloud computing is presented stress its key ideas, architectural principles, and state of the art operation as well as research challenges. The aim of this paper is to provide a better accepting of the design concept of cloud computing and identify important research directions in this increasingly important area.

Keywords Cloud Computing, Data Centers, Virtualization, Internet, Research challenges, PaaS, IaaS, SaaS.

Introduction: With the software development of processing and storage technologies and the success of the Internet, online computing capitals have become cheaper, more powerful and more universally available than ever before. This technological trend has enabled the ideas of a new computing model, which is mutually know as Cloud Computing, in which resources like CPU and storage are offered as general functions that can be rented andreleased by users through the Internet in an on demand fashion.

In this computing background, the traditional role of service provider is divided into two, one is the infrastructure providers who look after cloud platforms and lease resources according to a usage based costing model, and second is service providers, who rent capitals from one or many organization providers to serve the end users. The development of cloud computing has made a wonderful impact on the ITindustry over the past few years, where largebusinesseslike Google, and Microsoft strive to deliver more controlling, reliable and costefficient cloud plans, and business seek to reshape their business models to gain benefit from this new model. Actually, cloud computing provides several compelling features that make it attractive to business owners, as given below.

No direct investment: Cloud computing uses a pay as you go costing model. A packagesupplier does not need to capitalize in the setup to start gaining benefit from cloud computing. It simply rents properties from the cloud according to its own needs and pay for the usage.

Droppingfunctioningcharge:Capitals in a cloud location can be fast allocated and de-allocated on demand. Henceforth, a package supplier no longer needs to delivery capacities according to the peak load. This provides huge savings then resources can be released to save on operating costs when package request is low.

Extremely scalable: Infrastructure providers pool large amount of capitals from data centers and make them easily available. A package supplier can simply expand its service to large scales in order to handle quick increase in package demands.

This model is sometimes called surge computing.

Easy-goingapproach: Services hosted in the cloud are generally web-based. Then, they are easily available through a variability of devices with Internet connections. These devices not only include desktop and laptop computers, but also Mobility device like Cell Phone.

Dropping business risks and protectionoverheads: By outsourcing the service infrastructure to the clouds, a service provider shifts its business risks like hardware and software crashed to infrastructure providers, who often have better expertise and are better equipped for managing these risks. In addition, a service provider can cut down the hardware maintenance and the staff training costs.

However, although cloud computing has shown considerable openings to the IT industry, it also brings many unique challenges that need to be judiciouslyattended. This paper present a research of cloud computing, highlighting its key concepts, architectural principles, advanced implementations as well as research challenges. The aim is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this interesting topic.

The remainder of this paper is organized as follows. Section 2 coversasummary of cloud computing and associate it with other associated technologies. Section 3, covers the planning and architecture of cloud computing and present its design philosophies. The key features and types of cloud computing are covered in Section 4. &Section 5 researchof the moneymaking products as well as the current technologies used for this computing. Section 6, covers the current research topics in cloud computing. At last, the paper concludes in Section 7.

Section 2

Overview: This section covers a overall overview of cloud computing, including its meaning and a comparison with related thoughts.

The main thought processesfor cloud computing is not new. In 1960s anned that computing facilities would be carried to the overall public like utility. The word "cloud" has also been used in severalperspectives such as describing large ATM networks in the 1990s. Since then, the word cloud computing has been used mostly as a marketing word in a diversity of contexts to represent many unlike ideas. Certainly, the lack of a normal definition of cloud computing has made not only sell hypes, but also a fair amount of doubt and confusion. In this paper, I adopt the explanation of cloud computing provided by "The National Institute of Standards & Technology"as it covers, in myview, all the essential parts of cloud computing:

"The Model of Cloud Computing for allowingopportune, ondemand network door to a public pool of configurable computing resources like networks, servers, storage, applications, and services which can be quickly provisioned and freed with less management effort or service provider interaction."

The main reason for the reality of different observations of cloud computing is that computing, distinct other technical terms, is not a new technology, but somewhat a new processes model that brings composed a set of current technologies to run business in a different way. Really, most of the technologies used by cloud computing, such as virtualization and utility based costing, are not at all new. In its place, cloud computing powers these current technologies to chance the technological and financial requirements of current demand for IT.

Cloud computing is frequentlylikened to the some technologies, each of which shares positivecharacteristics with this computing:

Grid Computing: Grid computing is a spread-computingexample that organizes networked capitals to complete a joint computational objective. The growth of this computing was first driven by technicalapplications, which are usually computation intensive. Cloud computing is similar to this computing in that it also works distributed resources to complete applicationlevel objectives. However, cloud computing takes one step further by leveraging VT at multiple levels like hardware and application platform to realize resource sharing and dynamic resource provisioning.

Utility Computing: Utility computing symbolizes the model of deliveringcapitals on request and charging customers based on usage rather than a flat rate. Cloud computing can be supposed as anunderstanding of utility computing. It accepts a utility based pricing arrangementcompletely for economic reasons. By on demand resource provisioning and utility based pricing; service providers can truly maximize resource use and minimize itsworking costs.

Virtualization: Virtualization is a technology that summaries away the details of physical hardware and provides virtualized capitals for high-level applications. A virtualized server is usually called a virtual machine (VM). Virtualization forms the basis of cloud computing, as it provides the skill of combining computing capitals from clusters of servers and dynamically allotting or recasting virtual capitals to applications ondemand.

Section 3

Cloud computing design: This section defines the designing, business & various setup models of cloud computing.

3.1 Layer Model

Normally, the design of a cloud-computing environment can be separated into 4 layers: as in Fig. 1. I describe each of them in detail:

The hardware layer: The responsible of this layerto look after the physical capitals of the cloud, withservers, network routers, network switches, power supply and AC systems. In habit, this layer is normallydesigned in place at data centers. Data center commonlycovers thousands of servers that are pleased in racks and organized through network switches, network routers or other network fabrics. Normal issues at this layer include hardware configuration, responsibility acceptance, network traffic management, power supply and AC resource management.

Cloud computing’s Layer model

Fig. 1

Infrastructure/Virtualization layer: the infrastructure/virtualization layer designs a way of storage and computing capitals by dividing the physical capitals using virtualization machineries such as KVM and others machineries. This layer is anecessarymodule of cloud computing, because many key features, such as dynamic supplytransfer, are only be available bythese machineries.

Platform layer:Made on top of the setup layer, the platform layer consists of computer operating systems & application frameworks. The use of this layer is to reduce the load of hosting applications directly into VM containers. Like, Google App at this layer to provide API support for managing storage, database and business logic of normal web applications.

Application layer: At the Top of the hierarchy, this layer contains of the real cloud applications. Unlike from old-style applications, cloud applications can influence the automatic-scaling feature to reachbatter performance, accessibility and less operating cost.

Related to old-style service hosting environments like dedicated server farms, the design of cloud computing is more flexible. Alllayersarelightlyjoined with the layers given above and below, allowing each layer to change separately. This is similar to the design of the network OSI model for network management. The designing modularity permits cloud computing to support a wide range of application necessities while dropping management and upkeep overhead.

3.2 Business model

Cloud computing services are a service-driven business model. In other words, hardware and platformlevel capitals are provided as facilities on-demand basis. Theoretically, every layer of the designdefined in the above section can be applied as a service to the layer above.But, in practice, clouds proposal services that can be assembled into three categories: Software as a Service also called SaaS, Platform as a Service also called PaaS, and Infrastructure as a Service also called IaaS.

Infrastructure as a Service: IaaSrefers to on request provisioning of infrastructural capitals, habitually in terms of VMs. The cloud proprietor who offers IaaS is called an IaaSsupplier like GoGrid, EC2 etc.

Platform as a Service: PaaS refers to offering platform layer capitals, including computer operating system support and software development frameworkslike Google App, MS Windows Azure.

Software as a Service: SaaS refers to offeringon request applications over the Internet like Salesforce.com etc.

The business model of cloud computing is depicted by Fig. 2. According to the layered architecture of cloud computing it is entirely possible that a PaaS provider runs its cloud on top of an IaaS provider’s cloud. However, in the current practice, IaaS and PaaS providers are often parts of the same organization (e.g., Google and Salesforce). This is why PaaS and IaaS providers are often called the infrastructure providers or cloud providers

Fig 2 Business Model

3.3 Type Clouds

There are many issues to consider when going an enterprise application to the cloud environment. For example, some service providers are mostly interested in low operation cost, while others may prefer high reliability and security. Due to this, there are different types of clouds according to it own benefits and drawbacks.

Public clouds: A cloud in which service providers offer their resources as services to the general public. Public clouds offer several key benefits to service providers, including no initial capital investment on infrastructure and shifting of risks to infrastructure providers.

Private clouds: Also known as internal clouds, private clouds are designed for exclusive use by a single organization. A private cloud may be built and managed by the organization or by external providers. A private cloud offers the highest degree of control over performance, reliability and security.

Hybrid clouds: A hybrid cloud is a combination of public and private cloud models that tries to address the limitations of each approach. In a hybrid cloud, part of the service infrastructure runs in private clouds while the remaining part runs in public clouds. Hybrid clouds offer more flexibility than both public and private clouds.

Virtual Private Cloud: An alternative solution to addressing the limitations of both public and private clouds is called Virtual Private Cloud (VPC). A VPC is essentially a platform running on top of public clouds. VPC delivers seamless change from anexclusive service setup to a cloud-basedsetup, owing to the virtualized network layer.

Section 4

Characteristics of Cloud Computing:Cloud computing deliversnumeroussignificant features that are different from old-style service of computing, which I summarize below:

Multi Tenancy: In a cloud world, services kept by numeroussuppliers are co-located in a one data center. The processes performance and administration issues of these services are public among service providers and the setup provider. The layered design of cloud computing provides a natural division of accountabilities: the proprietor of each layer only needs to emphasis on the exactpurposesrelated with this layer. Yet, multi tenancy also introduces problems in understanding and managing the contacts among various investors.

Shared resource pooling: The infrastructure provider offers a pool of computing resources that can be dynamically assigned to multiple resource consumers. Like dynamic resource taskabilitydelivers much flexibility to setup providers for handling their own resource usage and working costs.

Geo distribution &global network access: Clouds are generally available through the Internet & use the Internet as a package delivery network. Therefore any device with Internet connectivity, be it a mobile, or a laptop, is able to access cloud services.

Service oriented: As mentioned previously, cloud computing adopts a service-driven operating model. Hence it places a strong emphasis on service management. In a cloud, each IaaS, PaaS and SaaS provider offers its service according to the Service Level Agreement (SLA) negotiated with its customers.

Dynamic resource provisioning: One of the key features of cloud computing is that computing resources can be obtained and released on the fly. Compared to the traditional model that provisions resources according to peak demand, dynamic resource provisioning allows service providers to acquire resources based on the current demand, which can considerably lower the operating cost.

Auto Organizing: Since resources can be allocated or de-allocated on request, service providers areauthorized to manage their store consumption according to their own needs. Also, the automaticstore management feature profits high speed that enables packagesuppliers to respond quickly to fast changes in package demand like the flash crowd effect.

Utility Based Costing:This computing employs a pay per use costing model. The exact costing scheme may vary from service to service. Like, SaaS provider may rent a virtual machine from an IaaS provider on a perhour basis. On the other side, SaaS provider that provides on request customer relationship management or CRM may charge its customers based on the number of clients it helpsUtility based Costing lowers package operating cost as it charges customers on a per use basis.

Section 5

State of the Art:In this section, I present the Stateofthe Art applications of cloud computing. I first define the key machineries currently used for cloud computing. Then, I review the popular cloud computing products.

5.1 Cloud computing technologies:This section provides a review of machineries used in cloud computing settings.

5.1.1 Architectural design of data centers: A data center, which is home to the computation power and storage, is central to cloud computing and contains thousands of devices like servers, switches and routers. Proper planning of this network architecture is critical, as it will heavily influence applications performance and throughput in such a distributed computing environment. Further, scalability and resiliency features need to be carefully considered.

Currently, a layered approach is the basic foundation of the network architecture design, which has been tested in some of the largest deployed data centers. The basic layers of a data center consist of the core, aggregation, and access layers, as shown in Fig. 3. The access layer is where the servers in racks physically connect to the network. There are typically 20 to 40 servers per rack, each connected to an access switch with a 1 Gbps link. Access switches usually connect to two aggregation switches for redundancywith 10 Gbps links.

The aggregation layer usually provides important functions, such as domain service, location service, server load balancing, and more. The core layer provides connectivity to multiple aggregation switches and provides a resilient routed fabric with no single point of failure. The core routers manage traffic into and out of the data center.

A popular practice is to leverage commodity Ethernet switches and routers to build the network infrastructure. In different business solutions, the layered network infrastructure can be elaborated to meet specific business challenges. Basically, the design of data center network architecture should meet the following objectives

Fig. 3 Basic layered design of data center network setup

Uniform high capacity: The maximum rate of a server- to-server traffic flow should be limited only by the fixedsize on the network boundarypath of the sending and receiving servers, and assigning servers to a package should be independent of the network topology.

Free VM migration: Virtualization allows the entire VM state to be transmitted across the network to migrate a VM from one physical machine to another. A cloud computing hosting service may migrate VMs for statistical multiplexing or dynamically changing communication patterns to achieve high bandwidth for tightly coupled hosts or to achieve variable heat distribution and power availability in the data center.

Resiliency: Failures will be joint at rule. The network setup must be fault accepting against various types of server failures, link outages, or server rack failures.

Scalability: The network setup must be able to measure to a big number of servers and allow for incremental growth.

Backward Compatibility: The network setup should be backward compatible with network switches &network routers running Ethernet & IP, because existing data centers have usually leveraged commodity Ethernet and IP based devices, they should also be used in the new design.

5.1.2 Distributed file system over clouds:Google File System (GFS) is a branded distributed file system which is developed by Google & specially planned to delivereffective, dependable access to data using large groups of product servers. Files are divided into pieces of 64 megabytes, and are usually added to or read and only extremely rarely overwritten or shrunk. Likened with traditional file systems, GFS is designed and improved to run on data centers to provide extremely high data outputs, low latency and survive unlike server failures.

Inspired by GFS, the open source Hadoop Distributed File System (HDFS) stores large files across multiple machines. It completes reliability by repeating the data across multiple servers. Similarly to GFS, data is stored on multiple geo diverse nodes.

5.1.3 Cloud’s Distributed application framework: HTTPbased applications usually conform to some web application framework such as Java EE. In current data center settings, groups of servers are also used for calculation and data severe jobs such as financial trend analysis, or film animation.

Map-Reduce is a software framework hosted by Google to support distributed computing on big data sets on groups of computers. Map-Reduce contains of one Master, to which client requests submit Map-Reduce jobs. The Master pushes work out to available task nodes in the data center, determined to keep the tasks as close to the data as possible. It knows which node contains the data, and which other hosts are close. If the task cannot be hosted on the node where the data is stored, importance is given to nodes in the same stand. In this way, network traffic on the main support is reduced, which also helps to improve output, as the support is usually the block.

The open source Hadoop Map-Reduce project is inspired by Google’s work. Now, many organizations are using Hadoop Map-Reduce to run large data intensive calculations.

5.2 CloudComputingCommercial Products: In this section, I provide a study of some of the leadingproducts of cloud computing.

Amazon EC2:Amazon Web Services (AWS) is a set of cloud services, providing cloud-based computation, storage and other functionality that enable organizations and individuals to deploy applications and services on an on-demand basis and at commodity prices. Amazon Web Services offerings are accessible over HTTP, using REST and SOAP protocols. Amazon Elastic Compute Cloud (Amazon EC2) enables cloud users to launch and manage server instances in data centers using APIs or available tools and utilities. EC2 in- stances are virtual machines running on top of the main virtualization engine. After creating and starting an instance, users can upload software and make changes to it.

For cloud users, Amazon Cloud Watch is a useful management tool which collects raw data from partnered AWS services such as Amazon EC2 and then processes the information into readable, near real-time metrics. The metrics about EC2 include, for example, CPU utilization, network in/out bytes, disk read/write operations, etc.

Google App: This is a stage for old-style web applications in Google Managed data centers. Now, the supported programming languages are Python and Java. Web frameworks that run on the Google App also with Pylons, and web2py, as well as a tradition Google written web application framework similar to JSP or ASP.NET. Google handles organizing code to a group, monitoring, failover, and introduction application examples as needed.

Following Table (Table No. 1) summarizes the three examples of popular cloud offerings in terms of the classes of utility computing, target types of application, and more importantly their models of computation, storage and auto scaling. Apparently, these cloud offerings are based on different levels of abstraction and management of the resources. Users can choose one type or combinations of several types of cloud offerings to satisfy specific business requirements.

Table 1 A comparison of representative commercial products

Cloud Provider

Amazon EC2

Windows Azure

Google App Engine

Classes of Utility Computing

Infrastructure service

Platform service

Platform service

Target Applications

General-purpose applications

General-purpose Windows applications

Traditional web applications with supported framework

Computation

OS Level on a Xen Virtual Machine

Microsoft Common Language Runtime (CLR) VM; Predefined roles of app. Instances

Predefined web application frameworks

Storage

Elastic Block Store; Amazon Simple Storage Service (S3); Amazon SimpleDB

Azure storage service and SQL Data Services

BigTable and MegaStore

Auto Scaling

Automatically changing the number of instances based on parameters that users specify

Automatic scaling based on application roles and a configuration file specified by users

Automatic Scaling which is transparent to users

Section 6

Research challenges:Although cloud computing has been widely adopted by the industry, the research on cloud computing is still at an early stage. Many existing issues have not been fully addressed, while new challenges keep emerging from industry applications. In this section, I summarize some of the challenging research issues in cloud computing.

6.1 Automated service provisioning: One of the key features of cloud computing is the capability of acquiring and releasing resources on-demand. The objective of a service provider in this case is to allocate and de-allocate resources from the cloud to satisfy its service level objectives (SLOs), while minimizing its operational cost. However, it is not obvious how a service provider can achieve this objective. In particular, it is not easy to determine how to map SLOs such as requirements to low level resource requirement such as CPU and memory requirements. Furthermore, to achieve high agility and respond to rapid demand fluctuations such as in flash crowd effect, the resource provisioning decisions must be made online.

Automated service provisioning is not a new problem. Dynamic resource provisioning for Internet applications has been studied extensively in the past. These approaches typically involve: (1) Constructing an application performance model that predicts the number of application instances required to handle demand at each particular level, in order to satisfy QoS requirements; (2) Periodically predicting future demand and determining resource requirements using the performance model; and (3) Automatically allocating resources using the predicted resource requirements. Application performance model can be constructed using various techniques, including Queuing theory, Control theory and Statistical Machine Learning.

Additionally, there is a distinction between proactive and reactive resource control. The proactive approach uses predicted demand to periodically allocate resources before they are needed. The reactive approach reacts to immediate demand fluctuations before periodic demand prediction is available. Both approaches are important and necessary for effective resource control in dynamic operating environments.

6.2 Virtual machine relocation:Virtualization can provide important benefits in cloud computing by allowing virtual machine relocation to balance load across the data center. In addition, virtual machine relocation enables healthy and very responsive provisioning in data centers. It has grown from process relocation techniques. More recently, Xen and VMWare have implemented "live" relocation of Virtual machine that includesvery short downtimes reaching from tens of milliseconds to a second.

The major benefits of VM migration are to avoid hotspots; however, this is not straightforward. Currently, detecting workload hotspots and initiating a migration lacks the agility to respond to sudden workload changes. Moreover, the in memory state should be transferred consistently and efficiently, with integrated consideration of resources for applications and physical servers.

6.3 Server consolidation:This is an effective approach to maximize resource utilization while minimizing energy consumption in a cloud-computing environment. Live VM migration technology is often used to consolidate VMs residing on multiple under-utilized servers onto a single server, so that the remaining servers can be set to an energy-saving state. The problem of optimally joining servers in a data center is often expressed as airregular of the vector bin packing problem, which is an NP hard optimization problematic. Various heuristics have been proposed for this problem. Additionally, dependencies among VMs, such as communication requirements, have also been considered recently.

However, server consolidation activities should not hurt application performance. It is known that the resource usage of individual VMs may vary over time.

6.4 Energy management: Improving energy efficiency is another major issue in cloud computing. It has been estimated that the cost of powering and cooling accounts for 53% of the total operational expenditure of data centers. Hence infrastructure providers are under enormous pressure to reduce energy consumption. The goal is not only to cut down energy cost in data centers, but also to meet government regulations and environmental standards.

Designing energy-efficient data centers has recently received considerable attention. This problem can be approached from several directions. For example, energy- efficient hardware architecture that enables slowing down CPU speeds and turning off partial hardware components has become commonplace. Energy-aware job scheduling and server consolidation are two other ways to reduce power consumption by turning off unused machines.

6.5 Traffic management and analysis: Analysis of data traffic is important for today’s data centers. For example, many web applications rely on analysis of traffic data to optimize customer experiences. Network operators also need to know how traffic flows through the network in order to make many of the management and planning decisions.

Currently, there is not much work on measurement and analysis of data center traffic. Greenberg report data center traffic characteristics on flow sizes and concurrent flows, and use these to guide network infrastructure design.

6.6 Data Security:Data security is another important research topic in cloud computing. Since service providers typically do not have access to the physical security system of data centers, they must rely on the infrastructure provider to achieve full data security. Even for a virtual private cloud, the service provider can only specify the security setting remotely, with- out knowing whether it is fully implemented. The infrastructure provider, in this context, must achieve the following objectives: (1) privacy, for secure data access and allocation, and (2) auditability, for showing whether security setting of applications has been tampered or not. Privacy is usually accomplished using cryptographic procedures, while auditability can be accomplished using remote attestation methods.

6.7 Software Frameworks: Cloud computing provides a compelling platform for hosting large scale data intensive applications. Typically, these applications leverage MapReduce frameworks such as Hadoop for scalable and fault-tolerant data processing. Recent work has shown that the performance and resource consumption of a MapReduce job is highly dependent on the type of the application. For instance, Hadoop tasks such, as sort is Input Output intensive, whereas grip requires significant CPU resources. Furthermore, the VM allocated to each Hadoop node may have mixedfeatures. For example, the bandwidth available to a VM is dependent on other VMs collocated on the same server.

6.8 Storage Technologies &Data Management: Software frameworks such as Map-Reduce and its various implementations such as Hadoop and Dryad are designed for distributed processing of data intensive tasks. As mentioned previously, these frameworks typically operate on Internet scale file systems such as GFS and HDFS. These file systems are different from traditional distributed file systems in their storage structure, access pattern and application-programming interface.

Section 7

Conclusion:Cloud computing has newly developed as a new model for hosting services over the Internet. The growth of computing is fast changing the landscape of IT, and finallyrotating the longheld potential of helpful computing into a reality.

However, despite the importantprofitsopen by cloud technology, the up-to-date technologies are not developedsufficient to understand its full prospective. Some of the key challenges in this domain, along with automatic resource provisioning, power supply management and data security management, are only first to obtain attention from the research group. Then, I believe there is stillwonderfulchance for researchers to make revolutionaryassistances in this field, and bring important impact to their growth in the business.

In this paper, I have examined the State of the Art of cloud computing, covering its important concepts, architectural designs, prominent features, key skills as well as research instructions. As the growth of cloud computing technology is still at afirst stage, I hope my work will provide a better thoughtful of the design challenges of cloud computing, and cover the way for further research in this area.