TL;DR: This work focuses on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SAAS Users, and uses the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.
Abstract: Cloud Computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about overprovisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or underprovisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the datacenters that provide those services. The services themselves have long been referred to as Software as a Service (SaaS). The datacenter hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility Computing. We focus on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SaaS Users. From a hardware point of view, three aspects are new in Cloud Computing.
TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
TL;DR: This presentation will set out the eScience agenda by explaining the current scientific data deluge and the case for a “Fourth Paradigm” for scientific exploration.
Abstract: This presentation will set out the eScience agenda by explaining the current scientific data deluge and the case for a “Fourth Paradigm” for scientific exploration. Examples of data intensive science will be used to illustrate the explosion of data and the associated new challenges for data capture, curation, analysis, and sharing. The role of cloud computing, collaboration services, and research repositories will be discussed.
TL;DR: It is shown that it is possible to map the internal cloud infrastructure, identify where a particular target VM is likely to reside, and then instantiate new VMs until one is placed co-resident with the target, and how such placement can then be used to mount cross-VM side-channel attacks to extract information from a target VM on the same machine.
Abstract: Third-party cloud computing represents the promise of outsourcing as applied to computation. Services, such as Microsoft's Azure and Amazon's EC2, allow users to instantiate virtual machines (VMs) on demand and thus purchase precisely the capacity they require when they require it. In turn, the use of virtualization allows third-party cloud providers to maximize the utilization of their sunk capital costs by multiplexing many customer VMs across a shared physical infrastructure. However, in this paper, we show that this approach can also introduce new vulnerabilities. Using the Amazon EC2 service as a case study, we show that it is possible to map the internal cloud infrastructure, identify where a particular target VM is likely to reside, and then instantiate new VMs until one is placed co-resident with the target. We explore how such placement can then be used to mount cross-VM side-channel attacks to extract information from a target VM on the same machine.
TL;DR: This work presents Eucalyptus -- an open-source software framework for cloud computing that implements what is commonly referred to as Infrastructure as a Service (IaaS); systems that give users the ability to run and control entire virtual machine instances deployed across a variety physical resources.
Abstract: Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similar in spirit to existing grid and HPC resource management and programming systems. These types of systems offer a new programming target for scalable application developers and have gained popularity over the past few years. However, most cloud computing systems in operation today are proprietary, rely upon infrastructure that is invisible to the research community, or are not explicitly designed to be instrumented and modified by systems researchers. In this work, we present Eucalyptus -- an open-source software framework for cloud computing that implements what is commonly referred to as Infrastructure as a Service (IaaS); systems that give users the ability to run and control entire virtual machine instances deployed across a variety physical resources. We outline the basic principles of the Eucalyptus design, detail important operational aspects of the system, and discuss architectural trade-offs that we have made in order to allow Eucalyptus to be portable, modular and simple to use on infrastructure commonly found within academic settings. Finally, we provide evidence that Eucalyptus enables users familiar with existing Grid and HPC systems to explore new cloud computing functionality while maintaining access to existing, familiar application development software and Grid middle-ware.
TL;DR: The strengths, weaknesses, opportunities and threats for the industry, and some of the key issues facing governmental agencies who will be involved in the regulation of cloud computing.
Abstract: The evolution of cloud computing over the past few years is potentially one of the major advances in the history of computing. However, if cloud computing is to achieve its potential, there needs to be a clear understanding of the various issues involved, both from the perspectives of the providers and the consumers of the technology. While a lot of research is currently taking place in the technology itself, there is an equally urgent need for understanding the business-related issues surrounding cloud computing. In this article, we identify the strengths, weaknesses, opportunities and threats for the cloud computing industry. We then identify the various issues that will affect the different stakeholders of cloud computing. We also issue a set of recommendations for the practitioners who will provide and manage this technology. For IS researchers, we outline the different areas of research that need attention so that we are in a position to advice the industry in the years to come. Finally, we outline some of the key issues facing governmental agencies who, due to the unique nature of the technology, will have to become intimately involved in the regulation of cloud computing.
TL;DR: In this article, a distributed application is defined as an application made up of distinct components (e.g., virtual appliances, virtual machines, virtual interfaces, virtual volumes, virtual network connections, etc.) in separate runtime environments.
Abstract: Teachings of this application include a computing network that may include multiple different data centers and/or server grids which are deployed in different geographic locations. In at least one embodiment, at least some of the server grids may be operable to provide on-demand, grid and/or utility computing resources for hosting various types of distributed applications. In at least one embodiment, a distributed application may be characterized as an application made up of distinct components (e.g., virtual appliances, virtual machines, virtual interfaces, virtual volumes, virtual network connections, etc.) in separate runtime environments. In at least one embodiment, different ones of the distinct components of the distributed application may be hosted or deployed on different platforms (e.g., different servers) connected via a network. In some embodiments, a distributed application may be characterized as an application that runs on two or more networked computers.
TL;DR: This paper develops a comprehensive taxonomy for describing cloud computing architecture and uses this taxonomy to survey several existing cloud computing services developed by various projects world-wide, to identify similarities and differences of the architectural approaches of cloud computing.
Abstract: The computational world is becoming very large and complex. Cloud Computing has emerged as a popular computing model to support processing large volumetric data using clusters of commodity computers. According to J.Dean and S. Ghemawat [1], Google currently processes over 20 terabytes of raw web data. It's some fascinating, large-scale processing of data that makes your head spin and appreciate the years of distributed computing fine-tuning applied to today's large problems. The evolution of cloud computing can handle such massive data as per on demand service. Nowadays the computational world is opting for pay-for-use models and Hype and discussion aside, there remains no concrete definition of cloud computing. In this paper, we first develop a comprehensive taxonomy for describing cloud computing architecture. Then we use this taxonomy to survey several existing cloud computing services developed by various projects world-wide such as Google, force.com, Amazon. We use the taxonomy and survey results not only to identify similarities and differences of the architectural approaches of cloud computing, but also to identify areas requiring further research.
TL;DR: OpenNebula as mentioned in this paper is an open source, virtual infrastructure manager that deploys virtualized services on both a local pool of resources and external IaaS clouds, providing features not found in other cloud software or virtualization-based data center management software.
Abstract: One of the many definitions of "cloud" is that of an infrastructure-as-a-service (IaaS) system, in which IT infrastructure is deployed in a provider's data center as virtual machines. With IaaS clouds' growing popularity, tools and technologies are emerging that can transform an organization's existing infrastructure into a private or hybrid cloud. OpenNebula is an open source, virtual infrastructure manager that deploys virtualized services on both a local pool of resources and external IaaS clouds. Haizea, a resource lease manager, can act as a scheduling back end for OpenNebula, providing features not found in other cloud software or virtualization-based data center management software.
TL;DR: CloudSim as mentioned in this paper is an extensible simulation toolkit that enables modelling and simulation of cloud computing environments, and it supports the creation of one or more virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to suitable VMs.
Abstract: Cloud computing aims to power the next generation data centers and enables application service providers to lease data center capabilities for deploying applications depending on user QoS (Quality of Service) requirements. Cloud applications have different composition, configuration, and deployment requirements. Quantifying the performance of resource allocation policies and application scheduling algorithms at finer details in Cloud computing environments for different application and service models under varying load, energy performance (power consumption, heat dissipation), and system size is a challenging problem to tackle. To simplify this process, in this paper we propose CloudSim: an extensible simulation toolkit that enables modelling and simulation of Cloud computing environments. The CloudSim toolkit supports modelling and creation of one or more virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to suitable VMs. It also allows simulation of multiple Data Centers to enable a study on federation and associated policies for migration of VMs for reliability and automatic scaling of applications.
TL;DR: In this article, a distributed distributed computer system processes data having select content represented by one or more predetermined words, characters, etc. The system has a plurality of SC data stores in a server cloud for respective security designated data and scarcity designated data, each with respective access controls thereat.
Abstract: Distributed computer system processes data having select content (SC) represented by one or more predetermined words, characters, etc. The system has a plurality of SC data stores in a server cloud for respective security designated (Sec-D) data and scarcity designated (S-D) data, each with respective access controls thereat. The SC data stores are is operatively coupled on a network. An identification module for identifying SC data stores for the Sec-D data and S-D data in the server cloud. A processor activates an SC data stores in the server cloud thereby permitting access to the SC data stores and respective Sec-D data and S-D data based upon an application of one or more of said access controls thereat. The processor has a reconstruction module operating as a data process employing the respective access controls to combine one or more of the Sec-D data and S-D data.
TL;DR: The presentation “Cloud Computing: Benefits, risks and recommendations for information security” will cover some the most relevant information security implications of cloud computing from the technical, policy and legal perspective.
Abstract: The presentation “Cloud Computing: Benefits, risks and recommendations for information security” will cover some the most relevant information security implications of cloud computing from the technical, policy and legal perspective.
TL;DR: Wang et al. as discussed by the authors considered the task of allowing a third party auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic data stored in the cloud.
Abstract: Cloud Computing has been envisioned as the next-generation architecture of IT Enterprise. It moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. This unique paradigm brings about many new security challenges, which have not been well understood. This work studies the problem of ensuring the integrity of data storage in Cloud Computing. In particular, we consider the task of allowing a third party auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic data stored in the cloud. The introduction of TPA eliminates the involvement of client through the auditing of whether his data stored in the cloud is indeed intact, which can be important in achieving economies of scale for Cloud Computing. The support for data dynamics via the most general forms of data operation, such as block modification, insertion and deletion, is also a significant step toward practicality, since services in Cloud Computing are not limited to archive or backup data only. While prior works on ensuring remote data integrity often lacks the support of either public verifiability or dynamic data operations, this paper achieves both. We first identify the difficulties and potential security problems of direct extensions with fully dynamic data updates from prior works and then show how to construct an elegant verification scheme for seamless integration of these two salient features in our protocol design. In particular, to achieve efficient data dynamics, we improve the Proof of Retrievability model [1] by manipulating the classic Merkle Hash Tree (MHT) construction for block tag authentication. Extensive security and performance analysis show that the proposed scheme is highly efficient and provably secure.
TL;DR: This issue's articles tackle topics including architecture and management of cloud computing infrastructures, SaaS and IaaS applications, discovery of services and data in cloud computing infrastructure, and cross-platform interoperability.
Abstract: Cloud computing is a disruptive technology with profound implications not only for Internet services but also for the IT sector as a whole. Its emergence promises to streamline the on-demand provisioning of software, hardware, and data as a service, achieving economies of scale in IT solutions' deployment and operation. This issue's articles tackle topics including architecture and management of cloud computing infrastructures, SaaS and IaaS applications, discovery of services and data in cloud computing infrastructures, and cross-platform interoperability. Still, several outstanding issues exist, particularly related to SLAs, security and privacy, and power efficiency. Other open issues include ownership, data transfer bottlenecks, performance unpredictability, reliability, and software licensing issues. Finally, hosted applications' business models must show a clear pathway to monetizing cloud computing. Several companies have already built Internet consumer services such as search, social networking, Web email, and online commerce that use cloud computing infrastructure. Above all, cloud computing's still unknown "killer application" will determine many of the challenges and the solutions we must develop to make this technology work in practice.
TL;DR: To ensure that decisions are informed and appropriate for the cloud computing environment, the industry itself should establish coherent and effective policy and governance to identify and implement proper security methods.
Abstract: Today, we have the ability to utilize scalable, distributed computing environments within the confines of the Internet, a practice known as cloud computing. In this new world of computing, users are universally required to accept the underlying premise of trust. Within the cloud computing world, the virtual environment lets users access computing power that exceeds that contained within their own physical worlds. Typically, users will know neither the exact location of their data nor the other sources of the data collectively stored with theirs. The data you can find in a cloud ranges from public source, which has minimal security concerns, to private data containing highly sensitive information (such as social security numbers, medical records, or shipping manifests for hazardous material). Does using a cloud environment alleviate the business entities of their responsibility to ensure that proper security measures are in place for both their data and applications, or do they share joint responsibility with service providers? The answers to this and other questions lie within the realm of yet-to-be-written law. As with most technological advances, regulators are typically in a "catch-up" mode to identify policy, governance, and law. Cloud computing presents an extension of problems heretofore experienced with the Internet. To ensure that such decisions are informed and appropriate for the cloud computing environment, the industry itself should establish coherent and effective policy and governance to identify and implement proper security methods.
TL;DR: This paper focuses on technical security issues arising from the usage of Cloud services and especially by the underlying technologies used to build these cross-domain Internet-connected collaborations.
Abstract: The Cloud Computing concept offers dynamically scalable resources provisioned as a service over the Internet. Economic benefits are the main driver for the Cloud, since it promises the reduction of capital expenditure (CapEx) and operational expenditure (OpEx). In order for this to become reality, however, there are still some challenges to be solved. Amongst these are security and trust issues, since the user's data has to be released to the Cloud and thus leaves the protection-sphere of the data owner. Most of the discussions on this topics are mainly driven by arguments related to organizational means. This paper focuses on technical security issues arising from the usage of Cloud services and especially by the underlying technologies used to build these cross-domain Internet-connected collaborations.
TL;DR: Helping to overcome the lack of understanding currently preventing even faster adoption of cloud computing, this book arms readers with guidance essential to make smart, strategic decisions on cloud initiatives.
Abstract: Cloud Computing: Implementation, Management, and Security provides an understanding of what cloud computing really means, explores how disruptive it may become in the future, and examines its advantages and disadvantages It gives business executives the knowledge necessary to make informed, educated decisions regarding cloud initiatives The authors first discuss the evolution of computing from a historical perspective, focusing primarily on advances that led to the development of cloud computing They then survey some of the critical components that are necessary to make the cloud computing paradigm feasible They also present various standards based on the use and implementation issues surrounding cloud computing and describe the infrastructure management that is maintained by cloud computing service providers After addressing significant legal and philosophical issues, the book concludes with a hard look at successful cloud computing vendors Helping to overcome the lack of understanding currently preventing even faster adoption of cloud computing, this book arms readers with guidance essential to make smart, strategic decisions on cloud initiatives
TL;DR: Some security issues that have to be included in service level agreements (SLA) are put forward to help some of the enterprises to look forward in using the cloud services.
Abstract: In past three decades, the world of computation has changed from centralized (client-server not web-based) to distributed systems and now we are getting back to the virtual centralization (Cloud Computing). Location of data and processes makes the difference in the realm of computation. On one hand, an individual has full control on data and processes in his/her computer. On the other hand, we have the cloud computing wherein, the service and data maintenance is provided by some vendor which leaves the client/customer unaware of where the processes are running or where the data is stored. So, logically speaking, the client has no control over it. The cloud computing uses the internet as the communication media. When we look at the security of data in the cloud computing, the vendor has to provide some assurance in service level agreements (SLA) to convince the customer on security issues. Organizations use cloud computing as a service infrastructure, critically like to examine the security and confidentiality issues for their business critical insensitive applications. Yet, guaranteeing the security of corporate data in the "cloud" is difficult, if not impossible, as they provide different services like Software as a service (SaaS), Platform as a service (PaaS), and Infrastructure as a service (IaaS). Each service has their own security issues. So the SLA has to describe different levels of security and their complexity based on the services to make the customer understand the security policies that are being implemented. There has to be a standardized way to prepare the SLA irrespective to the providers. This can help some of the enterprises to look forward in using the cloud services. In this paper, we put forward some security issues that have to be included in SLA.
TL;DR: This book, written by recognized authorities in the tech security world, addresses issues that affect any organization preparing to use cloud computing as an option and provides the detailed information on cloud computing security that has been lacking, until now.
Abstract: This book, written by recognized authorities in the tech security world, addresses issues that affect any organization preparing to use cloud computing as an option. Cloud computing has emerged as a popular way for corporations to save money that would otherwise go into their IT infrastructure. However, along with the promise of cloud computing there has also been considerable skepticism about the type and extent of security and privacy that these services provide. Cloud Security and Privacy walks you through the steps you need to take to ensure your web applications are secure and your data is safe, and addresses regulatory issues such as audit and compliance. Ideal for IT personnel who need to deliver and maintain applications in the cloud, business managers looking to cut costs, service providers, and investors, this book provides the detailed information on cloud computing security that has been lacking, until now.
TL;DR: In this paper, the authors describe a method and system that processes data in a distributed computing system to survive an electromagnetic pulse (EMP) attack, where the data input or put through the computing system is processed to obtain the SC and other associated content.
Abstract: A method and system processes data in a distributed computing system to survive an electromagnetic pulse (EMP) attack. The computing system has proximal select content (SC) data stores and geographically distributed distal data stores, all with respective access controls. The data input or put through the computing system is processed to obtain the SC and other associated content. The process then extracts and stores such content in the proximal SC data stores and geographically distributed distal SC data stores. The system further processes data to geographically distribute the data with data processes including: copy, extract, archive, distribute, and a copy-extract-archive and distribute process with a sequential and supplemental data destruction process. In this manner, the data input is distributed or spread out over the geographically distributed distal SC data stores. The system and method permits reconstruction of the processed data only in the presence of a respective access control.
TL;DR: The privacy challenges that software engineers face when targeting the cloud as their production environment to offer services are assessed, and key design principles to address these are suggested.
Abstract: Privacy is an important issue for cloud computing, both in terms of legal compliance and user trust, and needs to be considered at every phase of design. In this paper the privacy challenges that software engineers face when targeting the cloud as their production environment to offer services are assessed, and key design principles to address these are suggested.
TL;DR: The author distinguishes between clouds that provide on-demand computing instances and those that provide in-service computing capacity, which are two different types of clouds.
Abstract: To understand clouds and cloud computing, we must first understand the two different types of clouds. The author distinguishes between clouds that provide on-demand computing instances and those that provide on-demand computing capacity. Cloud computing doesn't yet have a standard definition, but a good working description of it is to say that clouds, or clusters of distributed computers, provide on-demand resources and services over a network, usually the Internet, with the scale and reliability of a data center.
TL;DR: In order to support the maximum number of user and elastic service with the minimum resource, the Internet service provider invented the cloud computing as mentioned in this paper, and within a few years, emerging cloud computing has became the hottest technology.
Abstract: In order to support the maximum number of user and elastic service with the minimum resource, the Internet service provider invented the cloud computing. within a few years, emerging cloud computing has became the hottest technology. From the publication of core papers by Google since 2003 to the commercialization of Amazon EC2 in 2006, and to the service offering of AT&T Synaptic Hosting, the cloud computing has been evolved from internal IT system to public service, from cost-saving tools to revenue generator, and from ISP to telecom. This paper introduces the concept, history, pros and cons of cloud computing as well as the value chain and standardization effort.
TL;DR: This paper proposes CloudSim: a new generalized and extensible simulation framework that enables seamless modelling, simulation, and experimentation of emerging Cloud computing infrastructures and management services.
Abstract: Cloud computing focuses on delivery of reliable, secure, fault-tolerant, sustainable, and scalable infrastructures for hosting Internet-based application services. These applications have different composition, configuration, and deployment requirements. Quantifying the performance of scheduling and allocation policy on a Cloud infrastructure (hardware, software, services) for different application and service models under varying load, energy performance (power consumption, heat dissipation), and system size is an extremely challenging problem to tackle. To simplify this process, in this paper we propose CloudSim: a new generalized and extensible simulation framework that enables seamless modelling, simulation, and experimentation of emerging Cloud computing infrastructures and management services. The simulation framework has the following novel features: (i) support for modelling and instantiation of large scale Cloud computing infrastructure, including data centers on a single physical computing node and java virtual machine; (ii) a self-contained platform for modelling data centers, service brokers, scheduling, and allocations policies; (iii) availability of virtualization engine, which aids in creation and management of multiple, independent, and co-hosted virtualized services on a data center node; and (iv) flexibility to switch between space-shared and time-shared allocation of processing cores to virtualized services.
TL;DR: In this paper, the theoretical basis of the CALIPSO lidar cloud and aerosol discrimination (CAD) algorithm is reviewed and enhancements made to the version 2 algorithm that is used in the current data release (release 2).
Abstract: The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in April 2006 to provide global vertically resolved measurements of clouds and aerosols Correct discrimination between clouds and aerosols observed by the lidar aboard the CALIPSO satellite is critical for accurate retrievals of cloud and aerosol optical properties and the correct interpretation of measurements This paper reviews the theoretical basis of the CALIPSO lidar cloud and aerosol discrimination (CAD) algorithm, and describes the enhancements made to the version 2 algorithm that is used in the current data release (release 2) The paper also presents a preliminary assessment of the CAD performance based on one full day (12 August 2006) of expert manual classification and on one full month (July 2006) of the CALIOP 5-km cloud and aerosol layer products Overall, the CAD algorithm works well in most cases The 1-day manual verification suggests that the success rate is in the neighborh
TL;DR: There exist an increasing number of large companies that are offering cloud computing infrastructure products and services that do not entirely resemble the visions of these individual compo- firms.
Abstract: Recently the cloud computing paradigm has been receiving significant excitement and attention in the media and blogosphere To some, cloud computing seems to be little more than a marketing umbrella, encompassing topics such as distributed computing, grid computing, utility computing, and softwareas-a-service, that have already received significant research focus and commercial implementation Nonetheless, there exist an increasing number of large companies that are offering cloud computing infrastructure products and services that do not entirely resemble the visions of these individual compo-
TL;DR: SnowFlock provides sub-second VM cloning, scales to hundreds of workers, consumes few cloud I/O resources, and has negligible runtime overhead, and to evaluate SnowFlock, the implementation of the VM fork abstraction.
Abstract: Virtual Machine (VM) fork is a new cloud computing abstraction that instantaneously clones a VM into multiple replicas running on different hosts. All replicas share the same initial state, matching the intuitive semantics of stateful worker creation. VM fork thus enables the straightforward creation and efficient deployment of many tasks demanding swift instantiation of stateful workers in a cloud environment, e.g. excess load handling, opportunistic job placement, or parallel computing. Lack of instantaneous stateful cloning forces users of cloud computing into ad hoc practices to manage application state and cycle provisioning. We present SnowFlock, our implementation of the VM fork abstraction. To evaluate SnowFlock, we focus on the demanding scenario of services requiring on-the-fly creation of hundreds of parallel workers in order to solve computationally-intensive queries in seconds. These services are prominent in fields such as bioinformatics, finance, and rendering. SnowFlock provides sub-second VM cloning, scales to hundreds of workers, consumes few cloud I/O resources, and has negligible runtime overhead.
TL;DR: This paper first presents a business model framework for Clouds, subsequently reviews and classifies current Cloud offerings in the light of this framework, and discusses challenges that have to be mastered in order to make the Cloud vision come true and points to promising areas for future research.
Abstract: Lately, a new computing paradigm has emerged: “Cloud Computing”. It seems to be promoted as heavily as the “Grid” was a few years ago, causing broad discussions on the differences between Grid and Cloud Computing. The first contribution of this paper is thus a detailed discussion about the different characteristics of Grid Computing and Cloud Computing. This technical classification allows for a well-founded discussion of the business opportunities of the Cloud Computing paradigm. To this end, this paper first presents a business model framework for Clouds. It subsequently reviews and classifies current Cloud offerings in the light of this framework. Finally, this paper discusses challenges that have to be mastered in order to make the Cloud vision come true and points to promising areas for future research.
TL;DR: Although the performance of Hyrax is poor for CPU-bound tasks, it is shown to tolerate node-departure and offer reasonable performance in data sharing, and the scalability of hyrax is evaluated experimentally and compared to that of Hadoop.
Abstract: : Today's smartphones operate independently of each other, using only local computing, sensing, networking, and storage capabilities and functions provided by remote Internet services. It is generally difficult or expensive for one smartphone to share data and computing resources with another. Data is shared through centralized services, requiring expensive uploads and downloads that strain wireless data networks. Collaborative computing is only achieved using ad hoc approaches. Coordinating smartphone data and computing would allow mobile applications to utilize the capabilities of an entire smartphone cloud while avoiding global network bottlenecks. In many cases, processing mobile data in-place and transferring it directly between smartphones would be more efficient and less susceptible to network limitations than off loading data and processing to remote servers. We have developed Hyrax, a platform derived from Hadoop that supports cloud computing on Android smartphones. Hyrax allows client applications to conveniently utilize data and execute computing jobs on networks of smartphones and heterogeneous networks of phones and servers. By scaling with the number of devices and tolerating node departure, Hyrax allows applications to use distributed resources abstractly, oblivious to the physical nature of the cloud. The design and implementation of Hyrax is described, including experiences in porting Hadoop to the Android platform and the design of mobile specific customizations. The scalability of Hyrax is evaluated experimentally and compared to that of Hadoop. Although the performance of Hyrax is poor for CPU-bound tasks, it is shown to tolerate node-departure and offer reasonable performance in data sharing. A distributed multimedia search and sharing application is implemented to qualitatively evaluate Hyrax from an application development perspective.
TL;DR: This paper proposes a mechanism for managing SLAs in a cloud computing environment using the Web Service Level Agreement framework, developed for SLA monitoring and SLA enforcement in a Service Oriented Architecture (SOA).
Abstract: Cloud computing that provides cheap and pay-as-you-go computing resources is rapidly gaining momentum as an alternative to traditional IT Infrastructure. As more and more consumers delegate their tasks to cloud providers, Service Level Agreements(SLA) between consumers and providers emerge as a key aspect. Due to the dynamic nature of the cloud, continuous monitoring on Quality of Service (QoS) attributes is necessary to enforce SLAs. Also numerous other factors such as trust (on the cloud provider) come into consideration, particularly for enterprise customers that may outsource its critical data. This complex nature of the cloud landscape warrants a sophisticated means of managing SLAs. This paper proposes a mechanism for managing SLAs in a cloud computing environment using the Web Service Level Agreement(WSLA) framework, developed for SLA monitoring and SLA enforcement in a Service Oriented Architecture (SOA). We use the third party support feature of WSLA to delegate monitoring and enforcement tasks to other entities in order to solve the trust issues. We also present a real world use case to validate our proposal.