With the rapid development of processing and storage technologies and the success of the Internet, computing resources have become cheaper, more powerful and more ubiquitously available than ever before. This technological trend has enabled the realization of a new computing model called cloudcomputing, in which resources (e.g., CPU and storage) are provided as general utilities that can be leased and released by users through the Internet in an on-demand fashion. In this paper we provide a introductory information about the cloudcomputing and the related technologies such as grid computing, utility computing, Autonomic computing .Classification about the security issues and the importance of the security to the cloud are also highlighted- which include the following section under discussion Traditional security ,Availability ,Third-party data control . Along with this we have focused on the research challenges and provided information about them , which we hope will give the directions for the further research work in the cloudcomputing
CloudComputing, envisioned as the next generation architecture of IT Enterprise is a talk of the town these days. The way cloud has been dominating the IT market, a major shift towards the cloud can be expected in the coming years. Cloudcomputing offers real benefits to companies seeking a competitive edge in today’s economy. Many more providers are moving into this area, and the competition is driving prices even lower. Attractive pricing, the ability to free up staff for other duties, and the ability to pay for ―as needed‖ services will continue to drive more businesses to consider cloudcomputing. Mobile cloudcomputing is expected to emerge as one of the biggest market for cloud service providers and cloud developers. Although Cloudcomputing can be seen as a new phenomenon which is set to revolutionize the way we use the Internet, there is much to be cautious about. There are many new technologies emerging at a rapid rate, each with technological advancements and with the potential of making human’s lives easier. However, one must be very careful to understand the security risks and challenges posed in utilizing these technologies. Cloudcomputing is no exception. Cloud service providers need to inform their customers on the level of security that they provide on their cloud. T his research effort presents an overview of CloudComputing, building blocks of CloudComputing which includes different models of cloudcomputing, overview of CloudComputing architecture and CloudComputing entities. Furthermore, research challenges which are currently faced in the Cloudcomputing were also highlighted. Cloudcomputing has the potential to become a frontrunner in promoting a secure, virtual and economically viable IT solution in the future. As the development of cloudcomputing technology is still at an early stage, this research effort will provide a better understanding of the design challenges of cloudcomputing, and pave the way for further research in this area.
In cloudcomputing there are certain distributed resources that requires to be managed across a heterogeneous computing environment. All these resources consumes large amount of energy as they appears to be “always on” to the end users point of view. The techniques by which all the distribution of resources is done are highly inefficient in terms of energy usage. So while studying the Green Cloudcomputing we analyze the whole energy consumption of the computing resources, this would be based on the types of services and conditions to facilitate green cloudcomputing to save overall energy consumption in the related information communication systems. Now days when everything is mobile dependent we may explore green mobile communication under Green CloudComputing. So under green cloudcomputing we certainly explore and research the use of virtualization in system and network resources in order to minimize energy usage while still fulfilling the service requirements and operational constraints of a cloud. Certain work has been done towards green cloudcomputing in context of the major causes of energy inefficiency in data centers is the idle power wasted when servers run at low utilization. The study made certainly focus on how to keep servers run at low utilization by workload consolidation. Moreover it is been claimed that the request arrival rate at servers fluctuate with time. So, in regard with these mechanisms has been developed to predict the future arrival rates from history and estimate the optimal number of servers for a class of arrival rates. Various literatures provide the solutions for dimensions such as: energy-efficient hardware, energy-aware scheduling, power-minimization in server cluster and power-minimization in mobile as well as wired networks. Feng- Seng Chu  focus greatly on the overall impact on energy consumption brought by cloudcomputing and find out when it is green.
Abstract: Cloudcomputing is a set of IT services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. Usually CloudComputing services are delivered by a third party provider who owns the infrastructure. CloudComputing holds the potential to eliminate the requirements for setting up of high-cost computing infrastructure for IT-based solutions and services that the industry uses. It promises to provide a flexible IT architecture, accessible through internet from lightweight portable devices. This would allow multi-fold increase in the capacity and capabilities of the existing and new software. This new economic model for computing has found fertile ground and is attracting massive global investment. Many industries, such as banking, healthcare and education are moving towards the cloud due to the efficiency of services provided by the pay-per-use pattern based on the resources such as processing power used, transactions carried out, bandwidth consumed, data transferred, or storage space occupied etc. In a cloudcomputing environment, the entire data resides over a set of networked resources, enabling the data to be accessed through virtual machines. Despite the potential gains achieved from the cloudcomputing, the organizations are slow in accepting it due to security issues and challenges associated with it. Security is one of the major issues which hamper the growth of cloud. There are various research challenges also there for adopting cloudcomputing such as well managed service level agreement (SLA), privacy, interoperability and reliability. This research paper presents what cloudcomputing is, the various cloud models and the overview of the cloudcomputing architecture. This research paper also analyzes the key research challenges present in cloudcomputing and offers best practices to service providers as well as enterprises hoping to leverage cloud service to improve their bottom line in this severe economic climate.
be loaded on “bare-metal”, or intoan operating system/application virtual environment of choice. When a user has the right tocreate an image, that user usually starts with a “NoApp” or a base-line image (e.g., Win XP or Linux) without any except most basic applications that come with the operating system, and extends it with his/her applications. Similarly, when an author constructs composite images (aggregates of two or more images we call environments that are loaded synchronously), theuser extends service capabilities of VCL. Anauthor can program an image for sole use onone or more hardware units, if that is desired, or for sharing of the resources with other users.Scalability is achieved through a combination of multi-user service hosting, application virtualization, and both time and CPU multiplexing and load balancing. Authors must be component (base-line image and applications) experts and must have good understanding of the needs of the user categories above them in the Figure2 triangle. Some of the functionalities acloud framework must provide for them are image creation tools, image and service management tools, service brokers, service registration and discovery tools, security tools, provenance collection tools, cloud component aggregations tools, resource mapping tools, license management tools, fault- tolerance and fail-over mechanisms, and so on . It is important to note that the authors, for themost part, will not be cloud framework experts, and thus the authoring tools and interfaces mustbe appliances: easy-to-learn and easy-to-useand they must allow the authors to concentrateon the “image” and service development rather than struggle with the cloud infrastructure intricacies.2.3.3. Service Composition Similarly, services integration and provisioning experts should be able to focus on creationof composite and orchestrated solutions neededfor an end-user. They sample and combine existing services and images, customize them, updateexisting services and images, and developnew composites. They may also be the front for
Another research and engineering challenge is security. For end-users to feel comfortable with a “cloud” solution that holds their software, data and processes, there should exist considerable assurances that services are highly reliable and available, as well as secure and safe, and that privacy is protected. This raises the issues of end-to-end service isolation through VPN and SSH tunnels and VLANs, and the guarantees one may have that the data and the images keep their integrity in the “cloud”. Some of the work being done by the NC State Secure Open Sys- tems Initiative [ 37 ] involves watermarking of the images and data to ensure verifiable integrity. While NC State experience with VCL is excel- lent and our security solution has been holding up beautifully over the last four years, security tends to be a moving target and a lot of chal- lenges remain.
SDN has two main advantages over traditional networks in regards to detection and response to attacks: (1) the (logically) centralized management model of SDN allows administrators to quickly isolate or block attack traffic patterns without the need to access and reconfigure several heterogeneous hardware (switches, routers, firewalls, and intrusion detection systems); (2) detection of attacks can be made a distributed task among switches (SDN controllers can define rules on switches to generate events when flows considered malicious are detected), rather than depending on expensive intrusion detection systems. SDN can also be used to control how traffic is directed to network monitoring devices (e.g., intrusion detection systems) as proposed in . Quick response is particularly important in highly dynamic cloud environments. Traditional intrusion detection systems (IDS) mainly focus on detecting suspicious activities and are limited to simple actions such as disabling a switch port or notifying (sending email) to a system administrator. SDN opens the possibility of taking complex actions such as changing the path of suspicious activities in order to isolate them from known trusted communication. Research will focus on how to recast existing IDS mechanisms and algorithms in SDN contexts, and development of new algorithms to take full advantage of multiple points of action. For example, as each switch can be used to detect and act on attacks,  has shown the improvement of different traffic anomaly detection algorithms (Threshold Random Walk with Credit Based rate limiting, Maximum Entropy, network traffic anomaly detection based on packet bytes, and rate limiting) using Openflow and NOX by placing detectors closer to the edge of the network (home or small business networks instead of the ISP) while maintaining the line rate performance.
The resource allocation in cloud environment is an important and challenging research topic. Verma et al.  formulate the problem of dynamic placement of applications in virtualized heterogeneous systems as a continuous optimization: The placement of VMs at each time frame is optimized to minimize resource consumption under certain perfor- mance requirements. Chaisiri et al.  study the trade-off between the advance reservation and the on-demand resource allocation, and propose a VM placement algorithm based on stochastic integer programming. The proposed algorithm minimizes the total cost of resource provision in infrastructure as a service (IaaS) cloud. Wang et al.  present a virtual appliance-based automatic resource provisioning framework for large vir- tualized data centers. Their framework can dynamically allocate resources to applications by adding or removing VMs on physical servers. Verma et al. , Chaisiri et al. , and Wang et al.  study cloud resource allocation from VM placement perspective. Bacigalupo et al.  quanti- tatively compare the effectiveness of different techniques on response time prediction. They study different cloud services with different priorities, including urgent cloud services that demand cloud resource at short notice and dynamic enterprise systems that need to adapt to frequent changes in the workload. Based on these cloud services, the layered queuing network and historical performance model are quantitatively compared in terms of prediction accuracy. Song et al.  present a resource allocation approach according to application priorities in multiapplication virtualized cluster. This approach requires machine learning to obtain the utility functions for applications and defines the application priorities in advance. Lin and Qi  develop a self-organizing model to manage cloud resources in the absence of centralized management control. Nan et al.  present opti- mal cloud resource allocation in priority service scheme to minimize the resource cost. Appleby et al.  present a prototype of infrastructure, which can dynamically allocate cloud resources for an e-business comput- ing utility. Xu et al.  propose a two-level resource management system with local controllers at the VM level and a global controller at the server level. However, they focus only on resource allocation among VMs within a cloud server [19,20].
The research team synthesized liquid-like pastes of the thermoelectric par- ticles needed to transform body heat into energy, and then screen printed the paste onto a glass fabric with a mesh pattern. This process allowed them to arrange hundreds of these thermoelectric particles onto one area of the band. Although thermoelectric generators are not new technologies, this par- ticular solution opens up possibilities for wearable devices. Although the research is in its early stages, KAIST scientists see the potential for a fu- ture where wearable devices will only need a small battery, or no battery at all, and depend almost entirely on a thermoelectric generator. If tech companies can eventually use this technology to manufacture wearable devices that don’t need to be charged often or at all, such devices will likely be more appealing to consumers.
The past decades have witnessed the success of centralized comput- ing infrastructures in many application domains. Then, the emergence of the Internet brought numerous users of remote applications based on the technologies of distributed computing. Research in distributed computing gave birth to the development of grid computing. Though grid is based on distributed computing, the conceptual basis for grid is somewhat different. Computing with grid enabled researchers to do computationally intensive tasks by using limited infrastructure that was available with them and with the support of high processing power that could be provided by any third party, and thus allowing the researchers to use grid computing, which was one of the first attempts to provide computing resources to users on payment basis. This technology indeed became popular and is being used even now. An associated problem with grid technology was that it could only be used by a certain group of people and it was not open to the public. Cloud com- puting in simple terms is further extension and variation of grid computing, in which a market-oriented aspect is added. Though there are several other important technical differences, this is one of the major differences between grid and cloud. Thus came cloudcomputing, which is now being used as a public utility computing software and is accessible by almost every person through the Internet. Apart from this, there are several other properties that make cloud popular and unique. In cloud, the resources are metered, and a user pays according to the usage. Cloud can also support a continuously varying user demands without affecting the performance, and it is always available for use without any restrictions. The users can access cloud from any device, thus reaching a wider range of people.
The evolution of networking technology to support large-scale data centers is most evident at the access layer due to rapid increase of number of servers in a data center. Some research work (Greenberg, Hamilton, Maltz, & Patel, 2009; Kim, Caesar, & Rexford, 2008) calls for a large Layer-2 domain with a ﬂatter data center network architecture (2 layers vs. 3 layers). While this approach may ﬁt a homoge- nous, single purpose data center environment, a more prevalent approach is based on the concept of switch virtualization which allows the function of the logical Layer-2 access layer to span across multiple physical devices. There are several architectural variations in implementing switch virtualization at the access layer. They include Virtual Blade Switch (VBS), Fabric Extender, and Virtual Ethernet Switch technologies. The VBS approach allows multiple physical blade switches to share a common management and control plane by appearing as a single switching node (Cisco Systems, 2009d). The Fabric Extender approach allows a high-density, high-throughput, multi-interface access switch to work in conjunction with a set of fabric extenders serving as “remote I/O modules” extending the internal fabric of the access switches to a larger number of low-throughput server access ports (Cisco Systems, 2008). The Virtual Ethernet Switch is typically software based access switch integrated inside a hypervisor at the server side. These switch vir- tualization technologies allow the data center to support multi-tenant cloud services and provide ﬂexible conﬁgurations to scale up and down the deployment capacities according to the level of workloads (Cisco Systems, 2009a, 2009c).
This book comprehensively debates on the emergence of mobile cloudcomputing from cloudcomputing models. Various technological and architectural advancements in mobile and cloudcomputing have been reported. It has meticulously explored the design and architecture of computational offloading solutions in cloud and mobile cloudcomputing domains to enrich mobile user experience. Furthermore, to optimize mobile power consumption, existing solutions and policies toward green mobile computing, green cloudcomputing, green mobile networking, and green mobile cloudcomputing are briefly discussed. The book also presents numerous cloud and mobile resource allo- cation and management schemes to efficiently manage existing resources (hardware and software). Recently, integrated networks (e.g., WSN, VANET, MANET) have sig- nificantly helped mobile users to enjoy a suite of services. The book discusses existing architecture, opportunities, and challenges, while integrating mobile cloud comput- ing with existing network technologies such as sensor and vehicular networks. It also briefly expounds on various security and privacy concerns, such as application security, authentication security, data security, and intrusion detection, in the mobile cloud com- puting domain. The business aspects of mobile cloudcomputing models in terms of resource pricing models, cooperation models, and revenue sharing among cloud pro- viders are also presented in the book. To highlight the standings of mobile cloud comput- ing, various well-known, real-world applications supported by mobile cloudcomputing models are discussed. For example, the demands and issues while deploying resource- intensive applications, including face recognition, route tracking, traffic management, and mobile learning, are discussed. This book concludes with various future research directions in the mobile cloudcomputing domain to improve the strength of mobile cloudcomputing and to enrich mobile user experience.
Abstract: On demand or on pay per use of resource such as: network, storage and server these all facilities are provided by cloudcomputing through internet is called cloudcomputing. Although, cloudcomputing is facilitating the Information Technology industry, the research and development in this arena is yet to be satisfactory. Our contribution in this paper is an advanced survey focusing on cloudcomputing concept and most advanced research issues. This paper provides a better understanding of the cloudcomputing and identifies important research issues in this burgeoning area of computer science. Section 1 contains the introduction, in the section 2, we provide an overview of cloudcomputing, section 3 contains the security architecture and section 4 will focus on the research issues and security issue. We conclude the paper on section 5 along with references.
As cloudcomputing is comprised of various hardcore technologies like networking, virtualization, software development, it has a vivid scope of research in different directions. Image (OS kernel/Virtual Appliance) Optimization , Fault tolerance , Multitenancy , Cloud Migration , Virtualization , Security etc. But security concerns are the most prioritized one for end user to feel comfortable with cloud for software, data and processes, he uses in terms of its privacy, integrity etc .
Cloudcomputing has opened new options of collaboration between research teams in the field of high performance computing and numerical research. Running computational workloads in virtual machines became common in recent years. However, the use of computing containers provides many additional advantages besides just proving new possible runtime choice. One of the most important (and often underappreciated) is an option to improve the reproducibility of research results based on complex mathematical modeling. This paper provides an overview of architecture based on computing containers and continuous integration tools we used to achieve reproducible numerical results.
Susan Sutherland has post graduate qualifications in IS., business administration and education. She has worked in large and complex enterprises both public and private. Her experience includes operational and at strategic levels and has worked on the mainframe, midrange and desktop applications systems; and infrastructure and networks. Her infrastructure and network experience includes implementations of X.500, X400 and X435 standards. She has also consulted in migrating applications to Web 2.0. She was part of a team that implemented an internet security gateway service for a large government department. She had pioneered the deployment of the internet in the Australian government. She is interested in the deployment of bleeding edge technologies and their migration and integration into mainstream computing. Hence her motivation to undertake this research study in cloudcomputing interoperability is a natural progression of her previous work.
Cloudcomputing is the development of distributedcomputing, parallel computing, grid computing and virtualization technologies which define the scenario of a new era.Cloud computing is the latest effort in delivering computing resources as a service. It represents a shift away from computing as a product that is purchased, to computing as a service that is delivered to consumers over the internet from large-scale data centres – or “clouds”. Whilst cloudcomputing is gaining growing popularity in the IT industry, academia appeared to be lagging behind the rapid developments in this field. Cloudcomputing is an emerging model of business computing. In this paper, we explore the concept of cloud architecture and aims to provide an overview of the swiftly developing advances in the technical foundations of cloudcomputing and their research efforts. Structured along the technical aspects on the cloud agenda and also compares cloudcomputing with grid computing. We also address the characteristics and applications of several popular cloudcomputing platforms. In this paper, we aim to pinpoint the challenges and issues of cloudcomputing. We identified several challenges from the cloudcomputing adoption perspective and we also highlighted the cloud interoperability issue that deserves substantial further research and development. However, security and privacy issues present a strong barrier for users to adapt into cloudcomputing systems.
Mobile cloudcomputing aims to augment the resource-constraint mobile devices, but currently it is like a baby that requires attention. The ABI research believes more than 240 million business will use services provided by cloud service providers through mobile devices by 2015. Mobile cloudcomputing is a growing technology that includes both cloudcomputing and mobile computing benefits. Also it is highly applicable for mobile devices. This paper has given an extensive and survey of mobile cloudcomputing technology including its definitions, architecture, motivation for developing, advantages, challenges and future research directions. For better understanding of mobile cloudcomputing before describing it, cloudcomputing is described.
The main aim of this work is to present a difference between Grid Computing and CloudComputing. Cloudcomputing has many advantages over Grid Computing, clouds will not replace grids, as grids have not replaced capability HPC, over the last 10 years as some have predicated. All three technologies have their place, what we will see over the next couple of years is that these different computing nodes will more and more grow together with the WWW and the Internet, until all these resources become one global infrastructure for information, Knowledge, computation and communication, the WWW. We think it is more likely that grids will be re-branded or merge into cloudcomputing, Grid Computing helped create a certain technology reality which made clouds possible. And when it comes to IaaS (infrastructure as s service), We think in five years something like 80 to 90 percent of the computation are doing could be cloud-based. In a word, the concept of CloudComputing is becoming more and more popular. Now, CloudComputing is in the beginning stage. All kinds of companies are providing all kinds of Cloudcomputing service, from software application to net storage and mail filter. We believe cloudcomputing will become main technology in our information life. Cloud has owned all conditions. Now the dream of Grid Computing will be realized by CloudComputing. It will be a great event in the IT history .
Nearly equal in significance level are the rest of the challenges cited by channel firms making the move to cloud, with most of those hurdles centered on financial decisions. Initial start up costs, for example, can be minimal or quite large, depending on whether or not they involved building a data center to provide cloud services. Interestingly, the largest channel firms cited this as a major challenge, though they are most likely to have the deeper pockets needed to outfit a new data center if they don’t already have one in existence. Meantime, cash flow and other financial considerations ranked highest among channel firms (63%) involved in all four types of cloud business models outlined in this study. This suggests that the level of commitment they have made to cloud has complicated financial fundamentals; one example would be the effects of a decreased reliance on legacy streams of revenue, which in the short-‐term could create cash flow concerns as they ramp cloud sales.