Cloud Computing By P.Mahesh 131309862010.

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Presentation transcript:

Cloud Computing By P.Mahesh 131309862010

What is Cloud Computing? Cloud computing is a metaphor used by Technology or IT Services companies for the delivery of computing requirements as a service to a homogeneous community of end-recipients. The term cloud theoretically signifies abstraction of technology, resources and its location that are very vital in building integrated computing infrastructure(including networks, systems & applications). 

Characteristics Device and location independence enable users to access systems using a web browser regardless of their location or what device they are using (e.g., PC, mobile phone). Virtualization  technology allows servers and storage devices to be shared and utilization be increased. Applications can be easily migrated from one physical server to another.

Reliability  is improved if multiple redundant sites are used, which makes well-designed cloud computing suitable for business continuity and disaster recovery. Scalability  and Elasticity via dynamic ("on- demand") provisioning of resources on a fine- grained, self-service basis near real-time, without users having to engineer for peak loads.

Security : could improve due to centralization of data, increased security-focused resources, Security is often as good as or better than other traditional systems, in part because providers are able to devote resources to solving security issues that many customers cannot afford. However, the complexity of security is greatly increased when data is distributed over a wider area or greater number of devices and in multi-tenant systems that are being shared by unrelated users.

Performance is monitored, and consistent and loosely coupled architectures are constructed using web services as the system interface. Maintenance of cloud computing applications is easier, because they do not need to be installed on each user's computer and can be accessed from different places.

Service Models Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS)

Infrastructure as a Service (IaaS) In this most basic cloud service model, cloud providers offer computers – as physical or more often as virtual machines.  IaaS providers supply these resources on demand from their large pools installed in data centers.   Local area networks including IP addresses are part of the offer.

Iaas To deploy their applications, cloud users then install operating system images on the machines as well as their application software. In this model, it is the cloud user who is responsible for patching and maintaining the operating systems and application software. Cloud providers typically bill IaaS services on a utility computing basis, that is, cost will reflect the amount of resources allocated and consumed.

Software as a Service (SaaS) In this model, cloud providers install and operate application software in the cloud and cloud users access the software from cloud clients. The cloud users do not manage the cloud infrastructure and platform on which the application is running. This eliminates the need to install and run the application on the cloud user's own computers simplifying maintenance and support. What makes a cloud application different from other applications is its elasticity

Platform as a Service (PaaS) In the PaaS model, cloud providers deliver a computing platform and/or solution stack typically including operating system, programming language execution environment, database, and web server. Application developers can develop and run their software solutions on a cloud platform without the cost and complexity of buying and managing the underlying hardware and software layers.

Cloud Architecture

Linear programming Linear programming is an algorithmic and computational tool which captures the first order effects of various system parameters that should be optimized, and is essential to engineering optimization. It has been widely used in various engineering disciplines that analyze and optimize real-world systems, such as packet routing, flow control, power management of data centers, etc.

Architecture of linear programmig

Design Goals To enable secure and practical outsourcing of LP under the aforementioned model, our mechanism design should achieve the following security and performance guarantees. Correctness: Any cloud server that faithfully follows the mechanism must produce an output that can be decrypted and verified successfully by the customer. Soundness: No cloud server can generate an incorrect output that can be decrypted and verified successfully by the customer with non-negligible probability.

Input/output privacy: No sensitive information from the customer’s private data can be derived by the cloud server during performing the LP computation. Efficiency: The local computations done by customer should be substantially less than solving the original LP on his own. The computation burden on the cloud server should be within the comparable time complexity of existing practical algorithms solving LP problems.

THE PROPOSED SCHEMES Mechanism Design Framework We propose to apply problem transformation for mechanism design. The general framework is adopted from a generic approach , while our instantiation is completely different and novel. In this framework, the process on cloud server can be represented by algorithm ProofGen and the process on customer can be organized into three algorithms (KeyGen,ProbEnc, ResultDec).

KeyGen(1k) → {K}. This is a randomized key generation algorithm which takes a system security parameter k, and returns a secret key K that is used later by customerto encrypt the target LP problem. ProbEnc(K,ǿ) → {ǿk}. This algorithm encrypts the input tuple into K with the secret key K. According to problem transformation, the encrypted input K has the same form as , and thus defines the problem to be solved in the cloud.

ProofGen(K) → {(y,Γ)}. This algorithm augments a generic solver that solves the problem K to produce both the output y and a proof Γ. The output y later decrypts to x, and Γ is used later by the customer to verify the correctness of y or x. ResultDec(K, y, Γ) → {x,⊥}. This algorithm may choose to verify either y or x via the proof Γ. In any case,a correct output x is produced by decrypting y using the secret K. The algorithm outputs ⊥ when the validation fails, indicating the cloud server was not performing the computation faithfully.

Thank You