Ieee projects 2012 2013 - Cloud Computing
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Ieee projects 2012 2013 - Cloud Computing Ieee projects 2012 2013 - Cloud Computing Document Transcript

  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com IEEE FINAL YEAR PROJECTS 2012 – 2013 Cloud ComputingCorporate Office: Madurai 227-230, Church road, Anna nagar, Madurai – 625 020. 0452 – 4390702, 4392702, +9199447933980 Email: info@elysiumtechnologies.com, elysiumtechnologies@gmail.com Website: www.elysiumtechnologies.comBranch Office: Trichy 15, III Floor, SI Towers, Melapudur main road, Trichy – 620 001. 0431 – 4002234, +919790464324. Email: trichy@elysiumtechnologies.com, elysium.trichy@gmail.com. Website: www.elysiumtechnologies.comBranch Office: Coimbatore 577/4, DB Road, RS Puram, Opp to KFC, Coimbatore – 641 002. +919677751577 Website: Elysiumtechnologies.com, Email: info@elysiumtechnologies.comBranch Office: Kollam Surya Complex, Vendor junction, Kollam – 691 010, Kerala. 0474 – 2723622, +919446505482. Email: kerala@elysiumtechnologies.com. Website: www.elysiumtechnologies.comBranch Office: Cochin 4th Floor, Anjali Complex, near south over bridge, Valanjambalam, Cochin – 682 016, Kerala. 0484 – 6006002, +917736004002. Email: kerala@elysiumtechnologies.com, Website: www.elysiumtechnologies.com IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com CLOUD COMPUTING 2012 – 2013EGC A Cloud-Based Scheme for Protecting Source-Location Privacy against Hotspot-3201 Locating Attack in Wireless Sensor Networks A In wireless sensor networks, adversaries can make use of traffic information to locate the monitored objects, e.g., to hunt endangered animals or kill soldiers. In this paper, we first define a hotspot phenomenon that causes an obvious inconsistency in the network traffic pattern due to a large volume of packets originating from a small area. Second, we develop a realistic adversary model, assuming that the adver-sary can monitor the network traffic in multiple areas, rather than the entire network or only one area. Using this model, we introduce a novel attack called Hotspot-Locating where the adversary uses traffic analysis techniques to locate hotspots. Finally, we propose a cloud-based scheme for efficiently pro-tecting source nodes location privacy against Hotspot-Locating attack by creating a cloud with an irregular shape of fake traffic, to counteract the inconsistency in the traffic pat-tern and camouflage the source node in the nodes forming the cloud. To reduce the energy cost, clouds are active only during data transmission and the intersection of clouds creates a larger merged cloud, to reduce the number of fake packets and also boost privacy preservation. Simulation and analyti-cal results demonstrate that our scheme can provide stronger privacy protection than routing-based schemes and requires much less energy than global-adversary-based schemes.EGC3202 A Dataflow-Based Scientific Workflow Composition Framework Scientific workflow has recently become an enabling technology to automate and speed up the scientific discovery process. Although several scientific workflow management systems (SWFMSs) have been developed, a formal scientific workflow composition model in which workflow constructs are fully compositional one with another is still missing. In this paper, we propose a dataflow-based scientific workflow composition framework consisting of (1) a dataflow-based scientific workflow model that separates the declaration of the workflow interface from the definition of its functional body; (2) a set of workflow constructs, including Map, Reduce, Tree, Loop, Conditional, and Curry, which are fully compositional one with another; (3) a dataflow-based exception handling approach to support hierarchical exception propagation and user-defined exception handling. Our workflow composition framework is unique in that workflows are the only operands for composition; in this way, our approach elegantly solves the two-world problem in existing composition frameworks, in which composition needs to deal with both the world of tasks and the world of workflows. The proposed framework is implemented and several case studies are conducted to validate our techniques. IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com EGC A Secure Erasure Code-Based Cloud Storage System with Secure Data Forwarding 3203 A cloud storage system, consisting of a collection of storage servers, provides long-term storage services over the Internet. Storing data in a third partys cloud system causes serious concern over data confidentiality. General encryption schemes protect data confidentiality, but also limit the functionality of the storage system because a few operations are supported over encrypted data. Constructing a secure storage system that supports multiple functions is challenging when the storage system is distributed and has no central authority. We propose a threshold proxy re- encryption scheme and integrate it with a decentralized erasure code such that a secure distributed storage system is formulated. The distributed storage system not only supports secure and robust data storage and retrieval, but also lets a user forward his data in the storage servers to another user without retrieving the data back. The main technical contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as forwarding operations over encoded and encrypted messages. Our method fully integrates encrypting, encoding, and forwarding. We analyze and suggest suitable parameters for the number of copies of a message dispatched to storage servers and the number of storage servers queried by a key server. These parameters allow more flexible adjustment between the number of storage servers and robustness.EGC A Stable Network-Aware VM Placement for Cloud Systems3204 Virtual Machine (VM) placement has to carefully consider the aggregated resource consumption of co-located VMs in order to obey service level agreements at lower possible cost. In this paper, we focus on satisfying the traffic demands of the VMs in addition to CPU and memory requirements. This is a much more complex problem both due to its quadratic nature (being the communication between a pair of VMs) and since it involves many factors beyond the physical host, like the network topologies and the routing scheme. Moreover, traffic patterns may vary over time and predicting the resulting effect on the actual available bandwidth between hosts within the data center is extremely difficult. We address this problem by trying to allocate a placement that not only satisfies the predicted communication demand but is also resilient to demand time-variations. This gives rise to a new optimization problem that we call the Min Cut Ratio-aware VM Placement (MCRVMP). The general MCRVMP problem is NP-Hard, hence, we introduce several heuristics to solve it in reasonable time. We present extensive experimental results, associated with both placement computation and run-time performance under time-varying traffic demands, to show that our heuristics provide good results (compared to the optimal solution) for medium size data centers.EGC A Time-Series Pattern Based Noise Generation Strategy for Privacy Protection in Cloud3205 Computing IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com Cloud computing promises an open environment where customers can deploy IT services in a pay-as-you-go fashion while saving huge capital investment in their own IT infrastructure. Due to the openness, various malicious service providers may exist. Such service providers may record service information in a service process from a customer and then collectively deduce the customers private information. Therefore, from the perspective of cloud computing security, there is a need to take special actions to protect privacy at client sides. Noise obfuscation is an effective approach in this regard by utilising noise data. For instance, it generates and injects noise service requests into real customer service requests so that service providers would not be able to distinguish which requests are real ones if their occurrence probabilities are about the same. However, existing typical noise generation strategies mainly focus on the entire service usage period to achieve about the same final occurrence probabilities of service requests. In fact, such probabilities can fluctuate in a time interval such as three months and may significantly differ than other time intervals. In this case, service providers may still be able to deduce the customers privacy from a specific time interval although unlikely from the overall period. That is to say, the existing typical noise generation strategies could fail to protect customers privacy for local time intervals. To address this problem, we develop a novel time-series pattern based noise generation strategy. Firstly, we analyse previous probability fluctuations and propose a group of time- series patterns for predicting future fluctuated probabilities. Then, based on these patterns, we present our strategy by forecasting future occurrence probabilities of real service requests and generating noise requests to reach about the same final probabilities in the next time interval. The simulation evaluation demonstrates that our strateg- can cope with these fluctuations to significantly improve the effectiveness of customers privacy protection.EGC An Autonomous Reliability-Aware Negotiation Strategy for Cloud Computing3206 Environments Cloud computing paradigm allows subscription-based access to computing and storages services over the Internet. Since with advances of Cloud technology, operations such as discovery, scaling, and monitoring are accomplished automatically, negotiation between Cloud service requesters and providers can be a bottleneck if it is carried out by humans. Therefore, our objective is to offer a state-of-the-art solution to automate the negotiation process in Cloud environments. In previous works in the SLA negotiation area, requesters trust whatever QoS criteria values providers offer in the process of negotiation. However, the proposed negotiation strategy for requesters in this work is capable of assessing reliability of offers received from Cloud providers. In addition, our proposed negotiation strategy for Cloud providers considers utilization of resources when it generates new offers during negotiation and concedes more on the price of less utilized resources. The experimental results show that our strategy helps Cloud providers to increase their profits when they are participating in parallel negotiation with multiple requesters.EGC Building crawler engine on cloud computing infrastructure3207 This paper is aimed to create implementation crawler engine or search engine using cloud computing infrastructure. This approach use virtual machines on a cloud computing infrastructure to run service engine crawlers and also for IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com application servers. Based on our initial experiments, this research has successfully built crawler engine that runs on Virtual Machine (VM) of cloud computing infrastructure. The use of Virtual Machine (VM) on this architecture will help to ease setup or installation, maintenance or VM terminating that has been running with some particular service crawler engine as needed. With this infrastructure, the increasing or decreasing in capacity and capability of multiple engine crawlers could set easily and more efficiently.EGC Client Classification Policies for SLA Enforcement in Shared Cloud Datacenters3208 In Utility computing business model, the owners of the computing resources negotiate with their potential clients to sell computing power. The terms of the Quality of Service (QoS) and the economic conditions are established in a Service- Level Agreement (SLA). There are many scenarios in which the agreed QoS cannot be provided because of errors in the service provisioning or failures in the system. Since providers have usually different types of clients, according to their relationship with the provider or by the fee that they pay, it is important to minimize the impact of the SLA violations in preferential clients. This paper proposes a set of policies to provide better QoS to preferential clients in such situations. The criterion to classify clients is established according to the relationship between client and provider (external user, internal or another privileged relationship) and the QoS that the client purchases (cheap contracts or extra QoS by paying an extra fee). Most of the policies use key features of virtualization: Selective Violation of the SLAs, Dynamic Scaling of the Allocated Resources, and Runtime Migration of Tasks. The validity of the policies is demonstrated through exhaustive experiments. EGC COCA: Computation Offload to Clouds Using AOP 3209 In this paper, we describe COCA -- Computation Offload to Clouds using AOP (aspect-oriented programming). COCA is a programming framework that allows smart phones application developers to offload part of the computation to servers in the cloud easily. COCA works at the source level. By harnessing the power of AOP, COCA inserts appropriate offloading code into the source code of the target application based on the result of static and dynamic profiling. As a proof of concept, we integrate COCA into the Android development environment and fully automate the new build process, making application programming and software maintenance easier. With COCA, mobile applications can now automatically offload part of the computation to the cloud, achieving better performance and longer battery life. Smart phones such as iPhone and Android phones can now easily leverage the immense computing power of the cloud to achieve tasks that were considered difficult before, such as having a more complicated artificial-intelligence engine. EGC Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search 3210 based Request Partitioning The Cloud represents a computing paradigm where shared configurable resources are provided as a service over the IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com Internet. Adding intra or inter cloud communication resources to the resource mix leads to a networked cloud computing environment. Following the Cloud Infrastructure as a Service paradigm and in order to create a flexible management framework, it is of paramount importance to address efficiently the resource mapping problem within this context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different administrative domains, in this article a hierarchical framework is described. First, a novel request partitioning approach based on Iterated Local Search is introduced that facilitates the cost-efficient and on-line splitting of user requests among eligible Cloud service Providers (CPs) within a networked cloud environment. Following and capitalizing on the outcome of the request partitioning phase, the embedding phase - where the actual mapping of requested virtual to physical resources is performed – can be realized through the use of a distributed intra- cloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a thorough evaluation of the proposed overall framework on a simulated networked cloud environment is provided and critically compared against an exact request partitioning solution as well as another common intra-domain virtual resource embedding solution.EGC Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments3211 In wireless sensor networks, adversaries can make use of traffic information to locate the monitored objects, e.g., to hunt endangered animals or kill soldiers. In this paper, we first define a hotspot phenomenon that causes an obvious inconsistency in the network traffic pattern due to a large volume of packets originating from a small area. Second, we develop a realistic adversary model, assuming that the adver-sary can monitor the network traffic in multiple areas, rather than the entire network or only one area. Using this model, we introduce a novel attack called Hotspot-Locating where the adversary uses traffic analysis techniques to locate hotspots. Finally, we propose a cloud-based scheme for efficiently pro-tecting source nodes location privacy against Hotspot-Locating attack by creating a cloud with an irregular shape of fake traffic, to counteract the inconsistency in the traffic pat-tern and camouflage the source node in the nodes forming the cloud. To reduce the energy cost, clouds are active only during data transmission and the intersection of clouds creates a larger merged cloud, to reduce the number of fake packets and also boost privacy preservation. Simulation and analyti-cal results demonstrate that our scheme can provide stronger privacy protection than routing-based schemes and requires much less energy than global-adversary-based schemes.EGC Environmental and disaster sensing using cloud computing infrastructure3212 The remote monitoring system is growing very rapidly due to the growth of supporting technologies as well. Problem that may occur in remote monitoring such as the number of objects to be monitored and how fast, how much data to be transmitted to the data center to be processed properly. This study proposes using a cloud computing infrastructure as processing center in the remote sensing data. This study focuses on the situation for sensing on the environment condition and disaster early detection. Where those two things, it has become an important issue, especially in big cities big cities that have many residents. This study proposes to build the conceptual and also prototype model in a IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com comprehensive manner from the remote terminal unit until development method for data retrieval. We also propose using FTR-HTTP method to guarantee the delivery from remote client to server.EGC Framework on large public sector implementation of cloud computing3213 Cloud computing enables IT systems to be scalable and elastic. One significant advantage of it is users no longer need to determine their exact computing resource requirements upfront. Instead, they request computing resources as required, on-demand. This paper is written to introduce a framework specific for large public sector entities on how to migrate to cloud computing. This paper can then be also be a reference for the Organizations to overcome its limitations and to convince their stakeholders to further implement various types of Cloud Computing service models.EGC Identification of SME readiness to implement cloud computing3214 Cloud Computing allows the use of information technology based on the on-demand utility. This technology can provide benefits to small and medium enterprises with limited capital, human resources, and access to marketing network. A survey conducted on SMEs in the district of Coblong Bandung to dig up the IT needs and analyze their readiness to adopt cloud computing technologies. The survey results stated that SMEs respondents are more suitable to implement Software as a Service with public cloud deployment method. SMEs are ready to implement this technology, but require appropriate training and role models that can be used as an example because their technology adoption characteristics that are late majority.EGC Interactive 3D visualization of soical network data using cloud computing3215 The social networks have revolutionized the online communication and data sharing. The researchers are now focusing on mining and analysis of large amount of social network data for a variety of purposes. However, because of the huge amount of continuously changing data, the data analysis in a daunting task. OLAP analysis is a famous data analysis method which can be used to analyze social data. This work extends our previous work in which we developed interactive 3D visual data cubes for high volume/dimension OLAP data analysis. The implementation of this scheme on traditional computing resources is much time consuming and resource intensive. The advances in cloud computing motivated us to use the cost effective cloud computing for the task of 3D visualization of social networks data. Therefore, in this paper, we propose the usage of cloud computing platforms as a possible solution for analyzing large amount of social network data. . IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.comEGC MORPHOSYS: Efficient Colocation of QoS-Constrained Workloads in the Cloud3216 In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the hosts resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.EGC On Handling Large-Scale Polynomial Multiplications in Compute Cloud Environments3217 using Divisible Load Paradigm Large-scale polynomial product computations often used in aerospace applications such as satellite image processing and sensor networks data processing always pose considerable challenge when processed on networked computing systems. With non-zero communication and computation time delays of the links and processors on a networked infrastructure, the computation becomes all the more challenging. In this research, we attempt to investigate the use of a divisible load paradigm to design efficient strategies to minimize the overall processing time for performing large-scale polynomial product computations in compute cloud environments. We consider a compute cloud system with the resource allocator distributing the entire load to a set of virtual CPU instances (VCI) and the VCIs propagating back the processed results to resource allocator for postprocessing. We consider heterogeneous networks in our analysis and we derive fundamental recursive equations and a closed-form solution for the load fractions to be assigned to each VCI. Our analysis also attempts to eliminate any redundant VCI-link pairs by carefully considering the overheads associated with load distribution and processing. Finally, we quantify the performance of the strategies via rigorous simulation studies.EGC Optimal Multiserver Configuration for Profit Maximization in Cloud Computing3218 As cloud computing becomes more and more popular, understanding the economics of cloud computing becomes critically important. To maximize the profit, a service provider should understand both service charges and business IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com costs, and how they are determined by the characteristics of the applications and the configuration of a multiserver system. The problem of optimal multiserver configuration for profit maximization in a cloud computing environment is studied. Our pricing model takes such factors into considerations as the amount of a service, the workload of an application environment, the configuration of a multiserver system, the service level agreement, the satisfaction of a consumer, the quality of a service, the penalty of a low quality service, the cost of renting, the cost of energy consumption, and a service providers margin and profit. Our approach is to treat a multiserver system as an M/M/m queueing model, such that our optimization problem can be formulated and solved analytically. Two server speed and power consumption models are considered, namely, the idle-speed model and the constant-speed model. The probability density function of the waiting time of a newly arrived service request is derived. The expected service charge to a service request is calculated. The expected net business gain in one unit of time is obtained. Numerical calculations of the optimal server size and the optimal server speed are demonstrated.EGC Optimization of Resource Provisioning Cost in Cloud Computing3219 In cloud computing, cloud providers can offer cloud consumers two provisioning plans for computing resources, namely reservation and on-demand plans. In general, cost of utilizing computing resources provisioned by reservation plan is cheaper than that provisioned by on-demand plan, since cloud consumer has to pay to provider in advance. With the reservation plan, the consumer can reduce the total resource provisioning cost. However, the best advance reservation of resources is difficult to be achieved due to uncertainty of consumers future demand and providers resource prices. To address this problem, an optimal cloud resource provisioning (OCRP) algorithm is proposed by formulating a stochastic programming model. The OCRP algorithm can provision computing resources for being used in multiple provisioning stages as well as a long-term plan, e.g., four stages in a quarter plan and twelve stages in a yearly plan. The demand and price uncertainty is considered in OCRP. In this paper, different approaches to obtain the solution of the OCRP algorithm are considered including deterministic equivalent formulation, sample-average approximation, and Benders decomposition. Numerical studies are extensively performed in which the results clearly show that with the OCRP algorithm, cloud consumer can successfully minimize total cost of resource provisioning in cloud computing environments.EGC Policy-Based Automation of SLA Establishment for Cloud Computing Services3220 We propose a policy-based framework for the automated establishment of SLAs for cloud computing services. The proposed framework supports multiple interaction models for SLA establishment giving consumers and providers the flexibility to choose one that is most appropriate in a given context, while simultaneously supporting multiple concurrent SLA interactions using different interaction models. We describe the underlying policies, focussing on the key features and contributions of the framework. We also validate our framework through a real-world use-case scenario using the Amazon EC2 service. IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.comEGC Privacy Mechanism for Applications in Cloud Computing3221 Applications stored in the cloud enable users to access and perform tasks in real time, reducing costs in the acquisition of computer resources. Although there are benefits, this paradigm also brings security and privacy risks to users, such as theft of information or identity. This paper proposes a mechanism able to provide privacy protection for users to use applications that address issues of identity, confidentiality and user preferences.EGC Real-time rendering for massive terrain data using GPUs3222 Real-time rendering for massive terrain data is a challenging work. Previous GPUs are not suitable for rendering massive mesh data. Recently, with tessellation shaders and geometry shader added on a GPU, it is possible to tessellate triangles or quad patches to improve geometrical features of mesh objects. In this paper, we propose a massive terrain rendering technique in real-time using GPUs. We made displacement and normal map from massive terrain data on the GPU. As a result, we could tessellate a coarse base mesh with a high resolution texture as displacement map and normal map for shading from massive terrain data.EGC3223 RO-BURST: A Robust Virtualization Cost Model for Workload Consolidation over Clouds As more public cloud computing platforms are emerging in the market, a great challenge for these Infrastructure as a Server (IaaS) providers is how to measure the cost and charge the Software as a Service (SaaS) clients for the cloud computing services. This problem is compounded as virtualization technology is deployed in many cloud platforms to consolidate servers and improve their utilization. This paper studies three different but related models for apportioning costs in a private or public cloud environment supported by virtualized data centers. With given workload placement scenarios and randomly selected workloads, these models estimate the cost for each workload. Through simulations and thorough comparisons of the results, we finally champion the RO-BURST model tailored for the service providers need, that is characterized by robustness and burstiness. What is more, we import Cost Volatility Factors to ensure that our model is able to adjust itself to the market and multiform demands in power and hardware components, such as disks and CPU, showing its compatibility and extensibility. We also come up with a pricing strategy with respect to servers the workload employs, which generates an applicable and less placement-sensitive fee for the clientsEGC Service Level Agreement for Distributed Mutual Exclusion in Cloud Computing3224 In Cloud Computing, Service Level Agreement (SLA) is a contract that defines a level and a type of QoS between a cloud provider and a client. Since applications in a Cloud share resources, we propose two tree-based distributed mutual exclusion algorithms that support the SLA concept. The first one is a modified version of the priority-based Kanrar- IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com Chaki algorithm [1] while the second one is a novel algorithm, based on Raymond algorithm [2], where a deadline is associated with every request. In both cases, our aim is to improve Critical Section execution rate and to reduce the number of SLA violations, which, for the first algorithm represents the number of priority inversions (i.e. a higher priority request is satisfied after a lower one) and for the second one, the number of requests whose deadline is not respected. Performance evaluation results show that our solutions significantly reduce SLA violations avoiding message overhead.EGC SLA-based Optimization of Power and Migration Cost in Cloud Computing3225 Cloud computing systems (or hosting datacenters) have attracted a lot of attention in recent years. Utility computing, reliable data storage, and infrastructure-independent computing are example applications of such systems. Electrical energy cost of a cloud computing system is a strong function of the consolidation and migration techniques used to assign incoming clients to existing servers. Moreover, each client typically has a service level agreement (SLA), which specifies constraints on performance and/or quality of service that it receives from the system. These constraints result in a basic trade-off between the total energy cost and client satisfaction in the system. In this paper, a resource allocation problem is considered that aims to minimize the total energy cost of cloud computing system while meeting the specified client-level SLAs in a probabilistic sense. The cloud computing system pays penalty for the percentage of a clients requests that do not meet a specified upper bound on their service time. An efficient heuristic algorithm based on convex optimization and dynamic programming is presented to solve the aforesaid resource allocation problem. Simulation results demonstrate the effectiveness of the proposed algorithm compared to previous work.EGC Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private3226 Clouds With the advent of cloud computing and the need to satisfy growing customers resource demands, cloud providers now operate increasing amounts of large data centers. In order to ease the creation of private clouds, several open-source Infrastructure-as-a-Service (IaaS) cloud management frameworks (e.g. Open Nebula, Nimbus, Eucalyptus, Open Stack) have been proposed. However, all these systems are either highly centralized or have limited fault tolerance support. Consequently, they all share common drawbacks: scalability is limited by a single master node and Single Point of Failure (SPOF). In this paper, we present the design, implementation and evaluation of a novel scalable and autonomic (i.e. self-organizing and healing) virtual machine (VM) management framework called Snooze. For scalability the system utilizes a self-organizing hierarchical architecture and performs distributed VM management. Moreover, fault tolerance is provided at all levels of the hierarchy, thus allowing the system to self-heal in case of failures. Our evaluation conducted on 144 physical machines of the Grid5000 experimental test bed shows that the fault tolerance features of the framework do not impact application performance. Moreover, negligible cost is involved in performing distributed VM management and the system remains highly scalable with increasing amounts of resources. IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com EGC Taking up autonomous SOA framework into cloud computing 3227 Cloud computing is an extension of Service Oriented Architecture (SOA). For cloud elastic nature, it will often need to dynamically reconfiguring and reorganising the services interaction as some unpredictable events, such as crashes or network problems, will typically cause service unavailability. The complexity and dynamism of current global network system require an architecture that is capable of autonomously changing its structure and functionality to meet the changes with little human intervention. In this paper, an autonomic SOA framework is proposed to extend the intelligence and capability in the cloud. The use of case-based reasoning and the architectural consideration of autonomic computing paradigm are presented.EGC THEMIS: A Mutually Verifiable Billing System for the Cloud Computing Environment3228 With the widespread adoption of cloud computing, the ability to record and account for the usage of cloud resources in a credible and verifiable way has become critical for cloud service providers and users alike. The success of such a billing system depends on several factors: the billing transactions must have integrity and nonrepudiation capabilities; the billing transactions must have a minimal computation cost; and the SLA monitoring should be provided in a trusted manner. Existing billing systems are limited in terms of security capabilities or computational overhead. In this paper, we propose a secure and nonobstructive billing system called THEMIS as a remedy for these limitations. The system uses a novel concept of a cloud notary authority for the supervision of billing. It generates mutually verifiable binding information that can be used to resolve future disputes between a user and a cloud service provider in a computationally efficient way. Furthermore, to provide a forgery-resistive SLA monitoring mechanism, we devised a SLA monitoring module enhanced with a trusted platform module (TPM), called S-Mon. This work has been undertaken on a real cloud computing service called iCubeCloud.EGC Toward Secure and Dependable Storage Services in Cloud Computing3229 Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
  • Elysium Technologies Private Limited Approved by ISO 9001:2008 and AICTE for SKP Training Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai http://www.elysiumtechnologies.com, info@elysiumtechnologies.com efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.EGC Towards Trusted Services: Result Verification Schemes for MapReduce3230 Recent development in Internet-scale data applications and services, combined with the proliferation of cloud computing, has created a new computing model for data intensive computing best characterized by the MapReduce paradigm. The MapReduce computing paradigm, pioneered by Google in its Internet search application, is an architectural and programming model for efficiently processing massive amount of raw unstructured data. With the availability of the open source Hadoop tools, applications built based on the MapReduce computing model are rapidly growing. In this work, we focus on a unique security concern on the MapReduce architecture. Given the potential security risks from lazy or malicious servers involved in a MapReduce task, we design efficient and innovative mechanisms for detecting cheating services under the MapReduce environment based on watermark injection and random sampling methods. The new detection schemes are expected to significantly reduce the cost of verification overhead. Finally, extensive analytical and experimental evaluation confirms the effectiveness of our schemes in MapReduce result verification.EGC Video analysis tools for cloud-based motion detection3230 We present a fast moving object detection application by extending the functionality of open source tools that are available freely on the Internet. This application can be placed on a cloud infrastructure and performs fast processing so that the costs needed to use the cloud resources can be minimized. IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects