Cloud ComputingNO PRJ

TITLEABSTRACT DOMAIN YOP

1 CloudMoV: Cloud-based Mobile Social TV

The rapidly increasing power of personal mobile devices (smartphones, tablets, etc.) is providing much richer contents and social interactions to users on the move. This trend however is throttled by the limited battery lifetime of mobile devices and unstable wireless connectivity, making the highest possible quality of service experienced by mobile users not feasible. The recent cloud computing technology, with its rich resources to compensate for the limitations of mobile devices and connections, can potentially provide an ideal platform to support the desired mobile services. Tough challenges arise on how to effectively exploit cloud resources to facilitate mobile services, especially those with stringent interaction delay requirements. In this paper, we propose the design of a Cloud-based, novel Mobile sOcial tV system (CloudMoV). The system effectively utilizes both PaaS (Platform-as-a-Service) and IaaS (Infrastructure-as-a-Service) cloud services to offer the living-room experience of video watching to a group of disparate mobile users who can interact socially while sharing the video. To guarantee good streaming quality as experienced by the mobile users with time-varying wireless connectivity, we employ a surrogate for each user in the IaaS cloud for video downloading and social exchanges on behalf of the user. The surrogate performs efficient stream transcoding that matches the current connectivity quality of the mobile user. Given the battery life as a key performance bottleneck, we advocate the use of burst transmission from the surrogates to the mobile users, and carefully decide the burst size which can lead to high energy efficiency and streaming quality. Social interactions among the users, in terms of spontaneous textual exchanges, are effectively achieved by efficient designs of data storage with BigTable and dynamic handling of large volumes of concurrent messages in a typical PaaS cloud. These various designs for flexible transcoding c- pabilities, battery efficiency of mobile devices and spontaneous social interactivity together provide an ideal platform for mobile social TV services. We have implemented CloudMoV on Amazon EC2 and Google App Engine and verified its superior performance based on real-world experiments.

Cloud Computing

2013

2 An Improved Mutual Authentication Framework for Cloud Computing

In this paper, wehave propose a user authentication scheme for cloud computing. The proposed framework providesmutual authentication and session key agreement in cloud computing environment. The scheme executesin three phases such as server initialization phase, registration phase, authentication phase. Detailed security analyses have been made to validate the efficiency of the scheme. Further, the scheme has the resistance to possible attacks in cloud computing.

Cloud Computing

2013

3    Utility-aware deferred load balancing in the cloud driven by dynamic pricing of electricity

Distributed computing resources in a cloud computing environment provides an opportunity to reduce energy and its cost by shifting loads in response to dynamically varying availability of energy. This variation in electrical power availability is represented in its dynamically changing price that can be used to drive workload deferral against performance requirements. But such deferral may cause user dissatisfaction. In this paper,we quantify the impact of deferral on user satisfaction andutilize flexibility from the service level agreements (SLAs) for deferral to adapt with dynamic price variation. We differentiate among the jobs based on their requirements for responsiveness and schedule them for energy saving while meeting deadlines and user satisfaction. Representing utility as decaying functionsalong with workload deferral, we make a balance between loss of user satisfaction and energy efficiency. We model delay as decaying functions and guarantee that no job violates the maximum deadline, and we minimize the overall energy cost. Our simulation on MapReduce traces show that energy consumption can be reduced by 15%, with such utility-aware deferred load balancing. We also found that considering utility as a decaying function gives better cost reduction than load balancing with a fixed deadline.

Cloud Computing

2013

#56, II Floor, Pushpagiri Complex, 17th Cross 8th Main, Opp Water Tank,Vijaynagar,Bangalore-560040.

Website: www.citlprojects.com, Email ID: projects@citlindia.com,hr@citlindia.comMOB: 9886173099 / 9986709224, PH : 080 -23208045 / 23207367

JAVA / J2EE PROJECTS – 2013(Networking, Network-Security, Mobile Computing, Cloud Computing, Wireless Sensor Network, Datamining,

Webmining, Artificial Intelligence, Vanet, Ad-Hoc Network)

4  A new framework to integrate wireless sensor networks with cloud computing

Wireless Sensor Networks (WSN) has been a focus for research for several years. WSN enables novel and attractive solutions for information gathering across the spectrum of endeavour including transportation, business, health-care, industrial automation, and environmental monitoring. Despite these advances, the exponentially increasing data extracted from WSN is not getting adequate use due to the lack of expertise, time and money with which the data might be better explored and stored for future use. The next generation of WSN will benefit when sensor data is added to blogs, virtual communities, and social network applications. This transformation of data derived from sensor networks into a valuable resource for information hungry applications will benefit from techniques being developed for the emerging Cloud Computing technologies. Traditional High Performance Computing approaches may be replaced or find a place in data manipulation prior to the data being moved into the Cloud. In this paper, a novel framework is proposed to integrate the Cloud Computing model with WSN. Deployed WSN will be connected to the proposed infrastructure. Users request will be served via three service layers (IaaS, PaaS, SaaS) either from the archive, archive is made by collecting data periodically from WSN to Data Centres (DC), or by generating live query to corresponding sensor network.

Cloud Computing

2013

5   A packet marking approach to protect cloud environment against DDoS attacks

Cloud computing uses internet and remote servers for maintaining data and applications. It offers through internet the dynamic virtualized resources, bandwidth and on-demand software's to consumers and promises the distribution of many economical benefits among its adapters. It helps the consumers to reduce the usage of hardware, software license and system maintenance. Simple Object Access Protocol (SOAP) is the system that allows the communications interaction between different web services. SOAP messages are constructed using either HyperText Transport Protocol (HTTP) and/or Extensible Mark-up Language (XML). The new form of Distributed Denial of Service (DDoS) attacks that could potentially bring down a cloud web services through the use of HTTP and XML. Cloud computing suffers from major security threat problem by HTTP and XML Denial of Service (DoS) attacks. HX-DoS attack is a combination of HTTP and XML messages that are intentionally sent to flood and destroy the communication channel of the cloud service provider. To address the problem of HX-DoS attacks against cloud web services there is a need to distinguish between the legitimate and illegitimate messages. This can be done by using the rule set based detection, called CLASSIE and modulo marking method is used to avoid the spoofing attack. Reconstruct and Drop method is used to make decision and drop the packets on the victim side. It enables us to improve the reduction of false positive rate and increase the detection and filtering of DDoS attacks.

Cloud Computing

2013

6 C-MART: Benchmarking the Cloud Parallel and Distributed Systems

Cloud computing environments provide on-demand resource provisioning, allowing applications to elastically scale. However, application benchmarks currently being used to test cloud management systems are not designed for this purpose. This results in resource underprovisioning and quality-of-service (QoS) violations when systems tested using these benchmarks are deployed in production environments. We present C-MART, a benchmark designed to emulate a modern web application running in a cloud computing environment. It is designed using the cloud computing paradigm of elastic scalability at every application tier and utilizes modern web-based technologies such as HTML5, AJAX, jQuery, and SQLite. C-MART consists of a web application, client emulator, deployment server, and scaling API. The deployment server automatically deploys and configures the test environment in orders of magnitude less time than current benchmarks. The scaling API allows users to define and provision their own customized datacenter. The client emulator generates the web workload for the application by emulating complex and varied client behaviors, including decisions based on page content and prior history. We show that C-MART can detect problems in management systems that previous benchmarks fail to identify, such as an increase from 4.4 to 50 percent error in predicting server CPU utilization and resource underprovisioning in 22 percent of QoS measurements.

Cloud Computing

2013

7 Pre-emptive scheduling of on-line real time services with task migration for cloud computing

This paper presents a new scheduling approach to focus on providing a solution for online scheduling problem of real-time tasks using “Infrastructure as a Service” model offered by cloud computing. The real time tasks are scheduled pre-emptively with the intent of maximizing the total utility and efficiency. In traditional approach, the task is scheduled non- pre-emptively with two different types of Time Utility Functions (TUFs) - a profit time utility function and a penalty time utility function. The task with highest expected gain is executed. When a new task arrives with highest priority then it cannot be taken for execution until it completes the currently running task. Therefore the higher priority task is waiting for a longer time. This scheduling method sensibly aborts the task when it misses its deadline. Note that, before a task is aborted, it consumes system resources including network bandwidth, storage space and processing power. This leads to affect the overall system performance and response time of a task. In our approach, a preemptive online scheduling with task migration algorithm for cloud computing environment is proposed in order to minimize the response time and to improve the efficiency of the tasks. Whenever a task misses its deadline, it will be migrated the task to another virtual machine. This improves the overall system performance and maximizes the total utility. Our simulation results outperform the traditional scheduling algorithms such as the Earliest Deadline First (EDF) and an earlier scheduling approach based on the similar model.

Cloud Computing

2013

8 Facial Expression Recognition in the Encrypted Domain Based on Local Fisher Discriminant Analysis

Facial expression recognition forms a critical capability desired by human-interacting systems that aim to be responsive to variations in the human's emotional state. Recent trends toward cloud computing and outsourcing has led to the requirement for facial expression recognition to be performed remotely by potentially untrusted servers. This paper presents a system that addresses the challenge of performing facial expression recognition when the test image is in the encrypted domain. More specifically, to the best of our knowledge, this is the first known result that performs facial expression recognition in the encrypted domain. Such a system solves the problem of needing to trust servers since the test image for facial expression recognition can remain in encrypted form at all times without needing any decryption, even during the expression recognition process. Our experimental results on popular JAFFE and MUG facial expression databases demonstrate that recognition rate of up to 95.24 percent can be achieved even in the encrypted domain.

Cloud Computing

2013

9  Optimistic fuzzy based signature identification in cloud using multimedia mining and analysis techniques

Client level security issues in the cloud computing became a major challenge in service access process in cloud environment. Day by day number of threats over the network increasing because of the huge demand for the cloud product and service. The existing authentication systems are unable to provide the sufficient security and user Identification techniques. The proposed scheme, Trying to provide the Optimistic user signature identification through mining analysis and also using Fuzzy logic based user classification module provide the sufficient security for the cloud service access. This scheme reduces the complexity involved in the key exchange process in cryptographic techniques. With the help of strong mining tools and fuzzy computations, trying to prove that proposed scheme will provide sufficient user classification and security.

Cloud Computing

2013

10  Toward Secure Multikeyword Top-k Retrieval over Encrypted Cloud Data

Cloud computing has emerging as a promising pattern for data outsourcing and high-quality data services. However, concerns of sensitive information on cloud potentially causes privacy problems. Data encryption protects data security to some extent, but at the cost of compromised efficiency. Searchable symmetric encryption (SSE) allows retrieval of encrypted data over cloud. In this paper, we focus on addressing data privacy issues using SSE. For the first time, we formulate the privacy issue from the aspect of similarity relevance and scheme robustness. We observe that server-side ranking based on order-preserving encryption (OPE) inevitably leaks data privacy. To eliminate the leakage, we propose a two-round searchable encryption (TRSE) scheme that supports top-$(k)$ multikeyword retrieval. In TRSE, we employ a vector space model and homomorphic encryption. The vector space model helps to provide sufficient search accuracy, and the homomorphic encryption enables users to involve in the ranking while the majority of computing work is done on the server side by operations only on ciphertext. As a result, information leakage can be eliminated and data security is ensured. Thorough security and performance analysis show that the proposed scheme guarantees high security and practical efficiency.

cloud computing

2013

11 Mona: Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud

With the character of low maintenance, cloud computing provides an economical and efficient solution for sharing group resource among cloud users. Unfortunately, sharing data in a multi-owner manner while preserving data and identity privacy from an untrusted cloud is still a challenging issue, due to the frequent change of the membership. In this paper, we propose a secure multi-owner data sharing scheme, named Mona, for dynamic groups in the cloud. By leveraging group signature and dynamic broadcast encryption techniques, any cloud user can anonymously share data with others. Meanwhile, the storage overhead and encryption computation cost of our scheme are independent with the number of revoked users. In addition, we analyze the security of our scheme with rigorous proofs, and demonstrate the efficiency of our scheme in experiments.

Cloud Computing

2013

12  Optimizing Cloud Resources for Delivering IPTV Services Through Virtualization

Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings. However, achieving similar savings with real-time services can be a challenge. In this paper, we seek to lower a provider's costs for real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of selected services. Using Live TV and Video-on-Demand (VoD) as examples, we show that we can take advantage of the different deadlines associated with each service to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support multiple services, without missing the deadline for any service. We construct the problem as an optimization formulation that uses a generic cost function. We consider multiple forms for the cost function (e.g., maximum, convex and concave functions) reflecting the cost of providing the service. The solution to this formulation gives the number of servers needed at different time instants to support these services. We implement a simple mechanism for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results show that we are able to reduce the load by ~ 24% (compared to a possible ~ 31%). We also show that there are interesting open problems in designing mechanisms that allow time-shifting of load in such environments.

Cloud Computing

2013

13    An Effective Network Traffic Classification Method with Unknown Flow Detection

Traffic classification technique is an essential tool for network and system security in the complex environments such as cloud computing based environment. The state-of-the-art traffic classification methods aim to take the advantages of flow statistical features and machine learning techniques, however the classification performance is severely affected by limited supervised information and unknown applications. To achieve effective network traffic classification, we propose a new method to tackle the problem of unknown applications in the crucial situation of a small supervised training set. The proposed method possesses the superior capability of detecting unknown flows generated by unknown applications and utilizing the correlation information among real-world network traffic to boost the classification performance. A theoretical analysis is provided to confirm performance benefit of the proposed method. Moreover, the comprehensive performance evaluation conducted on two real-world network traffic datasets shows that the proposed scheme outperforms the existing methods in the critical network environment.

Cloud Computing

2013

14 A Refined RBAC Model for Cloud Computing

Cloud computing is a fast growing field which is arguably a new computing paradigm. In cloud computing, computing resources are provided as services over the Internet and users can access resources on based on their payments. This paper discusses cloud computing and its related security risks, with a focus on access control. As a traditional access control mechanism, role-based access control (RBAC) model can be used to implement several important security principles such as least privilege, separation of duties, and data abstraction. This paper shows an on-going effort by refining entities in RBAC used for cloud computing, and further discusses their security implications. We argue that RBAC is well suited to many situations in cloud computing where users or applications can be clearly separated according to their job functions.

Cloud Computing

2012

15 Building Crawler Engine on Cloud Computing Infrastructure

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 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.

Cloud Computing

2012

16 Reliable Re-encryption in Unreliable Clouds

A key approach to secure cloud computing is for the data owner to store encrypted data in the cloud, and issue decryption keys to authorized users. Then, when a user is revoked, the data owner will issue re-encryption commands to the cloud to re-encrypt the data, to prevent the revoked user from decrypting the data, and to generate new decryption keys to valid users, so that they can continue to access the data. However, since a cloud computing environment is comprised of many cloud servers, such commands may not be received and executed by all of the cloud servers due to unreliable network communications. In this paper, we solve this problem by proposing a timebased re-encryption scheme, which enables the cloud servers to automatically re-encrypt data based on their internal clocks. Our solution is built on top of a new encryption scheme, attributebased encryption, to allow fine-grain access control, and does not require perfect clock synchronization for correctness.

Cloud Computing

2012

17 Towards Green P2P: Analysis of Energy Consumption in P2P and Approaches to Control

Nowadays, information and communication technology (ICT) has become more and more energy conscious. In this paper, we focus on peer-to-peer systems which contribute a major fraction of the Internet traffic. This paper proposes analytical models of energy consumption in P2P system. The model considers content pollution, the most common attack in P2P system, which has received little attention in previous work on green P2P. The analysis of the models shows that the popular sleep method in green computing potentially affects peer-to-peer performance. When the online time of clean copy holders is over cut, the system collapses. To find the balance between energy saving and system maintenance, the concept energy effectiveness is introduced. An approach for controlling energy consumption while keeping the system stable is suggested. We show that the whole system can be benefited if some warm-hearted and smart peers are willing to spend a little extra cost on energy, when most peers over cut their power on time. This approach can perfectly complement the popular sleep methods in green computing.

Cloud Computing

2012

18 Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud

In recent years ad-hoc parallel data processing has emerged to be one of the killer applications for Infrastructure-as-a-Service (IaaS) clouds. Major Cloud computing companies have started to integrate frameworks for parallel data processing in their product portfolio, making it easy for customers to access these services and to deploy their programs. However, the processing frameworks which are currently used have been designed for static, homogeneous cluster setups and disregard the particular nature of a cloud. Consequently, the allocated compute resources may be inadequate for big parts of the submitted job and unnecessarily increase processing time and cost. In this paper we discuss the opportunities and challenges for efficient parallel data processing in clouds and present our research project Nephele. Nephele is the first data processing framework to explicitly exploit the dynamic resource allocation offered by today’s IaaS clouds for both, task scheduling and execution. Particular tasks of a processing job can be assigned to different types of virtual machines which are automatically instantiated and terminated during the job execution.

Cloud Computing

2012

19 Dynamic Load- - Balanced Multicast

Data-intensive parallel applications on clouds need to deploy large data sets from the cloud’s storage facility toall compute nodes as fast as possible. Many multicast algorithms have been proposed for clusters and grid environments. The most common approach is to construct one or more spanning trees based on the network topology and network monitoring data in order to maximize available bandwidth and avoid bottleneck links.

Cloud Computing

2012

for Data Intensive Applications on Clouds 2010

However, delivering optimal performance becomes difficult once the available bandwidth changes dynamically.

20 Service Oriented Architecture for Cloud based Travel Reservation Software as a Service

Cloud is gaining popularity as means for saving cost of IT ownership and accelerating time to market due to ready-to-use, dynamically scalable computing infrastructure and software services offered on Cloud on pay-per-use basis. Design of software solution for delivery as a shared service over Cloud requires specific considerations. In this paper we describe an approach for design of travel reservations solution for use by corporate business travelers based on Service Oriented Architecture, Software-as-a-Service, and Cloud Computing paradigms.

Cloud Computing

2012

21 A New Wireless Web Access Mode Based on Cloud Computing 2008

As most websites are designed for desktop PCs, it is extremely uncomfortable to browse these large pages on a wireless handheld device with small screen and limited user interface. So it is necessary to adapt these web pages to small screen devices. Besides, as the limited computing ability and capacity of storage of wireless handheld devices, it is also extremely challenging to deploy existing web page adaptation engine. By referring to huge computing ability and storage resource of cloud computing infrastructure, a new wireless web access mode is proposed. Firstly, the system framework is present. Subsequently, the two key components of system are described in detail: the one is distributed web page adaptation engine, which is designed for the purpose that the engine can be carried by computing cloud distributed and parallel; the other is distributed web page blocks management based on cloud computing, which is proposed so that the web page adaptation engine can be deployed reasonably. Moreover, a prototype system and a set of evaluation experiments have been implemented.

Cloud Computing

2012