Collaborative Cloud Research Articles

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

Cloud computing enables a revolutionary paradigm of consuming ICT services. However, due to the inadequately described service information, users often feel confused while trying to find the optimal services. Although some approaches are proposed to deal with cloud service retrieval and recommendation issues, they would only work for certain restricted scenarios in dealing with basic service specifications. Indeed, the missing extent is that most of the cloud services are “agile” whilst there are many vague service terms and descriptions. This paper proposes an agility-oriented and fuzziness-embedded cloud service ontology model, which adopts agility-centric design along with OWL2 (Web Ontology Language) fuzzy extensions. The captured cloud service specifications are maintained in an open and collaborative manner, as the fuzziness in the model accepts rating updates from users on the fly. The model enables comprehensive service specification by capturing cloud concept details and their interactions, even across multiple service categories and abstraction levels. Utilizing the model as a knowledge base, a service recommendation system prototype is developed. Case studies demonstrate that the approach can outperform existing practices by achieving effective service search, retrieval and recommendation outcomes.

Resource Selection in Collaborative CloudComputing Based on User Preference

In many researches they have created one environment with multiple clouds for scalable capabilities. The demand for scalable resources in some applications has been rapidly increased. By understanding the mutual dependencies between resources, utilization of users, user preferences a collaborative cloud computing has been introduced, It can be achieve emphasized efficient management of resources and user satisfaction between distributed resources in Collaborative cloud computing. These which do collaboratively supported by many organizations (Google, Microsoft, Amazon). Collaborative cloud computing (CCC) is next logical step in evolution of cloud and service grid technologies. Here mainly discussing about how resource selection done in collaborative cloud, resource selection based on user preferences, which mostly user preferred resources. This environment is to point out the suitable resources, ability and capability of resources, user requirements, and availability of resources. So that users can choose credible cloud platform.

Research on Cloud Manufacturing Resource Allocation in Distributed Computing Environment

With the rapid development of network information technology, manufacturing presents a development trend of networking, virtualization, intelligence and servitization. Cloud manufacturing (CMg) with a new type of service-oriented manufacturing model is put forward and excellently satisfies the development requirements of modern manufacturing enterprises. With considering the complex characteristics of cloud manufacturing, firstly, we construct Cloud manufacturing resource scheduling system architecture to schedule service task and allocate manufacturing resource, which includes user requirements, task plan, global task scheduling, service collaboration allocation, virtualization and cloud manufacturing resource. Secondly, we propose a comprehensive resource allocation model based on auctions theory to satisfy different users’ request, and then the greedy method is used to search the optimal bid in the bid set. Finally, we implement some simulation experiments, and simulation results show that the solution algorithm of CARA’s winner determination problem gets the same solution as the M-HEU algorithm with less time complexity, and it is more applicable, efficient and effective for online multi-resource allocation.

과업특성 및 기술특성이 클라우드 SaaS를 통한 협업 성과에 미치는 영향에 관한 연구

과업특성 및 기술특성이 클라우드 SaaS를 통한 협업 성과에 미치는 영향에 관한 연구

Design and implementation of a collaborative team-based cloud storage system

With the rapid development of the Internet and information technology, cloud computing has been increasing in popularity. Cloud Storage Services, in which users can store their own files in the Int...

English

Cloud computing is rising as a prevailing data interactive model to take in users’ data which has been remotely stored in an online cloud server. On-demand cloud applications is offered by the cloud services without any local infrastructure limitations. Multiple users may wish to access and share another user's authorised data fields to achieve successful benefits. whenever user request another users for information sharing, Access request itself may uncover the client's security regardless of whether it can obtain the data access permissions or not. The option of granting/revoking data access and ranking at the admin level for the number of times the particular file has been requested is not present in the existing system .In a Proposed System Ranking Based shared authority privacypreserving authentication protocol (RSAPA) address the above privacy issue for cloud storage. And provide ranking at the Admin level .In the RSAPA,1) shared access authority is achieved by the anonymous access request matching mechanism, without out revealing the user’s privacy for a data demand 2) user can access his own data fields by attribute based access control 3) Data sharing between the different users is achieved by proxy re-encryption in cloud server In the mean time, universal compose capability (UC) model is built to demonstrate that the SAPA hypothetically has the outline accuracy .It demonstrates that the proposed protocol acknowledging privacy-preserving data access authority sharing, is keen for multi-user collaborative cloud applications. In our model, privacy is achieved by encrypting the data it can prevent the unapproved access. Also, we are going to raise the security level of the owner of the data and confidentiality of the information by giving access to the users

G-Route: an energy-aware service routing protocol for green cloud computing

In this paper, we present the design and implementation of Green Route (G-Route), an autonomic service routing protocol for constructing energy-efficient provider paths in collaborative cloud architectures. The chief contribution of this work resides in autonomously selecting the optimal set of composite service components sustaining the most efficient energy consumption characteristics among a set of providers for executing a particular service request. For ensuring the accountability of the system, the routing decision engine is designed to operate by processing accountable energy measurements extracted securely from within the cloud data centers using trusted computing technologies and cryptographic mechanisms. By pushing green computing constraints into the service routing decision engine, we can leverage the collaborative cloud computing model to maximize the energy savings achieved. This is realized by focusing on a path of providers that execute the service requests instead of directing the green computing efforts towards a single provider site. To the best of our knowledge, G-Route is the first service routing protocol that utilizes the collaborative properties among cloud providers to select "green" service routes and thus, to enhance the energy savings in the overall cloud computing infrastructure. The devised G-Route design is developed and deployed in a real cloud computing environment using the Amazon EC2 cloud platform. The experimental results obtained analyze the protocol convergence characteristics, traffic overhead, and resilience under anomalous service configurations and conditions and demonstrate the capability of the proposed system to significantly reduce the overall energy requirements of collaborative cloud services.

A Combinatorial Auction-based collaborative cloud services platform

In this paper, we introduce a combinatorial auction-based market model to enable Cloud Service Providers (CSPs) to satisfy complex user requirements collaboratively, where the CSPs are connected in a social network and communication costs among them cannot be ignored. However, in many situations CSPs may lie about their private information in order to maximize their earnings. Therefore, we combine the combinatorial auction with the VCG-auction mechanism to ensure that CSPs do not lie in auction. Based on above market model, we construct a collaborative cloud platform, which is divided into three layers: The user-layer receives requests from end-users, the auction-layer matches the requests with the cloud services provided by the Cloud Service Provider (CSP), and the CSP-layer forms a coalition to improve serving ability to satisfy complex requirements of users. In fact, the aim of the coalition formation is to find suitable partners for a particular CSP, and, we propose two heuristic algorithms for the coalition formation. The Breadth Traversal Algorithm (BTA) and Revised Ant Colony Algorithm (RACA) are proposed to form a coalition when bidding for a single cloud service in the auction. The experimental results show that RACA outperforms the BTA in bid price and our methods work well compared to the existing auction-based method in terms of economic efficiency. Other experiments were conducted to evaluate the impact of the communication cost on coalition formation and to assess the impact of iteration times for the optimal bidding price.

Combining Efficiency, Fidelity, and Flexibility in Resource Information Services

A large-scale resource sharing system (e.g., collaborative cloud computing and grid computing) creates a virtual supercomputer by providing an infrastructure for sharing tremendous amounts of resources (e.g., computing, storage, and data) distributed over the Internet. A resource information service, which collects resource data and provides resource search functionality for locating desired resources, is a crucial component of the resource sharing system. In addition to resource discovery speed and cost (i.e., efficiency), the ability to accurately locate all satisfying resources (i.e., fidelity) is also an important metric for evaluating service quality. Previously, a number of resource information service systems have been proposed based on Distributed Hash Tables (DHTs) that offer scalable key-based lookup functions. However, these systems either achieve high fidelity at low efficiency, or high efficiency at low fidelity. Moreover, some systems have limited flexibility by only providing exact-matching services or by describing a resource using a pre-defined list of attributes. This paper presents a resource information service that offers high efficiency and fidelity without restricting resource expressiveness, while also providing a similar-matching service. Extensive simulation and PlanetLab experimental results show that the proposed service outperforms other services in terms of efficiency, fidelity, and flexibility; it dramatically reduces overhead and yields significant enhancements in efficiency and fidelity.

Litrature Survey on Collaborative Cloud ComputingFor Sharing Resource in Trustworthy Manner

Collaborative Cloud Computing (CCC) is the very new technique which makes the promising and secured way of transmitting the data over distributed cloud servers; the main objective for developing CCC is to create collected and cooperative development over cloud service providers Collaborative Cloud Computing method uses two different types of mechanism for activating the cloud server they are resource management and reputation management technique therefore we can avoid over node of traffic congestion hence we can generate high quality of double bandwidth over node. In the previous research work a single value will be added to the reputation management so that it can represent every node with the unique ID, even though the value has been assigned to the every node the server could not able to identify resources to individual types of user’s therefore QoS (Quality of Service) could not able to meet by the resources selection allocator. In order to find the solution for the problem we proposed new a method called Harmony in the Collaborative Cloud Computing platform. Harmony method used to access the resource and reputation technique with help of three different types of key value search method they are as follows, integrated multi – faceted resource/reputation management, multi – QoS oriented resource selection process and price – assisted resource/reputation control technique. Data has been traced out from different online trading platforms like EBay, Amazon, etc in order to implies major drawbacks in multi – faceted reputation and higher reputed selection of nodes in the cloud servers hence trace driven and simulation method is implemented and executed in the plant lab for getting trustworthy of sharing the resource management and reputation management in the Quality of Service (QoS). In this survey paper we compared various research parameters for Collaborative Cloud Computing (CCC).

QoE Guarantee Scheme Based on Cooperative Cognitive Cloud and Opportunistic Weight Particle Swarm

It is well known that the Internet application of cloud services may be affected by the inefficiency of cloud computing and inaccurate evaluation of quality of experience (QoE) seriously. In our paper, based on construction algorithms of cooperative cognitive cloud platform and optimization algorithm of opportunities weight particle swarm clustering, the QoE guarantee mechanism was proposed. The mechanism, through the sending users of requests and the cognitive neighbor users’ cooperation, combined the cooperation of subcloud platforms and constructed the optimal cloud platform with the different service. At the same time, the particle swarm optimization algorithm could be enhanced dynamically according to all kinds of opportunity request weight, which could optimize the cooperative cognitive cloud platform. Finally, the QoE guarantee scheme was proposed with the opportunity weight particle swarm optimization algorithm and collaborative cognitive cloud platform. The experimental results show that the proposed mechanism compared is superior to the QoE guarantee scheme based on cooperative cloud and QoE guarantee scheme based on particle swarm optimization, compared with optimization fitness and high cloud computing service execution efficiency and high throughput performance advantages.

Shared Authority Based Privacy-Preserving Authentication Protocol in Cloud Computing

Cloud computing is an emerging data interactive paradigm to realize users' data remotely stored in an online cloud server. Cloud services provide great conveniences for the users to enjoy the on-demand cloud applications without considering the local infrastructure limitations. During the data accessing, different users may be in a collaborative relationship, and thus data sharing becomes significant to achieve productive benefits. The existing security solutions mainly focus on the authentication to realize that a user's privative data cannot be illegally accessed, but neglect a subtle privacy issue during a user challenging the cloud server to request other users for data sharing. The challenged access request itself may reveal the user's privacy no matter whether or not it can obtain the data access permissions. In this paper, we propose a shared authority based privacy-preserving authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access authority is achieved by anonymous access request matching mechanism with security and privacy considerations (e.g., authentication, data anonymity, user privacy, and forward security); 2) attribute based access control is adopted to realize that the user can only access its own data fields; 3) proxy re-encryption is applied to provide data sharing among the multiple users. Meanwhile, universal composability (UC) model is established to prove that the SAPA theoretically has the design correctness. It indicates that the proposed protocol is attractive for multi-user collaborative cloud applications.

Preserving Privacy by Enhancing Security inCloud

Cloud computing is emerging as a prevalent data interactive paradigm to realize users’ data remotely stored in an online cloud server. Cloud services provide more benefits for the users to enjoy the on-demand cloud applications without considering the local limitations. When accessing the data, many users may be in a collaborative relationship, and thus sharing of is significant to achieve productive benefits. The present solutions for security focuses on the authentication to realize that a user’s privative data cannot be accessed if it is found to be unauthorized, but it eliminates a subtle privacy issue during a user challenging the cloud server to request other users when the data being shared. The challenge is the request for accessing reveals the user’s privacy no matter whether it has got the data access permissions. The distributed privacy-preserving authentication protocol (SAPA) which is authority based to address above privacy issue for cloud storage. shared authority based privacy-preserving authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access is achieved by anonymous access request matching mechanism with security and privacy considerations 2) attribute based access control is adopted to realize that the user can only access its own data fields; 3) proxy re-encryption is applied by the cloud server to provide data sharing among the many users. Meanwhile, universal compos ability (UC) model is established to prove that the SAPA theoretically has the correct design. This clearly shows that the proposed protocol realizing privacy-preserving data access authority sharing is impressive for multiple users collaborative cloud applications.

Incentive-based resource assignment and regulation for collaborative cloud services in community networks

Community networks are a successful example of a collective where communities operate ICT infrastructure based on the principle of reciprocal sharing of network bandwidth. Cloud computing, common in today's Internet, has however not materialised within community networks. We analyse in this paper socio-technical characteristics of community networks in order to derive scenarios for community clouds. Based on an architecture for such a community cloud, we implement a prototype for the incentive-driven resource assignment component and evaluate its behaviour experimentally. In simulations of large-scale community cloud scenarios we study the behaviour of the incentive mechanism in different configurations. Our evaluation gives insight into how the developed mechanisms regulate the consumption of cloud resources. Our results suggest a further integration of this regulation component into current cloud management platforms in order to open them up for the operation of an ecosystem of collaborative cloud services in community networks.

Collaborative design in the era of cloud computing

The paper describes the application of the latest Information Technologies in business processes such as design and manufacturing. More specifically it examines the use of cloud computing in the mechanical drawing and design process of an enterprise. It proposes a specific architecture with different servers, for the implementation of a collaborative cloud based Design system. Finally as an application example, it compares the operating cost of an industry’s design department before and after the use of the proposed system. This example uses a private cloud deployment model so that the comparison of the operating cost would be feasible. While public cloud may offer more functionality and economy, private cloud is best suitable to make conclusions and comparison between on-premise and cloud operation, because all of the cost is handled by the organization that uses it.

Multi‐tenancy authorization models for collaborative cloud services

SummaryThe cloud service model intrinsically caters to multiple tenants, most obviously not only in public clouds but also in private clouds for large organizations. Currently, most cloud service providers isolate user activities and data within a single tenant boundary with no or minimum cross‐tenant interaction. It is anticipated that this situation will evolve soon to foster cross‐tenant collaboration supported by Authorization as a Service. At present, there is no widely accepted model for cross‐tenant authorization. Recently, Calero et al. informally presented a multi‐tenancy authorization system (MTAS), which extends the well‐known role‐based access control model by building trust relations among collaborating tenants. In this paper, we formalize this MTAS model and propose extensions for finer‐grained cross‐tenant trust. We also develop an administration model for MTAS. We demonstrate the utility and practical feasibility of MTAS by means of an example policy specification in extensible access control markup language. To further test the metrics of the model, we develop a prototype system and conduct experiments on it. The result shows that the prototype has 12‐ms policy decision overhead on average and is scalable. We anticipate that researchers will develop additional multi‐tenant authorization models before eventual consolidation and convergence to standard industry practice. Copyright © 2014 John Wiley & Sons, Ltd.

Cloud Collaboration: Cloud-based Instruction for Business Writing Class

Cloud computing technologies, such as Google Docs, Adobe Creative Cloud, Dropbox, and Microsoft Windows Live, have become increasingly appreciated to the next generation digital learning tools. Cloud computing technologies encourage students’ active engagement, collaboration, and participation in their learning, facilitate group work, and support knowledge or information sharing among students. With the cloud features, learning can be accessed anywhere at any time and the world can be a classroom. Students can learn from anywhere and teachers can teach from anywhere. Cloud-based app features such as convenient and on-demand network access to a shared pool of files are indeed providing support for learning and instruction. Learning is now turned into anywhere learning and collaboration, both locally and globally. This study focuses the scope of potential of these cloud technologies for future educators to develop an understanding of how they can be embraced into the instruction. This is a case-study research (n= 28) into the use of cloud-based technology, Google Docs, to support learning in a face-to-face college business writing class. Data pertaining to student Google Docs use and activities will be collected. The first section of this study summarizes the definition of cloud computing technologies with examples of cloud resources. The second section determines the effects of technology, specifically the integration of cloud computing technologies with business English writing instruction, on students’ perception of teacher’s role. The following section identifies the potential benefits to learning and teaching from cloud-based learning environment.

Evacuation and Emergency Management Using a Federated Cloud

Contemporary disaster relief techniques fall significantly short in terms of efficiency and timeliness. In a postdisaster scenario, the generation and transmission of voluminous data at a high velocity impacts the communication framework. This work exploits the benefits of opportunistic communication and efficient big data management policies, focusing on the collaboration of multiple private and/or public clouds of diverse nature to perform damage assessment and determine the spatial distribution of the live victims and their physical and mental status. Based on the analytics, real-time decision making of the rescue operation is achieved.

협업을 위한 클라우드 스토리지에서의 사용자 인증과 데이터 보호에 관한 연구

Abstract The Collaborative Cloud Storage is that several members of collaborating group together use data stored in a storage. Therefore, it is obvious that it is more complicated and important to protect data stored in the sharing storage than general cloud storage, not Collaborative Cloud Storage. this paper proposes a method for user authentication and data protection. Key Words : Cloud, Storage, Collaboration, User Authentication, Data Protection * 이 논문은 2013학년도 세명대학교 교내학술연구비 지원에 의해 수행된 연구임 Received 21 July 2014, Revised 18 August 2014Accepted 20 September 2014Corresponding Author: Jae-Young Lee(Dept. of Liberal Education, Semyung University) Email: klitie@semyung.ac.krⒸ The Society of Digital Policy & Management. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is ISSN: 1738-1916 properly cited.

On Developing Fair and Orderly Cloud Markets

While cloud markets promise virtually unlimited resource supplies, standardized commodities and proper services, some providers may not be able to offer effectual physical capacity to serve large customers. A solution is cloud collaborations, in which multiple providers unite forces in order to conjointly offer capacities in the cloud markets. Supposably, both the Quality of Service and security properties of such collaborations will be determined by “the weakest link in the chain”, therefore resulting in a trade-off between the monetary aggregates, cumulative capacity and the non-functional attributes of a cloud collaboration. Based on previous research, this paper examines efficient composition of cloud collaborations from the broker's perspective, considering Quality of Service and information security requirements of multiple cloud providers and users and presents an exact approach CCCP-EXA.KOM for building cloud collaborations. Furthermore, it proposes a Mixed Integer Programming-based heuristic optimization approach CCCP-PRIOSORT.KOM and provides its quantitative evaluation in comparison with prior optimal approach.