Social Cloud Computing: A Vision for Socially Motivated Resource Sharing

2012 ◽  
Vol 5 (4) ◽  
pp. 551-563 ◽  
Author(s):  
Kyle Chard ◽  
Kris Bubendorfer ◽  
Simon Caton ◽  
Omer F. Rana
2014 ◽  
Vol E97.B (12) ◽  
pp. 2668-2679 ◽  
Author(s):  
Wei LIU ◽  
Ryoichi SHINKUMA ◽  
Tatsuro TAKAHASHI

10.29007/848q ◽  
2019 ◽  
Author(s):  
Mohammed O. Alannsary ◽  
Yasser M. Hausawi

Cloud computing is a relatively mature and robust technology that has promised its users with several proven advantages, such as cost reduction, immediate scalability, and resource sharing. The Cloud is built based on providing resources as services, such as providing Infrastructure, Platform, and Software as a Service. Such approach enables Cloud users to access these services based on their demand. In the government sector of Saudi Arabia, adoption and utilization of the Cloud is minimal. Despite being adopted officially, the Cloud has not been yet implemented properly. In our work we introduce how the government sector in Saudi Arabia can adopt and implement a Cloud Solution through utilizing its services and while considering issues related to its security.


2021 ◽  
Author(s):  
◽  
Kyle Chard

<p>The computational landscape is littered with islands of disjoint resource providers including commercial Clouds, private Clouds, national Grids, institutional Grids, clusters, and data centers. These providers are independent and isolated due to a lack of communication and coordination, they are also often proprietary without standardised interfaces, protocols, or execution environments. The lack of standardisation and global transparency has the effect of binding consumers to individual providers. With the increasing ubiquity of computation providers there is an opportunity to create federated architectures that span both Grid and Cloud computing providers effectively creating a global computing infrastructure. In order to realise this vision, secure and scalable mechanisms to coordinate resource access are required. This thesis proposes a generic meta-scheduling architecture to facilitate federated resource allocation in which users can provision resources from a range of heterogeneous (service) providers. Efficient resource allocation is difficult in large scale distributed environments due to the inherent lack of centralised control. In a Grid model, local resource managers govern access to a pool of resources within a single administrative domain but have only a local view of the Grid and are unable to collaborate when allocating jobs. Meta-schedulers act at a higher level able to submit jobs to multiple resource managers, however they are most often deployed on a per-client basis and are therefore concerned with only their allocations, essentially competing against one another. In a federated environment the widespread adoption of utility computing models seen in commercial Cloud providers has re-motivated the need for economically aware meta-schedulers. Economies provide a way to represent the different goals and strategies that exist in a competitive distributed environment. The use of economic allocation principles effectively creates an open service market that provides efficient allocation and incentives for participation. The major contributions of this thesis are the architecture and prototype implementation of the DRIVE meta-scheduler. DRIVE is a Virtual Organisation (VO) based distributed economic metascheduler in which members of the VO collaboratively allocate services or resources. Providers joining the VO contribute obligation services to the VO. These contributed services are in effect membership “dues” and are used in the running of the VOs operations – for example allocation, advertising, and general management. DRIVE is independent from a particular class of provider (Service, Grid, or Cloud) or specific economic protocol. This independence enables allocation in federated environments composed of heterogeneous providers in vastly different scenarios. Protocol independence facilitates the use of arbitrary protocols based on specific requirements and infrastructural availability. For instance, within a single organisation where internal trust exists, users can achieve maximum allocation performance by choosing a simple economic protocol. In a global utility Grid no such trust exists. The same meta-scheduler architecture can be used with a secure protocol which ensures the allocation is carried out fairly in the absence of trust. DRIVE establishes contracts between participants as the result of allocation. A contract describes individual requirements and obligations of each party. A unique two stage contract negotiation protocol is used to minimise the effect of allocation latency. In addition due to the co-op nature of the architecture and the use of secure privacy preserving protocols, DRIVE can be deployed in a distributed environment without requiring large scale dedicated resources. This thesis presents several other contributions related to meta-scheduling and open service markets. To overcome the perceived performance limitations of economic systems four high utilisation strategies have been developed and evaluated. Each strategy is shown to improve occupancy, utilisation and profit using synthetic workloads based on a production Grid trace. The gRAVI service wrapping toolkit is presented to address the difficulty web enabling existing applications. The gRAVI toolkit has been extended for this thesis such that it creates economically aware (DRIVE-enabled) services that can be transparently traded in a DRIVE market without requiring developer input. The final contribution of this thesis is the definition and architecture of a Social Cloud – a dynamic Cloud computing infrastructure composed of virtualised resources contributed by members of a Social network. The Social Cloud prototype is based on DRIVE and highlights the ease in which dynamic DRIVE markets can be created and used in different domains.</p>


2021 ◽  
Vol 11 (4) ◽  
pp. 80-99
Author(s):  
Syed Imran Jami ◽  
Siraj Munir

Recent trends in data-intensive experiments require extensive computing and storage resources that are now handled using cloud resources. Industry experts and researchers use cloud-based services and resources to get analytics of their data to avoid inter-organizational issues including power overhead on local machines, cost associated with maintaining and running infrastructure, etc. This article provides detailed review of selected metrics for cloud computing according to the requirements of data science and big data that includes (1) load balancing, (2) resource scheduling, (3) resource allocation, (4) resource sharing, and (5) job scheduling. The major contribution of this review is the inclusion of these metrics collectively which is the first attempt towards evaluating the latest systems in the context of data science. The detailed analysis shows that cloud computing needs research in its association with data-intensive experiments with emphasis on the resource scheduling area.


2019 ◽  
pp. 592-620
Author(s):  
Poonam Saini ◽  
Awadhesh Kumar Singh

Resource sharing is the most attractive feature of distributed computing. Information is also a kind of resource. The portable computing devices and wireless networks are playing a dominant role in enhancing the information sharing and thus in the advent of many new variants of distributed computing viz. ubiquitous, grid, cloud, pervasive and mobile. However, the open and distributed nature of Mobile Ad Hoc Networks (MANETs), Vehicular Ad Hoc Networks (VANETs) and cloud computing systems, pose a threat to information that may be coupled from one user (or program) to another. The chapter illustrates the general characteristics of ad hoc networks and computing models that make obligatory to design secure protocols in such environments. Further, we present a generic classification of various threats and attacks. In the end, we describe the security in MANETs, VANETs and cloud computing. The chapter concludes with a description of tools that are popularly used to analyze and access the performance of various security protocols.


Author(s):  
Punit Gupta ◽  
Ravi Shankar Jha

With increase of information sharing over the internet or intranet, we require techniques to increase the availability of shared resource over large number of users trying to access the resources at the same time. Many techniques are being proposed to make access easy and more secure in distributed environment. Information retrieval plays an important to serve the most reliant data in least waiting, this chapter discuses all such techniques for information retrieval and sharing over the cloud infrastructure. Cloud Computing services provide better performance in terms of resource sharing and resource access with high reliability and scalability under high load.


2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yazan Al-Issa ◽  
Mohammad Ashraf Ottom ◽  
Ahmed Tamrawi

Cloud computing is a promising technology that is expected to transform the healthcare industry. Cloud computing has many benefits like flexibility, cost and energy savings, resource sharing, and fast deployment. In this paper, we study the use of cloud computing in the healthcare industry and different cloud security and privacy challenges. The centralization of data on the cloud raises many security and privacy concerns for individuals and healthcare providers. This centralization of data (1) provides attackers with one-stop honey-pot to steal data and intercept data in-motion and (2) moves data ownership to the cloud service providers; therefore, the individuals and healthcare providers lose control over sensitive data. As a result, security, privacy, efficiency, and scalability concerns are hindering the wide adoption of the cloud technology. In this work, we found that the state-of-the art solutions address only a subset of those concerns. Thus, there is an immediate need for a holistic solution that balances all the contradicting requirements.


2018 ◽  
Vol 2018 ◽  
pp. 1-17
Author(s):  
Imad Al-Samman ◽  
Reham Almesaeed ◽  
Angela Doufexi ◽  
Mark Beach

Responding to the unprecedented challenges imposed by the 5G technologies, mobile operators have given significant attention to Heterogeneous Cloud Radio Access Networks (H-CRAN) due to their beneficial features of performing optimization, cost effectiveness, and improving spectral and energy efficiency performance. H-CRAN inherits the attractive benefits of Heterogeneous Networks (HetNet) and the cloud computing by facilitating interference mitigation, scalability, and radio resource control. Consequently, H-CRAN is proposed in this article as a cost-effective potential solution to alleviate intertier interference and improve cooperative processing gains in HetNets by employing cloud computing. H-CRAN can provide efficient resource sharing at the spectrum, network, and infrastructure levels. Therefore, this article proposes H-CRAN cooperative interference mitigation method that enhances the time sharing among Radio Remote Heads (RRH) users. The study proposes an enhanced Almost Blank Subframe (ABSF) technique to increase the SINR and throughput of the small-cell (low power base station) and macrocell users. Simulation results show that the proposed Dynamic Programming-Diverse Almost Blank Subframe (ABSF) Pattern (DP-DAP) scheme improved the macro- and small-cell users up to 56% and 35%, respectively, as compared to other state-of-the-art ABSF schemes.


2013 ◽  
Vol 347-350 ◽  
pp. 2793-2798
Author(s):  
Lin Na Huang ◽  
Bao Guo Gu

Cloud computing, with superior computing power, low-cost and high-security, will be applied to the resource-sharing area of E-government information with great significance and value. From the point of theory, technology and practice, it is scientifically feasible to build a cloud-based E-government information resource-sharing platform, and some areas are actively building this. This paper, through analysis of the problems existing in Cangzhou E-Government and through the design of the E-government cloud computing model, puts forward new ways to explore the development of regional E-government based on cloud computing.


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