A high performance peer to cloud and peer model augmented with hierarchical secure communications

Sun, Zhe; Shen, Jun

doi:10.1016/j.jss.2012.08.062

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…In our pilot work [17], we proposed peer-to-cloud and peer-to-peer models for resource sharing and storage in service-oriented contexts. Such models can have higher upload and download speeds than a traditional cloud model, user model or peer-to-server-peer model, and can be more robust to the failures of peers or servers in the cloud environment [17,18].…”

Section: System Framework and Previous Workmentioning

confidence: 99%

“…Such models can have higher upload and download speeds than a traditional cloud model, user model or peer-to-server-peer model, and can be more robust to the failures of peers or servers in the cloud environment [17,18]. Hence, we adopt this design and apply its concept as the topology of the new system for micro open learning.…”

Section: System Framework and Previous Workmentioning

confidence: 99%

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Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

et al. 2017

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Abstract:Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs. In this paper, we focus on constructing a knowledge base to support the decision-making process of MLaaS. MLaas is built using a top-down approach. A conceptual graph-based ontology construction is first developed. An educational data mining and learning analytic strategy is then proposed for the data level. The learning resource adaptation still requires learners' historical information. To compensate for the absence of this information initially (aka 'cold start'), we set up a predictive ontology-based mechanism. As the first resource is delivered to the beginning of a learner's learning journey, the micro OER recommendation is also optimized using a tailored heuristic.

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Section: System Framework and Previous Workmentioning

confidence: 99%

Section: System Framework and Previous Workmentioning

confidence: 99%

Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

et al. 2017

Self Cite

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“…A performance evaluation model, which selects appropriate neighbor nodes with high performance during file distribution, was proposed in [10] to improve the file download efficiency in MP2P networks. In [11], the node in MP2P network selected its neighbors with maximum reputation value to forward the query walker during the search process, which solved the low resource search efficiency.…”

Section: Neighbor Selectionmentioning

confidence: 99%

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Liu¹,

Yang²,

Guan³

et al. 2017

JESTR

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Complex computational tasks, such as topology construction and neighbor selection, which affect the file download efficiency in mobile peer-to-peer (MP2P) networks, are difficult to perform given the limited performance of mobile nodes. Thus, a cloud-assisted cooperative mechanism (CACM) for file download was proposed in this study to address this problem. The CACM aimed to construct a stable network topology based on the improved ant colony optimization algorithm and select appropriate neighbor nodes by adopting multiple strategies in the download process. Moreover, the main computational tasks were offloaded from the mobile nodes to the cloud server. Simulation results indicate that the file download efficiency of the CACM is close to that of BitTorrent in the first download stage, and CACM performs better at the second stage. In addition, the average download time of the CACM is reduced by at least 5% compared with BitTorrent, and its performance remains unchanged with the expansion of the network scale. The finding in this study proves that the research of CACM is crucial in improving the file download efficiency in MP2P networks.

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“…In [8], the authors proposed a peer to cloud and peer (P2CP) system in which cloud servers can communicate among each other through three secure tunnels: (i) clouduser data transmission tunnel, (ii) clients data transmission tunnel, (iii) common data transmission tunnel.…”

Section: Secure Data Transmissionmentioning

confidence: 99%

Data and Application Security in Cloud

Barnwal

Ghosh

2014

Bio-Inspiring Cyber Security and Cloud Services: Trends and Innovations

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Cloud computing is an emerging technological paradigm, which provides computing resources as utility. Like other day-to-day utilities, cloud computing follows pay-as-you-use model, where users are charged according to the usage without regard to where the services are hosted or how they are delivered. Today, majority of companies follow an IT infrastructure-driven business model. With the growing demand, rise in customer base and market place competitions, companies prefer focusing on respective business policies and services they offer, rather than IT management overheads. Therefore, there is a high probability that the future of present day business model may shift to clouds where non-IT companies no longer have to procure, manage, and maintain IT resources. They will host applications and data to the servers, which are deployed by cloud providers, possibly in geographically dispersed locations. However, security is a major challenge before outsourcing any IT needs of business. As cloud provides a multi-tenant virtual computing environment, where competitive businesses may co-exist, hosting of sensitive information for mission-critical applications is of utmost concern. This chapter reviews the recent works reported specifically in the area of data and application security relevant to cloud computing. Some works which use biologically inspired phenomenon to manage security and load balancing in cloud environment, have also been studied. The aim of this chapter is to provide an insight into the present state-of-the-art cloud security problems, proposed solutions, and identify future research directions as well as scopes in various security issues.

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A high performance peer to cloud and peer model augmented with hierarchical secure communications

Cited by 7 publications

References 13 publications

Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Data and Application Security in Cloud

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