Privacy-preserving outsourced classification in cloud computing

Li, Ping; Li, Jin; Huang, Zhengan; Gao, Chongzhi; Chen, Wenbin; Chen, Kai

doi:10.1007/s10586-017-0849-9

Cited by 206 publications

(107 citation statements)

References 31 publications

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“…The workflow scheduling problem is an inherited problem from the heterogeneous computing environments, for which different research efforts were made to address the scheduling problem [9][10][11]. However, heterogeneous computing environments are not easy to set up, and their capability of giving more uniform performance with less failure is quite limited in comparison to the cloud environments [12,13]. Moreover, the main objective of the various previous efforts in addressing the workflow scheduling problem in heterogeneous environments is to only minimize the finish time.…”

Section: Introductionmentioning

confidence: 99%

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Manasrah

Ali

2018

Wireless Communications and Mobile Computing

182

106

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Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.

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Section: Introductionmentioning

confidence: 99%

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Manasrah

Ali

2018

Wireless Communications and Mobile Computing

182

106

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“…In it, the data processing occurs in part at the network edge or between the cloud-to-end that can best meet customer necessities rather than entirely processing the data in a comparatively fewer number of massive clouds. Operators use the edge-of-things computing paradigm to provide network and computing services in a flexible and resource-efficient way [8][9][10][11]. Network virtualization is one of the main technologies and promoters of edge-of-things computing.…”

Section: Introductionmentioning

confidence: 99%

Reliable design for virtual network requests with location constraints in edge-of-things computing

Zhang

Sangaiah

2018

J Wireless Com Network

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How to efficiently map virtual networks (VNs) onto a shared physical network is a challenging issue in the field of network virtualization in edge-of-things computing. Since an efficient VN mapping approach can reduce network resource consumption, lower latency, and enhance service reliability, it is important for both customers and network service providers. In this paper, we study the problem of mapping multiple VNs with geographic location constraints onto a physical network while considering the survivability and reliability requirements of each VN request in edge-ofthings based data centers. We present the model of this problem and propose a Geographic-Guided Survivable Multiple VN Mapping (GG-SMVNM) algorithm to efficiently solve this problem, which simultaneously considers resource sharing and mapping VN links and nodes in edge-of-things computing. Furthermore, we conduct a large amount of simulations to validate and evaluate our proposed approach. The simulation results show that the proposed method is superior to the existing solution.

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“…With the popularity of the camera and development of video surveillance system [24], video has gradually become one of the main carrier of daily life records [9,19]. Nowadays, security cameras are deployed in various places.…”

Section: Introductionmentioning

confidence: 99%

Video abstract system based on spatial-temporal neighborhood trajectory analysis algorithm

Huang

Cai

et al. 2018

Multimed Tools Appl

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In this paper, a video abstract system based on spatial-temporal neighborhood trajectory analysis algorithm which is mainly used to process surveillance videos is proposed. The algorithm uses the spatial adjacency of foreground targets and tracks the spatialtemporal neighboring moving targets to get their whole trajectories in order to meet the requirement of processing speed and accuracy. The indicators consist of trajectory detection rate, trajectory tracking average continuity and video abstract processing speed are used to evaluate the effectiveness of the system. We compare the algorithm with the other three algorithms, and the results show that spatial-temporal neighborhood trajectory analysis algorithm has sufficient trajectory detection rate and processing speed for surveillance video abstraction.

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Privacy-preserving outsourced classification in cloud computing

Cited by 206 publications

References 31 publications

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Reliable design for virtual network requests with location constraints in edge-of-things computing

Video abstract system based on spatial-temporal neighborhood trajectory analysis algorithm

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