OPRC: An Online Personalized Reputation Calculation Model in Service-Oriented Computing Environments

Du, Xin; Cai, Wei; Zhu, Changsheng; Chen, Yindong

doi:10.1109/access.2019.2925778

Cited by 26 publications

(7 citation statements)

References 29 publications

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“…x q and use this value as the public key of node x, as shown in Equation (5). And the private key of node x is generated by Equation ( 6).…”

Section: Generate Public and Private Keysmentioning

confidence: 99%

“…1,2 In addition, intelligent systems are concerned with the problem of how systems interact with human users in dynamic physical environments. [3][4][5] The research of intelligent systems still confronts many challenges in recent days. For example, searching for the best path to the target is computationally intensive and is performed in a large state space.…”

Section: Introductionmentioning

confidence: 99%

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IPSadas: Identity‐privacy‐aware secure and anonymous data aggregation scheme

Ren

Wang

et al. 2021

Int J of Intelligent Sys

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Intelligent systems are technologically advanced machines that can sense and respond to the surrounding environment. They have been widely used in medicine, military, transportation, automation, and other fields. However, when these systems deal with their environments, problems such as leakage of identities may occur. The adversary can damage the system communication and attack important nodes. To handle resource-constrained wireless sensor network environments, we propose a secure and anonymous data aggregation scheme. First, based on the bilinear mapping operation and onion routing concepts, we propose a key negotiation and secure information transmission scheme, which conducts confidential transmission and anonymous forwarding of messages in data aggregation. Second, an aggregation routing scheme based on link direction and residual energy is proposed to pledge messages that can arrive the base station without passing through many nodes, which saves network resources to a certain extent. Third, on the basis of the first two contributions, we propose an identity-privacy-aware secure and anonymous data aggregation scheme that protects the identity's privacy. This scheme can conceal the real identity of important nodes and protect the anonymity of messages and link relationships. In addition, an anonymous identity

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“…x q and use this value as the public key of node x, as shown in Equation (5). And the private key of node x is generated by Equation ( 6).…”

Section: Generate Public and Private Keysmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IPSadas: Identity‐privacy‐aware secure and anonymous data aggregation scheme

Ren

Wang

et al. 2021

Int J of Intelligent Sys

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show abstract

“…• The stay time of vehicle: The stay time refers to the time from the beginning to the moment the vehicle leaves the vehicular cloud. Since our hypothetical scene is a highway, we use the freeway mobility model [28] to mimic the behavior of the vehicles. Then the trajectory…”

Section: B Candidate Vehiclesmentioning

confidence: 99%

V2V-Based Task Offloading and Resource Allocation in Vehicular Edge Computing Networks

He¹,

Wang²,

Du³

et al. 2021

Preprint

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In the research and application of vehicle ad hoc networks (VANETs), it is often assumed that vehicles obtain cloud computing services by accessing to roadside units (RSUs). However, due to the problems of insufficient construction quantity, limited communication range and overload of calculation load of roadside units, the calculation mode relying only on vehicle to roadside units is difficult to deal with complex and changeable calculation tasks. In this paper, when the roadside unit is missing, the vehicle mobile unit is regarded as a natural edge computing node to make full use of the excess computing power of mobile vehicles and perform the offloading task of surrounding mobile vehicles in time. In this paper, the OPFTO framework is designed, an improved task allocation algorithm HGSA is proposed, and the pre-filtering process is designed with full consideration of the moving characteristics of vehicles. In addition, vehicle simulation experiments show that the proposed strategy has the advantages of low delay and high accuracy compared with other task scheduling strategies, which provides a reference scheme for the construction of Urban Intelligent Transportation in the future.

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“…The formulation of the optimal data placement is a NPhard problem with constraints, such as the storage of these datacenters and placement cost of datasets for different datacenters and so on. Contemporarily, Several studies have mapped it to the knapsack packing problem [11], [12], [13], [14], and hence, to obtain the optimal solution to this problem, they proposed several methods using heuristic algorithms, such as the genetic algorithm (GA) and particle swarm optimization (PSO). These evolutionary computationary algorthms, which simulate the behaviors of birds, nuts, or fishes in continuous search spaces, are well-suited for solving NP-hard problems.…”

Section: Introductionmentioning

confidence: 99%

A Novel Data Placement Strategy for Data-Sharing Scientific Workflows in Heterogeneous Edge-Cloud Computing Environments

Tang

Lu³

et al. 2020

2020 IEEE International Conference on Web Services (ICWS)

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The heterogeneous edge-cloud computing paradigm can provide a more optimal direction to deploy scientific workflows than traditional distributed computing or cloud computing environments. Due to the different sizes of scientific datasets and some of these datasets must keep private, it is still a difficult problem to finding an data placement strategy that can minimize data transmission as well as placement cost. To address this issue, this paper combines advantages of both edge and cloud computing to construct a data placement model, which can balance data transfer time and data placement cost using intelligent computation. The most difficult research challenge the model solved is to consider many constrain in this hybrid computing environments, which including shared datasets within individual and among multiple workflows across various geographical regions. According to the constructed model, the study propose a new data placement strategy named DE-DPSO-DPS, which using a discrete particle swarm optimization algorithm with differential evolution (DE-DPSO-DPA) to distribute these scientific datasets. The strategy also not only consider the characteristics such as the number and storage capacity of edge micro-datacenters, the bandwidth between different datacenters and the proportion of private datasets, but also analysis the performance of algorithm during the workflows execution. Comprehensive experiments are designed in simulated heterogeneous edge-cloud computing environments demonstrate that the data placement strategy can effectively reduce the data transmission time and placement cost as compared to traditional strategies for data-sharing scientific workflows.

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OPRC: An Online Personalized Reputation Calculation Model in Service-Oriented Computing Environments

Cited by 26 publications

References 29 publications

IPSadas: Identity‐privacy‐aware secure and anonymous data aggregation scheme

IPSadas: Identity‐privacy‐aware secure and anonymous data aggregation scheme

V2V-Based Task Offloading and Resource Allocation in Vehicular Edge Computing Networks

A Novel Data Placement Strategy for Data-Sharing Scientific Workflows in Heterogeneous Edge-Cloud Computing Environments

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