Review on Offloading of Vehicle Edge Computing

Wang, Mingwei; Yi, Hualing; Jiang, Feng; Li, Gang; Gao, Min

doi:10.37965/jait.2022.0120

Cited by 18 publications

(6 citation statements)

References 12 publications

(13 reference statements)

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“…The taxonomy presented in the work offers valuable insights and classifications, which greatly contribute to the comprehension and advancement of DNA-based security models. Wang et al [85] conduct a comprehensive analysis focusing on offloading in vehicle edge computing. They provide valuable information about the challenges and state-of-the-art techniques in this area.…”

Section: Data Security and Quantum Computingmentioning

confidence: 99%

A Novel Quantum Hash-Based Attribute-Based Encryption Approach for Secure Data Integrity and Access Control in Mobile Edge Computing-Enabled Customer Behavior Analysis

Singamaneni,

Muhammad,

Ali

2024

IEEE Access

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The domain of Mobile Edge Computing (MEC) has seen rapid growth, making consumer behavior research an essential element in many applications. Nevertheless, in MEC systems that are decentralized and have limited resources, challenges arise in ensuring both data integrity and access control. This paper introduces a new technique called Quantum Hash-Based Attribute-Based Encryption (QH-ABE) to address these issues. Previously, there were several methods available to guarantee data integrity and access control in MEC. However, these systems had limits in managing large and intricate datasets, lacked a standardized protocol for revocation, and incurred significant computational cost. We were prompted by these restrictions to suggest a more efficient technique, which included the use of the QH-ABE method in our study. The suggested solution integrates hash functions with quantum computing concepts to enhance security and control access in MEC-enabled consumer behavior research. The suggested technique provides several benefits compared to traditional hash algorithms by using hash functions. In this technique, we introduce a Recursive Non-Linear Polynomial graph-centered Integrity Algorithm (RNLPIA). RNLPIA enhances security by thwarting covert alterations to data and guaranteeing tamper-evident measures via the generation of unique hash values derived from the content of the data. The suggested method's efficacy and efficiency are proved by a comprehensive experimental assessment, highlighting its capability to fulfill the data integrity and access control needs of MEC situations. The performance of our technology showcases its potential and paves the way for using quantum computing technologies for accessing control and data security. This work contributes to the progress of privacy-preserving, secure analysis of consumer behavior in the dynamic MEC environment.INDEX TERMS Access control, Attribute-based encryption (ABE), Customer behavior analysis, Data integrity and security, Mobile edge computing (MEC), Quantum key distribution.

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Section: Data Security and Quantum Computingmentioning

confidence: 99%

A Novel Quantum Hash-Based Attribute-Based Encryption Approach for Secure Data Integrity and Access Control in Mobile Edge Computing-Enabled Customer Behavior Analysis

Singamaneni,

Muhammad,

Ali

2024

IEEE Access

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“…These advancements include deep learning, programming question generation, and automated control and calibration [78][79][80][81][82][83][84][85][86][87]. HPC also continues to expand along with computing offload [88]. As the technology behind these systems deepens, so does the ability to perform these analyses with more efficiency and detail.…”

Section: Future Improvementsmentioning

confidence: 99%

Reduced-Dimension Surrogate Modeling to Characterize the Damage Tolerance of Composite/Metal Structures

Arndt,

Crusenberry,

Heng

et al. 2023

Modelling

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Complex engineering models are typically computationally demanding and defined by a high-dimensional parameter space challenging the comprehensive exploration of parameter effects and design optimization. To overcome this curse of dimensionality and to minimize computational resource requirements, this research demonstrates a user-friendly approach to formulating a reduced-dimension surrogate model that represents a high-dimensional, high-fidelity source model. This approach was developed specifically for a non-expert using commercially available tools. In this approach, the complex physical behavior of the high-fidelity source model is separated into individual, interacting physical behaviors. A separate reduced-dimension surrogate model is created for each behavior and then all are summed to formulate the reduced-dimension surrogate model representing the source model. In addition to a substantial reduction in computational resources and comparable accuracy, this method also provides a characterization of each individual behavior providing additional insight into the source model behavior. The approach encompasses experimental testing, finite element analysis, surrogate modeling, and sensitivity analysis and is demonstrated by formulating a reduced-dimension surrogate model for the damage tolerance of an aluminum plate reinforced with a co-cured bonded E-glass/epoxy composite laminate under four-point bending. It is concluded that this problem is difficult to characterize and breaking the problem into interacting mechanisms leads to improved information on influential parameters and efficient reduced-dimension surrogate modeling. The disbond damage at the interface between the resin and metal proved the most difficult mechanism for reduced-dimension surrogate modeling as it is only engaged in a small subspace of the full parameter space. A binary function was successful in engaging this damage mechanism when applicable based on the values of the most influential parameters.

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“…The first paper presents a survey on the main offloading schemes and methods in the Vehicle Edge Computing field and a classification of the current offloading of computing tasks into different categories. The paper also discusses the prospect of Vehicle Edge Computing [3]. (ii) Boolean logic specifies combinations of true and false values to make a logical conclusion.…”

Section: Preview Of the Studies In This Issuementioning

confidence: 99%

Latest Advances on AI and Robotics Applications

Silva

2022

JAIT

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The applications of artificial intelligence and robotics, their associated technologies, and their integration continue to grow and are seen in more and more diverse fields. With these considerations in mind, this issue of the Journal of Artificial Intelligence and Technology presents five state-of-the-art peer-reviewed contributions, ranging from theory to prototyping, and covering several distinct application topics.

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Review on Offloading of Vehicle Edge Computing

Cited by 18 publications

References 12 publications

A Novel Quantum Hash-Based Attribute-Based Encryption Approach for Secure Data Integrity and Access Control in Mobile Edge Computing-Enabled Customer Behavior Analysis

A Novel Quantum Hash-Based Attribute-Based Encryption Approach for Secure Data Integrity and Access Control in Mobile Edge Computing-Enabled Customer Behavior Analysis

Reduced-Dimension Surrogate Modeling to Characterize the Damage Tolerance of Composite/Metal Structures

Latest Advances on AI and Robotics Applications

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