Credible and economic multimedia service optimization based on game theoretic in hybrid cloud networks

Cao, Tengfei; Zhong, Lujie; Xiao, Han; Song, Chengru; Yang, Shujie; Xu, Changqiao

doi:10.1002/ett.3779

Cited by 13 publications

(9 citation statements)

References 35 publications

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“…Cao et al 34 have presented a new multimedia service optimization mechanism that is introduced to gather the fore mentioned user requirements while ensuring service reliability. Initially, a credible system is intended to aid mobile users differentiate between trusted cloud providers.…”

Section: Related Work: a Brief Reviewmentioning

confidence: 99%

A secured authentication and DSM‐KL ascertained performance optimization of a hybrid block chain‐enabled framework for a multiple WSN

Baskaran¹,

Kannaiah

Ramanujam

2021

Int J Communication

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Summary Block chain is extensively seen as a potential alternative in the safety and efficiency problems of the vast internet of things (IoT) data to allow safe and successful data storage/processing/sharing. In this manuscript, a secured authentication and deep slime mould optimized kernel learning (DSM‐KL) ascertained performance optimization of a hybrid block chain‐enabled framework for a multiple wireless sensor network (WSN) is proposed to recover data security performance and efficiency. To reflect the reality of the multi‐WSN network better, local block chain and public block chain are deployed, and a hybrid block chain model is created as per the various capabilities and energy of different nodes. A multi‐WSN network model is intended. It has numerous nodes on IoT. Based on dissimilar functions of nodes, the IoT nodes are divided into base stations, cluster heads and ordinary nodes based on its capabilities that facilitate management and cooperation of nodes. A DSM‐KL algorithm for dynamically selecting/adjusting block producer, consensus algorithm, block size and block interval to recover efficiency to handle both dynamic and broad dimensional properties of IoT systems is designed. The simulation process is executed in the MATLAB platform. The proposed DSM‐KL attains lower drop 27.53%, higher delivery ratio 28.56%, lower drop 28.64%, lower energy depletion rate 38.63%, higher network active time 38.47%, lower overhead 26.47% and higher throughput 27.67%, and the performances are compared with the existing methods such as deep reinforcement learning (DRL) and block chain and reinforcement learning (RLBC), respectively.

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Section: Related Work: a Brief Reviewmentioning

confidence: 99%

A secured authentication and DSM‐KL ascertained performance optimization of a hybrid block chain‐enabled framework for a multiple WSN

Baskaran¹,

Kannaiah

Ramanujam

2021

Int J Communication

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“…A tree search algorithm is used for choosing the optimal SIDs, DIDs, and radio resource blocks to achieve maximum energy efficiency for DIDs. In Reference 15, a secure mechanism is provided to transfer multimedia data in hybrid cloud networks. Edge computing and cloud computing provides services to mobile users collaboratively and competitively.…”

Section: Introductionmentioning

confidence: 99%

A systematic survey on internet of things: Energy efficiency and interoperability perspective

Rana

Singh

2020

Trans Emerging Tel Tech

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With the provision of rapid advancement in smart devices used in various technological fields exponentially increases the heterogeneity and energy consumption in internet of things (IoT). The technological leap in information and communication technology instigates the heterogeneity in smart devices, frameworks, architectures, communication technologies, and various industrial and nonindustrial applications. Therefore, a detailed taxonomy of IoT is proposed covering the diverse aspect of IoT lacking interoperability and energy efficiency. Existing research lacks the root causes of heterogeneity and energy consumption at the industrial and technological level. Keeping this in view, our research identified industrial integration and technological challenges. Moreover, we explore the effect on IoT devices when different types of energy harvesters are connected with IoT devices. Our comprehensive research addresses the various issues such as resource management, fog data analytics, energy consumption, heterogeneity, scalability, and the role of quality of service, data science, machine learning to accomplish interoperability and energy efficiency in IoT.

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“…In implementing various applications of the IoT, security 9 and efficiency 10,11 are mostly concerned. To widely collect sensory data and construct efficient MCS applications, multidimensional sensory data are often aggregated in the cloud platform.…”

Section: Introductionmentioning

confidence: 99%

A verifiable and privacy‐preserving multidimensional data aggregation scheme in mobile crowdsensing

Jiang

Zhao

Tang

et al. 2020

Trans Emerging Tel Tech

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Mobile crowdsensing has become a popular data collection paradigm and has been extensively studied. Since the analysis of sensory data usually reveals privacy of mobile users, data aggregation technology is widely used to avoid privacy disclosure. However, traditional privacy‐preserving data aggregation schemes cannot provide aggregate statistics of multidimensional data in fine‐grained areas or resist collusive attacks. Moreover, the cloud platform is not fully trusted, and it is challenging to verify the correctness of data aggregation results. To provide privacy‐preserving multidimensional statistics within fine‐grained areas and verify results of data aggregation, we propose a verifiable privacy‐preserving data aggregation scheme in this article, which is based on data double‐masking, Shamir's secret sharing, and bilinear mapping. Specifically, a key agreement is utilized to establish mask seeds for users, while the users are required to extend mask values and generate the verification key with bilinear mapping. The cloud platform aggregates masked data and provides proof of computational results. Theoretical analysis demonstrates our scheme can protect data and location privacy, verify the aggregation results, and improve the rubustness to failure. The simulation results show that the computational overhead of mobile devices by using the proposed anticollusion scheme is better than that of homomorphic encryption. In addition, the computational complexity of task requesters is less than that of the PVPA scheme for verification of multidimensional aggregation results.

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Credible and economic multimedia service optimization based on game theoretic in hybrid cloud networks

Cited by 13 publications

References 35 publications

A secured authentication and DSM‐KL ascertained performance optimization of a hybrid block chain‐enabled framework for a multiple WSN

A secured authentication and DSM‐KL ascertained performance optimization of a hybrid block chain‐enabled framework for a multiple WSN

A systematic survey on internet of things: Energy efficiency and interoperability perspective

A verifiable and privacy‐preserving multidimensional data aggregation scheme in mobile crowdsensing

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