Optimal Computing Resource Management Based on Utility Maximization in Mobile Crowdsourcing

Meng, Haoyu; Zhu, Ying; Deng, Ruilong

doi:10.1155/2017/1494851

Cited by 5 publications

(4 citation statements)

References 34 publications

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“…In computing resource sharing, Meng, Zhu [174] proposed the following pricing approach: the intermediary first announces a basic price, then providers and requesters update their optimal amount of supply and demand; the price is also updated in a timely manner, and this process is repeated until the price is stable. Additionally, Wang, Wang [173] proposed an approach based on computational latency, wherein the quality-of-experience performance is considered.…”

Section: Intermediary Pricingmentioning

confidence: 99%

See 1 more Smart Citation

A Systematic Literature Review on Pricing Strategies in the Sharing Economy

Yang

Xia

2021

Sustainability

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As an emerging business model, the sharing economy has gained a large amount of academic attention; the pricing problem in the sharing economy has also been widely investigated. Aiming to capture the current state-of-the-art research on pricing strategies in the sharing economy and foreseeing directions for future research, this article conducts a systematic literature review and content analysis of 158 articles from the Scopus and Web of Science databases. As a result, first, this review proposes an extended definition covering B2C and C2C models and a model structure covering the entire supply chain, based on which 158 articles are categorized into nine sub-models covering 30 scenarios. Second, the general characteristics (i.e., research fields, time and journal distributions, research themes and scenarios) and technical details (i.e., theories, methodologies, approaches, models, and conclusions) of the 158 articles are reviewed and summarized by the pricing party, business mode, and scenario. Finally, this review proposes some future research directions of existing scenarios from the perspectives of information asymmetry, market competition, and empirical approaches, and discusses some extensions, including uninvestigated scenarios and COVID-19-related topics; correspondingly, this review suggests some analytical models and empirical approaches that can be employed to fill these gaps. The proposed research directions and corresponding approaches can be references for future research.

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Section: Intermediary Pricingmentioning

confidence: 99%

“…Additionally, Wang, Wang [173] proposed an approach based on computational latency, wherein the quality-of-experience performance is considered. Both approaches maximize all participants' profits and ensure system efficiency [173,174].…”

Section: Intermediary Pricingmentioning

confidence: 99%

A Systematic Literature Review on Pricing Strategies in the Sharing Economy

Yang

Xia

2021

Sustainability

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“…The paper did not use realistic IoT and cloud scenarios. In [21], energy-delay computing is tended to in a task allocation setting. Given the significance of cost and energy in delay-delicate interactions for mentioning and giving processing resources, an ideal strategy for delay-sensitive associations was introduced.…”

Section: Related Workmentioning

confidence: 99%

Performance Management in Clustered Edge Architectures Using Particle Swarm Optimization

Azimi

Pahl

Shirvani

2021

Communications in Computer and Information Science

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Recently distributed computing capacities are brought to the edge of the Internet, permitting Internet-of-Things applications to process calculation all the more locally and subsequently more productively and this has brought a totally different scope of apparatuses and usefulness. This instrument can The most significant characterizing highlights of edge processing are low latency, location awareness, wide geographic distribution, versatility, support for countless nodes, etc. We want to likely limit the latency and delay in edge-based structures. We center around a progressed compositional setting that considers communication and processing delays and the management effort notwithstanding a real request execution time in an operational efficiency situation. Our design is based on multi-cluster edge layer with nearby autonomous edge node clusters. We will contend that particle swarm optimization as a bio-motivated optimization approach is a perfect candidate for distributed IoT load handling in self-managed edge clusters. By designing a controller and utilizing a particle swarm optimization algorithm, we show that delay and end-to-end latency can be reduced.

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“…A resource optimization method in [31] was designed for content delivery, using some discrete time slots or transmission opportunities to deliver media contents to the service points when the network connectivity is intermittent. In addition, Meng et al proposed an optimal real-time pricing strategy for computer resource management in [32], where computing resources are managed to benefit the overall system. However, these works mainly focus on single aspect of system resource or management of homogeneous device, while our paper proposes an integrated management framework, from the perspective of heterogeneous equipment management, multi-type resource management and so on.…”

Section: Framework For Cap Problemsmentioning

confidence: 99%

CrowdOS: A Ubiquitous Operating System for Crowdsourcing and Mobile Crowd Sensing

Liu

Guo

et al. 2019

Preprint

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With the rise of crowdsourcing and mobile crowdsensing techniques, a large number of crowdsourcing applications or platforms (CAP) have appeared. In the mean time, CAP-related models and frameworks based on different research hypotheses are rapidly emerging, and they usually address specific issues from a certain perspective. Due to different settings and conditions, different models are not compatible with each other. However, CAP urgently needs to combine these techniques to form a unified framework. In addition, these models needs to be learned and updated online with the extension of crowdsourced data and task types, thus requiring a unified architecture that integrates lifelong learning concepts and breaks down the barriers between different modules. This paper draws on the idea of ubiquitous operating systems and proposes a novel OS (CrowdOS), which is an abstract software layer running between native OS and application layer. In particular, based on an in-depth analysis of the complex crowd environment and diverse characteristics of heterogeneous tasks, we construct the OS kernel and three core frameworks including Task Resolution and Assignment Framework (TRAF ), Integrated Resource Management (IRM), and Task Result quality Optimization (TRO). In addition, we validate the usability of CrowdOS, module correctness and development efficiency. Our evaluation further reveals TRO brings enormous improvement in efficiency and a reduction in energy consumption.

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Optimal Computing Resource Management Based on Utility Maximization in Mobile Crowdsourcing

Cited by 5 publications

References 34 publications

A Systematic Literature Review on Pricing Strategies in the Sharing Economy

A Systematic Literature Review on Pricing Strategies in the Sharing Economy

Performance Management in Clustered Edge Architectures Using Particle Swarm Optimization

CrowdOS: A Ubiquitous Operating System for Crowdsourcing and Mobile Crowd Sensing

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