A novel analysis of delay and power consumption for polling schemes in the IoT

Wei

Wireless Communications and Mobile Computing

2021

Although the Chinese economy has developed rapidly since the reform and opening up, the income distribution gap is widening year by year. The final social income distribution pattern is highly dependent on the primary distribution pattern. Therefore, the changing trend and influencing factors of labor income share have become the focus of academic research and the focus of government attention. Based on this, this article proposes enterprise financing based on Internet of Things data analysis technology. Studies on the impact of restraints on labor income shares will help further research on the impact of corporate financial restraints on future labor income shares. Based on the financial data reports published in the CCER database and the company’s IPO prospectus and annual report, this paper discusses whether the company’s key business products belong to the Internet of Things’ key technology application categories. Take 226 IoT companies as the research objects of this article, and conduct a secondary screening. The final survey sample is used to investigate the impact of corporate funding constraints on labor income share. Tests have proved that among the 179 resource-based enterprises undergoing transformation, 109 enterprises have undergone intraindustry transformation, accounting for 48.23% of the overall sample and 60.89% of the sample of transformed enterprises. Downstream expansion makes the business industry expand. This shows that funding constraints have a negative impact on labor income share. This is primarily the result of the impact of the long-term debt-to-asset ratio on labor income share.

Section: Corporate Financing Constraintsmentioning

confidence: 99%

Impact of Enterprise Financing Constraints on Labor Income Share Based on Internet of Things Data Analysis Technology

Wei

Wireless Communications and Mobile Computing

2021

“…Additionally, current communication technologies cannot support a large number of user terminals. In cellular networks, the spectrum eciency drops drastically with increasing user density [2,3]. To meet the demand for data computing services, a large number of large-scale data centers have been deployed.…”

Section: Introductionmentioning

confidence: 99%

Resource Management Framework Based on the Stackelberg Game in Vehicular Edge Computing

Wang

et al. 2020

Complexity

With the emergence and development of the Internet of Vehicles (IoV), quick response time and ultralow delay are required. Cloud computing services are unfavorable for reducing delay and response time. Mobile edge computing (MEC) is a promising solution to address this problem. In this paper, we combined MEC and IoV to propose a specific vehicle edge resource management framework, which consists of fog nodes (FNs), data service agents (DSAs), and cars. A dynamic service area partitioning algorithm is designed to balance the load of DSA and improve the quality of service. A resource allocation framework based on the Stackelberg game model is proposed to analyze the pricing problem of FNs and the data resource strategy of DSA with a distributed iteration algorithm. The simulation results show that the proposed framework can ensure the allocation efficiency of FN resources among the cars. The framework achieves the optimal strategy of the participants and subgame perfect Nash equilibrium.

“…(1) Node synchronization. Owing to the limited energy, EH-WSN is able to communicate for only a short time, and the nodes have to communicate in a synchronized time slot [14,15] . EH-WSN usually runs out of power due to lack of energy and misses the time slot, thereby causing low efficiency of network communication or even paralysis.…”

Section: Introductionmentioning

confidence: 99%

An Efficient EH-WSN Energy Management Mechanism

Gao

Cheng

et al. 2018

Tinshhua Sci. Technol.

An Energy-Harvesting Wireless Sensor Network (EH-WSN) depends on harvesting energy from the environment to prolong network lifetime. Subjected to limited energy in complex environments, an EH-WSN encounters difficulty when applied to real environments as the network efficiency is reduced. Existing EH-WSN studies are usually conducted in assumed conditions in which nodes are synchronized and the energy profile is knowable or calculable. In real environments, nodes may lose their synchronization due to lack of energy. Furthermore, energy harvesting is significantly affected by multiple factors, whereas the ideal hypothesis is difficult to achieve in reality. In this paper, we introduce a general Intermittent Energy-Aware (IEA) EH-WSN platform.For the first time, we adopted a double-stage capacitor structure to ensure node synchronization in situations without energy harvesting, and we used an integrator to achieve ultra-low power measurement. With regard to hardware and software, we provided an optimized energy management mechanism for intermittent functioning. This paper describes the overall design of the IEA platform, and elaborates the energy management mechanism from the aspects of energy management, energy measurement, and energy prediction. In addition, we achieved node synchronization in different time and energy environments, measured the energy in reality, and proposed the light weight energy calculation method based on measured solar energy. In real environments, experiments are performed to verify the high performance of IEA in terms of validity and reliability. The IEA platform is shown to have ultra-low power consumption and high accuracy for energy measurement and prediction.