Resource tokenization for crowdfunding of wireless networks

This paper presents a novel blockchain-based spectrum tokenization method used to crowdsource wireless network deployment projects. Crowdsourcing is a method of financing certain projects and ideas through the funds collected by individuals or businesses in an open marketplace. The method presented in this paper finances the wireless network deployment projects belonging to service providers or governments. The method tokenizes proposed novel wireless resource units, and sells these units to investors. A new Value Unit Per User (VUPU) resource unit is introduced with a new pricing scheme depending on a load of a base station. A novel Proof of Data Load (PoDLO) consensus algorithm is proposed which is used to verify data and traffic load of a base station. Device Diversity Factor (DDF) and Subscriber Unique Permanent Identifier (SUPI) Factor (SUF) are proposed new ways to determine the value of a base station and a network cluster.

Development of a Digital Model of the Agricultural Tool Working Element

The digital twin is a virtual model of the agricultural tool working element that allows you to calculate and predict its expected behavior during the entire period of operation.(Research purpose) To develop an algorithm for consistent models that make up the digital twin of the agricultural tool working element.(Materials and methods) The fi rst component of the digital twin algorithm was determined by the method of accelerated imitation loading of the wedgelock ripper working element, which was accepted as the research object. The second component was determined by testing various soils with the specifi cation of power equivalents. The physical and mechanical properties of soils and materials (hardening) for the manufacture of working elements were taken into account during the description of the following components.(Results and discussion) The author showed that the algorithm for constructing a digital twin of the agricultural tool working element consisted from a chain of successive actions and was a system for digital description of the working element, which ensured the standard lifetime during operation. The results of a simulated immersion which registered the nature of the normal forces distribution over the friction surfaces were accepted as the fi rst component of the algorithm. The second component – the results of determining the force equivalent when loading the working element in a real soil environment. The possibility of constructing maps of the intensity of the friction surface abrasive wear, predictive calculations of structural elements was revealed. The third and fourth components were used to ensure the working element standard lifetime, based on the minimum production costs, correlated to the standard resource unit of development.(Conclusions) The resulting algorithm for constructing a digital twin is a convenient tool for creating new designs of agricultural tools working elements.

Congestion Probabilities in a Multi-Cluster C-RAN Servicing a Mixture of Traffic Sources

A multi-cluster cloud radio access network (C-RAN) is considered in this paper where the remote radio heads (RRHs) form different clusters. A cluster includes RRHs that have the same radio resource unit capacity. In addition, all RRHs are separated from the common pool of computational resource units named baseband units. Each RRH accommodates calls whose arrival process can be random, quasi-random, or even bursty. The latter is modeled according to the compound Poisson process where calls arrive in the C-RAN in the form of batches whose size (in calls) is generally distributed. An arriving call requires a radio and a computational resource unit so as to be accepted in the C-RAN. If at least one of these units is not available, the call is blocked. To analyze the proposed multi-cluster C-RAN we model it as a loss system, show that the steady-state probabilities have a product form solution and propose an algorithm for the computation of congestion probabilities. The accuracy of the proposed algorithm is verified via simulation.

Contribution of Street Trees to Carbon Sequestration: A Case Study from Varanasi, India

Street trees are a valuable resource for a city, because they lower ambient temperatures, mitigate urban heat island effects, reduce runoff of rainwater and the abundance of aerial particulate matter, add visual appeal to the urban landscape and store and sequester significant amount of carbon from the ambient CO2. In this paper, we have quantified carbon storage and sequestration by street trees in the campus of Banaras Hindu University located within a highly crowded city of India. Street trees in the BHU campus account for 9.8×107 kg stem biomass, and stored 4.6×107 kg carbon in the stems. By interpolating the electricity resource unit values campus street trees stored 7.3×107 KWH energy. These trees, of course, have to be properly managed for maintaining their vigour and function.

Inequality in resource allocation and population dynamics models

The Hassell model has been widely used as a general discrete-time population dynamics model that describes both contest and scramble intraspecific competition through a tunable exponent. Since the two types of competition generally lead to different degrees of inequality in the resource distribution among individuals, the exponent is expected to be related to this inequality. However, among various first-principles derivations of this model, none is consistent with this expectation. This paper explores whether a Hassell model with an exponent related to inequality in resource allocation can be derived from first principles. Indeed, such a Hassell model can be derived by assuming random competition for resources among the individuals wherein each individual can obtain only a fixed amount of resources at a time. Changing the size of the resource unit alters the degree of inequality, and the exponent changes accordingly. As expected, the Beverton–Holt and Ricker models can be regarded as the highest and lowest inequality cases of the derived Hassell model, respectively. Two additional Hassell models are derived under some modified assumptions.