The influence of demand response on wind-integrated power system considering participation of the demand side

The future of networking will be driven by the current emerging trends of combining the physical and virtual realities in cyberspace. Considering the ambient pandemic challenges, the role of virtual and augmented reality will definitely grow over time by transforming into the paradigm of the Metaverse of Things, where each person, thing or other entity will simultaneously exist within multiple synchronized realities. In this paper, we propose a novel framework for future metaverse applications composed of multiple synchronized data flows from multiple operators through multiple wearable devices and with different quality requirements. A new service quality model is proposed based on a customizable utility function for each individual data flow. The proposed approach is based on dynamic fine-grained data flow allocation and service selection using non-fungible tokens, which can be traded over the blockchain among users and operators in a decentralized mobile network environment. 

/pdf/blockchain-empowered-service-management-for-the-2kl93f98.pdf

Blockchain-Empowered Service Management for the Decentralized Metaverse of Things

This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modified Roth-Erev individual reinforcement learning algorithm (1995) to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained and that market microstructure is strongly predictive for the relative market power of buyers and sellers, independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms.

Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing

Tremendous growth of the mobile network market driven by technology evolution requires a corresponding paradigm shift of the economic aspects of mobile networks. The high heterogeneity and flexibility of 5G mobile networks have led operators to shift their business models towards an open spectrum market. In this paper, we first introduce a comprehensive techno-economic framework to investigate a heterogeneous network (HetNet) that consists of two operators: a macro cell operator and a small cell operator, operating in conditions of an open spectrum market. Both operators coexist in such a way that the small cell operator leases the spectrum from the macro cell operator. In contrast to other similar studies, in our framework, we apply the concept of evolutionary stable equilibrium (ESE), which provides some level of intuition to the behaviour of the operators. In addition, we implement the method of dynamic service selection by the end users based on a utility function, which is sensitive to both the service price and the expected throughput. To analyse the techno-economic performance of the system, we develop a real-world simulation model that encompasses a 3D urban environment using real network topology from the OpenCellID database; this model includes a large number of end users with realistic mobility patterns. The simulation results show that, from the user’s perspective, the network switching mode provides better service at a lower price due to high market competition. From the view of the operator, the most profitable mode is the static contract because there is stable service demand regardless of the price. The multi-homing mode is a promising intermediate solution that can satisfy both the end users and the operators.

Techno-economic framework for dynamic operator selection in a multi-tier heterogeneous network

Cognitive radio networks are the next step to tackle scarcity in wireless networks given the increasing demand of radioelectric spectrum where the proposed solution is to share said resource to improve this situation. In the present article, a review of the current state of spectrum sharing in cognitive radio networks. To achieve this purpose, the articles published over the last 4 years on the matter were reviewed including topics such as mobile networks and TV. Some studies and simulations proposed to share the spectrum is shown. The current state of the studies reveals that there has been significant progress in this research area yet it is necessary to continue similar studies and set in motion different schemes.

/pdf/spectrum-sharing-in-cognitive-radio-networks-18o1o0exs0.pdf

Spectrum sharing in cognitive radio networks

Dynamic spectrum leasing and retail pricing using an experimental economy

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Dynamic spectrum leasing and retail pricing using an experimental economy