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Fog computing is a promising and challenging paradigm that enhances cloud computing by enabling efficient data processing and storage closer to data sources and users. This paper introduces a game-theoretic approach called GTRADPMFC (Game-Theoretic Resource Allocation and Dynamic Pricing Mechanism in Fog Computing) to address resource allocation and dynamic pricing challenges in fog computing environments with limited resources. The proposed model features non-cooperative competition among fog nodes for resources and dynamic pricing mechanisms to encourage efficient resource utilization. Theoretical analysis and simulations demonstrate that GTRADPMFC improves resource efficiency and overall fog computing system performance. Additionally, the paper discusses how to handle situations with insufficient samples and provide flexibility for users unable to meet completion time requirements. GTRADPMFC effectively manages resource allocation by establishing pricing in fog computing, considering potential delays in completion time. This is achieved through research, simulations, convergence analysis, complexity evaluation, and optimization guarantees.

The problematic situation that has developed in the housing and communal sector in Ukraine is well known. It is largely related to the conflict of goals and interests of interested parties. Thus, the owners of residential premises are concerned about the reduction of the quality of housing and communal services against the growth of tariffs. Resource supplying and contracting (servicing) organizations are dissatisfied with untimely and incomplete payment for the provided resources and services, while the state is worried about the lower availability of housing and utility services for most of the population. In their turn, the management companies (MCs) believe that their interests are infringed on both by the state and local self-government bodies. Dissatisfaction is experienced by managing organizations, which fulfill contractual obligations to resource suppliers, contractors, and owners of apartments, but, nevertheless, are a constant object of criticism. In modern conditions, the state cannot remove itself from the activities to reform the sphere of housing and communal services. Its policy should be focused on the realization of economic interests of all economic entities of the housing and utilities sector through the creation of mutually beneficial economic conditions at all levels of interaction between them, namely in the provision, distribution, exchange, and consumption of all types of housing and utility services to meet the ever-increasing demands of the population. [ABSTRACT FROM AUTHOR]

The problematic situation that has developed in the housing and communal sector in Ukraine is well known. It is largely related to the conflict of goals and interests of interested parties. Thus, the owners of residential premises are concerned about the reduction of the quality of housing and communal services against the growth of tariffs. Resource supplying and contracting (servicing) organizations are dissatisfied with untimely and incomplete payment for the provided resources and services, while the state is worried about the lower availability of housing and utility services for most of the population. In their turn, the management companies (MCs) believe that their interests are infringed on both by the state and local self-government bodies. Dissatisfaction is experienced by managing organizations, which fulfill contractual obligations to resource suppliers, contractors, and owners of apartments, but, nevertheless, are a constant object of criticism. In modern conditions, the state cannot remove itself from the activities to reform the sphere of housing and communal services. Its policy should be focused on the realization of economic interests of all economic entities of the housing and utilities sector through the creation of mutually beneficial economic conditions at all levels of interaction between them, namely in the provision, distribution, exchange, and consumption of all types of housing and utility services to meet the ever-increasing demands of the population.

This paper proposes a game-theoretic model for peer-to-peer (P2P) energy trading between a consumer and a prosumer living in a community. The proposed real-time pricing model is based on the Stackelberg game, and the consumer and prosumer are the follower and leader in the game, respectively. Therefore, the prosumer first proposes the trading price and then proposes the trading quantity based on the optimal scheduling of the energy storage system considering the determined trading price, load profile, P2P trading demand, etc. Subsequently, the consumer decides to purchase quantity by adjusting his/her load usage according to the trading price and quantity suggested by the prosumer. In this regard, a power flow analysis was conducted based on the participants' bidding strategy to analyze the changes in the electricity flow in a distribution system in which P2P energy trading occurs. Consequently, changes in power flow from the point of common coupling before and after P2P trading were verified, and the voltage stability of each bus was confirmed. In addition, the distribution system usage charge was calculated to reduce the operational burden of the distribution system operator and suggest an operation strategy that can enable P2P energy trading.

Cooperation among sensor nodes and the unreliability of acoustic channels are the significant challenges in underwater acoustic sensor networks (UASNs). In UASNs, the unreliability may results in high packet loss due to the high bit-error-rate and packets being dropped due to network congestion. High packet loss decreases the transmission rate in a network. An effective secure transmission mechanism is very much essential among the nodes in UASNs. In this paper, a trust strategy-based dynamic Bayesian game (TSDBG) model is proposed to resolve these problems. In TSDBG, a secure suite is created among the nodes in the network. Trust and Payoff are calculated for each node to evaluate the particular node involved in the packet-dropping and misbehaving activities that occurred during the transmission. Each node updates its trust value using Bayes' rule. Regular nodes are continuously monitored to analyze their neighbor nodes based on trust value. The simulation results reveal that the proposed scheme significantly reduces the packet-dropping attack, misbehaving activities of malicious nodes, propagation delay, and thereby enhancing secure transmission. [ABSTRACT FROM AUTHOR]

We harness the game-theoretic approach to propose a new conceptual framework for industrial land redevelopment research. Stemming from Harvey's notion of “urbanization of capital” and Foucault's study on “power relations”, we analyze the driver and regulator of urban spatial restructuring. We contend that the redevelopment of industrial land should be re-conceptualized as the competition for land rent gap or land rent surplus. Land redevelopment in urban China could be theoretically interpreted as multiple games between the original land-user and local government or the alliance between local government and new developers. Different equilibriums of games lead to various models/types of redevelopment. [ABSTRACT FROM AUTHOR]

The explosive growth of private cars in China and other developing countries has attracted a great deal of renewed research interest in car ownership. This paper investigates households’ car ownership decision-making process from the perspective of household time allocation. Applying the game-theoretic approach to capturing household members’ interactive decision-making mechanism, we propose a two-stage model that links household members’ short-term time allocation decisions to long-term car ownership decisions. The first stage models the bargaining of household members (e.g., husband and wife) over the car ownership decision, taking into consideration of government policies for regulating car ownership; and the second stage is a generalized Nash equilibrium model for activity-travel pattern analysis incorporating individuals’ interactions concerning activity participation. The existence and uniqueness of the generalized Nash equilibrium solution is examined, and a heuristic procedure that combines backwards induction and method of exhaustion is adopted to solve the two-stage game. The proposed model is applied to an empirical case study in Beijing, which demonstrates the applicability of the model in predicting car ownership and examining interactions between car ownership and household time allocation. The empirical model is applied to assess the impacts of plate-number-based vehicle usage rationing policies on car ownership and time allocation to travel and daily activities. Results show that the model can be applied to evaluate the car ownership impacts of car usage rationing policies. [ABSTRACT FROM AUTHOR]

With the deregulation of the power sector, distribution system planning is transforming from the traditional integrated decision mode to the multiple-player-based decentralized paradigm. However, this could potentially cause an adverse impact on the performance of the system due to interest con ict of market players during operations. To address such an issue, this paper develops a game-theoretic framework for active distribution network planning under the electricity market. The interplay between the distribution utility (DISCO) and distributed generation investors (DGO) is formulated as a noncooperative, two-person-based Stackelberg game in which the DISCO, as the leader of the game, makes expansion of the grid to achieve the least-cost operation, and DGOs, as followers, pursue for maximizing their profits from DG investment based on the condition of the network structure. The real-time network reconfiguration has been considered as a new active management option in this work, and the uncertainties associated with DG are also taken into account. To solve such game-theoretic model effectively, a heuristic-based algorithm is also proposed and combined with the dynamic optimal power ow analysis. The numerical results on a 33-bus distribution network verify the validity of the proposed methodology. [ABSTRACT FROM AUTHOR]

Multiuser diversity gains can be achieved by assigning channels to users with better channel quality in multiuser systems. To avoid the extensive information exchange required for centralized approaches, we propose a distributed fair pricing strategy for a slotted Aloha system in which users act selfishly to improve their own utilities for both the collision model and the multipacket reception (MPR) model. Based on a game theoretic framework, we show that multiuser diversity gains can be achieved by appropriately designing the Nash equilibrium thresholds for the selfish users to preserve the throughput and revenue achieved in the classical slotted Aloha systems. The network enforces fairness among different users by employing a pricing policy that favors equal access probabilities. Our simulation results show that significant multiuser diversity gains are achieved in terms of energy consumption and/or spectral efficiency. [ABSTRACT FROM PUBLISHER]

Energy harvesting technologies are required for autonomous sensor networks for which using a power source from a fixed utility or manual battery recharging is infeasible. An energy harvesting device (e.g., a solar cell) converts different forms of environmental energy into electricity to be supplied to a sensor node. However, since it can produce energy only at a limited rate, energy saving mechanisms play an important role to reduce energy consumption in a sensor node. In this article we present an overview of the different energy harvesting technologies and the energy saving mechanisms for wireless sensor networks. The related research issues on energy efficiency for sensor networks using energy harvesting technology are then discussed. To this end, we present an optimal energy management policy for a solar-powered sensor node that uses a sleep and wakeup strategy for energy conservation. The problem of determining the sleep and wakeup probabilities is formulated as a bargaining game. The Nash equilibrium is used as the solution of this game. [ABSTRACT FROM PUBLISHER]

This paper considers interference characterization and management in wireless ad hoc networks using MIMO techniques. The power allocation in each link is built into a non-cooperative game where a utility function is identified and maximized. Due to poor channel conditions, some links have very low data transmission rates even though their transmit powers are high. Therefore, a mechanism for shutting down links is proposed in order to reduce cochannel interference and improve energy efficiency. The multiuser water-filling and the gradient projection methods are compared with the proposed game theoretic approach in terms of system capacity and energy efficiency. It is shown that using the proposed method with the link shut-down mechanism allows the MIMO ad hoc network to achieve the highest energy efficiency and the highest system capacity [ABSTRACT FROM PUBLISHER]

In recent years, fiscal performance in Central Europe has steadily deteriorated, in contrast to the improvement in the Baltics. This paper explores the determinants of such differences among countries on the path to European Union (EU) accession. Regression estimates suggest that economic and institutional fundamentals do not provide a full explanation. An alternative explanation lies in the political economy of the accession process, and a game-theoretic model illustrates why a country with a stronger bargaining position might have an incentive to deviate from convergence to the Maastricht criteria. The model generates alternative fiscal policy regimes – allowing for regime shifts – depending on country characteristics and EU policies. [ABSTRACT FROM AUTHOR]

• Cooperative and non-cooperative modes of energy hubs to seek profit maximization. • Spatiotemporal correlations of renewable energies and price responsive loads. • Nonlinear AC power flows and Weymouth equations in an integrated energy market. • Nash equilibrium in game-theoretic approach for the behaviour of strategic players. Utilizing renewable energy sources like wind turbines and solar panels is increasing annually due to environmental and economic opportunities. Wind speed and solar irradiation depend on the time of day and the location of the site. The correlation of renewable energies with load and consequently with price in an energy market yields a more accurate estimation of energy optimization and consumption patterns. This problem will be more complicated when energy hubs choose to play in the integrated energy markets based on their coalitions with other energy hubs. An energy hub may join another energy hub to cooperate in an energy market or play self-autonomous to maximize its profit. This paper proposes a spatiotemporal correlation of wind speed, solar irradiation, and price responsive loads considering cooperative and non-cooperative modes of energy hubs based on a game-theoretic approach in an integrated energy market. This paper applies mathematical programming with equilibrium constraints to solve the highly competitive behavior of the energy hubs in this market considering loss. Two comparative and comprehensive case studies demonstrate the strategic actions of the energy hubs in these complicated conditions. [ABSTRACT FROM AUTHOR]

We use a game-theoretic approach to investigate the problem of selfish traffic with rational nodes in WLANs and propose a game-theoretic EDCA (G-EDCA) to improve QoS. Simulation results show that G-EDCA performs much better than EDCA in terms of throughput, bandwidth, delay, and bitdrop- rate. [ABSTRACT FROM PUBLISHER]