In this paper, the problem of distributed home energy management system with storage (HoMeS) in a coalition, which consists of multiple microgrids and multiple customers, is studied using the multiple-leader-multiple-follower Stackelberg game theoretic model-a multistage and multilevel game. The microgrids, which act as the leaders, need to decide on the minimum amount of energy to be generated with the help of a central energy management unit and the optimum price per unit energy to maximize their profit. On the other hand, the customers, which act as the followers, need to decide on the optimum amount of energy to be consumed, including the energy to be requested for storage. Using the proposed distributed scheme, i.e., HoMeS, the earned profit of the grid improves up to 55%, and the customers consume almost 30.79% higher amount of energy, which, in turn, increases the utilization of the generated energy by the microgrids.
SUMMARYIn this paper, we propose a distributed topology management algorithm, named T-Must, which orchestrates coalition formation game between camera and scalar sensor (SS) nodes, for use in wireless multimedia sensor networks. In the proposed solution, connectivity among the peer camera sensor (CS) nodes is maintained, and coverage is ensured between them. Only the scalar data are not sufficient to describe an event in a particular monitored area. In many cases, multimedia data (specifically, video data) are required to provide more precise information about the event. As the CS nodes, which sense and transmit multimedia data, are costlier than the SS nodes, the former are deployed in the monitored area in lesser numbers compared to the latter ones. In case of CS nodes, power consumption due to sensing is also significant, similar to power consumption for the transmission and reception of packets. Therefore, in this work, in order to increase the network lifetime, topology is controlled by forming coalition between the CS and SS nodes. Upon occurrence of an event, the SS nodes send scalar data to their associated CS nodes. If the scalar data received from SS nodes cross a preconfigured threshold, the associated CS node in the coalition starts sensing the event, captures the video data, and forwards the video data toward other coalitions or sink.
Sensor-cloud computing is envisioned to be one of the key enabling technologies for remote health monitoring. Integration of sensed data into cloud applications in sensor-cloud will help in real-time monitoring of patients over geographically distributed locations. In this study, the authors study the optimal gateway selection problem in sensor-cloud framework for real-time patient monitoring system by using a zero-sum game model. In the proposed model, a gateway acts as the first player, and chooses the strategy based on the available bandwidth, whereas a user request acts as the second player, and follows the strategy chosen by the first player. The authors evaluate the execution time for selecting the optimal gateway through which the sensed data will be fetched to the cloud platform. In addition, the authors show how user requests are serviced by the gateways to access data from cloud platform optimally. The authors also show that by using the proposed approach, the execution time decreases, thereby helping in forming a reliable, efficient and real-time architecture for health monitoring.
Existing works on energy trading consider different schemes for forming energy trading networks, which assume that each plug-in hybrid electric vehicle (PHEV) is connected with a single micro-grid. Consequently, in on-peak hours, a PHEV obtains the requested energy during the allotted time slot by paying a higher price. Alternatively, the PHEV waits for a significant duration of time to get serviced until the on-peak hour elapses. In this study, the authors propose that a PHEV may obtain energy from any of the available micro-grids within a coalition instantaneously without paying higher price. In this work, the problem of energy trading network topology control (ENTRANT) for PHEVs is studied as a 'multi-leader multi-follower Stackelberg game'. In this game, each PHEV acts as a leader, and decides the amount of energy to be requested to the selected micro-grid. On the other hand, the micro-grids act as followers, need to decide the price per unit energy. Using variational inequality, it is shown that the proposed scheme, ENTRANT, has generalised Nash equilibrium, which is also socially optimal. ENTRANT enables the PHEVs and the micro-grids within a coalition to reach the equilibrium state, is evaluated theoretically, as well as through simulations.
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