Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount ...Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount of data generated by IoT devices remains a challenge to the building management systems(BMSs)in terms of intensity and complexity.Different from cloud computing and edge computing,we propose a computation sharing architecture in smart buildings to incentivize idle computing devices(ICDs,sellers)to offload computational tasks for the BMS(buyer).In this paper,we design a hierarchical game model,consisting of a Stackelberg game and a Cournot game,to achieve a dynamic increase in computational capacity for the BMS.To guarantee the utility of BMS and ICDs,the Stackelberg game model is built to analyze the interactions between BMS and ICDs.Then,the Cournot game model is presented to formulate the internal competition among multiple ICDs.Under the premise of the subgame perfect Nash equilibrium,the BMS can quote the optimal pricing strategy,and the ICDs can share the corresponding optimal amount of computing resources.Finally,the simulation results show that the BMS’s computational capacity is enhanced on-demand,and each participant in the game obtains maximal utility.展开更多
Computational grids （CGs） aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the res...Computational grids （CGs） aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the resource allocation algorithm in their own benefit, and their selfish behavior may lead to severe performance degradation and poor efficiency. In this paper, game theory is introduced to solve the problem of barging for resource collection in heterogeneous distributed systems. By using the Cournot model that is an important model in static and complete information games, the algorithm is optimized in order to maximize the benefit. It can be seen that the approach is more suitable to the real situation and has practical use. Validity of the solutions is shown.展开更多
基金in part by the Natural Science Foundation of China under Grant 61871446,61801238the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX18_0887the Natural Science Foundation of Jiangsu Province under Grant BK20170758.
文摘Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount of data generated by IoT devices remains a challenge to the building management systems(BMSs)in terms of intensity and complexity.Different from cloud computing and edge computing,we propose a computation sharing architecture in smart buildings to incentivize idle computing devices(ICDs,sellers)to offload computational tasks for the BMS(buyer).In this paper,we design a hierarchical game model,consisting of a Stackelberg game and a Cournot game,to achieve a dynamic increase in computational capacity for the BMS.To guarantee the utility of BMS and ICDs,the Stackelberg game model is built to analyze the interactions between BMS and ICDs.Then,the Cournot game model is presented to formulate the internal competition among multiple ICDs.Under the premise of the subgame perfect Nash equilibrium,the BMS can quote the optimal pricing strategy,and the ICDs can share the corresponding optimal amount of computing resources.Finally,the simulation results show that the BMS’s computational capacity is enhanced on-demand,and each participant in the game obtains maximal utility.
基金Project supported by the Science Foundation of Shanghai Municipal Commission of Science and Technology(Grant No.00JC14052)
文摘Computational grids （CGs） aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the resource allocation algorithm in their own benefit, and their selfish behavior may lead to severe performance degradation and poor efficiency. In this paper, game theory is introduced to solve the problem of barging for resource collection in heterogeneous distributed systems. By using the Cournot model that is an important model in static and complete information games, the algorithm is optimized in order to maximize the benefit. It can be seen that the approach is more suitable to the real situation and has practical use. Validity of the solutions is shown.
