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The possibility and expediency of estimation of risk factors based on fundamental positions of information and entropy are grounded. In accordance with the principle of addiction, the possibility of using the H-criterion as an indicator of business uncertainty is shown. The algorithm of risk estimation of these investments is offered.

The possibility and expediency of estimation of risk factors based on fundamental positions of information and entropy are grounded. In accordance with the principle of addiction, the possibility of using the H-criterion as an indicator of business uncertainty is shown. The algorithm of risk estimation of these investments is offered. [ABSTRACT FROM AUTHOR]

The power distribution internet of things (PD-IoT) has the complex network architecture, various emerging services, and the enormous number of terminal devices, which poses rigid requirements on substrate network infrastructure. However, the traditional PD-IoT has the characteristics of single network function, management and maintenance difficulties, and poor service flexibility, which makes it hard to meet the differentiated quality of service (QoS) requirements of different services. In this paper, we propose the software-defined networking (SDN)- enabled PD-IoT framework to improve network compatibility and flexibility, and investigate the virtual network function (VNF) embedding problem of service orchestration in PD-IoT. To solve the preference conflicts among different VNFs towards the network function node (NFV) and provide differentiated service for services in various priorities, a matching-based priorityaware VNF embedding (MPVE) algorithm is proposed to reduce energy consumption while minimizing the total task processing delay. Simulation results demonstrate that MPVE significantly outperforms existing matching algorithm and random matching algorithm in terms of delay and energy consumption while ensuring the task processing requirements of high-priority services. [ABSTRACT FROM AUTHOR]

Various approaches have been introduced over the years to evaluate information in the expected utility framework. This paper analyzes the relationship between the degree of risk aversion and the selling price of information in a lottery setting with two actions. We show that the initial decision on the lottery as well as the attitude of the decision maker towards risk as a function of the initial wealth level are critical to characterizing this relationship. When the initial decision is to reject, a non-decreasingly risk averse decision maker asks for a higher selling price as he gets less risk averse. Conversely, when the initial decision is to accept, non-increasingly risk averse decision makers ask a higher selling price as they get more risk averse if information is collected on bounded lotteries. We also show that the assumption of the lower bound for lotteries can be relaxed for the quadratic utility family. [ABSTRACT FROM AUTHOR]