Energy Efficiency Maximization Strategy for Sink Node in SWIPT-Enabled Sensor-Cloud Based on Optimal Stopping Rules

Leveraging energy harvesting abilities in wireless network devices has emerged as an effective way to prolong the lifetime of energy constrained systems.The system gains are usually optimized by designing resource allocation algorithm appropriately.However,few works focus on the interaction that channel’s time-vary characters make the energy transfer inefficiently.To address this,we propose a novel system operation sequence for sensor-cloud system where the Sinks provide SWIPT for sensor nodes opportunistically during downlink phase and collect the data transmitted from sensor nodes in uplink phase.Then,the energy-efficiency maximization problem of the Sinks is presented by considering the time costs and energy consumption of channel detection.It is proved that the formulated problem is an optimal stopping process with optimal stopping rules.An optimal energy-efficiency(OEE)algorithm is designed to obtain the optimal stopping rules for SWIPT.Finally,the simulations are performed based on the OEE algorithm compared with the other two strategies to verify the effectiveness and gains in improving the system efficiency.

Optimal stopping investment in a logarithmic utility-based portfolio selection problem

Background:In this paper,we study the right time for an investor to stop the investment over a given investment horizon so as to obtain as close to the highest possible wealth as possible,according to a Logarithmic utility-maximization objective involving the portfolio in the drift and volatility terms.The problem is formulated as an optimal stopping problem,although it is non-standard in the sense that the maximum wealth involved is not adapted to the information generated over time.Methods:By delicate stochastic analysis,the problem is converted to a standard optimal stopping one involving adapted processes.Results:Numerical examples shed light on the efficiency of the theoretical results.Conclusion:Our investment problem,which includes the portfolio in the drift and volatility terms of the dynamic systems,makes the problem including multi-dimensional financial assets more realistic and meaningful.

Optimal stopping in predictable setting

In this study,we delve into the optimal stopping problem by examining the p(ϕ(τ),τ∈T_(0)^(p))case in which the reward is given by a family of nonnegative random variables indexed by predictable stopping times.We aim to elucidate various properties of the value function family within this context.We prove the existence of an optimal predictable stopping time,subject to specific assumptions regarding the reward functionϕ.

From Optimal Stopping Problems over Tree Sets to Optimal Stopping Problems over Partially Ordered Sets

In this paper, we discuss relations between optimal stopping problems over tree sets and partially ordered sets, prove that there is a 1-1 correspondence between them and so every optimal strategy can be obtained in the set of optimal control variables.

Relay Selection Scheme for AF System with Partial CSI and Optimal Stopping Theory

Relay selection for Relay Assisted(RA)networks is an economical and effective method to improve the spectrum efficiency.Relay selection performs especially well when the source node has accurate and timely Channel State Information(CSI).However,since perfect CSI knowledge is rarely available,research of relay selection with partial(statistical)CSI is of paramount importance.In this paper,relay selection for RA networks with statistical CSI is formulated as a Multiple-Decision(MD)problem.And,the cost of obtaining the CSI is also considered in the formulated problem.Two relay selection schemes,Maximal Selection Probability(MSP)and Maximal Spectrum Efficiency Expectation(MSEE),are proposed to solve the formulated MD problem under different optimal criteria assumptions based on the optimal stopping theory.The MSP scheme maximizes the probability that the Best Assisted Relay Candidate(BARC)can be selected,whereas the MSEE scheme provides the maximal expectation of the spectrum efficiency.Experimental results show that the proposed schemes effectively improve the spectrum efficiency,and the MSEE scheme is more suitable for stable communication cases.Meanwhile,the MSP scheme is more suitable for burst communication cases.

Optimal stopping of multi-project software testing in the context of software cybernetics

Software cybernetics explores the interplay between control theory/engineering and software theory/engineering. The controlled Markov chains (CMC) approach to software testing follows the idea of software cybernetics and treats software testing as a control problem. The software under test serves as a controlled object and the software testing strategy serves as the corresponding controller. The software under test and the software testing strategy make up a closed-loop feedback control system, and the theory of controlled Markov chains can be used to design and optimize software testing strategies in accordance with testing/reliability goals given a priori. In this paper we apply the CMC approach to the optimal stopping problem of multi-project software testing. The problem under consideration assumes that a single stopping action can stop testing of all the software systems under test simultaneously. The theoretical results presented in this paper describe how to test multiple software systems and when to stop testing in an optimal manner. An illustrative example is used to explain the theoretical results. The study of this paper further justifies the effectiveness of the CMC approach to software testing in particular and the idea of software cybernetics in general.

A Useful Extension of It 's Formula with Applications to Optimal Stopping

Given a continuous semimartingale M = （Mt）t≥〉0 and a d-dimensional continuous process of locally bounded variation V = （V^1,……, V^d）, the multidimensional Ito Formula states that f（Mt, Vt） - f（M0, V0） = ∫[0, t] Dx0f（Ms, Vs）dMs＋∑i=1^d∫[0, t] Dxi F（Ms, Vs）dVs^i＋1/2∫[0, t] Dx0^2 f（Ms, Vs）d 〈M〉s if f（x0,……,xd） is of C^2-type with respect to x0 and of C^1-type with respect to the other arguments This formula is very useful when solving various optimal stopping problems based on Brownian motion. However, in such application the function f typically fails to satisfy the stated conditions in that its first partial derivative with respect to x0 is only absolutely continuous. We prove that the formula remains true for such functions and demonstrate its use with two examples from Mathematical Finance.

Optimal stopping time on discounted semi-Markov processes

This paper attempts to study the optimal stopping time for semi- Markov processes (SMPs) under the discount optimization criteria with unbounded cost rates. In our work, we introduce an explicit construction of the equivalent semi-Markov decision processes (SMDPs). The equivalence is embodied in the expected discounted cost functions of SMPs and SMDPs, that is, every stopping time of SMPs can induce a policy of SMDPs such that the value functions are equal, and vice versa. The existence of the optimal stopping time of SMPs is proved by this equivalence relation. Next, we give the optimality equation of the value function and develop an effective iterative algorithm for computing it. Moreover, we show that the optimal and ε-optimal stopping time can be characterized by the hitting time of the special sets. Finally, to illustrate the validity of our results, an example of a maintenance system is presented in the end.

Optimal Stopping Time of a Portfolio Selection Problem with Multi-assets

In this work,we study a right time for an investor to stop the investment among multi-assets over a given investment horizon so as to obtainmaximum profit.We formulate it to a two-stage problem.The main problem is not a standard optimal stopping problem due to the non-adapted term in the objective function,and we turn it to a standard one by stochastic analysis.The subproblem with control variable in the drift and volatility terms is solved first via stochastic control method.A numerical example is presented to illustrate the efficiency of the theoretical results.

Dual Control Methods for a Mixed Control Problem with Optimal Stopping Arising in Optimal Consumption and Investment

This paper studies a problem of optimal investment and consumption with early retirement option under constant elasticity variation(CEV)model with finite horizon.Two risky assets are involved in the model with one following geometric Brownian motion and the other a CEV model.This problem is a kind of two dimensional mixed control and optimal stopping problems with finite horizon.The existence and continuity of the optimal retirement threshold surfaces are proved and the working and retirement regions are characterized theoretically.Least-squares Monte-Carlo methods are developed to solve this mixed control and optimal stopping problem.The algorithms are well implemented and the optimal retirement threshold surfaces,optimal investment strategies and the optimal consumptions are drawn via examples.

Employee Stock Options＂ Accounting for Optimal Hedging, Suboptimal Exercises, and Contractual Restrictions

Employee stock options （ESOs） have become an integral component of compensation in the US. In view of their significant cost to firms, the Financial Accounting Standards Board （FASB） has mandated expensing ESOs since 2004. The main difficulty of ESO valuation lies in the uncertain timing of exercises, and a number of contractual restrictions of ESOs further complicate the problem. We present a valuation framework that captures the main characteristics of ESOs. Specifically, we incorporate the holder＇s risk aversion, and hedging strategies that include both dynamic trading of a correlated asset and static positions in market-traded options. Their combined effect on ESO exercises and costs are evaluated along with common features like vesting periods, job termination risk and multiple exercises. This leads to the study of a joint stochastic control and optimal stopping problem. We find that ESO values are much less than the corresponding Black-Scholes prices due to early exercises, which arise from risk aversion and job termination risk; whereas static hedges induce holders to delay exercises and increase ESO costs.

Optimal Rules to Adopt High Technology under Uncertainty

In the research of choosing the optimal timing for the high technology products, especially IT products to the market, most studies prefer to provide the scope or infnnum of timing. In this paper, an optimal rule is adopted to guild the timing of high technology product to the market, this idea is illustrated through the theory of optimal stopping, and a high approach is developed to theoretical framework for timing decision. On this basis, a random programming model is established, in which the objective function is the expected profit to adopt high technology and the constraint condition is the successful probability over critical value a with all variables beyond the rule, and it is used to find the optimal timing of adopt high technology product.

Optimal Timing of Business Conversion for Solvency Improvement

In this paper,we study the optimal timing to convert the risk of business for an insurance company in order to improve its solvency.The cash flow of company evolves according to a jump-diffusion process.Business conversion option offers the company an opportunity to transfer the jump risk business out.In exchange for this option,the company needs to pay both fixed and proportional transaction costs.The proportional cost can also be seen as the profit loading of the jump risk business.We formulated this problem as an optimal stopping problem.By solving this stopping problem,we find that the optimal timing of business conversion mainly depends on the profit loading of the jump risk business.A larger profit loading would make the conversion option valueless.The fixed cost,however,only delays the optimal timing of business conversion.In the end,numerical results are provided to illustrate the impacts of transaction costs and environmental parameters to the optimal strategies.

L^(p)-solutions of Multi-dimensional Oblique Reflected BSDEs and Optimal Switching Problem on Finite or Infinite Time Horizon

In this paper,we study mulit-dimensional oblique reflected backward stochastic differential equations(RBSDEs)in a more general framework over finite or infinite time horizon,corresponding to the pricing problem for a type of real option.We prove that the equation can be solved uniquely in L^(p)(1<p≤2)-space,when the generators are uniformly continuous but each component taking values independently.Furthermore,if the generator of this equation fulfills the infinite time version of Lipschitzian continuity,we can also conclude that the solution to the oblique RBSDE exists and is unique,despite the fact that the values of some generator components may affect one another.

The pricing of perpetual convertible bond with credit risk

Convertible bond gives holder the right to choose a conversion strategy to maximize the bond value, and issuer also has the right to minimize the bond value in order to maximize equity value. When there is default occurring, conversion and calling strategies are invalid. In the framework of reduced form model, we reduce the price of convertible bond to variational inequalities, and the coefficients of variational inequalities are unbounded at the original point. Then the existence and uniqueness of variational inequality are proven. Finally, we prove that the conversion area, the calling area and the holding area are connected subsets of the state space.

TIME INCONSISTENCY AND REPUTATION IN MONETARY POLICY: A STRATEGIC MODELLING IN CONTINUOUS TIME

This article develops a model to examine the equilibrium behavior of the time inconsistency problem in a continuous time economy with stochastic and endogenized distortion. First, the authors introduce the notion of sequentially rational equilibrium, and show that the time inconsistency problem may be solved with trigger reputation strategies for stochastic setting. The conditions for the existence of sequentially rational equilibrium are provided. Then, the concept of sequentially rational stochastically stable equilibrium is introduced. The authors compare the relative stability between the cooperative behavior and uncooperative behavior, and show that the cooperative equilibrium in this monetary policy game is a sequentially rational stochastically stable equilibrium and the uncooperative equilibrium is sequentially rational stochastically unstable equilibrium. In the long run, the zero inflation monetary policies are inherently more stable than the discretion rules, and once established, they tend to persist for longer periods of the time.

A SECRETARY PROBLEM ON FUZZY SETS

This paper deals with a secretary problem on fuzzy sets, which allows both the recall of applicants and the uncertainty of a current applicant receiving an offer of employmellt. A new decision criterion is given to select a satisfactory applicant. This result extends the works of M.C.K. Yang and M.H. Smith.

A unique solution to a semilinear Black-Scholes partial differential equation for valuing multi-assets of American options

In this paper, by using the optimal stopping theory, the semilinear Black-Scholes partial differential equation （PDE） was invesigated in a fixed domain for valuing two assets of American （call-max/put-min） options. From the viscosity solution of a PDE, a unique viscosity solution was obtained for the semilinear Black-Scholes PDE.

The Convergence Rate from Discrete to Continuous Optimal Investment Stopping Problem

The author studies the optimal investment stopping problem in both continuous and discrete cases, where the investor needs to choose the optimal trading strategy and optimal stopping time concurrently to maximize the expected utility of terminal wealth.Based on the work of Hu et al.(2018) with an additional stochastic payoff function,the author characterizes the value function for the continuous problem via the theory of quadratic reflected backward stochastic differential equations(BSDEs for short) with unbounded terminal condition. In regard to the discrete problem, she gets the discretization form composed of piecewise quadratic BSDEs recursively under Markovian framework and the assumption of bounded obstacle, and provides some useful a priori estimates about the solutions with the help of an auxiliary forward-backward SDE system and Malliavin calculus. Finally, she obtains the uniform convergence and relevant rate from discretely to continuously quadratic reflected BSDE, which arise from corresponding optimal investment stopping problem through above characterization.

Penalization schemes for BSDEs and reflected BSDEs with generalized driver

The paper is directly motivated by the pricing of vulnerable European and American options in a general hazard process setup and a related study of the corresponding pre-default backward stochastic differential equations(BSDE)and pre-default reflected backward stochastic differential equations(RBSDE).The goal of this work is twofold.First,we aim to establish the well-posedness results and comparison theorems for a generalized BSDE and a reflected generalized BSDE with a continuous and nondecreasing driver A.Second,we study penalization schemes for a generalized BSDE and a reflected generalized BSDE in which we penalize against the driver in order to obtain in the limit either a constrained optimal stopping problem or a constrained Dynkin game in which the set of minimizer's admissible exercise times is constrained to the right support of the measure generated by A.