Stochastic Steepest Descent Optimization of Multiple-Objective Mobile Sensor Coverage


We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the scheduling decision is effected by a simple constant-time coin toss operation only. We apply our method to the scheduling of a mobile sensor's coverage time among a set of points of interest (PoIs). The coverage algorithm is guided by a Markov chain, wherein the sensor at PoI $i$ decides to go to the next PoI $j$ with transition probability $p_{ij}$. We use steepest descent to compute the transition probabilities for optimal tradeoff among different performance goals with regard to the distributions of per-PoI coverage times and exposure times and the entropy and energy efficiency of sensor movement. For computational efficiency, we show how we can optimally adapt the step size in steepest descent to achieve fast convergence. However, we found that the structure of our problem is complex, because there may exist surprisingly many local optima in the solution space, causing basic steepest descent to easily get stuck at a local optimum. To solve the problem, we show how proper incorporation of noise in the search process can get us out of the local optima with high probability. We provide simulation results to verify the accuracy of our analysis and show that our method can converge to the globally optimal control parameters under different assigned weights to the performance goals and different initial parameters.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Stochastic Geometry Analysis of Coordinated Beamforming Small Cell Networks With CSI Delay - 2018ABSTRACT:This letter characterizes the performance of coordinated beamforming (CBF) in frequency division duplex systems
PROJECT TITLE :Stochastic Routing and Scheduling Policies for Energy Harvesting Communication Networks - 2018ABSTRACT:During this Project, we have a tendency to study the joint routing-scheduling downside in energy harvesting
PROJECT TITLE :Spatial Field Reconstruction and Sensor Selection in Heterogeneous Sensor Networks With Stochastic Energy Harvesting - 2018ABSTRACT:We tend to address the two fundamental issues of spatial field reconstruction and
PROJECT TITLE :Optimal Sequential Fusion Estimation With Stochastic Parameter Perturbations, Fading Measurements, and Correlated Noises - 2018ABSTRACT:This Project focuses on the linear optimal recursive sequential fusion filter
PROJECT TITLE :Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation - 2018ABSTRACT:Stochastic network optimization problems entail finding resource allocation policies that are optimum on

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry