Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.

Intelligent plant cultivation robots based on key marker algorithm and improved A* algorithm

Intelligent plant cultivation robots play a vital role in plant intelligent cultivation. Aiming at the problem of low accuracy and low efficiency of intelligent plant cultivation robots in searching for target plants in unknown environments, this paper proposes an intelligent plant cultivation robot based on key marker algorithm and improved A* algorithm. In terms of target plant positioning, a key marker algorithm based on YOLO V3 is proposed. Accurately find the target plant in the location environment, mark the key coordinate location of the target plant, and plan the routes. In terms of route planning, the self-node search strategy for the traditional A* algorithm has disadvantages such as many path turning points and large turning angles. By analyzing annealing algorithm, ant colony algorithm and A* algorithm, this paper proposes an improved A* algorithm. Finally, experiments with many different scenes prove that the intelligent plant cultivation robot proposed in this paper can effectively improve the accuracy of target plant detection and the efficiency of route planning.

Path Planning for Autonomous Articulated Vehicle Based on Improved Goal-Directed Rapid-Exploring Random Tree

The special steering characteristics and task complexity of autonomous articulated vehicle (AAV) make it often require multiple forward and backward movements during autonomous driving. In this paper, we present a simple yet effective method, named head correction with fixed wheel position (HC-FWP), for the demand of multiple forward and backward movements. The goal-directed rapid-exploring random tree (GDRRT) algorithm is first used to search for a feasible path in the obstacle map, and then, the farthest node search (FNS) algorithm is applied to obtain a series of key nodes, on which HC-FWP is used to correct AAV heading angles. Simulation experiments with Dynapac CC6200 articulated road roller parameters show that the proposed improved goal-directed rapid-exploring random tree (IGDRRT), consisting of GDRRT, FNS, and HC-FWP, can search a feasible path on maps that require the AAV to move back and forth.

An Node Search of DFS with Spanning Tree in Undirected Graphs

In a graph, spanning tree is a subgraph it is also a tree which relates all the vertices together. So it 'Spans' the first graph yet utilizing less edges Graph Search is a calculated plot that visits vertices or edges in a graph, in a request dependent on the availability of the graph. In graph search, edges are visited all things considered once and not all edges are visited. The ones that are visited structure a spanning tree for the vertices that are associated with the beginning vertex by a path. A spanning tree for a lot of vertices VER is a lot of edges without cycles that associates VER. So in a spanning tree, there is actually one path between any two of the vertices. This is the fundamental explanation behind the utility of DFS. DFS utilize stacks and creates insignificant spanning tree fulfilling an assortment of conditions.

Sorting of Section Contour Data Based on Linear Quadtree

A method based on the linear quadtree is proposed to sort the discrete data of the section contour. Firstly the contour data are distributed to different nodes of the linear quadtree and the data in the same node are sorted. Then neighbor node search regulations are established to help sort data in different nodes counter-clockwise. Experiment shows that the presented method can sort the data effectively.