A Trusted Real-Time Scheduling Model for Wireless Sensor Networks

Heterogeneous multicore and multiprocessor systems have been widely used for wireless sensor information processing, but system energy consumption has become an increasingly important issue. To ensure the reliable and safe operation of sensor systems, the task scheduling success rate of heterogeneous platforms should be improved, and energy consumption should be reduced. This work establishes a trusted task scheduling model for wireless sensor networks, proposes an energy consumption model, and adopts the ant colony algorithm and bee colony algorithm for the task scheduling of a real-time sensor node. Experimental result shows that the genetic algorithm and ant colony algorithm can efficiently solve the energy consumption problem in the trusted task scheduling of a wireless sensor and that the performance of the bee colony algorithm is slightly inferior to that of the first two methods

Energy-Efficient, Reliable and QoS-Aware Task Mapping on Cyber-Physical Systems

Cyber-Physical Systems (CPS) usually consist of a set of embedded systems (CPS nodes) connected through wireless communication, providing multiple functionalities that support different types of applications. During CPS deployment, application tasks are mapped on the CPS nodes with the objective of enhancing real-time performance, energy efficiency, and execution reliability. To satisfy these requirements, effective task mapping approaches should be designed based on different types of tasks, platforms, applications, and system requirements. In this paper, we provide a comprehensive survey regarding the task mapping methods in CPS