Abstract
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.
Highlights
Energy consumption has become a major problem in wireless sensor networks
The genetic algorithm is taken as a standard to compare the performance of the ant colony algorithm and bee colony algorithm
The results shown in the table cannot verify the advantages and disadvantages of the bee colony algorithm in task scheduling
Summary
Energy consumption has become a major problem in wireless sensor networks. The reduction of energy consumption to prolong the lifetime of networks is a widespread concern. Wireless sensor networks perform mainly real-time tasks. We need to focus on reducing energy consumption under the premise of meeting specified task deadlines. The real-time task scheduling of wireless sensor networks involves forming a mapping relationship between the realtime task scheduling and the processors within the acceptable time scope of the system. The real-time tasks are assigned to the processors according to the mapping relationship. In this way, the tasks can be executed within the deadline. The mapping relationship should effectively meet time and resource constraints
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