Abstract
A wireless sensor network (WSN) is one of the core technologies of the Internet of things. It is an important means to realize a real-time geographic information system. Related research has shown that in the future, tens of billions of sensors and intelligent terminal equipment will be connected to WSNs based on the establishment of the function of the Internet of things. This study presents a heuristic algorithm to balance the energy consumption of each sensor node. It proposes a new real-time dynamic allocation algorithm for sensor tasks based on the concept of this heuristic algorithm and by considering that a multisensory system is composed of a phased-array radar. This allocation algorithm can dynamically assign tasks to the most suitable sensor before tasks fail to arrive, which ensures that the sensor can achieve a good load balance and extend network lifetime. A simulation experiment is conducted, and results validate the proposed algorithm. The energy consumption of mobile sensor nodes is effectively balanced. The path-planning algorithm standardizes the energy consumption of each mobile sensor node across the network , thereby effectively prolonging network lifetime.
Highlights
In a mixed wireless sensor network (WSN), static sensor nodes are distributed in the environment to collect data, and mobile sensor nodes within a certain region collect data in accordance with the planning of the line mobile
This study proposes a heuristic algorithm to balance the energy consumption of each sensor
The algorithm can dynamically assign tasks to the most appropriate sensor before tasks fail to arrive, which ensures that the sensor can achieve good load balancing and prolong network lifetime
Summary
In a mixed wireless sensor network (WSN), static sensor nodes are distributed in the environment to collect data, and mobile sensor nodes within a certain region collect data in accordance with the planning of the line mobile. The mobile sensor nodes along a lattice network stop moving back and forth among stopping points, i.e., the center point of each cell. When mobile sensor nodes stop, the lattice network will bear all the data transmission work of the static sensor. The annual urban expansion area index, center of gravity transfer model, fractal dimension index, and elastic coefficient of urban expansion– population growth are used to explore the temporal and spatial characteristics of urban expansion [1]. Renewable energy resources (RESs) are not fully environmentally safe. Different RESs are associated with varying environmental impacts [4]. The understanding of the spatial and temporal dynamics of the urban expansion of Hurghada is the cornerstone for formulating a view regarding future urban uses and for utilizing limited available resources [5]
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