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Ideally, transcriptomic data sets addressing all five DACS areas would be used in order to maximize network coverage.
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The mesh topology places no restrictions on the connectivity between nodes, maximizing network coverage.
Traditional algorithms primarily aim at maximizing network coverage rate, which leads to the creation of the "energy hole" in the region near the sink node.
That is, maximizing network coverage involves backbone configurations, where nodes are spread in regions, where wireless users are deployed whereas assuring robust backbone connectivity involves bringing backbone nodes together to increase connectivity and/or strength of connectivity.
Maximizing network coverage can increase ridership.
Given a number of router nodes to deploy, a deployment area and positions of client nodes in the area, an optimization problem can be formulated aiming to find the placement of router nodes so as to maximize network connectivity and user coverage.
The objective is to maximize network lifetime while fulfilling diversified coverage constraints, i.e., different targets may require different sensing quality in terms of the number of transducers, sampling rate, sensing data rate, etc.
Find a way to maximize network intelligence.
Find a way to maximize network intelligence.
Remarks: The objective function wants to maximize the network coverage rate while minimize the total moving distance of sensors.
In yet another work carried out in [21] PSO is applied to optimize the sensor deployment strategy in order to maximize the network coverage in mobile sensor network.
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