In partitioned sensor networks, objective-variable tour planning is used for mobile data collection.

PROJECT TITLE :

Objective-Variable Tour Planning for Mobile Data Collection in Partitioned Sensor Networks

ABSTRACT:

Wireless sensor networks can achieve greater energy efficiency and more even load distribution through the collection of data using mobile elements (WSNs). However, the design of paths can become more difficult in environments with complex network architectures. An objective-variable tour planning (OVTP) strategy for mobile data gathering in partitioned wireless sensor networks is presented in this work as a solution to the problem of the network environment. Our research, in contrast to previous studies that focused on connected networks, is centered on disjoint networks with connectivity requirements. These networks are intended to support delay-hash applications and energy-efficient scenarios, respectively. We begin by developing a mechanism for converging-aware location selection, which macroscopically converges rendezvous points (RPs) in order to establish a basis for a short tour. Next, we create a delay-aware path formation mechanism, which builds a quick tour connecting all of the segments using a new convex hull algorithm and a new genetic operation. This allows us to minimize the total amount of time spent traveling. In addition, we come up with an energy-aware path extension mechanism, which chooses suitable additional RPs in accordance with particular metrics in order to lessen the amount of energy that is wasted during the process of data transmission. Extensive simulations have shown that the new strategy is effective and has advantages in terms of the path length, the amount of energy that is depleted, and the data collection ratio.

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