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An Optimized Dynamic Trickle Algorithm for Media Technology

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An omnipresent revolutionary technology is what the Internet of Things (IoT) has brought to this century, connecting objects in a sequence of domains around people, since it plays a concrete role in the media technologies used daily. IoT turns media technologies objects, whether they are automated or self-control with less or no human intervention activity. A unique IoT component is a Low power and Lossy Networks (LLNs). It is a resource-constrained, where the trickle algorithm is an essential component of the IPv6 routing protocol over low power and lossy network RPL. Its job is to control and manage the network routing traffic. RPL routing protocol is used widely in the IoT. One of the main components of RPL is the trickle timer algorithm. It intends to make the information exchanging between the IoT nodes more straightforward, scalable, and energy-efficient approach. RPL has usage limitations, where the listening time for this is short, so the nodes have not enough time to transmit, and thus, to reduce the network performance. Several enhancements have been suggested in order to overcome this short-flow. This work will address those variants and intends to enhance the current trickle algorithm and its variants in order to achieve more scalable and less power consumption.
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RPL; IoT; Protocol; Dynamic Trickle Algorithm; Cooja; Objective Function; DODAGs; DAG; PDR; Media Technology

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