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Adaptive Data Dissemination Algorithm Based on Storing-Discarding Equilibrium for OUSNs

Opportunistic underwater sensor networks (OUSNs) are deployed for various underwater applications, such as underwater creatures tracking and tactical surveillance. The data dissemination in OUSNs differs significantly from those in terrestrial… Click to show full abstract

Opportunistic underwater sensor networks (OUSNs) are deployed for various underwater applications, such as underwater creatures tracking and tactical surveillance. The data dissemination in OUSNs differs significantly from those in terrestrial wireless sensor networks or delay-tolerant networks, due to the signal irregularity in underwater communications and the limited storage capacity of the nodes in OUSNs. To alleviate the storage overflows on nodes and make room for the newly arriving data packets, some stored data packets ought to be actively discarded by nodes. This research begins with the construction of a differential equation set to describe the propagation process of data packets in OUSNs, and the storing-discarding equilibrium is investigated such that each data packet is expected to propagate and disappear during the allowable dissemination time slots. After that, the optimal storing probabilities and discarding probabilities are obtained for the nodes with different in-degrees to maximize the delivery ratio of data packets. Then, we propose an Adaptive Data Dissemination Algorithm (ADDA) for the storage-limited OUSNs with signal irregularity, where at each time slot the newly arriving data packets are stored and the stored data packets are discarded by nodes according to the obtained storing probabilities and discarding probabilities, respectively. Simulation results demonstrate the excellent performance of ADDA, showing that it can enhance the delivery ratio of data packets and reduce the number of storage overflows.

Keywords: adaptive data; discarding equilibrium; data packets; data dissemination; dissemination; storing discarding

Journal Title: IEEE Transactions on Services Computing
Year Published: 2022

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