Data Dissemination And Collection Algorithms For Collaborative Sensor Networks Using Dynamic Cluster Heads

TL;DR

This paper introduces new algorithms for data dissemination and collection in wireless sensor networks, utilizing dynamic cluster heads to efficiently gather data from randomly distributed sensors with limited resources.

Contribution

The paper proposes two novel algorithms that dynamically select cluster heads for data dissemination and collection, improving efficiency in resource-constrained sensor networks.

Findings

Algorithms enable efficient data collection with fewer queries.

Dynamic cluster head selection adapts to network changes.

Enhanced energy efficiency in sensor data dissemination.

Abstract

We develop novel data dissemination and collection algorithms for Wireless Sensor Networks (WSNs) in which we consider $n$ sensor nodes distributed randomly in a certain field to measure a physical phenomena. Such sensors have limited energy, shortage coverage range, bandwidth and memory constraints. We desire to disseminate nodes' data throughout the network such that a base station will be able to collect the sensed data by querying a small number of nodes. We propose two data dissemination and collection algorithms (DCA's) to solve this problem. Data dissemination is achieved through dynamical selection of some nodes. The selected nodes will be changed after a time slot $t$ and may be repeated after a period $T$.