Multisource Adaptive Data Distribution and Routing in Wireless Sensor Networks

TL;DR

This paper proposes an adaptive data distribution and routing framework for wireless sensor networks that minimizes energy consumption, data delivery time, and congestion, validated through extensive NS2 simulations.

Contribution

It introduces a novel adaptive framework for multisource data transmission in wireless sensor networks, optimizing energy, delay, and congestion control.

Findings

Framework reduces energy consumption compared to traditional protocols.

It achieves lower data delivery times in simulations.

The approach effectively manages network congestion.

Abstract

The wireless sensor network is a collection of energy-constrained nodes. Their objective is to sense, collect and process information for some ad-hoc purpose. Typically the nodes are deployed in geographically inaccessible regions. Thus the most challenging task is to design a network with minimal power consumption. As the nodes have to collect and process data very fast, minimizing data delivery time is another objective. In addition to this, when multiple sources transmit data simultaneously, the network load gradually increases and it may lead to congestion. In this paper we have proposed an adaptive framework in which multiple sources transmit data simultaneously with minimal end-to-end data delivery time and minimal energy consumption besides ensuring that congestion remains at an optimum low so that minimal number of data packets are dropped. This paper presents an adaptive framework to achieve the above-mentioned objectives. This framework has been used over Mac 802.11 and extensive simulations have been carried out in NS2 to prove the effectiveness of the framework over traditional Mac as well as few other existing protocols.