Cross-Layer Strategies for Throughput Maximization in Data Aggregating Wireless Networks

TL;DR

This paper explores cross-layer strategies involving node placement, power, and transmission time adjustments to maximize the minimum throughput in data-aggregating wireless networks with power constraints.

Contribution

It introduces a comprehensive approach combining placement, power, and scheduling optimizations for throughput maximization in linear wireless networks.

Findings

Adaptive strategies improve throughput fairness.

Simulation results show significant performance gains.

Different strategies suit various network scenarios.

Abstract

We consider a data aggregating wireless network where all nodes have data to send to a single destination node, the sink. We consider a linear placement of nodes with the sink at one end. The nodes communicate directly to the sink (single hop transmission) and we assume that the nodes are scheduled one at a time by a central scheduler (possibly the sink). The wireless nodes are power limited and our network objective (notion of fairness) is to maximize the minimum throughput of the nodes subject to the node power constraints. In this work, we consider network designs that permit adapting node transmission time, node transmission power and node placements, and study cross- layer strategies that seek to maximize the network throughput. Using simulations, we characterize the performance of the dif- ferent strategies and comment on their applicability for various network scenarios.