Router and gateway node placement in wireless mesh networks for emergency rescue scenarios

Mariusz Wzorek,Cyrille Berger,Patrick Doherty

doi:10.1007/s43684-021-00012-0

Abstract

The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations. The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers, and are used in the generation of ad hoc Wireless Mesh Networks (WMN). Several fundamental problems are considered and algorithms are proposed to solve these problems. The Router Node Placement problem (RNP) and a generalization of it that takes into account additional constraints arising in actual field usage is considered first. The RNP problem tries to determine how to optimally place routers in a WMN. A new algorithm, the RRT-WMN algorithm, is proposed to solve this problem. It is based in part on a novel use of the Rapidly Exploring Random Trees (RRT) algorithm used in motion planning. A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and Particle Swarm Optimization (PSO), shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios. The Gateway Node Placement Problem (GNP) tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service (QoS) constraints.Two alternatives are proposed for solving the combined RNP-GNP problem. The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm. The second approach, WMNbyAreaDecomposition, proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions, thus creating a number of simpler RNP problems that are then solved concurrently. Both algorithms are evaluated on real-world GIS models of different size and complexity. WMNbyAreaDecomposition is shown to outperform existing algorithms using 73% to 92% fewer router nodes while at the same time satisfying all QoS requirements.

Highlights

The importance of effective communication and efficient data/knowledge transfer is essential for the coordination of life-saving activities in regions affected by natural or man-made disasters
The most common formulation of the Gateway Node Placement (GNP) problem used in previous work [14, 21, 22], assumes that the router node placement is given and the goal is to find a minimum number of gateways and their placement so that network Quality of Service (QoS) constraints are guaranteed
– It provides a new definition of the Router Node Placement problem (RNP) problem taking into account both technical constraints associated with Wireless Mesh Networks (WMN) and structural constraints commonly associated with areas affected by disasters

Summary

Introduction

The importance of effective communication and efficient data/knowledge transfer is essential for the coordination of life-saving activities in regions affected by natural or man-made disasters. Two additional constraints are proposed and used when calculating a solution for an RNP problem: 1) enforcing line-of-sight requirement between two connected mesh routers, and 2) excluding obstacles from possible node placements The latter constraint relates to the example mission scenario depicted, where one wants to avoid delivery of mesh router nodes on collapsed building structures or densely vegetated areas with trees in order to increase the robustness of the network connections. The most common formulation of the GNP problem used in previous work [14, 21, 22], assumes that the router node placement is given and the goal is to find a minimum number of gateways and their placement so that network QoS constraints are guaranteed This is done by dividing the WMN backbone network, represented as a graph, into a set of disjoint clusters (sub-networks) covering the entire network. The algorithm continues the decomposition with an increasing number of sub-regions until the QoS constraints are satisfied, finding the minimum number of gateways

Contributions This papers makes the following contributions:

Router node placement

Experimental evaluation for solving RNP problems

Comparative evaluation using randomly generated problems

Experimental evaluation for solving combined RNP-GNP problems

Field deployment of ad hoc wireless mesh networks

Findings

Conclusions