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Handling of resource allocation in flying ad hoc network through dynamic graph modeling

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Abstract

Now a days, Flying ad hoc network (FANET) as a trending wireless classification has a vibrant area of research. FANET architecture can also be viewed as a special form of a distributed system in which unmanned aerial vehicles are the nodes with highly dynamic behavior in terms of their mobility. Now, resource allocation problem is always a concern in distributed architecture, so as in FANET. The concept of mutual exclusion plays a vital role and ensures the access of shared resources in a mutual access manner by the nodes running on different processors. Through this research work, we modeled FANET as an application of a dynamic graph by applying its properties and propose a token-based resource allocation algorithm in FANET to achieve distributed mutual exclusion. We have used Neo4j as a graph database to model our work and present better results in terms of various performance metrics as compared to existing work in FANET till date.

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Funding

This study was not funded by any organization.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology (NIT), Jote, Arunachal Pradesh, India

    Ashish Singh Parihar & Swarnendu Kumar Chakraborty

  2. Department of Computer Science, KIET Group of Institutions, Delhi-NCR, Ghaziabad, Uttar Pradesh, India

    Ashish Singh Parihar

Authors
  1. Ashish Singh Parihar
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Correspondence to Ashish Singh Parihar.

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Appendices

Appendix-I (Symbol notations)

Symbol

Description

N

Number of nodes in the network

βr

The arrival rate of the Poisson process

€

Maximum delay in-between node to node communication

g

Upper bound limit of messages generated by a node

αx

Traversing cost of an Ad hoc from node x

βx^y

Switch between x and y

λ

Average time unit for message generation by a node after CS release

δ

Broadcast message

ε

Request message

ζ

Request acknowledge message

η

Permission message

θ

Token message

ι

Total number of CS to be invoked simultaneously in the system

T

The propagation time of a message

Appendix-II (List of Abbreviations)

FANET

Flying ad hoc network

MANET

Mobile ad hoc network

VANET

Vehicular ad hoc network

UAV

Unmanned aerial vehicle

DME

Distributed mutual exclusion

DS

Distributed system

CS

Critical section

RL

Reverse link

DAG

Directed acyclic graph

MRME

Mobile resource mutual exclusion

DCGM

Dynamic chain graph model

WN

Wireless node

CR

Communication range

EA

Edge addition

ED

Edge deletion

NA

Node addition

ND

Node deletion

RC_UAV

Resource centric UAV

BFS

Breath first search

DFS

Depth first search

LP

Logic programming

AI

Artificial intelligence

DSt

Data Structure

DB

Data bases

GG

Graph games

C-FG

Chip-Firing Games

DGM

Distributed graph modeling

FTN

Forecasting traffic network

FP

Forecast performance

GE

Gene expression

OP

Optimization problems

IG

Internet graph

FN

Friendship network

PN

Proximity network

ETN

Extract temporal node

DLP

Dynamic Link prediction

RS

Recommender systems

TP

Time Prediction

DSoSG

Discrete sequence of static graphs

CFM

Classical flow model

TM

Threshold model

SoS

Sequence of snapshots

LFM

Log file model

R-o

Re-optimization

RGM

Random graph model

MLwGF

Machine learning with graph factorization

SW

Stream walk

E-DM

Encode-Decode model

I/DDA

Incremental/Decremental dynamic algorithm

C

Compiler

SNwTI

Static network with time instances

RN

Resource network

R-WN

Real-world networks

TSN

Time series network

TDN

Time dependent networks

SyN

Synthetic networks

TN

Temporal networks

HN

Heterogeneous network

SN

Social networks

CN

Communication networks

TrN

Transportation networks

L

Labeling

MPD

Message propagation delay

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Parihar, A.S., Chakraborty, S.K. Handling of resource allocation in flying ad hoc network through dynamic graph modeling. Multimed Tools Appl 81, 18641–18669 (2022). https://doi.org/10.1007/s11042-022-11950-z

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