A Proposal of a Greedy Neural Network for Route Assignments in Multihop Radio Networks

Takayuki Baba, Nobuo Funabiki, Seishi Nishikawa

Research output: Contribution to journalArticle

Abstract

In a radio communications network, all of the nodes cannot communicate with each other directly. Then packets are transferred from a source node to a destination node through several nodes. Therefore, we need to schedule transfer timing at each node, and communications routes must be assigned to minimize the total transfer time when many packet transfers are requested. This problem is divided into two problems: the communications route assignment problem and the scheduling problem. The former problem is subdivided into the communication route candidate extraction problem and the communication route se-lection problem. This paper first proposes an evaluation function (Cost) which gives the lowest limit of the total transfer time for the communication route assignment problem. Next this paper proposes a k-shortest route extraction procedure for the communication route extraction problem. This procedure is based on the k-shortest route algorithm. It prevents extraction of a route whose number of hops is more than the upper limit, sets an appropriate number of extraction routes, prevents loops, and prevents redundant route extraction. We also propose a greedy neural network procedure for the communication route selection problem. This procedure introduces the to function into the operation equation of the neuron initial value setting based on the number of hops and a cost minimization term for the evaluation function. The procedure uses an appropriate termination condition for iterative computation. It also uses the first-order maximum neuron. Through simulations of 500-vertex communication network examples, the proposed procedure has the merits of high precision, short computation, and smaller number of computations in a region.

Original languageEnglish
Pages (from-to)52-60
Number of pages9
JournalSystems and Computers in Japan
Volume30
Issue number13
Publication statusPublished - Nov 30 1999
Externally publishedYes

Fingerprint

Radio Networks
Multi-hop
Assignment
Neural Networks
Neural networks
Communication
Vertex of a graph
Function evaluation
Evaluation Function
Assignment Problem
Communication Networks
Neurons
Telecommunication networks
Neuron
Cost Minimization
Radio communication
Limit Set
Cost functions
Termination
Scheduling Problem

Keywords

  • Communication route assignment problem
  • Greedy neural network
  • Maximum neuron
  • Radio communication

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Hardware and Architecture
  • Information Systems
  • Theoretical Computer Science

Cite this

A Proposal of a Greedy Neural Network for Route Assignments in Multihop Radio Networks. / Baba, Takayuki; Funabiki, Nobuo; Nishikawa, Seishi.

In: Systems and Computers in Japan, Vol. 30, No. 13, 30.11.1999, p. 52-60.

Research output: Contribution to journalArticle

@article{f8aef36eb08d49c39a9f7d74a604566c,
title = "A Proposal of a Greedy Neural Network for Route Assignments in Multihop Radio Networks",
abstract = "In a radio communications network, all of the nodes cannot communicate with each other directly. Then packets are transferred from a source node to a destination node through several nodes. Therefore, we need to schedule transfer timing at each node, and communications routes must be assigned to minimize the total transfer time when many packet transfers are requested. This problem is divided into two problems: the communications route assignment problem and the scheduling problem. The former problem is subdivided into the communication route candidate extraction problem and the communication route se-lection problem. This paper first proposes an evaluation function (Cost) which gives the lowest limit of the total transfer time for the communication route assignment problem. Next this paper proposes a k-shortest route extraction procedure for the communication route extraction problem. This procedure is based on the k-shortest route algorithm. It prevents extraction of a route whose number of hops is more than the upper limit, sets an appropriate number of extraction routes, prevents loops, and prevents redundant route extraction. We also propose a greedy neural network procedure for the communication route selection problem. This procedure introduces the to function into the operation equation of the neuron initial value setting based on the number of hops and a cost minimization term for the evaluation function. The procedure uses an appropriate termination condition for iterative computation. It also uses the first-order maximum neuron. Through simulations of 500-vertex communication network examples, the proposed procedure has the merits of high precision, short computation, and smaller number of computations in a region.",
keywords = "Communication route assignment problem, Greedy neural network, Maximum neuron, Radio communication",
author = "Takayuki Baba and Nobuo Funabiki and Seishi Nishikawa",
year = "1999",
month = "11",
day = "30",
language = "English",
volume = "30",
pages = "52--60",
journal = "Systems and Computers in Japan",
issn = "0882-1666",
publisher = "John Wiley and Sons Inc.",
number = "13",

}

TY - JOUR

T1 - A Proposal of a Greedy Neural Network for Route Assignments in Multihop Radio Networks

AU - Baba, Takayuki

AU - Funabiki, Nobuo

AU - Nishikawa, Seishi

PY - 1999/11/30

Y1 - 1999/11/30

N2 - In a radio communications network, all of the nodes cannot communicate with each other directly. Then packets are transferred from a source node to a destination node through several nodes. Therefore, we need to schedule transfer timing at each node, and communications routes must be assigned to minimize the total transfer time when many packet transfers are requested. This problem is divided into two problems: the communications route assignment problem and the scheduling problem. The former problem is subdivided into the communication route candidate extraction problem and the communication route se-lection problem. This paper first proposes an evaluation function (Cost) which gives the lowest limit of the total transfer time for the communication route assignment problem. Next this paper proposes a k-shortest route extraction procedure for the communication route extraction problem. This procedure is based on the k-shortest route algorithm. It prevents extraction of a route whose number of hops is more than the upper limit, sets an appropriate number of extraction routes, prevents loops, and prevents redundant route extraction. We also propose a greedy neural network procedure for the communication route selection problem. This procedure introduces the to function into the operation equation of the neuron initial value setting based on the number of hops and a cost minimization term for the evaluation function. The procedure uses an appropriate termination condition for iterative computation. It also uses the first-order maximum neuron. Through simulations of 500-vertex communication network examples, the proposed procedure has the merits of high precision, short computation, and smaller number of computations in a region.

AB - In a radio communications network, all of the nodes cannot communicate with each other directly. Then packets are transferred from a source node to a destination node through several nodes. Therefore, we need to schedule transfer timing at each node, and communications routes must be assigned to minimize the total transfer time when many packet transfers are requested. This problem is divided into two problems: the communications route assignment problem and the scheduling problem. The former problem is subdivided into the communication route candidate extraction problem and the communication route se-lection problem. This paper first proposes an evaluation function (Cost) which gives the lowest limit of the total transfer time for the communication route assignment problem. Next this paper proposes a k-shortest route extraction procedure for the communication route extraction problem. This procedure is based on the k-shortest route algorithm. It prevents extraction of a route whose number of hops is more than the upper limit, sets an appropriate number of extraction routes, prevents loops, and prevents redundant route extraction. We also propose a greedy neural network procedure for the communication route selection problem. This procedure introduces the to function into the operation equation of the neuron initial value setting based on the number of hops and a cost minimization term for the evaluation function. The procedure uses an appropriate termination condition for iterative computation. It also uses the first-order maximum neuron. Through simulations of 500-vertex communication network examples, the proposed procedure has the merits of high precision, short computation, and smaller number of computations in a region.

KW - Communication route assignment problem

KW - Greedy neural network

KW - Maximum neuron

KW - Radio communication

UR - http://www.scopus.com/inward/record.url?scp=0347018751&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0347018751&partnerID=8YFLogxK

M3 - Article

VL - 30

SP - 52

EP - 60

JO - Systems and Computers in Japan

JF - Systems and Computers in Japan

SN - 0882-1666

IS - 13

ER -