An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks

Overloaded network devices are becoming an increasing problem especially in resource limited networks with the continuous and rapid increase of wireless devices and the huge volume of data generated. Admission and routing control policy at a network device can be used to balance the goals of maximiz...

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Main Author: Essia Hamouda
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/22/6566
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spelling doaj-9e23841d046b4a31a42cb2f81ce195d22020-11-25T04:07:29ZengMDPI AGSensors1424-82202020-11-01206566656610.3390/s20226566An Optimal Flow Admission and Routing Control Policy for Resource Constrained NetworksEssia Hamouda0J. H. Brown College of Business & Public Administration, California State University, San Bernardino, CA 92407, USAOverloaded network devices are becoming an increasing problem especially in resource limited networks with the continuous and rapid increase of wireless devices and the huge volume of data generated. Admission and routing control policy at a network device can be used to balance the goals of maximizing throughput and ensuring sufficient resources for high priority flows. In this paper we formulate the admission and routing control problem of two types of flows where one has a higher priority than the other as a Markov decision problem. We characterize the optimal admission and routing policy, and show that it is a state-dependent threshold type policy. Furthermore, we conduct extensive numerical experiments to gain more insight into the behavior of the optimal policy under different systems’ parameters. While dynamic programming can be used to solve such problems, the large size of the state space makes it untractable and too resource intensive to run on wireless devices. Therefore, we propose a fast heuristic that exploits the structure of the optimal policy. We empirically show that the heuristic performs very well with an average reward deviation of 1.4% from the optimal while being orders of magnitude faster than the optimal policy. We further generalize the heuristic for the general case of a system with <i>n</i> (<inline-formula><math display="inline"><semantics><mrow><mi>n</mi><mo>></mo><mn>2</mn></mrow></semantics></math></inline-formula>) types of flows.https://www.mdpi.com/1424-8220/20/22/6566wireless communicationperformance optimizationmarkov decision processenergy efficiencythreshold routingsensor networks
collection DOAJ
language English
format Article
sources DOAJ
author Essia Hamouda
spellingShingle Essia Hamouda
An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks
Sensors
wireless communication
performance optimization
markov decision process
energy efficiency
threshold routing
sensor networks
author_facet Essia Hamouda
author_sort Essia Hamouda
title An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks
title_short An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks
title_full An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks
title_fullStr An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks
title_full_unstemmed An Optimal Flow Admission and Routing Control Policy for Resource Constrained Networks
title_sort optimal flow admission and routing control policy for resource constrained networks
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-11-01
description Overloaded network devices are becoming an increasing problem especially in resource limited networks with the continuous and rapid increase of wireless devices and the huge volume of data generated. Admission and routing control policy at a network device can be used to balance the goals of maximizing throughput and ensuring sufficient resources for high priority flows. In this paper we formulate the admission and routing control problem of two types of flows where one has a higher priority than the other as a Markov decision problem. We characterize the optimal admission and routing policy, and show that it is a state-dependent threshold type policy. Furthermore, we conduct extensive numerical experiments to gain more insight into the behavior of the optimal policy under different systems’ parameters. While dynamic programming can be used to solve such problems, the large size of the state space makes it untractable and too resource intensive to run on wireless devices. Therefore, we propose a fast heuristic that exploits the structure of the optimal policy. We empirically show that the heuristic performs very well with an average reward deviation of 1.4% from the optimal while being orders of magnitude faster than the optimal policy. We further generalize the heuristic for the general case of a system with <i>n</i> (<inline-formula><math display="inline"><semantics><mrow><mi>n</mi><mo>></mo><mn>2</mn></mrow></semantics></math></inline-formula>) types of flows.
topic wireless communication
performance optimization
markov decision process
energy efficiency
threshold routing
sensor networks
url https://www.mdpi.com/1424-8220/20/22/6566
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