Adaptive In-Network Processing for Bandwidth and Energy Constrained Mission-Oriented Multihop Wireless Networks

Sharanya Eswaran, James Edwards, Thomas F. La Porta, Archan Misra

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

In-network Processing, involving operations such as filtering, compression, and fusion is a technique widely used in wireless sensor and ad hoc networks for reducing the communication overhead. In many tactical stream-oriented applications, especially in military scenarios, both link bandwidth and node energy are critically constrained resources. For such applications, innetwork processing itself imposes nonnegligible computing cost. In this work, we have developed a unified, utility-based closed-loop control framework that permits distributed convergence to both 1) the optimal level of compression performed by a forwarding node on streams, and 2) the best set of nodes where the operators of the stream processing graph should be deployed. We also show how the generalized model can be adapted to more realistic cases, where the in-network operator may be varied only in discrete steps, and where a fusion operation cannot be fractionally distributed across multiple nodes. Finally, we provide a real-time implementation of the protocol on an 802.11b network with a video application and show that the performance of the network is improved significantly in terms of the packet loss, node lifetime, and quality of video received.

Original languageEnglish (US)
Pages (from-to)1484-1498
Number of pages15
JournalIEEE Transactions on Mobile Computing
Volume11
Issue number9
DOIs
StatePublished - Jan 1 2012

Fingerprint

Wireless networks
Bandwidth
Fusion reactions
Processing
Packet loss
Ad hoc networks
Telecommunication links
Network protocols
Communication
Sensors
Costs

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

@article{3591ca8fdaff4751a7e8f702313197d9,
title = "Adaptive In-Network Processing for Bandwidth and Energy Constrained Mission-Oriented Multihop Wireless Networks",
abstract = "In-network Processing, involving operations such as filtering, compression, and fusion is a technique widely used in wireless sensor and ad hoc networks for reducing the communication overhead. In many tactical stream-oriented applications, especially in military scenarios, both link bandwidth and node energy are critically constrained resources. For such applications, innetwork processing itself imposes nonnegligible computing cost. In this work, we have developed a unified, utility-based closed-loop control framework that permits distributed convergence to both 1) the optimal level of compression performed by a forwarding node on streams, and 2) the best set of nodes where the operators of the stream processing graph should be deployed. We also show how the generalized model can be adapted to more realistic cases, where the in-network operator may be varied only in discrete steps, and where a fusion operation cannot be fractionally distributed across multiple nodes. Finally, we provide a real-time implementation of the protocol on an 802.11b network with a video application and show that the performance of the network is improved significantly in terms of the packet loss, node lifetime, and quality of video received.",
author = "Sharanya Eswaran and James Edwards and {La Porta}, {Thomas F.} and Archan Misra",
year = "2012",
month = "1",
day = "1",
doi = "10.1109/TMC.2011.169",
language = "English (US)",
volume = "11",
pages = "1484--1498",
journal = "IEEE Transactions on Mobile Computing",
issn = "1536-1233",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "9",

}

Adaptive In-Network Processing for Bandwidth and Energy Constrained Mission-Oriented Multihop Wireless Networks. / Eswaran, Sharanya; Edwards, James; La Porta, Thomas F.; Misra, Archan.

In: IEEE Transactions on Mobile Computing, Vol. 11, No. 9, 01.01.2012, p. 1484-1498.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Adaptive In-Network Processing for Bandwidth and Energy Constrained Mission-Oriented Multihop Wireless Networks

AU - Eswaran, Sharanya

AU - Edwards, James

AU - La Porta, Thomas F.

AU - Misra, Archan

PY - 2012/1/1

Y1 - 2012/1/1

N2 - In-network Processing, involving operations such as filtering, compression, and fusion is a technique widely used in wireless sensor and ad hoc networks for reducing the communication overhead. In many tactical stream-oriented applications, especially in military scenarios, both link bandwidth and node energy are critically constrained resources. For such applications, innetwork processing itself imposes nonnegligible computing cost. In this work, we have developed a unified, utility-based closed-loop control framework that permits distributed convergence to both 1) the optimal level of compression performed by a forwarding node on streams, and 2) the best set of nodes where the operators of the stream processing graph should be deployed. We also show how the generalized model can be adapted to more realistic cases, where the in-network operator may be varied only in discrete steps, and where a fusion operation cannot be fractionally distributed across multiple nodes. Finally, we provide a real-time implementation of the protocol on an 802.11b network with a video application and show that the performance of the network is improved significantly in terms of the packet loss, node lifetime, and quality of video received.

AB - In-network Processing, involving operations such as filtering, compression, and fusion is a technique widely used in wireless sensor and ad hoc networks for reducing the communication overhead. In many tactical stream-oriented applications, especially in military scenarios, both link bandwidth and node energy are critically constrained resources. For such applications, innetwork processing itself imposes nonnegligible computing cost. In this work, we have developed a unified, utility-based closed-loop control framework that permits distributed convergence to both 1) the optimal level of compression performed by a forwarding node on streams, and 2) the best set of nodes where the operators of the stream processing graph should be deployed. We also show how the generalized model can be adapted to more realistic cases, where the in-network operator may be varied only in discrete steps, and where a fusion operation cannot be fractionally distributed across multiple nodes. Finally, we provide a real-time implementation of the protocol on an 802.11b network with a video application and show that the performance of the network is improved significantly in terms of the packet loss, node lifetime, and quality of video received.

UR - http://www.scopus.com/inward/record.url?scp=85008539400&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85008539400&partnerID=8YFLogxK

U2 - 10.1109/TMC.2011.169

DO - 10.1109/TMC.2011.169

M3 - Article

VL - 11

SP - 1484

EP - 1498

JO - IEEE Transactions on Mobile Computing

JF - IEEE Transactions on Mobile Computing

SN - 1536-1233

IS - 9

ER -