Collecting Data in Ad-Hoc Networks with Reduced Uncertainty

Liron Levin; Alon Efrat; Michael Segal

Collecting Data in Ad-Hoc Networks with Reduced Uncertainty

Liron Levin, Alon Efrat, Michael Segal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We consider the data gathering problem in wireless ad-hoc networks where a data mule traverses a set of sensors, each with vital information on its surrounding, and collects their data. The mule goal is to collect as much data as possible, thereby reducing the information uncertainty, while minimizing its travel distance. We show that the problem is solvable by a generalized version of the Prize Collecting Steiner Tree Problem, and present a dual-primal 6-approximation algorithm for solving it. Simulation results show that the proposed schema converges to the optimal results for varying set of topologies, such as grids, stars, linear and random networks.

Original language	American English
Title of host publication	2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013
Pages	659-666
Number of pages	8
State	Published - 3 Sep 2013
Event	2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013 - Tsukuba Science City, Japan Duration: 13 May 2013 → 17 May 2013

Conference

Conference	2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013
Country/Territory	Japan
City	Tsukuba Science City
Period	13/05/13 → 17/05/13

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Modelling and Simulation

Cite this

@inproceedings{28caf4dcf5134ec49374945db2c08895,

title = "Collecting Data in Ad-Hoc Networks with Reduced Uncertainty",

abstract = "We consider the data gathering problem in wireless ad-hoc networks where a data mule traverses a set of sensors, each with vital information on its surrounding, and collects their data. The mule goal is to collect as much data as possible, thereby reducing the information uncertainty, while minimizing its travel distance. We show that the problem is solvable by a generalized version of the Prize Collecting Steiner Tree Problem, and present a dual-primal 6-approximation algorithm for solving it. Simulation results show that the proposed schema converges to the optimal results for varying set of topologies, such as grids, stars, linear and random networks.",

author = "Liron Levin and Alon Efrat and Michael Segal",

year = "2013",

month = sep,

day = "3",

language = "American English",

isbn = "9783901882548",

pages = "659--666",

booktitle = "2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013",

note = "2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013 ; Conference date: 13-05-2013 Through 17-05-2013",

}

Levin, L, Efrat, A & Segal, M 2013, Collecting Data in Ad-Hoc Networks with Reduced Uncertainty. in 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013., 6576418, pp. 659-666, 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013, Tsukuba Science City, Japan, 13/05/13.

TY - GEN

T1 - Collecting Data in Ad-Hoc Networks with Reduced Uncertainty

AU - Levin, Liron

AU - Efrat, Alon

AU - Segal, Michael

PY - 2013/9/3

Y1 - 2013/9/3

N2 - We consider the data gathering problem in wireless ad-hoc networks where a data mule traverses a set of sensors, each with vital information on its surrounding, and collects their data. The mule goal is to collect as much data as possible, thereby reducing the information uncertainty, while minimizing its travel distance. We show that the problem is solvable by a generalized version of the Prize Collecting Steiner Tree Problem, and present a dual-primal 6-approximation algorithm for solving it. Simulation results show that the proposed schema converges to the optimal results for varying set of topologies, such as grids, stars, linear and random networks.

AB - We consider the data gathering problem in wireless ad-hoc networks where a data mule traverses a set of sensors, each with vital information on its surrounding, and collects their data. The mule goal is to collect as much data as possible, thereby reducing the information uncertainty, while minimizing its travel distance. We show that the problem is solvable by a generalized version of the Prize Collecting Steiner Tree Problem, and present a dual-primal 6-approximation algorithm for solving it. Simulation results show that the proposed schema converges to the optimal results for varying set of topologies, such as grids, stars, linear and random networks.

UR - http://www.scopus.com/inward/record.url?scp=84883182239&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9783901882548

SP - 659

EP - 666

BT - 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013

T2 - 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2013

Y2 - 13 May 2013 through 17 May 2013

ER -

Collecting Data in Ad-Hoc Networks with Reduced Uncertainty

Abstract

Conference

All Science Journal Classification (ASJC) codes

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