TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In se...

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Published in:Wireless networks Vol. 16; no. 4; pp. 985 - 997
Main Authors: Ergen, Sinem Coleri, Varaiya, Pravin
Format: Journal Article
Language:English
Published: Boston Springer US 01.05.2010
Springer Nature B.V
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ISSN:1022-0038, 1572-8196
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Abstract Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.
AbstractList Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10-70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.
Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10-70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.[PUBLICATION ABSTRACT]
Author Ergen, Sinem Coleri
Varaiya, Pravin
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  givenname: Sinem Coleri
  surname: Ergen
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  organization: Wireless Sensor Networks Lab, sponsored by Pirelli and Telecom Italia
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  givenname: Pravin
  surname: Varaiya
  fullname: Varaiya, Pravin
  organization: University of California
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Keywords MAC protocol
Scheduling algorithm
Sensor network
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PublicationSubtitle The Journal of Mobile Communication, Computation and Information
PublicationTitle Wireless networks
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ChakrabortyG.Genetic algorithm to solve optimum TDMA transmission schedule in broadcast packet radio NetworksIEEE Transactions on Communications200452576577710.1109/TCOMM.2004.826234
NgoC. Y.LiV. O. K.Centralized broadcast scheduling in packet radio networks via genetic-fix algorithmsIEEE Transactions on Communications20035191439144110.1109/TCOMM.2003.816950
MaoJ.WuZ.WuX.A TDMA scheduling scheme for many-to-one communications in wireless sensor networksComputer Communications200730486387210.1016/j.comcom.2006.10.006
GandhamS.DawandeM.PrakashR.Link scheduling in sensor networks: Distributed edge colering revisitedEEE INFOCOM2005424922762
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RamaswamiR.ParhiK. K.Distributed scheduling of broadcasts in a radio networkINFOCOM19892497504
Wang, Y., & Henning, I. (2007). A deterministic distributed TDMA scheduling algorithm for wireless sensor networks. IEEE WiCom, 2759–2762.
BansalS.KumarP.SinghK.An improved duplication strategy for scheduling precedence constrained graphs in multiprocessor systemsIEEE Transactions on Parallel and Distributed Systems200314653354410.1109/TPDS.2003.1206502
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G. Chakraborty (183_CR9) 2004; 52
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H. Fattah (183_CR5) 2002; 9
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References_xml – reference: ErgenS. C.VaraiyaP.On multi-hop routing for energy efficiencyIEEE Communications Letters200591088088110.1109/LCOMM.2005.10007
– reference: TavliB.HeinzelmanW. B.MH-TRACE: Multihop time reservation using adaptive control for energy efficiencyIEEE Journal on Selected Areas in Communications200422594295310.1109/JSAC.2004.826932
– reference: Ahuja, R. K., Magnanti, T. L., & Orlin, J. B. (1993). Network flows, Prentice Hall, Inc.
– reference: Wang, Y., & Henning, I. (2007). A deterministic distributed TDMA scheduling algorithm for wireless sensor networks. IEEE WiCom, 2759–2762.
– reference: ChakrabortyG.Genetic algorithm to solve optimum TDMA transmission schedule in broadcast packet radio NetworksIEEE Transactions on Communications200452576577710.1109/TCOMM.2004.826234
– reference: FattahH.LeungC.An overview of scheduling algorithms in wireless multimedia networksIEEE Wireless Communications200295768310.1109/MWC.2002.1043857
– reference: Uysal BiyikogluE.PrabhakarB.El GamalA.Energy-efficient packet transmission over a wireless linkIEEE/ACM Transactions on Networking2002101248749910.1109/TNET.2002.801419
– reference: RamaswamiR.ParhiK. K.Distributed scheduling of broadcasts in a radio networkINFOCOM19892497504
– reference: LAN-MAN Standards Committee of the IEEE Computer Society. (1997). Wireless LAN medium access control (MAC) and physical layer(PHY) specification (1997 ed.). New York, NY, USA: IEEE, IEEE Std 802.11.
– reference: GandhamS.DawandeM.PrakashR.Link scheduling in sensor networks: Distributed edge colering revisitedEEE INFOCOM2005424922762
– reference: BansalS.KumarP.SinghK.An improved duplication strategy for scheduling precedence constrained graphs in multiprocessor systemsIEEE Transactions on Parallel and Distributed Systems200314653354410.1109/TPDS.2003.1206502
– reference: MaoJ.WuZ.WuX.A TDMA scheduling scheme for many-to-one communications in wireless sensor networksComputer Communications200730486387210.1016/j.comcom.2006.10.006
– reference: NgoC. Y.LiV. O. K.Centralized broadcast scheduling in packet radio networks via genetic-fix algorithmsIEEE Transactions on Communications20035191439144110.1109/TCOMM.2003.816950
– reference: EphremidesA.TruongT. V.Scheduling broadcasts in multihop radio networksIEEE Transactions on Communications199038445646010.1109/26.52656
– reference: GandhamS.ZhangY.HuangQ.Distributed time-optimal scheduling for convergecast in wireless sensor networksComputer Networks20085236106291140.68342
– reference: Narayanaswamy, S., Kawadia, V., Sreenivas, R. S., & Kumar, P. R. (2002). Power control in Ad-Hoc networks: Theory, architecture, algorithm and implementation of the COMPOW protocol. Proceedings of European wireless, Italy, February.
– reference: Wang, W., Wang, Y., Li, X., Song, W., & Frieder, O. (2006). Efficient interference-aware TDMA link scheduling for static wireless networks. IEEE GLOBECOM, 262–273.
– reference: Hedetniemi, S. T., Jacobs, D.P., & Srimani, P. K. (2002). Fault tolerant distributed coloring algorithms that stabilize in linear time. International parallel and distributed processing symposium (IPDPS), April.
– reference: ErgenS. C.VaraiyaP.PEDAMACS: Power efficient and delay aware medium access protocol for sensor networksIEEE Transactions on Mobile Computing20075792093010.1109/TMC.2006.100
– reference: Cheung, S. Y., Coleri, S., Dundar, B., Ganesh, S., Tan, C.W., & Varaiya, P. (2006). Traffic measurement and vehicle classification with a single magnetic sensor. Journal of Transportation Research Board, 1917.
– reference: RamanathanS.LloydE. L.Scheduling algorithms for multihop radio networksIEEE/ACM Transactions on Networking19931216617710.1109/90.222924
– reference: Wu, Z., & Raychaudhuri, D. (2004). D-LSMA: Distributed link scheduling multiple access protocol for QoS in Ad-hoc networks. IEEE GLOBECOM, 1670–1675.
– reference: Polastre, J., Szewczyk, R., Sharp, C., & Culler, D. (2004). The mote revolution: Low power wireless sensor network devices, hot chips 16: A symposium on high performance chips, August.
– reference: Choi, H., Wang, J., & Hughes, E. A. (2005). Scheduling on sensor hybrid networks. IEEE ICCCN, 503–508.
– reference: Krishnamachari, B., Wicker, S. B., & Bejar, B. (2001). Phase transition phenomena in wireless Ad-Hoc networks. Symposium on Ad-Hoc wireless networks, GlobeCom2001, San Antonio, Texas, November.
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SubjectTerms Access control
Communications Engineering
Computer Communication Networks
Electrical Engineering
Energy consumption
Engineering
Genetic algorithms
Heuristic
IT in Business
Networks
Protocol
Schedules
Scheduling
Scheduling algorithms
Sensors
Signal processing
Studies
Wireless communications
Wireless networks
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