G remit an algorithm for building energy efficient multicast trees in wireless ad hoc networks
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G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks. Bin Wang and Sandeep K. S. Gupta Computer Science and Engineering Department Arizona State University Tempe, AZ, USA {Bin.Wang,Sandeep.Gupta}@asu.edu. Outline. Problem Statement Challenges

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G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks

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G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks

Bin Wang and Sandeep K. S. Gupta

Computer Science and Engineering Department

Arizona State University

Tempe, AZ, USA

{Bin.Wang,Sandeep.Gupta}@asu.edu


Outline

  • Problem Statement

  • Challenges

  • Background and Related Work

  • System Model & Assumptions

  • Node’s Energy Consumption Metric

  • G-REMiT Algorithm & Performance Results

  • Conclusions


Problem Statement

  • Given a set of nodes with

    • wireless transceiver and

    • power control ability

  • Find

    • a group-shared multicast tree such that the total energy consumption of all the nodes is minimized


Difference of Wired & Wireless Network

Wired Network Graph

Wireless Network Graph


Challenges

  • Transmission Power determines

    • The total amount of energy consumed on the link

    • Feasible of the link

    • Network topology


Background and Current State of Art

  • Multicasting

    • What is?

      • Allow one entity to communicate efficiently with multiple entities residing in a subset of the nodes in the network

    • Why multi-destination delivery in a single message?

      • Transparency; Efficiency; Concurrency

    • Applications (e.g, distributed database, distributed games, teleconferencing)


Background and Current State of Art

Wireless Multicast Advantage


Background and Current State of Art

  • Building energy-efficient broadcast/ multicast tree

    • Optimal solution is NP-hard problem [Li LCN2001], heuristic algorithm is needed

    • Distributed Solution vs. Centralized Solution

      • High overhead to obtain global knowledge

      • Dynamic of wireless link and data traffic


Background and Current State of Art

  • Current heuristic algorithms for building energy efficient broadcast/multicast tree

    • Minimize cost metric increment for adding a node in the source-based tree.

      • Using cost metric with energy cost (BIP/MIP, BLU/MLU, BLiMST/MLiMST [Wieselthier Infocom2000]); Dist-BIP-A, Dist-BIP-G [Wieselthier Milcom2002]

    • Refine a minimum spanning tree (MST) by cover as more downstream node as possible in source-based tree

      • EWMA, Dist-EWMA [Cagalj Mobicom2002]


System Model & Assumptions

  • Static Wireless Ad hoc Network

  • Each node knows the distance between itself and its neighbor nodes

  • Every node knows the number of nodes in the multicast group

  • Group message generation rate (in term of bit/s) at every node follow Poisson distribution. And all of these message generation rates are independent random variables


where is energy cost of transmission processing, is Euclidean distance between i and j,  is propagation loss exponent, K is a constant dependent upon the antenna.

Wireless Communication Model

  • The minimum power needed for link between nodes i and j for a packet transmission is:

  • For short range radio,

[Feeney Infocom2001]

So is not negligible


Node’s Energy consumption in different multicast sessions


A Group-shared Tree Example


Node’s energy cost metric in Group-shared Tree)

  • Energy consumed at node i is

  • If we introduce , then

  • Node’s Relative Energy Cost Metric


G-REMiT Algorithm

  • Idea: a node changes its connected tree neighbor to minimize the total energy consumption of tree.


has the largest positive value. So node 2 select node 6 as its new connection tree neighbor. And make .

Example of Refinement at a node for minimizing energy consumption of the Tree


R10 may be affected by , because

may be changed.

Tree’s Energy Consumption Oscillation Avoidance

  • Lemma 1 : Nodes that are on tree pathj,i are the only nodes in the multicast tree that may be affected by Changeix,j


Disconnection Refinement

  • Lemma 2: If i is not on tree pathj,x the tree remains connected after Changeix,j


G-REMiT Algorithm Description

  • Two phases (Core-Based Tree)

    • First Phase: using distributed algorithm to build MST [Gallager TPLS1983].

    • Second Phase: organized by rounds. Each round is leaded by the core node. It terminates G-REMiT algorithm where there is no gains by switching any node in the multicast tree.

      • In each round, a depth-first search algorithm is used to pass G-REMiT token to the nodes one by one.


Second Phase of G-REMiT


Performance Results

Normalized TPC when 50% nodes are multicast group nodes


Performance Results (Cont.)

Normalized TPC for a graph with 100 nodes


Conclusions

  • Energy consumption metric for evaluating energy-efficiency of multicast protocol in WANET

  • G-REMiT is a distributed algorithm to construct an energy-efficient multicast tree.

  • G-REMiT Perform better than BIP/MIP Dist-BIP-G, and Dist-BIP-A algorithms for long range radios.

  • All of the algorithms have similar performance for short range radios.


Future Work

  • Energy efficient multicast in mobile ad hoc network

  • Multicast tree lifetime extension

  • Other schemes for energy efficient multicast of short range radios

    • Directional antenna

    • Scheduling sleep mode among the nodes


Reference

[1] J.E. Wieselthier, G.D. Nguyen, and A. Ephremides. On the construction of energy-efficient broadcast and multicast tree in wireless networks. In Proceedings of the IEEE INFOCOM 2000, pages 585–594, Tel Aviv, ISRAEL, March 2000.

[2] J. E. Wieselthier, G. D. Nguyen, and A. Ephremides, Distributed algorithms for energy-efficient broadcasting in ad hoc networks, Proceedings of MilCom, Anaheim, CA, Oct. 2002.

[3] M. Cagalj, J.P. Hubaux, and C. Enz. Minimum-energy broadcast in All-wireless networks: NP-completeness and distribution issues. In Proceedings of ACM MobiCom 2002, pages 172 – 182,Atlanta, Georgia, September 2002.

[4] F. Li and I. Nikolaidis. On minimum-energy broadcasting in all-wireless networks. In Proceedings of the 26th Annual IEEE Conference on Local Computer Networks (LCN 2001), pages 193–202, Tampa, Florida, November 2001.

[5] R.G. Gallager, P. A. Humblet, and P. M. Spira. A distributed algorithm for minimum weight spanning trees. ACM Transactions on Programming Languages and Systems, 5(1):66–77, January 1983.

[6] L. M. Feeney and M. Nilsson. Investigating the energy consumption of a wireless network interface in an ad hoc networking environment. In Proceedings of IEEE INFOCOM, Anchorage, pages 1548 –1557, AK, April 2001.


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