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

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
Outline Multicast Trees in Wireless Ad Hoc Networks

  • Problem Statement

  • Challenges

  • Background and Related Work

  • System Model & Assumptions

  • Node’s Energy Consumption Metric

  • G-REMiT Algorithm & Performance Results

  • Conclusions


Problem statement
Problem Statement Multicast Trees in Wireless Ad Hoc Networks

  • 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
Difference of Wired & Wireless Network Multicast Trees in Wireless Ad Hoc Networks

Wired Network Graph

Wireless Network Graph


Challenges
Challenges Multicast Trees in Wireless Ad Hoc Networks

  • Transmission Power determines

    • The total amount of energy consumed on the link

    • Feasible of the link

    • Network topology


Background and current state of art
Background and Current Multicast Trees in Wireless Ad Hoc NetworksState 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 art1
Background and Current Multicast Trees in Wireless Ad Hoc NetworksState of Art

Wireless Multicast Advantage


Background and current state of art2
Background and Current Multicast Trees in Wireless Ad Hoc NetworksState 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 art3
Background and Current Multicast Trees in Wireless Ad Hoc NetworksState 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
System Model & Assumptions Multicast Trees in Wireless Ad Hoc Networks

  • 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


Wireless communication model

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
Node’s Energy consumption in different multicast sessions is Euclidean distance between i and j,


A group shared tree example
A Group-shared Tree Example is Euclidean distance between i and j,


Node s energy cost metric in group shared tree
Node’s energy cost metric in Group-shared Tree) is Euclidean distance between i and j,

  • Energy consumed at node i is

  • If we introduce , then

  • Node’s Relative Energy Cost Metric


G remit algorithm
G-REMiT Algorithm is Euclidean distance between i and j,

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


Example of refinement at a node for minimizing energy consumption of the 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


Tree s energy consumption oscillation avoidance

R its new connection tree neighbor. And make .10 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
Disconnection Refinement its new connection tree neighbor. And make .

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


G remit algorithm description
G-REMiT Algorithm Description its new connection tree neighbor. And make .

  • 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
Second Phase of G-REMiT its new connection tree neighbor. And make .


Performance results
Performance Results its new connection tree neighbor. And make .

Normalized TPC when 50% nodes are multicast group nodes


Performance results cont
Performance Results (Cont.) its new connection tree neighbor. And make .

Normalized TPC for a graph with 100 nodes


Conclusions
Conclusions its new connection tree neighbor. And make .

  • 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
Future Work its new connection tree neighbor. And make .

  • 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
Reference its new connection tree neighbor. And make .

[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.