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Energy-Efficient Broadcast and Multicast Trees for Reliable Wireless Communication. Suman Banerjee, Archan Misra, Jihwang Yeo and Ashok Agrawala IEEE Wireless Communications and Networking Conference (WCNC) 2003 Speaker: Ju-Mei Li. Outline. Introduction Calculating Energy Costs
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Energy-Efficient Broadcast and Multicast Trees for Reliable Wireless Communication Suman Banerjee, Archan Misra, Jihwang Yeo and Ashok Agrawala IEEE Wireless Communications and Networking Conference (WCNC) 2003 Speaker: Ju-Mei Li
Outline • Introduction • Calculating Energy Costs • Retransmission-Aware Minimum Energy Trees • Performance Comparisons • Conclusions
Introduction • In wireless environments • Individual links often have high error rates • Currently minimum-energy tree formation algorithms • Assign costs to links based on the energy spent in a signal transmission • Do not consider the link error rates
Introduction • Wieseltheir et al [10] • Have constant approximation ratios to the optimal solution for error-free wireless links • Three broadcast tree formation algorithms • Broadcast Incremental Power (BIP) • Broadcast Least-Unicast-cost (BLU) • Broadcast Link-based MST (BLiMST)
Introduction: BIP 2 4 10 8 9 1 6 7 5 3
Introduction: BLU and BLiMST 2 2 4 4 10 10 8 8 9 9 1 1 6 6 7 7 5 5 3 3 BLU BLiMST
Assumption • Error ratepi,jfor any link (i, j): 30~40% • No mobility • Packet will be retransmission until all children receive it • ACK • Chooses minimum power to reach each child which does not receive broadcast packet • NAK: just one NAK will be received by sender • Use a transmission power to reach all children on the tree
Calculating Energy Costs • Packet error rate, • S[i].error = p = 1 – (1 - pb)s • S[i].not_rcv_prob = S[i].not_rcv_prob * (S[i].error)tx pb is the bit error rate and s is the packet size
Calculating Energy Costs: ComputeTxCost(x, S) The set within the transmission power and is sorted by decreasing order of distance from x • For i1 • Px,i1: transmission a packet from x to i1 • Ex,i1: single transmission power • Use Px,i1 i1.error, i2.error and i3.error • Use i1.error tx (number of reliable transmissions of i1) • Use tx, Ex,i1 and i1.not_rcv_prob cost of i1 • Update i2.not_rcv_prob and i3.not_rcv_prob • For i2 • Px,i2: transmission a packet from x to i1 • Ex,i2: single transmission power • Use Px,i2 i1.error, i2.error and i3.error • Use i2.error tx (number of reliable transmissions of i2) • Use tx, Ex,i2 and i2.not_rcv_prob cost of i2 • Update i3.not_rcv_prob • For i3 • Px,i3: transmission a packet from x to i1 • Ex,i3: single transmission power • Use Px,i3 i1.error, i2.error and i3.error • Use i3.error tx (number of reliable transmissions of i3) • Use tx, Ex,i3 and i3.not_rcv_prob cost of i3 i1 i1 i3 i3 x i2 i2
Retransmission-Aware Minimum Energy Trees • RBIP • RBLU • RBLiMST • Sweep algorithm • Multicast trees
Retransmission-Aware Minimum Energy Trees: RBIP Update cost and parent of node 5 and node 6 5 5 3 3 2 2 6 6 1 7 7 4 4 Update Cost and parent of node 3 and node 4
Retransmission-Aware Minimum Energy Trees: RBIP • Like the BLU, but the cost of link (i, j) • Ei,j (reliable) = Ei,j * (1/1 – pi, j) 5 3 2 6 1 7 4
Retransmission-Aware Minimum Energy Trees: RBLiMST • Like extension of BLiMST algorithm 5 3 2 6 1 7 4
Retransmission-Aware Minimum Energy Trees • Sweep algorithm in a post order traversal of the tree • Δy = ComputeTxCost(y, Cy – {x}) – ComputeTxCost(y, Cy) • Δz = ComputeTxCost(z, Cz {x}) – ComputeTxCost(z, Cz) Cy Cz x z Cz y Cy Cz
Retransmission-Aware Minimum Energy Trees • Multicast trees • Compute the broadcast tree without using sweep algorithm • Delete nodes which do not lead to any multicast group numbers (in a single post-order traversal) • Sweep algorithm are performed on the remaining tree (in post-order)
Performance Comparisons • 100 nodes • Network environment • Random • Grid: 100*100 square gird • 100 runs for each result
Conclusions • for multi-hop wireless environments • Present energy-efficient reliable broadcast and multicast schemes • ACK • NAK