Reporter: Hung-Wei Liu Advisor: Tsung-Hung Lin 1

 Published in IET Communications, IET Commun., 2009, Vol. 3, Iss. 5, pp. 733–739  Author: H. Fariborzi, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA M. Moghavvemi, Department of Electrical Engineering, University of Malaya, Kuala Lumpur, Malaysia 2

 Introduction  EAMTR protocol  Simulation results and performance evaluation  Conclusions 3

 IEEE To render a favorable framework for WSN To define PHY and MAC layers  ZigBee- It is an integrated standard based on IEEE To specify the upper layers. Tree routing 4

 IEEE Meshed tree routing Mesh Fig.1 Tree routing in IEEE Fig.2 Meshed tree routing in IEEE

 Hotspot Problem A(R) D B(R) E C R: Router Fig.3 Both A and B have larger Workload (A>B>C=D=E) => Imbalance workload Workload flow R 6

 EAMTR protocol: The authors proposed in this paper Energy aware multi-tree routing To relieve the hotspot problems 7

 Addressing scheme  Initialisation phase  Tree selection phase  Normal phase  Recovery phase 8

 Addressing scheme 16-bit MAC short address The MAC address has two parts:  TIBs(Tree identification bits)  Node address 9

Fig.1 MAC short address assignment 10

 Initialisation phase The EAMTR trees are created in this phase. Parent-select sub-algorithm  To achieve more diverse topologies for different trees and, hence, increase the number of available routes from each node to the sink node(root). 11

 It considers two criteria for choosing the proper parent:  Minimum counter  Link quality index (LQI) 12

Sink P1P2 P3 Tree 1 link Tree 2 link Request connection in Tree 2 (a)Minimum counter P1 > P2, p2 are selected as P3 parent in Tree2 13

Sink P1P2 P3 Tree 1 link Tree 2 link Request connection in Tree 2 (b)Minimum counter P1 = P2,but LQI P1>P2, p1 are selected as P3 parent Fig. 2 parent-select sub-algorithm 14

 Tree selection phase All of the nodes gradually select their respective minimum cost tree as their main routing tree. NodeCost  It is a counter for each node, which is increased one unit upon selection of any of its respective trees as the main tree for any node in the network. 15

Sink P1P2 P3 15 NodeCost(P3,Tree1)= 15+15=30 Sink P1P2 P NodeCost(P3,Tree2)=10+15=25 Fig. 3 Tree selection phase: NodeCost(P3,Tree1)>NodeCost(P3,Tree2), the main routing tree of P3 is Tree2 16

 Normal phase In this phase, moderate changes in the number of nodes and topology of the network.  Recovery phase If a node x detected a failure of its main tree, node x would replace its old main tree with its first alternative tree in the lowest-cost queue as obtained by the tree selection algorithm. 17

 Experimental setup IEEE NS2 simulator For simulation and performance evaluation of EAMTR in comparison with :  ZTR(ZigBee tree routing)  AODVZ(ZigBee compliant version of ad hoc on demand vector routing) The environmental parameters is shown as Table 1: 18

ParameterValue Network area65 m * 65 m Number of nodes20,40,60,80,100,120,160 Transmission range of all nodes15 m Constant bit rate0.1 – 2 pps(packet per second) Packet size80 bytes TIB2 The beacon and superframe orders are set to 3. The simulation duration for the first three experiments is 1500s; the evaluation of energy consumption is performed over a 3000s interval. Table 1. Environmental parameters 19

 Performance metrics: Packet delivery ratio Average end-to-end delay Energy consumption 20

 Simulation result Figure 4. Packet delivery ratio for variable Number of nodes and traffic load of 0.7pps Figure 5. Average end-to-end delay for traffic load of 0.7pps 21

Figure 6. Distribution of energy consumption in the network: (a)EAMTR, (b)ZTR, (c)AODVZ (c) (b) (a) Energy consumed 22

 According to simulations by the IEEE NS-2.32 simulator, EAMTR contributes to reliability and stability of the network by balancing the energy consumption of nodes and relieving network congestion. 23

24