ELFR: Energy-aware Load-balancing Fault-tolerantRouting Scheme for Ad hoc Sensor Networks

Zongkai Yang, Zhiqiang Xiong, Wei Liu, Qifei Zhang, Bo ChengDept. of Electronics and Information Engineering, Huazhong University of Sci. & Tech., P.R.China

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Abstract- Most routing protocols for sensor networks try toextend network lifetime by minimizing the energy consumption,but have not taken the network reliability into account. To beadaptive to the harsh environment, we propose an Energy-aware,Load-balancing and Fault-tolerant routing scheme, termed asELFR. We first present a network robustness model. Basedon this model, we design the route discovery phase to makethe sensors to construct into a hop-leveled network which ismesh structure. We adopt a cross-layer design to measure thetransmission delay so as to detect the failed nodes. The routingscheme works with ACK feedback mechanism to transfer controlmessages to avoid producing extra control overhead messages.When nodes fail, the new healthy paths will be selected locallywithout rerouting. Simulation results show that our schemeis much robust, and it achieves better energy efficiency, loadbalancing and maintains good end-to-end delay.

I. INTRODUCTION

Reliability and fault tolerance issues in sophisticated sensornetworks have become a critical area of research today. An-other one of the most important design constraints in wirelesssensor network architectures [1] is Energy. The level of powerconsumption must be considered at each stage in wirelesssensor network design, as well as the reliability consideration.An energy-aware load-balanced fault-tolerant routing

scheme, termed as ELFR, is proposed in this paper. We focuson not the single nodes but the paths and the mesh structureof sensor networks. The joint nodes with multiple paths tosink play a very important role in our scheme. They maintainenergy and delay information of paths and conclude the pathfailing states so as to make the routing decision. Firstly, thesensor network is constructed as a hop leveled network by abroadcast from sink. Then the joint nodes which are on thecross of different paths obtain the path-congestion and path-energy information to figure out the fault knowledge and main-tain routing tables. We believe that wireless sensor networks(WSN) should operate in this kind of local, distributed manner.And we send control messages piggybacked on ACK packetsin MAC layer; therefore, little extra overhead messages areneeded. We evaluate ELFR via simulation using NS2 andcompare it to a classical robust routing protocol DirectedDiffusion [2] in wireless sensor networks and the on-demandrouting protocol AODV [3]. The performance results show that

This work is supported by the National Natural Science Foundation ofChina (No.60572049).

ELFR has better energy efficiency, load sharing and end-to-enddelay, and is more reliable than the others.

The rest of this paper is organized as follows. Section 2presents related works conducted in fault-tolerant and energy-efficient routing protocols in WSN. In section 3, we givethe robustness model and network model. Section 4 describesthe ELFR scheme. The simulation description and results areshown in section 5. At last we will conclude the paper insection 6.

II. RELATED WORKS

A fault-tolerant clustering scheme is proposed in [4] todetect the failure and to recover sensors from the failedgateway node. But the authors do not address how to placethe gateway/relay nodes and assume each sensor node in thefailed cluster has at least one backup relay node available,which is not very certain. Multi-path version of the DirectedDiffusion paradigm [2] uses multiple routing paths to transferdata, so that node failures in one path can be overcomeby sending the data through multiple paths, which increasesenergy consumption and can cause packet collisions. ARRIVE[5] and INSENS [6] use variations of this concept to cope withnode failures. [7] proposes a solution for tolerance to bothrandom node failure and area failure, while the nodes have toexchange information through a protocol that has three phaseswhich can be a cause for extra delays.

In [8] the authors propose to use multiple proxy nodes insensor networks and the FEC erasure code in routing layer.The concept of multiple proxy nodes is very interesting, butthose proxy nodes need to communicate with base station di-rectly. So they need stronger transfer power which is expensivein wireless sensor networks. [9] is based on flooding algorithmand proposes a new concept of virtual aperture. Althoughflooding mechanic is fault tolerant, the energy consumptionin [9] is considerable and not very suitable for WSN. Authorspropose a new routing scheme in [10], which maximizes thelifetime of sensor network by adjusting the number of packetstraversing each node over multiple routes. The scheme focuseson link fail and does not take the node fail into account.

In the schemes presented by [11], [12], sensor nodes havemultiple paths to forward their data. Multi-path routing hasthe advantage on sharing energy depletion between all sensornodes. However, the drawback of the multi-path routing in[11], [12] is that sensor nodes only keep a local view on energy

1-4244-0463-0/06/$20.00 ©2006 IEEE

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R3 R4

Fig. 1. A Simple Illustration of Robustness Model

TABLE I

ROBUSTNESS FOR DIFFERENT HoP ROUTING SCHEMES

Routing Scheme RRIR2R3R4

Robustnessj IRI qq( q)(I -q)(1- q)(I -q)3

usage of their neighbors and the nodes in network cannot havean even traffic dispatch. The load balanced schemes proposedby [13] focuses on how to get a global view on energy ofsensor nodes, but how to maintain and update the routinginformation is not solved well and the delay time and networkrobustness are not taken into account.

Energy constraint is very critical to reliability in WSN.Nodes stop working if they deplete their energy, thus links willbreak and some parts of or even the whole of the network willbe failed. Many power-saving researches have been proposedto save the precious energy of sensor nodes. They save energy

in different aspects such as reducing the power spending on

modulation circuits [14], presenting convergence protocol on

the IEEE 802.11 physical layer [15], managing the power

usage on MAC layer of sensor nodes [16], [17], gathering databased on adaptive modulation [18]. Among these schemes,some power-saving mechanisms [14], [16], [17], [15] focus on

an individual device. We argue that power-saving of individualsensor node is not enough in sensor networks and the collab-oration of sensor nodes should be designed. And [18] doesnot promise satisfied tradeoff between energy consumptionreducing, traffic load-sharing and end-to-end delay.

III. ROBUSTNESS MODEL AND NETWORK MODEL

A. Robustness Model

To study the effect of robustness to node failures we use

the following model: we assume that every source nodeand intermediate node are liable to fail independently withprobability q, 0 < q < 1, and for simplicity we assume that thedestination node(sink node) is guaranteed to be working. Therobustness metric HR corresponding to the routing schemesRi, i = 1, 2, 3, 4 is the probability that a message sent fromthe source can reach the sink given these independent failureprobabilities. The calculation of this metric is in general a

difficult problem, with no known polynomial algorithm [19].For the sample configuration, however, this is easy to solveexactly as there are only 5 nodes involved. The correspondingrobustness metrics for each routing scheme can be calculatedto the values shown in the final column of table I.

. if(h( h,>h)2. does nothing3. })4. else if (hy = {1,-I5. x adds y into its ill-boundliAlk table6. }7. else8. x deletes its in-bound link table9. x adds y into its in-boUnd link table10. set lh, = h, + IIl }12. while ( wait for sone tine)l3. if (receives initial iessage again)14. goto 115.16.17. re-broadcast the initial i-essage with hx

Fig. 2. Initial Hop Leveled Network Algorithm

Let us now understand the implication of these calculations.In scheme R1, there is only one source node and a sink node,so obviously the robustness (i.e. the possibility of successfultransmission from source to sink) is 1 -q. And there areone source, intermediate and sink node respectively in routingscheme R2. The source node takes two hops to reach the sinkand the robustness is (1 q)2. Similarly, the robustness ofscheme R4 is (1 -q)3. Scheme R3 is much different becausesource node send data to sink through multiple paths. If oneof the two intermediate nodes in scheme R3 is robust, thedata from source will be relayed to sink successfully, so therobustness of scheme R3 is (1 -q) (1 q2). And we can easilydraw a conclusion that the robustness

R1 > R3 > R2 > R4,O < q <1

Although this is a simple analytical example with a smallnumber of nodes and arbitrary placements, it provides aninsight that the robustness of multi-hop routing schemes islower than single hop and the robustness of multi-path ishigher than single path.

B. Network Model

Assume all nodes in the network employ a same trans-mission range and have the same initial energy. The levelednetwork is constructed as follows. Each node x maintains avariable hx which is the hop count to the sink. Initially, thesink S sets its hop count hs = 0 and the every other node xsets its hop count hx = oo. Then the sink broadcasts level-initializing message with its hop count hs to its neighbors.When node x receives the level-initializing message from nodey, it extracts the hop count value h from the message andconducts the following algorithm, as shown in Fig.2.

After node x calculating the hop level, instead of re-broadcasting the message immediately, it is supposed to waita certain time. Because the initial messages from higher levelnodes may arrive later and the node x must wait to establisha shortest path to sink. In the initial phase, the waiting timeis acceptable.

, , _ . . _ , _ . . . .

joint node x. And we can conclude

J(x) = min{max{P(yi), P(y2), , P(yk)}, L(x)}.

Take the Figure 4 for example, joint node e has two paths:b -> S and c -> S. As defined above, we can see P(b) =

L(b) = 6, P(c) = L(c) = 5 and J(e) = P(b) = 6. Alsowe may make out that P(d) = L(a) = 2 and J(f) =

min{max{P(d), J(e)}, L(f)J} 6. Now it is very clear thatnode f should not choose d as its forwarder only because L(d)is the maximum energy level among the neighbors of node f.

Fig. 3. Network Leveling Procedure

24

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Fig. 4. Example of Path Selection in the Energy-aware Leveled Network

According to the Robustness Model, we are aware that morehop counts routing scheme causes higher possibility to fail.Therefor we take the minimal-hop-count spanning mesh toconstruct the network routing. Figure 3 gives an illustratedexample for building a hop-leveled network.

IV. ELFR SCHEME

A. Energy-Aware path-based model

Note that a sensor node in the hop-leveled network may

have multiple shortest paths to relay data to sink. For example,consider a leveled network as shown in Figure 4. The numberbesides each node represents its energy level. When node fat level 3 hops away from the sink has the data packet tosend, it has three routing paths to select: f -> d -> a S,f -> e -> b -> S and f -> e -> c -> S. Suppose that nodef selects the forwarder only with the highest energy level inits neighbors, say node d. That means node f selects pathf -> d -> a -> S to forward the data to sink. However we

can see that the node a in this path has very low energy leveland will shortly run out of its energy.

In order to avoid this fault, the joint nodes, in Figure 4 theyare node f and e, must know the lowest energy level of its eachpath to sink. Let L(x) denote the energy level of node x, andnotes that L(x) = Ei(I < i < k) (Ek is the energy level ofnode x and defined above). Let P(x) denote the energy levelof the path start at the node . Notes that P(x) is much differentfrom L(x), L(x) is the energy level of node while P(x) isthe lowest energy level of the path. That is to say, P(x) =

min{L(ni), L(n2), ..., L(nk)},, n,n2, ... , nk are the nodes

in the path. Let J(x) denote the path-available informationin joint nodes. Let Y1, Y2, . . ., Yk denote the neighbors of the

B. Energy-aware scheme using MAC Layer piggybackingBefore the initial phase described in section 2, the energy

level of each node is Ek and consequently the energy level ofeach path P(x) is Ek too. After the initial procedure, routingpaths will be established in the sensor networks and some

energy is supposed to be consumed. If the energy level ofnode x reduces to L(x) = Ek1 or even less, node x will findL(x) < P(x) and broadcast energy-level-changed message tothe network. Only the node y which hop level is hx + 1 willreceive this kind of message and compares L(x) with its ownenergy level L(y) and P(x). If L(x) < L(y) and L(x) <P(x), node y will update the energy level of this path andre-broadcast the energy-level-changed message to the nodeswhich hop level is hx + 2. This re-broadcasting procedureends at the joint node or the leaf node of this path. Take theFigure 4 for example, if the energy level of node a reducesfrom 3 to 2, node a will broadcast the energy-level-changedmessage. If node b and sink receive this message, they willdiscard the messages because the hop levels don't match. Onlynode d will extract the message, update P(d) to 2 and sendthe message to node f. Thus node f may update its routingtable so as to make a proper forwarding decision. Also thejoint nodes mark themselves as joint nodes by hop level andthe number of up-link neighbors.When the joint nodes update the energy level of the path,

they should make the nodes in this path be aware of the newP(x) in case that each node in this path would broadcast an

energy-level-changed message even if its energy level remainsstill much higher than the P(x). In a scarce bandwidth andresource environment, such as sensor networks, we cannotafford to use announcing packets to update P(x) of every

node in the path. Instead we use the data packets with new

P(x) and each node may update the P(x) while this kind ofdata packets forwarding along the path.

This energy-aware path-based scheme shows advantages on

many aspects. Firstly the scheme provides good load-sharingand can prolong the network lifetime. This is because our

scheme selects the maximum energy level path for routing andavoids using low energy level nodes for relaying. Secondly, thecontrol overhead is very low and the sink need not broadcastperiodically.

C. Delay-aware and Fault-aware Scheme

Because of the scarce bandwidth and constrained energy

environment, we adopt cross-layer design and use the data

(b) (c)

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(I)

packets passing along the path to perform the delay measure-ment. Delay is measured at the sender, which timestamps thepacket entering the network output queue and calculates theround trip single hop delay in routing layer for this packetwhen receiving the ACK in MAC layer. We predefine athreshold Td and compute the current delay estimation bycombining the newly measured delay Dnew with previousdelays via the exponential weighted moving average (EWMA)[20]. And if Dnew changes from less than Td to greater thanTd, we may make the decision that this path is blocked andthe sender isway we proposed in energy-aware path-based scheme

above. As we can see from the Figure 4, if node a is congestedand node e will detect the blocking of this path. And whennode f receives the path blocked message, it will update therouting table and set the path e blocked. The correspondingprocess will conduct if Dnew changes from greater than Td toless than Td.Our delay-aware path-based scheme is very simple to im-

plement and costs little energy because of the low controloverhead. And the fault nodes will be detected quickly withoutcomplicated procedure by the delay information. With energy-aware function, the nodes which drain out their energy will bedefined as fault nodes. Depending on energy-aware and delay-aware function, ELFR scheme has the ability to be fault-awareand achieve perfect robustness and throughput.

V. SIMULATION

In our simulation environment, nodes are random distributedover a 500m x 500m area, with the sink (node 0) located at thecenter of the area. Each sensor has the same maximum batteryenergy capacity. All nodes return their data packets to the sinkrandomly, i.e. nodes start and stop sending data at random timeindependently and the sending rate is random chosen from 1packet per second to 4 packets per second. Each data packetis set to the fixed length (64 bytes) and a clear channel isassumed. Two different numbers of deploying nodes (50 and100) are simulated to evaluate the performances. There are50 different scenes (topology and packets generating) in eachof these two cases. In each scene, we alternate different q =0.01,0.05,0.1,0.2, ... ., 0.6 in simulation. The q represents thefailing possibility of nodes during the whole simulation time.

Figure 5-6 give the energy simulation results of our ELFRscheme in comparison to AODV, and DD(directed diffusion)routing protocols. The graphs show that with our scheme, thedistribution of residual energy level is much higher and evenercompared with the other schemes.

The other important performance metric we focus on inthis paper is the loss rate. After comparison of ELFR scheme,Directed Diffusion and AODV, we find that the loss rate ofELFR is indeed much lower than the other two protocols.Figure 7-8 will compare the average loss rate of the threeprotocols with 50 scenes of 50 and 100 nodes while settingnodes fail possibilities to q = 0.05. And Figure 9-10 comparethe total loss rate of these schemes with different node failingpossibilities from 0.01 to 0.6. From the Fig.7 and 8, we can see

Fig. 5. The Distribution Energy Level of Residual Energy Level (50 nodes)

Fig. 6. The Distribution Energy Level of Residual Energy Level (100 nodes)

that the loss rate ofAODV is much higher than the other twoschemes in both 50 and 100 nodes scenes, so we may concludethat the robustness of AODV is not as good as others.

VI. CONCLUSIONS AND LIMITS

This paper presents a robustness model and a novel routingscheme, termed as ELFR, using cross-layer design for ad hocsensor networks. Compared to Directed Diffusion and AODV,ELFR achieves better load-sharing, lower loss rate, better end-to-end delay and reliability. This is because ELFR makes jointnodes be aware of path-based energy, delay and reliabilitystates, so as to select the optimal path for routing. At thesame time, ELFR scheme builds a mesh structure for datarelay and uses cross-layer design to reduce the congestion,control overhead and improves the reliability in data delivery.Simulation results show better delay, loss rate and energyconservation.

However, our scheme also has its limits. From the sim-ulation figures, we may come to the conclusion that ELFRperforms much better in low density ad hoc sensor networks.While in high density networks, the loss rate of ELFR is notsuperior to DD only when the node failing possibility is high.In the future, we will improve the reliability of ELFR in largescale sensor networks.

50 Nodes

Possibility of Node Failing: Q=5% (50 Nodes)

Fig. 7. The Average Loss Rate of Different Scenes (50 nodes) Fig. 9.nodes)

The Total Loss Rate of Different Nodes Failing Possibilities (50

Possibility of Node Failing: Q=5% (100 Nodes)1

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Fig. 8. The Average Loss Rate of Different Scenes (100 nodes)Fig. 10.nodes)

The Total Loss Rate of Different Nodes Failing Possibilities (100

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