[ieee 2010 sixth international conference on wireless communication and sensor networks (wcsn) -...
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Reconstruction of Aggregation Tree in spite ofFaulty Nodes in Wireless Sensor Networks
Punit Sharma and Partha Sarathi MandalDepartment of Mathematics
Indian Institute of Technology GuwahatiGuwahati - 781 039, India
E-mail: {s.punit, psm}@iitg.ernet.in
AbstractβRecent advances in wireless sensor networks (WSNs)have led to many new promissing applications. However datacommunication between nodes consumes a large portion of thetotal energy of WSNs. Consequently efficient data aggregationtechnique can help greatly to reduce power consumption. Dataaggregation has emerged as a basic approach in WSNs inorder to reduce the number of transmissions of sensor nodesover aggregation tree and hence minimizing the overall powerconsumption in the network. If a sensor node fails during dataaggregation then the aggregation tree is disconnected. Hence theWSNs rely on in-network aggregation for efficiency but a singlefaulty node can severely influence the outcome by contributingan arbitrary partial aggregate value.
In this paper we have presented a distributed algorithm thatreconstruct the aggregation tree from the initial aggregation treeexcluding the faulty sensor node. This is a synchronous model,completed in several rounds. Our proposed scheme can handlemultiple number of faulty nodes as well.
Key words: Reconstruction, Aggregation tree, MST, WSNs,Distributed protocol, Node failure.
I. INTRODUCTION
A wireless sensor network (WSN) consists of a large num-ber of spatially distributed autonomous resource-constrainedtiny sensor devices which are used to lead many new promis-ing applications. The applications for WSNs are varied, typ-ically involving some kind of monitoring, tracking, or con-trolling. Specific applications include: Habitat monitoring [1],Object tracking [2], Nuclear reactor control, Fire detection,Traffic monitoring, Geographic routing [3], etc. However datacommunication between nodes consumes a large portion of thetotal energy of WSNs. Consequently efficient data aggregationtechnique can help greatly to reduce power consumption. Dataaggregation has emerged as a basic approach in WSNs inorder to reduce the number of transmissions of sensor nodesover aggregation tree and hence minimizing the overall powerconsumption in the network.
Depending on the application, sensor nodes either reporteach and every measurement or they perform in-networkaggregation to a gateway or a sink. In in-network aggregation[4] there is an underlying spanning tree rooted at the sink.Where every non-leaf nodes combine their own measurementswith the measurements of their child-nodes and send thecombined data to their respective parents. A large fraction of
978-1-4244-9730-0/10/$26.00 cβ2010 IEEE
WSN applications requires only a periodic collection of anaggregate value (e.g., count, sum, average, etc.). Aforemen-tioned in-network aggregation technique can reduce networksoverhead as follows: With in-network aggregation, rather thanrelaying individual measurements across multiple hops, eachnode transmits a single packet, summarizing the data from anentire area of the WSNs to the sink.
Typically, there are three types of sensor nodes in WSNs:leaf nodes, aggregators, and a querier (sink) [5]. The aggrega-tors collect data from a subset of the network, aggregate thedata using a suitable aggregation function and then transmitthe aggregated result to an upper aggregator or to the querierwho generates the query. The querier is entrusted with the taskof processing the received sensor data and derives meaningfulinformation reflecting the events in the target field. It canbe the base station or sometimes an external user who haspermission to interact with the network depending on thenetwork architecture. Data communications between sensornodes, aggregators and the queriers consume a large portionof the total energy consumption of the WSNs.
Most of the works [4]β[8] in literature focused on secureaggregation in WSNs. Secure aggregation means protectingdata from attackers, where attackers intend to change theaggregation value and mislead the sink (or base station)resulting incorrect aggregation. Chan et al. [6] and Haghaniet al. [8] considered faulty node as an attacker or adversarythat can compromise with sensor nodes by controlling theirfunctionality and inducing arbitrary deviations from the pro-tocols. But in our proposed algorithm, we have considerednode failure as a permanent failure.
A sensor node is called faulty, if it cannot be able to com-municate with any other sensor node in the WSNs. A sensornode may fail due to lack of battery power or some hardwarefailures. If a sensor node fails during data aggregation thenthe aggregation tree is disconnected. Hence the WSNs relyon in-network aggregation for efficiency but a single faultynode can severely influence the outcome by contributing anarbitrary partial aggregate value to the sink.
In a typical application, a WSN is scattered in a regionwhere it is meant to collect data through its sensor nodes. Weconsider WSNs as a weighted communication graph, πΊπ =(ππ, πΈπ) (say) where each sensor node is a vertex belongingto a set ππ, and the communication link between two sensor
nodes is defined as an edge belonging to a set πΈπ. Here edgeweight is the cartesian distance between two sensor nodes.One node can communicate with other nodes directly if theyare in its transmission range.
Using some distributed minimal spanning tree (MST) algo-rithm [9] it is possible to construct an initial aggregation tree(ππ). If one node fails, we assume, that by some fault detectionalgorithm [6], other nodes which are directly connected withthe faulty node, can detect the fault and the aggregation tree isdecomposed into number of trees (disjoint-set of forest) withrespect to the aggregation tree.
Our objective in the paper is follows: Given a weightedcommunication graph πΊπ and corresponding aggregation treeππ with π nodes, if one arbitrary node, π£π (say) fails thenhow to reconstruct the aggregation tree with πβ 1 nodes in adistributed way (excluding the faulty nodes), provided the re-duced communication graph, πΊ
β²π = (π
β²π , πΈ
β²π) is still connected
after removal of the faulty node, π£π where πβ²π = ππ β {π£π}
and πΈβ²π = πΈπ β { all edges are connected with π£π}.
A. Related Work:
Chan et al. proposed a protocol [6] where they consideredcorrupted node as a malicious aggregator node. Accordingto their protocol, the answer given by aggregator is a goodapproximation of the true value even when the aggregator anda fraction of the sensor nodes are corrupted. In the paper [8]Haghani et al. considered adversary node as a misbehaviornode that can severely influence the outcome by contributingan arbitrary partial aggregate value. The scheme relies oncostly operation to localize and exclude node that manipulatesthe aggreagtion when a fault is detected. Gallager et al. [9]proposed a distributed algorithm (distributive implementationof Primβs algorithm) constructing a MST of a connected graphin which the edge weights are unique. Their algorithm workson a message passing model. It uses a bottom-up approachand the overall message complexity of the MST algorithmis π(πΈ + πlg π). In the paper [7] Gao and Zhu proposed aDual-Head Cluster Based Secure Aggregation Scheme.
B. Our results:
The main contribution of this paper is a distributed al-gorithm for reconstruction of aggregation tree in wirelesssensor networks when an arbitrary sensor node fails duringaggregation. To the best of our knowledge, this is the firstdistributed protocol for reconstruction of aggregation treewhich can handle multiple concurrent permanent node failures.Unlike Gallager et al. algorithm [9] the edge weights ofunderlying communication graph may not be unique. We haveproved that the reconstructed aggregation tree is again a MST.This is a synchronous model that completes in several rounds.In terms of rounds, the complexity of our algorithm are π(1)in the best case and π(lg π) in the worst case. The proposedalgorithm can also handle multiple concurrent node failures.
II. RECONSTRUCTION OF AGGREGATION TREE
We consider here a connected WSN consisting of π sensornodes. Each sensor node has its unique id, where edge weight
is the cartesian distance between two nodes. We assume that ifone node fails the communication graph (πΊ
β²π) is still connected
and by some fault detection algorithm, neighbors of the faultynode can detect the fault. For simplicity we assume that ata time there is only one faulty node in the WSN. In thesection VII we will discuss about multiple node failure. Theproposed algorithm is synchronous; i.e., its perform in severalrounds. Due to failure of a node, the given aggregation tree(ππ) is decompose in to disjoint set of forest (cluster, say) withrespect to ππ. According to the algorithm each cluster findsthe minimum outgoing edge (πππ) and tries to merge withthe cluster on the other side of the edge. This is a distributedalgorithm based on message passing.
A. Notations
Following notations are used throughout the paper fordifferent type of messages. These messages are required duringexecution of the algorithm.
β ππππ ππ π (Find message): Fault detective node (clusterππππ‘, say) initiates the message within the cluster toinvoke the node(s) for finding πππ.
β ππππππ‘ ππ π (Report message): Every leaf node in thecluster sends a ππππππ‘ ππ π with πππ and own id to itsparent after finding πππ from it, and every intermediatenode sends ππππππ‘ ππ π to its parent after getting infor-mation about the πππ of its subtree including itself.
β π‘ππ π‘ ππ π (Test message): A node issue a π‘ππ π‘ ππ πthrough the πππ to know whether this edge is going tosome other cluster.
β ππππππ‘ ππ π (Accept message): A node sends aππππππ‘ ππ π after receiving π‘ππ π‘ ππ π if the π‘ππ π‘ ππ πsender is belonging to different cluster.
β ππππππ‘ ππ π (Reject message): A node sends aππππππ‘ ππ π after receiving π‘ππ π‘ ππ π if the π‘ππ π‘ ππ πmessage sender is belonging to the same cluster.
β ππππππ ππ π (Inform message): cluster ππππ‘ sends thismessage to the node in which the πππ is attached.
β πππππ πππ (Merge Request): Merging request from onecluster to some other cluster, containing cluster id.
β πππ‘πππππ ππ π (Internal message): This message is forpass the information in the same cluster.
β πππππ ππ π (Merge message): To ensure merging be-tween two clusters.
β ππππππ‘ ππ π (Commit message): For commitment.β ππππππ ππ π (Ignore message): Ignore requests.β ππππππ¦ ππ π (Modify message): This message is gener-
ated by the end points of the πππ after merging and itpasses in to the new cluster to find the new ππππ‘.
III. DESCRIPTION OF THE ALGORITHM
Suppose a sensor node, π£π with degree π is faulty inthe initial aggregation tree ππ. Removal of this faulty nodedecomposes the aggregation tree into π number of trees (orclusters), π1, π2, β β β , ππ (say). Then let us assume by somefault detection algorithm the node, π£πππ (ππππ‘ of the cluster,say) directly attached with the faulty node in each cluster, ππ
can find the information about the fault and starts followingreconstruction process.
A. Subround-I: Minimum outgoing edge (πππ) finding
For each cluster ππ, π£πππ named as ππππ‘ node initiates and
sends ππππ ππ π to its descenders within the cluster throughthe tree edges with the id of the ππππ‘, named as π ππ
π , which issame as π£πππ . After receiving ππππ ππ π every other nodesassign π ππ
π to its local variable (πππ’π π‘ππ ππ) and forwardsthe message to neighbors until it reach to leaf nodes. Afterreceiving ππππ ππ π leaf node finds the πππ and returnsa ππππππ‘ ππ π to the sender of ππππ ππ π. After receivingππππππ‘ ππ π all intermediate nodes modify πππ if possiblewith respect to its own πππ and forward the ππππππ‘ ππ π tothe ππππ‘ node. For finding πππ a node passes π‘ππ π‘ ππ π withπππ’π π‘ππ ππ through the possible πππ to test whether the otherend of this πππ is in the different cluster. If the other end ofπππ is in different cluster than the node returns a ππππππ‘ ππ πwith its own id otherwise the node returns a ππππππ‘ ππ π.
After receiving ππππππ‘ ππ π this node again tries to findthe next possible πππ among its neighbours until it receive aππππππ‘ ππ π or there is no possible πππ edge for node. In thatcase the node marks all such rejected edges not to use furtherfor πππ selection. There may be a possibility of multiple πππat any individual node. In this case the node selects πππ withminimum id node among the multiple ππππππ‘ ππ π.
After receiving ππππππ‘ ππ π the ππππ‘ node finally selectsa πππ for the cluster and sends ππππππ ππ π to the corre-sponding node π£πππ
π (say) attached with the πππ.
B. Subround-II: Merge message passing
The node, π£ππππ of each cluster, ππ sends a πππππ πππ
message along their respective πππ to some node of ππ , say.The decision after receiving πππππ πππ message as following:There are two cases:
1) If ππππ‘, π£πππ of ππ receives πππππ πππ and if theπππ’π π‘ππ ππ of ππ is less than the πππ’π π‘ππ ππ of ππ thenπ£πππ returns an ππππππ ππ π to π£πππ
π , otherwise π£πππ keepthe information in its database.
2) If some other node (π£π) excluding π£πππ of ππ receivesa πππππ πππ and if πππ’π π‘ππ ππ of ππ is less thanthe πππ’π π‘ππ ππ of ππ then the node π£π returns anππππππ ππ π to π£πππ
π , otherwise π£π forwards the mes-sage (πππ‘πππππ ππ π) to the ππππ‘ π£πππ .
C. Subround-III: Decision after receiving a merge messages
At the end of the previous Subround-II if ππππ‘ of ππ forsome π receives one or more than one πππππ πππ messagesthen it finds the minimum πππ’π π‘ππ ππ over all messages andsends a πππππ ππ π to the minimum id cluster and sendsππππππ ππ π to all others directly or via π£π node (π£π isconsidered in the case-2 of Subround-II). Now, if ππππ‘ of ππ
for some π does not receive any πππππ πππ or receive butpass a ππππππ ππ π to sender then the ππππ‘ of ππ sends aπππππ ππ π through the πππ (chosen in Subround-II) fromπ£ππππ node.
D. Subround-IV: Merging of clusters
In this subround each cluster ππ, for π = 1, 2, β β β , πsome node π£π (including ππππ‘) receives πππππ ππ π and/orππππππ ππ π from π£π (including ππππ‘) of some other clusterππ . If the message is ππππππ ππ π then drop the message.Otherwise merge these two clusters in the following ways:
1) If π£π sends a πππππ ππ π to π£π and if π πππ < π ππ
π thenππ sends a ππππππ‘ ππ π to ππ and ππ merge with ππ
by including the edge in the modified aggregation tree.After that the vertices attached with the edge initiateππππππ¦ ππ π over the new cluster π
β²π (, say) with the
information of π£πππ for the modification of ππππ‘. If π£πsends a πππππ ππ π to π£π and if π ππ
π > π πππ then
πππππ ππ π is drop without merging.2) If π£π does not send a πππππ ππ π to ππ then π£π sends
a ππππππ‘ ππ π and a ππππππ¦ ππ π (as a responds) tocluster ππ after receiving ππππππ¦ ππ π from its owncluster. Then ππ merge with ππ by including the edge inthe modified aggregation tree and ππ expand.
IV. THE ALGORITHM
πΊπ = (ππ, πΈπ)β Communication graphππ β Initial aggregation treeπ βDegree of the faulty node, π£πSubround-I: (Finding πππ)for each cluster ππ ; π = 1 to π doππππ‘, π£πππ initiates and sends < ππππ ππ π, π ππ
π >for each node π£π do
πππ’π π‘ππ πππ β π πππ
end forfor each node π£π (starts from leaf nodes) do
passes π‘ππ π‘ ππ π through its πππ β πΈβ²π of πΊ
β²π to some
other node π£πβ²if π ππ
π β= π πππβ² then
π£πβ² returns an ππππππ‘ ππ π to π£ππ£π passes a ππππππ‘ ππ π to the ππππ ππ π sender
elseπ£πβ² returns ππππππ‘ ππ π to π£π and marks this rejectededge in πΈ
β²π and π£π looks for the next possible πππ
end ifend forfor each node π£π (intermediate/ππππ‘) do
After receiving ππππππ‘ ππ π π£π modifies πππ ifrequired wrt its own πππ as above & forwardsππππππ‘ ππ π to its ancestor until it reaches to the ππππ‘When ππππ‘ receives the π£πππ
π then it passes theππππππ ππ π to the π£πππ
π if πππ is not attached withthe ππππ‘
end forend forif there is no πππ then
return Tree is reconstructed & the protocol is terminatedelse
moves for the Subround-IIend if
Subround-II: (Merge message passing)for each cluster ππ ; π = 1 to π doπ£ππππ sends a πππππ πππ from cluster ππ to some ππ
end forif π£πππ of ππ receives this πππππ πππ message then
if πΆπππ < πΆππ
π thenpasses an ππππππ ππ π to π£πππ
π
elsekeeps the message
end ifelse
if some other node π£π of ππ receives this πππππ πππmessage then
if πΆπππ < πΆππ
π thenpasses an ππππππ ππ π to π£πππ
π
elseπ£π receives this message and passes it to π£πππ of ππ
through an πππ‘πππππ ππ πend if
end ifend if
Subround-III: (Decision after receiving a merge messages)for each cluster ππ ; π = 1 to π do
if π£πππ receives πππππ πππ from some other clusters thensends πππππ ππ π to the minimum id cluster amongthem and ππππππ ππ π to others
elsesends πππππ ππ π from π£πππ
π through πππend if
end for
Subround-IV: (Merging of clusters)π£π of ππ receives either πππππ ππ π or/and ππππππ ππ πfrom ππ after the end of Subround-IIIif message is ππππππ ππ π then
drops the message without mergingelse
if ππ also sends a πππππ ππ π to ππ thenif π ππ
π < π πππ then
ππ passes a ππππππ‘ ππ π to ππ
ππ merges with ππ in some new cluster πβ²π
the nodes attached with merged edge initiates andsends ππππππ¦ ππ π within π
β²π .
πππ’π π‘ππ ππ of π£πβ² β πβ²π resets the value by π£πππ
elsedrops this received πππππ ππ π
end ifelseπ£π sends a ππππππ‘ ππ π and forwards ππππππ¦ ππ π(as a responds) to cluster ππ after receivingππππππ¦ ππ π from its own cluster and then ππ mergeswith ππ
end ifend ifRe-execute the protocol from Subround-I with modifiedclusters until termination.
V. COMPLEXITY ANALYSIS
Let π be the number of clusters after a node failure. We aremeasuring the complexity of the proposed algorithm in termsof rounds of execution and total number of message exchange.First we concentrate over possible best and worst rounds ofexecution.
β Case-1 (Best Case) If π£ππππ sends πππππ πππ to the min-
imum id cluster ππ (,say) for all π β {1, 2, β β β , π} β {π},then the tree would be reconstructed in one round.
β Case-2 (Worst Case) If every distinct pair of clus-ters exchange πππππ πππ in Subround-II and merge inSubround-IV then in one round, number of cluster re-duces by half. If this kind of merging process is continue,then after π(lg π) rounds the tree would be reconstructed.
Now we determine an upper bound for the number of messagesfor a cluster ππ.
Let the number of nodes in this cluster is ππ. Recall thetypes of messages used by the algorithm :ππππ ππ π: ππ β 1 ππππ ππ π messages.π‘ππ π‘ ππ π: (successful test and failed test.)ππππππ‘ ππ π: Acceptance requires two messages, success-ful test and accept. So the messages are 2ππ. Note thatππππππ ππ π also included in this count.ππππππ‘ ππ π: Note that an edge can be reject at most oncethroughout the execution of the algorithm. Rejection requirestwo messages: failed test and rejection. So, we have 2πΈmessages, where πΈ = β£πΈπβ£.ππππππ‘ ππ π: ππ β 1 ππππππ‘ ππ π.πππππ πππ: 1 (one) request for merging.ππππππ ππ π: at most π β 1 ππππππ ππ π throughout theexecution of the algorithm.πππ‘πππππ ππ π: at most ππ β 1 message.πππππ ππ π: one message.ππππππ‘ ππ π: one message for final commitmentππππππ¦ ππ π: ππ β 1 messages for modification.
The total number of message required for a cluster is 6ππ.Total number of message for all π clusters is
βππ=1(6ππ) =
6(πβ 1) where πβ 1 =βπ
π=1 ππ
Therefore the total number of message for merging of allπ clusters is π(πlg π + πΈ). Here π may be π β 1, thereforethe total counting brings us to π(πlg π+ πΈ).
VI. CORRECTNESS
Note that in a single round of proposed algorithm, everycluster sends a unique πππππ ππ π through πππ. In themerging of two or more than two clusters simultaneously, thenthere are exactly two clusters which can send a πππππ ππ πto each other through the same πππ.
Theorem 1: There is no cycle after merging two or moreclusters.
Proof: Let ππ be the initial aggregation tree with π nodesand π£π be the faulty node. Proof by induction on degree of π£πnode in ππ.Basis: Let deg(π£π ) = 1. Then after removing π£π from ππ, there
is only one cluster with π β 1 nodes. Clearly πβ²π with π β 1
nodes is again a tree.Let deg(π£π ) = 2 and ππ, ππ be the clusters. Let us supposecycle occurs in the merging of ππ and ππ . It is possible ifboth ππ and ππ send a πππππ ππ π to each other throughdifferent multiple πππ. But this contradicts Subround-III ofthe proposed algorithm. Since according to proposed algorithmboth ππ and ππ send a πππππ ππ π to each other through sameπππ. Hence there is no cycle in the merging of ππ and ππ .Inductive hypothesis: Let no cycle occurs in the merging of πor less clusters, i.e., deg(π£π ) β€ π.Inductive step: Now, let deg(π£π ) = π + 1 and ππ, for π =1, 2, β β β , π+1 be the clusters. Let us suppose cycle occurs inthe merging of these π + 1 clusters. It is possible if at leastthree clusters π1, π2, π3 (, say) send the πππππ ππ π to eachother as π1 to π2, π2 to π3, π3 to π1 in a round. But thiscontradicts our algorithm that there are exactly two clusterswhich send a πππππ ππ π to each other through the sameπππ in the merging of more than two clusters. Therefore cyclecannot occur in a round and number of cluster reduces. Now,by inductive hypothesis, cycle will not occur in the mergingof π + 1 clusters. Hence the theorem is true for any numberof clusters.
Theorem 2: Resultant reconstructed aggregation tree is aMST.
Proof: Let ππ be the initial aggregation tree and given thatis a MST with π nodes and π£π be the faulty node with degreeπ. Let π
β²π be the aggregation tree which is reconstructed using
our proposed algorithm with π β 1 nodes after removing thefaulty node π£π . Since ππ is a MST, therefore removal of π£π di-vides it in to π sub trees where each of them are individually aMST. Now suppose π
β²π is not a MST, it means there are at least
two clusters which is not merged with a minimum weightededge in the π
β²π. But it is a contradiction of our algorithm that
allows merging between different clusters through a minimalweighted edge. Hence the resultant reconstructed aggregationtree is again a MST.
VII. MULTIPLE SENSOR NODES FAILURE
If π number of nodes fail simultaneously and ifπ1, π2, β β β , ππ are the degrees of respective faulty nodes thenat most π1+π2+ β β β +ππ number of disjoint forest may form.Then same proposed algorithm can merge all disjoint forestand reconstruct the aggregation tree.
VIII. CONCLUSION
In this paper, we have proposed a distributed algorithm forreconstruction of aggregation tree in wireless sensor networkswhen an arbitrary sensor node fails during aggregation. Ourmodel is synchronous, performing in rounds. In terms ofrounds the time complexity of our algorithm is π(1) in thebest case, π(lg π) in the worst case. Our proposed algorithmcan also handel multiple concurrent sensor nodes failure. Butthe proposed algorithm cannot handel node failure duringthe reconstruction phase. In our future works we will try to
incorporate node failure during the reconstruction phase aswell.
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