CLUSTERING CHALLENGES AND OPEN ISSUES IN WSNSBy: Wail Mardini

Jordan University of Science and Technology

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AGENDA

Introduction Routing and Clustering Clustering advantages Issues and challenges Clustering approaches 1 Clustering approaches 2 Optimal number of relay nodes

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INTRODUCTION:

Energy consumption by communication accounts for about 70% of the total energy in wireless sensor networks. Sending data, receiving data and idle-

listening. Energy dissipation of idle-listening

can’t be ignored compared with energy consumption of sending and receiving. 3

INTRODUCTION (CONT.)(CONT.)

We need to minimize communication overhead to save power

In WSN, we usually want to send the sensor data to a sink (or multiple sinks)

To send data from source to destination, there are many issues to considerE.g. Verifying the availability of the

medium, Discovering the path if not have been done before and not changed!, ... etc

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ROUTING AND CLUSTERING

A ZigBee end-device cannot perform route discoveryThe ZigBee coordinator or a router will

perform route discovery on behalf of the end device.

Optimal path would include parameters such as link quality, number of hops, and

energy consumptionLink cost is usually used to

represent this combined value 5

ROUTING AND CLUSTERING (CONT.)(CONT.)

The ZigBee coordinator and routers create and maintain Routing tables

Used to determine the next hop for known destinations Route discovery table

Used during the discovery of new routes Contains path costs, the address of the device that

requested the route (source device), and the address of the last device that relayed the request to the current device

Neighbours table Contains information about the devices in its

transmission range. Updated every time the device receives a packet from

one of its neighbours.

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ROUTING AND CLUSTERING (CONT.)(CONT.)

Clustering: grouping the network nodes into a number of disjoint sets.

Nodes inside the same cluster can talk to each other (if needed, and if they have the capability), directly or through a special cluster node (called Cluster Head CH)

Nodes in different clusters, can only communicate through the CHs

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ROUTING AND CLUSTERING (CONT.)(CONT.)

CHs can communicate together directly or in multi-hop fashion.

In many wireless sensor network applications, sensor nodes usually just send data to the CH and then routed to the sink (‘s).

The main objective of clustering in Networking was originally to achieve scalability 8

ROUTING AND CLUSTERING (CONT.)(CONT.)

Figures Showing more than one node in the same

cluster wants to send data to the sink Instead of having every look for the route to

the sink, the CH knows the way! Also, less amount of data is usually sent

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ROUTING AND CLUSTERING (CONT.)(CONT.)

a) Single hop without clustering.

b) Multihop without clustering.

c) Single hop with clustering.

d) Multihop with clustering.

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ROUTING AND CLUSTERING (CONT.)(CONT.)Many clustering algorithms have

been proposed in the literature for ad-hoc networks

Many of such techniques care mostly about node reachability and delay

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CLUSTERING ADVANTAGES:CLUSTERING ADVANTAGES:

Scalability: enables the network to deal with growing demand of work resulted from increase in the network size and traffic.

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CLUSTERING ADVANTAGES (CONT.):CLUSTERING ADVANTAGES (CONT.):

Easier and simpler routing: Inside the cluster: the routing toward

the cluster head directly or often through few hops.

Between clusters: the data either go directly from CH or through a set of hops with very simple forwarding table.

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CLUSTERING ADVANTAGES (CONT.):CLUSTERING ADVANTAGES (CONT.):

Less communication bandwidth: Avoids redundant data

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CLUSTERING ADVANTAGES (CONT.):CLUSTERING ADVANTAGES (CONT.):

Power saving: CH usually give time slot for each member sensor to transmitsave power because the nodes can

sleepSave power because the chance of

collision and retransmission is reduced

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CLUSTERING OBJECTIVES:CLUSTERING OBJECTIVES: The clustering algorithms are designed

to directly targeting one or more of the following objectives:Maximal network lifetime: ultimate

objective, directly or indirectlyLoad balancing: through clusters density

and transmission ranges Fault-tolerance: backup CH Vs. Re-

clusteringIncreased connectivity and reduced delayMinimal cluster count: when special nodes

are used

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ISSUES AND CHALLENGESISSUES AND CHALLENGESSensors capability:

Homogenous sensor nodes: all sensors have equal capability (computation, communication and power)CHs usually elected from the sensor sCHs usually excluded from sensing dutiesSensors’ communication range is usually limited Sink not reachable: multi-hop is used. Sink reachable:

Transmit directly Transmit through hops (consumes less

energy?!)17

ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):

Sensors capability (Cont..)Heterogeneous sensor nodes:

Different sensor capabilities Usually some nodes can only be the CHsAlso, some nodes avoided from being CHs

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Base station (sink) and/or sensors

mobility: Affects cluster membershipRe-clustering is always possible

but:Time limitationCost and power consumed

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Events monitored by a sensor:

Intermittent (change every a while) Send data when new event triggered

Continual Periodic data transmission is usually needed

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Sensors operation:

Reactive mode Periodic reporting mode

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Data aggregation: possible or not

Note that computation consumes much less energy than communication

Data Fusion: using signal processing techniques (e.g. beamforming) to produce more accurate signal.

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Number of nodes per cluster and

number of clusters What is the optimal number?

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Nodes deployment: deterministic

or randomWhen the sensors are placed

manually Everything is usually set and

configured.When the sensors are placed

randomly Any distribution? Self-organizing is employed. 24

ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Sensors power: adjustable or not

Some algorithms assumes the sensors can adjust their power during their lifetime

Some sensors are preset for the power

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.):Sensor location:

Some sensors can determine its location Using GPS!Using some reference nodes and mathematical equations

If so, efficient clusters can be produced

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ISSUES AND CHALLENGES ISSUES AND CHALLENGES (CONT.):(CONT.): Even though the objective of many

clustering protocols was not to maximize network lifetimelifetime improvements can still be

achieved if data aggregation is exploited and the network is re-clustered periodically

Periodic re-clustering is necessary in order to heal disconnected regions and distribute energy consumption across all nodes.

Distributed clustering protocols that rely only on neighbourhood information are preferred for WSNs

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CLUSTERING CLUSTERING APPROACHES 1APPROACHES 1Dominating sets:

A dominating set of a given graph is a subset S of the graph vertices V such that every vertex in V-S is joined directly to at least one vertex in S.

Finding dominating set with the least number of members is an NP-complete problem

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CLUSTERING CLUSTERING APPROACHES 1:APPROACHES 1:

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CLUSTERING CLUSTERING APPROACHES 1:APPROACHES 1: Connected dominating sets:

the set S is connected This approach was popular in ad-hoc

networks The main concern was the delay

There has been some works to extended the idea to WSN with concentration on the energy

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CLUSTERING CLUSTERING APPROACHES 1:APPROACHES 1: Energy Constrained Dominating Set (ECDS)

The idea is to construct dominating set with a restriction on the number of the cluster members

It is only consider single hop clusters

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CLUSTERING CLUSTERING APPROACHES 1:APPROACHES 1:Energy Efficient Clustering Scheme

in wireless sensor networks (EECS)Cluster heads are chosen so that the

energy consumption over the entire network is evenHelps the network lives as long as possible

A node will chose a cluster head to ensure the overall energy consumption in the entire network is evenGlobal information required!

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CLUSTERING CLUSTERING APPROACHES 1:APPROACHES 1: Primal-dual based distributed

algorithms for vertex cover with semi-hard capacitiesEach vertex is assigned a weight and

capacityThe goal is to minimize the sum of the

weights without exceeding the capacity of any vertex.

The authors provide an approximation algorithm to solve this NP problem

No simulation presented! 33

CLUSTERING CLUSTERING APPROACHES 1:APPROACHES 1: An efficient distributed algorithm for

constructing small dominating setsA randomized distributed algorithm Linear order running timeThe dominating set size is under Log(n)

(with high probability)ECDS is based on this algorithm

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CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2: Low Energy Adaptive Clustering

Hierarchy (LEACH)Randomized and distributedNodes are picked from the deployed

sensors Tries to evenly spread work load among

nodes in the network. In cluster set-up phase, each node elects

itself to be a cluster head with a certain probability.

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CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2:LEACH (Cont..)

Then each non-cluster head node joins a cluster by choosing the cluster head that requires the minimum communication energy.

CHs role is rotated periodicallyEach cluster head aggregates data from

members and transmits the compressed data to the data sink directly.

It assumes only one-hop inter and intra clusters communication!

Constant time complexity (note)36

CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2: Energy Efficient Hierarchical Clustering

(EEHC) Distributed and randomized clustering

algorithm Main objective of maximizing the network

lifetime. The algorithm has low order running time (not

constant!) Two stages

Initial: sensor node announces itself as a CH with probability p to the neighboring nodes within its communication range. And process continues similar to LEACH

Extended stage: repeatedly clutering the CHs

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CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2: Hybrid Energy-Efficient Distributed

Clustering (HEED):Distributed clustering scheme Nodes are picked from the deployed

sensorsHEED considers a hybrid of energy and

communication cost when selecting CHsOnly sensors that have a high residual

energy can become CHs However, LEACH with a probability can select such low

residual energy as CH38

CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2:

HEED (cont..)Every node has three statuses during

clustering: Tentative cluster head, final cluster head, or

member node covered by one cluster head.A node with high remaining energy has

high probability to become a tentative cluster head

It assumes only one-hop intra-cluster and multi-hop inter-clusters

Constant time complexity39

CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2: Distributed Weight-based Energy-

efficient Hierarchical Clustering protocol (DWEHC)The goal is to achieve better balance

between cluster sizes keeping the energy at the lowest level

It assumes multi-hop inter and intra clusters communication!

Constant time complexity

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CLUSTERING CLUSTERING APPROACHES 2:APPROACHES 2: Transmit Power Control and Soft

ComputingApproximation algorithm Assumes the node has the capability to

change their power No details of the algorithm is given, just

the general ideaSome results using Matlab shows the

efficiency !

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OPTIMAL NUMBER OF RELAY NODES:LINEAR ORDER []

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OPTIMAL NUMBER OF RELAY NODES:LINEAR ORDER

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OPTIMAL NUMBER OF RELAY NODES:LINEAR ORDER

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OPTIMAL NUMBER OF RELAY NODES:SEMI-LINEAR ORDER

45Distances are exponentially distributed

OPTIMAL NUMBER OF RELAY NODES:SEMI-LINEAR ORDER: MATLAB RESULTS

d power optimal hops 10 210 1 20 240 1 30 290.02 1 40 360 1 50 411.11 2 60 460.02 2 70 517.78 2 80 560.05 3 90 602.53 3 100 650.03 3 46

OPTIMAL NUMBER OF RELAY NODES:RANDOM ORDER

Issues in using such optimal calculations in clustering Distribution of nodes

Sources of interference

For better calculations, we need to know the location of each node

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REFERENCES:References

[1] Ameer A. Abbasi and Mohamed Younis. A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30(14-15), 2007.

[2] J. Albath, M. Thakur, and S. Madria. Energy constrained dominating set for clustering in wireless sensor networks. apr 2010.

[3] Kyung-Bae Chang, Young-Bae Kong, and Gwi-Tae Park. Clustering algorithm in wireless sensor networks using transmit power control and soft computing. In De-Shuang Huang, Kang Li, and George Irwin, editors, Intelligent Control and Automation, volume 344 of Lecture Notes in Control and Information Sciences, pages 171–175. Springer Berlin / Heidelberg, 2006.

[4] Ping Ding, JoAnne Holliday, and Aslihan Celik. Distributed energy-efficient hierarchical clustering for wireless sensor networks. In Viktor K. Prasanna, Sitharama Iyengar, Paul G. Spirakis, and Matt Welsh, editors, Distributed Computing in Sensor Systems, volume 3560 of Lecture Notes in Computer Science, pages 322–339. Springer Berlin / Heidelberg, 2005.

[5] F. Grandoni, J. Könemann, A. Panconesi, and M. Sozio. Primal-dual based distributed algorithms for vertex cover with semi-hard capacities. In PODC ’05: Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing, pages 118–125, New York, NY, USA, 2005. ACM. 48

REFERENCES:References (cont.)

[6] W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan. An application-specific protocol architecture for wireless microsensor networks. Wireless Communications, IEEE Transactions on, 1(4), oct 2002.

[7] Lujun Jia, Rajmohan Rajaraman, and Torsten Suel. An efficient distributed algorithm for constructing small dominating sets. Distrib. Comput., 15(4):193–205, 2002.

[8] Inwhee Joe and Sungmoon Chung. The distance-power consumption tradeoff for cooperative wireless sensor networks. In Dominik lÄ™zak, Tai-hoon Kim, Alan C. Chang, Thanos Vasilakos, MingChu Li, and Kouichi Sakurai, editors, Communication and Networking, volume 56 of Communications in Computer and Information Science, pages 180–187. Springer Berlin Heidelberg, 2009.

[9] Dilip Kumar, Trilok C. Aseri, and R. B. Patel. Eehc: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications, 32(4), 2009.

[10] Mao Ye, Chengfa Li, Guihai Chen, and J. Wu. Eecs: an energy efficient clustering scheme in wireless sensor networks. apr 2005.

[11] O. Younis and S. Fahmy. Heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. Mobile Computing, IEEE Transactions on, 3(4), oct 2004.

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Questions

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