A survey on clustering algorithms for wireless sensor networks

doi:10.1504/IJSSC.2011.040339

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A survey on clustering algorithms for wireless sensor networks

Journal Article•DOI•

A survey on clustering algorithms for wireless sensor networks

Olutayo Boyinbode, Hanh Le, Makoto Takizawa

25 May 2011-International Journal of Space-Based and Situated Computing (Inderscience Publishers)-Vol. 1, pp 130-136

TL;DR: This paper synthesises existing clustering algorithms news's and highlights the challenges in clustering.

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Abstract: A wireless sensor network (WSN) consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability for large WSNs. Clustering also conserves the limited energy resources of the sensors. This paper synthesises existing clustering algorithms in WSNs and highlights the challenges in clustering.

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Proceedings Article•DOI•

A survey on routing protocols in Wireless Sensor Networks

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Mallanagouda Patil¹, Rajashekhar C. Biradar¹•Institutions (1)

Reva Institute of Technology and Management¹

01 Dec 2012

TL;DR: A survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs) and compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation.

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Abstract: This paper presents a survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs). Compared with traditional wireless networks, WSNs are characterized with denser levels of node deployment, higher unreliability of sensor nodes and severe power, computation and memory constraints. Various design challenges such as energy efficiency, data delivery models, quality of service, overheads etc., for routing protocols in WSNs are highlighted. We addressed most of the proposed routing methods along with scheme designs, benefits and result analysis wherever possible. The routing protocols discussed are classified into seven categories such as Data centric routing, Hierarchical routing, Location based routing, Negotiation based routing, Multipath based routing, Quality of Service (QoS) routing and Mobility based routing. This paper also compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation. The paper concludes with possible open research issues in WSNs.

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1,168 citations

Cites background from "A survey on clustering algorithms f..."

...This process can not only reduce the energy consumption, but also balance traffic load and improve the scalability[16]....
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Journal Article•DOI•

Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey

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Nikolaos A. Pantazis¹, Stefanos A. Nikolidakis², Dimitrios D. Vergados²•Institutions (2)

American Hotel & Lodging Educational Institute¹, University of Piraeus²

22 Jan 2013-IEEE Communications Surveys and Tutorials

TL;DR: The classification initially proposed by Al-Karaki, is expanded, in order to enhance all the proposed papers since 2004 and to better describe which issues/operations in each protocol illustrate/enhance the energy-efficiency issues.

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Abstract: The distributed nature and dynamic topology of Wireless Sensor Networks (WSNs) introduces very special requirements in routing protocols that should be met. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network's lifetime. During the recent years, many energy efficient routing protocols have been proposed for WSNs. In this paper, energy efficient routing protocols are classified into four main schemes: Network Structure, Communication Model, Topology Based and Reliable Routing. The routing protocols belonging to the first category can be further classified as flat or hierarchical. The routing protocols belonging to the second category can be further classified as Query-based or Coherent and non-coherent-based or Negotiation-based. The routing protocols belonging to the third category can be further classified as Location-based or Mobile Agent-based. The routing protocols belonging to the fourth category can be further classified as QoS-based or Multipath-based. Then, an analytical survey on energy efficient routing protocols for WSNs is provided. In this paper, the classification initially proposed by Al-Karaki, is expanded, in order to enhance all the proposed papers since 2004 and to better describe which issues/operations in each protocol illustrate/enhance the energy-efficiency issues.

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1,032 citations

Journal Article•DOI•

A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis

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Adil Fahad¹, Najlaa Alshatri¹, Zahir Tari¹, Abdullah Alamri¹, Ibrahim Khalil¹, Albert Y. Zomaya², Sebti Foufou³, Abdelaziz Bouras³ - Show less +4 more•Institutions (3)

RMIT University¹, University of Sydney², Qatar University³

12 Jun 2014-IEEE Transactions on Emerging Topics in Computing

TL;DR: Concepts and algorithms related to clustering, a concise survey of existing (clustering) algorithms as well as a comparison, both from a theoretical and an empirical perspective are introduced.

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Abstract: Clustering algorithms have emerged as an alternative powerful meta-learning tool to accurately analyze the massive volume of data generated by modern applications. In particular, their main goal is to categorize data into clusters such that objects are grouped in the same cluster when they are similar according to specific metrics. There is a vast body of knowledge in the area of clustering and there has been attempts to analyze and categorize them for a larger number of applications. However, one of the major issues in using clustering algorithms for big data that causes confusion amongst practitioners is the lack of consensus in the definition of their properties as well as a lack of formal categorization. With the intention of alleviating these problems, this paper introduces concepts and algorithms related to clustering, a concise survey of existing (clustering) algorithms as well as providing a comparison, both from a theoretical and an empirical perspective. From a theoretical perspective, we developed a categorizing framework based on the main properties pointed out in previous studies. Empirically, we conducted extensive experiments where we compared the most representative algorithm from each of the categories using a large number of real (big) data sets. The effectiveness of the candidate clustering algorithms is measured through a number of internal and external validity metrics, stability, runtime, and scalability tests. In addition, we highlighted the set of clustering algorithms that are the best performing for big data.

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833 citations

Cites background from "A survey on clustering algorithms f..."

...Despite a vast number of surveys for clustering algorithms available in the literature [1], [2], [7], and [38] for various domains (such as machine learning, data mining, information retrieval, pattern recognition, bio-informatics and semantic ontology), it is difficult for users to decide a priori…...
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Journal Article•DOI•

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

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Mohammad Abu Alsheikh¹, Shaowei Lin², Dusit Niyato¹, Hwee-Pink Tan²•Institutions (2)

Nanyang Technological University¹, Institute for Infocomm Research Singapore²

24 Apr 2014-IEEE Communications Surveys and Tutorials

TL;DR: An extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs is presented and a comparative guide is provided to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

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Abstract: Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002–2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

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704 citations

Additional excerpts

...classical clustering algorithms are presented in [78]....
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Journal Article•DOI•

A Survey on Clustering Routing Protocols in Wireless Sensor Networks

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Xuxun Liu¹•Institutions (1)

South China University of Technology¹

09 Aug 2012-Sensors

TL;DR: A comprehensive and fine grained survey on clustering routing protocols proposed in the literature for WSNs, and a novel taxonomy of WSN clustering routed methods based on complete and detailed clustering attributes are presented.

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Abstract: The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in a wide range of applications and it has become a hot research area. Based on network structure, routing protocols in WSNs can be divided into two categories: flat routing and hierarchical or clustering routing. Owing to a variety of advantages, clustering is becoming an active branch of routing technology in WSNs. In this paper, we present a comprehensive and fine grained survey on clustering routing protocols proposed in the literature for WSNs. We outline the advantages and objectives of clustering for WSNs, and develop a novel taxonomy of WSN clustering routing methods based on complete and detailed clustering attributes. In particular, we systematically analyze a few prominent WSN clustering routing protocols and compare these different approaches according to our taxonomy and several significant metrics. Finally, we summarize and conclude the paper with some future directions.

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635 citations

Cites background from "A survey on clustering algorithms f..."

...wireless sensor networks [39] 1Discussion of the main challenges for WSN clustering...
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References

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Open Access

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Journal Article•DOI•

An application-specific protocol architecture for wireless microsensor networks

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Wendi Heinzelman¹, Anantha P. Chandrakasan¹, Hari Balakrishnan¹•Institutions (1)

Massachusetts Institute of Technology¹

01 Oct 2002-IEEE Transactions on Wireless Communications

TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.

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Abstract: Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.

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10,296 citations

Journal Article•DOI•

HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks

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O. Younis¹, Sonia Fahmy¹•Institutions (1)

Purdue University¹

01 Oct 2004-IEEE Transactions on Mobile Computing

TL;DR: It is proved that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks.

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Abstract: Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. We propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in O(1) iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks. Simulation results demonstrate that our proposed approach is effective in prolonging the network lifetime and supporting scalable data aggregation.

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4,889 citations

Additional excerpts

...HEED considers a hybrid of energy and communication cost when selecting CHs. Unlike LEACH, it does not select cluster -head nodes randomly....
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...Hybrid Energy Efficient Distributed Clustering (HEED) [5]: HEED is a multi-hop clustering algorithm for Wireless Sensor Networks....
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...In HEED, Intra-cluster communication cost reflects the node degree or node’s proximity to the neighbour and is used by the nodes in deciding to join the cluster....
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...Several iterations involved in cluster formation in HEED can lead to overhead cost....
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...2002, pp.660 – 670 [4] V. Loscri, G. Morabito and S. Marano, “A Two-Level Hierarchy for Low-Energy Adaptive Clustering Hierarchy”, Proceedings of Vehicular Technology Conference 2005, vol3, 1809-1813 [5] O. Younis and S. Fahmy, “HEED: “A Hybrid Energy-Efficient Distributed Clustering Approach for Ad Hoc Sensor Networks,” IEEE Transactions on Mobile Computing, 2004, vol. 3, no. 4 [6] M. Ye, C. Li, G. Chen and J. Wu, “An Energy Efficient Clustering Scheme in Wireless Sensor Networks,” Ad Hoc & Sensor Wireless Networks, 2006, Vol.1, pp.1–21, [7] C. Li, M. Ye, G. Chen, J. Wu, “An energyefficient unequal clustering mechanism for wireless sensor networks,” in: Proceedings of 2005 IEEE International Conference on Mobile Adhoc and Sensor Systems Conference(MASS05), Washington, D.C., pp. 604-611, November 2005....
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Proceedings Article•DOI•

PEGASIS: Power-efficient gathering in sensor information systems

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S. Lindsey, Cauligi S. Raghavendra

09 Mar 2002

TL;DR: PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH, is proposed, where each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round.

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Abstract: Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an energy efficient manner is critical to operate the sensor network for a long period of time. In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000), a data collection problem is defined where, in a round of communication, each sensor node has a packet to be sent to the distant base station. If each node transmits its sensed data directly to the base station then it will deplete its power quickly. The LEACH protocol presented by W. Heinzelman et al. is an elegant solution where clusters are formed to fuse data before transmitting to the base station. By randomizing the cluster heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvement compared to direct transmissions, as measured in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH by about 100 to 300% when 1%, 20%, 50%, and 100% of nodes die for different network sizes and topologies.

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3,731 citations

"A survey on clustering algorithms f..." refers methods in this paper

...algorithms have been proposed to improve LEACH, such as PEGASIS [10], TEEN [11], APTEEN [12], MECH [18], LEACH-C [19] EEPSC [20] etc....
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...[10] S. Lindsey, C. Raghavendra, “PEGASIS: power-efficient gathering in sensor information systems,” in: Proceedings of 2002 IEEE Aerospace Conference, Big Sky, Montana, USA, vol.3, pp.1125-1130, March 2002....
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...Therefore, a large number of algorithms have been proposed to improve LEACH, such as PEGASIS [10], TEEN [11], APTEEN [12], MECH [18], LEACH-C [19] EEPSC [20] etc. 2....
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Proceedings Article•DOI•

TEEN: a routing protocol for enhanced efficiency in wireless sensor networks

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A. Manjeshwar¹, Dharma P. Agrawal¹•Institutions (1)

University of Cincinnati¹

23 Apr 2001

TL;DR: This paper proposes a formal classification of sensor networks, based on their mode of functioning, as proactive and reactive networks, and introduces a new energy efficient protocol, TEEN (Threshold sensitive Energy Efficient sensor Network protocol) for reactive networks.

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Abstract: Wireless sensor networks are expected to find wide applicability and increasing deployment in the near future. In this paper, we propose a formal classification of sensor networks, based on their mode of functioning, as proactive and reactive networks. Reactive networks, as opposed to passive data collecting proactive networks, respond immediately to changes in the relevant parameters of interest. We also introduce a new energy efficient protocol, TEEN (Threshold sensitive Energy Efficient sensor Network protocol) for reactive networks. We evaluate the performance of our protocol for a simple temperature sensing application. In terms of energy efficiency, our protocol has been observed to outperform existing conventional sensor network protocols.

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2,423 citations

Journal Article•DOI•

A survey on clustering algorithms for wireless sensor networks

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Ameer Ahmed Abbasi, Mohamed Younis¹•Institutions (1)

University of Maryland, Baltimore County¹

01 Oct 2007-Computer Communications

TL;DR: A taxonomy and general classification of published clustering schemes for WSNs is presented, highlighting their objectives, features, complexity, etc and comparing of these clustering algorithms based on metrics such as convergence rate, cluster stability, cluster overlapping, location-awareness and support for node mobility.

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2,283 citations

"A survey on clustering algorithms f..." refers methods in this paper

...[9] A. Abbasi, M. Younis, “A survey on clustering algorithms for wireless sensor networks, ” Computer Communications, vol. 30, pp. 2826- 2841, October 2007....
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...2002, pp.660 – 670 [4] V. Loscri, G. Morabito and S. Marano, “A Two-Level Hierarchy for Low-Energy Adaptive Clustering Hierarchy”, Proceedings of Vehicular Technology Conference 2005, vol3, 1809-1813 [5] O. Younis and S. Fahmy, “HEED: “A Hybrid Energy-Efficient Distributed Clustering Approach for Ad Hoc Sensor Networks,” IEEE Transactions on Mobile Computing, 2004, vol. 3, no. 4 [6] M. Ye, C. Li, G. Chen and J. Wu, “An Energy Efficient Clustering Scheme in Wireless Sensor Networks,” Ad Hoc & Sensor Wireless Networks, 2006, Vol.1, pp.1–21, [7] C. Li, M. Ye, G. Chen, J. Wu, “An energyefficient unequal clustering mechanism for wireless sensor networks,” in: Proceedings of 2005 IEEE International Conference on Mobile Adhoc and Sensor Systems Conference(MASS05), Washington, D.C., pp. 604-611, November 2005....
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...Cluster size and cluster geographical distribution might be conflicting In the following section, different clustering algorithms will be presented based on the above mentioned process/criteria and some by Abbasi and Younis [9] such as Cluster Count....
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...In the following section, different clustering algorithms will be presented based on the above mentioned process/criteria and some by Abbasi and Younis [9] such as Cluster Count....
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