scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

EESCA: Energy efficient structured clustering algorithm for wireless sensor networks

01 Dec 2016-pp 523-527
TL;DR: A hybrid cluster head selection method with the parameters Location centrality and Nodes' lingering energy on the fixed clusters is suggested that is good at load balancing with very low control overhead and extending network lifetime compared to conventional routing algorithm Low-Energy Adaptive Clustering Hierarchy (LEACH).
Abstract: Appropriate cluster head selection process in hierarchical cluster based routing algorithms is vital to make the wireless sensor networks energy efficient. This paper suggests a hybrid cluster head selection method with the parameters Location centrality and Nodes' lingering energy on the fixed clusters. The simulation outcome illustrates that the proposed algorithm is good at load balancing with very low control overhead and extending network lifetime compared to conventional routing algorithm Low-Energy Adaptive Clustering Hierarchy (LEACH).
Citations
More filters
Journal ArticleDOI
TL;DR: An Improved-Adaptive Ranking based Energy-efficient Opportunistic Routing protocol (I-AREOR) is proposed, based on regional density, relative distance, and residual energy of the sensor nodes, for improving sensor based communication in future smart cities.

74 citations

Journal ArticleDOI
16 Mar 2018-Sensors
TL;DR: Simulation results demonstrate that the proposed approach can not only postpone the death of the first node by almost 50% compared to LEACH, but that it also outperforms several related protocols with respect to energy efficiency.
Abstract: Clustering, as an essential part in an hierarchy protocol that can prolong the network lifetime, is influenced by the cluster head selection and clustering scheme. A new clustering algorithm called clustering by fast search and finding of density peaks (CFSFDP) based on local density and distance is implementable and efficient. In this paper, we combine this clustering algorithm with a hierarchy protocol in wireless sensor networks (WSNs). However, energy consumption in each round is unbalanced only considering these two variables during the clustering phase, which leads to the early death of the first node. In order to solve this problem, we take residual energy into consideration in our improved CFSFDP-E (energy) algorithm so as to ultimately balance the energy consumption of the network. We analyze different forms of energy and choose a dynamic threshold for each round in the CFSFDP-E algorithm. Simulation results demonstrate that the proposed approach can not only postpone the death of the first node by almost 50% compared to LEACH, but that it also outperforms several related protocols with respect to energy efficiency.

37 citations


Cites background or methods from "EESCA: Energy efficient structured ..."

  • ...Table 9 and Figure 8 show a network lifetime comparison of the proposed CFSFDP-E, KM-LEACH [3], DBCH [20] and EESCA [21]....

    [...]

  • ...From Figure 8, it is obvious that CFSFDP-E algorithm outperforms KM-LEACH, DBCH and EESCA in terms of energy consumption equilibrium....

    [...]

  • ...The Energy Efficient Structured Clustering Algorithm (EESCA) is a hybrid cluster head selection method with parameter location centrality and nodes’ residual energy on the fixed clusters [21]....

    [...]

  • ...The round when the first node dies is prolonged by 50% compared to LEACH and it also outperforms several classical protocols (LEACH-C, PEGASIS and SEP), improved LEACH and KM-LEACH protocols (ALEACH, C-LEACH and K-LEACH) and protocols proposed in recent years (DBCH and EESCA....

    [...]

  • ...• With the same simulation environment and parameters, it is proved that our proposed CFSFDP-E algorithm in WSN outperforms the classical protocols (LEACH [13], LEACH-C [14], PEGASIS [15] and SEP [16]), some improved protocols based on LEACH (ALEACH [17], C-LEACH [18] and K-LEACH [19]) and some new protocols which were proposed in the last three years (KM-LEACH [3], DBCH [20] and EESCA [21])....

    [...]

Journal ArticleDOI
TL;DR: The ability of this work to enhance LEACH while prolonging the lifetime and improving the performance of WSN is clarified, especially in the setup phase where CH is selected randomly.

26 citations

Journal ArticleDOI
TL;DR: Experimental results show that EESCA-WR is extremely scalable, energy-efficient with a minimum number of control messages, and can be used for large scale WSNs.
Abstract: Proper utilization of the available low-power is essential to extend the lifetime of the battery-operated wireless sensor networks (WSNs) for environmental monitoring applications. It is mandatory because the batteries cannot be replaced or recharged after deployment due to impracticality. To utilize the power properly, an appropriate cluster-based data gathering algorithm is needed which reduces the overall power consumption of the network significantly. So, in this paper, a grid-based data gathering algorithm called energy-efficient structured clustering algorithm with relay (EESCA-WR) is proposed. In this algorithm, the grids have a single grid leader (GL) and multiple grid relays (GRs). The count of GRs in a grid is variable based on the geographic location of the grid with respect to the destination sink (DS). By doing this, we ensure that the reduction in power consumption is achieved because of the multi-hop short-distance data communications. Also, the GLs are rotated in the right intervals in hybrid modes to minimize the usage of control messages considerably. A hybrid GL selection policy, a threshold-based GL rotation policy, and the policy of allotting dedicated relay-clusters in every grid make the proposed algorithm unique and better for homogeneous and heterogeneous wireless sensor networks. Performance evaluation of the proposed algorithm is carried out by varying the length of the field, the node-density, the grid-count, and the initial energy. Experimental results show that EESCA-WR is extremely scalable, energy-efficient with a minimum number of control messages, and can be used for large scale WSNs.

19 citations

Proceedings ArticleDOI
01 Aug 2017
TL;DR: This paper analyzed the impact of BS location on the energy efficiency of the network and proposed location improves the first node die (FND) by 20%, 14%, and 17%, and the last nodes die (LND) improves by 16%, 13% and 39% in uniformly distributed field.
Abstract: Wireless sensor networks (WSNs) have wide applications in environmental monitoring fields. Many algorithms were proposed for efficient information gathering. Especially the cluster based routing schemes are getting attention due to their energy efficiency. But in most of the clustering schemes, the base station (BS) which is used to gather the information is assumed to be located far from the field. In this paper, we analyzed the impact of BS location on the energy efficiency of the network. The proposed location improves the first node die (FND) by 20%, 14%, and 17%, improves the last node die (LND) by 16%, 13% and 39% in uniformly distributed field, improves FND by 16%, 14%, and 15%, improves LND by 6%, 12%, and 58% in randomly distributed field compared to the famous low energy adaptive clustering hierarchy (LEACH) algorithm, Energy based algorithm (ENERGY), and the recent algorithm energy efficient structured clustering algorithm (EESCA) respectively.

5 citations


Cites methods from "EESCA: Energy efficient structured ..."

  • ...PERFORMANCE ANALYSIS Algorithm Scene Distribut-ion Performance FND QND HND LND LEACH S1 Uniform 874 1037 1107 1300 Random 914 1025 1112 1308 S2 Uniform 860 1035 1094 1391 Random 857 1027 1095 1319 S3 Uniform 833 924 975 1259 Random 816 958 1001 1279 S4 Uniform 716 804 895 1202 Random 736 816 912 1239 ENERGY S1 Uniform 874 1114 1122 1300 Random 914 1118 1125 1308 S2 Uniform 860 1101 1110 1391 Random 857 1106 1113 1319 S3 Uniform 833 1035 1045 1259 Random 816 1041 1052 1279 S4 Uniform 716 967 977 1202 Random 736 975 984 1239 EESCA S1 Uniform 874 1089 1103 1300 Random 914 1083 1116 1308 S2 Uniform 860 1080 1102 1391 Random 857 1075 1116 1319 S3 Uniform 833 998 1003 1259 Random 816 997 1040 1279 S4 Uniform 716 897 905 1202 Random 736 887 1024 1239 The S3 and S4 move the BS far from the field which results in high energy consumption....

    [...]

  • ...In S1 and S2, EESCA is performing well compared to other algorithms....

    [...]

  • ...9 Performance of EESCA for different scenarios in randomly distributed field V. CONCLUSION WSNs are suitable for many applications where a fixed wired communication is not possible....

    [...]

  • ...EESCA initially selects the nodes which are closer to central position of the clusters as CHs....

    [...]

  • ...[17] P. Yuvaraj, and K. V. L. Narayana, “EESCA: Energy efficient structured clustering algorithm for wireless sensor networks,” 2016 International Conference on Computing, Analytics and Security Trends (CAST), pp. 523–527, 2016....

    [...]

References
More filters
Journal ArticleDOI
TL;DR: The concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics is described.

17,936 citations


"EESCA: Energy efficient structured ..." refers background in this paper

  • ...Sensed information is exchanged to an area of interest using wireless communication [1]....

    [...]

Journal ArticleDOI
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.
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.

10,296 citations


"EESCA: Energy efficient structured ..." refers methods in this paper

  • ...Figures also demonstrate the measure of the lifetime of the network is increased compared to LEACH....

    [...]

  • ...In contrast to the LEACH, EESCA is producing good balanced clusters and the cluster heads are selected based on the centrality and the residual energy of the nodes....

    [...]

  • ...When the area of deployment is increased in the network, LEACH is not performing well due to poor scalability....

    [...]

  • ...In LEACH, the cluster heads are selected randomly and thereby the possibility of selecting the nodes in the corner of the field as cluster heads is more....

    [...]

  • ...LEACH [8] is a very popular cluster based algorithm in which a probabilistic approach is used for the cluster head selection....

    [...]

Journal ArticleDOI
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.
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.

4,889 citations


"EESCA: Energy efficient structured ..." refers methods in this paper

  • ...Hybrid, Energy-Efficient, Distributed (HEED) approach [9] is a well-known algorithm that uses Lingering energy and Node proximity for the cluster head selection....

    [...]

Journal ArticleDOI
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.

2,283 citations


"EESCA: Energy efficient structured ..." refers background in this paper

  • ...Cluster based routing algorithms [7] are proved very useful for achieving better energy efficiency in the past....

    [...]

Journal ArticleDOI
TL;DR: Key applications and the main phenomena related to acoustic propagation are summarized, and how they affect the design and operation of communication systems and networking protocols at various layers are discussed.
Abstract: This paper examines the main approaches and challenges in the design and implementation of underwater wireless sensor networks. We summarize key applications and the main phenomena related to acoustic propagation, and discuss how they affect the design and operation of communication systems and networking protocols at various layers. We also provide an overview of communications hardware, testbeds and simulation tools available to the research community.

728 citations


"EESCA: Energy efficient structured ..." refers methods in this paper

  • ...Hence, WSNs are used in many applications [2] such as identifying unauthorized movements of enemy submarines and autonomous underwater vehicles (AUVs) [3], active volcano monitoring [4] by sensing signals using seismic and acoustic sensors to safeguard the people, forecasting climate changes in arctic and Antarctic regions to visualize the effects of global warming and forestfire monitoring for controlling etc....

    [...]