Bandwidth efficient cluster-based data aggregation for Wireless Sensor Network

Mantri, Dnyaneshwar S.; Prasad, Neeli R.; Prasad, Ramjee

doi:10.1016/j.compeleceng.2014.08.008

Cited by 37 publications

(13 citation statements)

References 15 publications

(15 reference statements)

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“…In [11], author used the aggregation principle to reduce the transmission time and active node interval for increase in the network lifetime and channel utilization. In [12], the idea of minimizing energy consumption by use of additive and divisible aggregation function at cluster head and sink is explored. In [13] Cluster Wide Correlated Grouping (CWCG), proposes the hybrid structure for data aggregation.…”

Section: Related Workmentioning

confidence: 99%

Mobility and Heterogeneity Aware Cluster-Based Data Aggregation for Wireless Sensor Network

Mantri

Prasad

2015

Wireless Pers Commun

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Internet of things is the modern era, which offers a variety of novel applications for mobile targets and opens the new domains for the distributed data aggregations using wireless sensor networks. However, low cost tiny sensors used for network formation generate the large amount of redundant sensing data and hence, results in energy and bandwidth constraints. In this context, the paper proposes the sink mobility and nodes heterogeneity aware cluster-based data aggregation algorithm (MHCDA) for efficient bandwidth utilization and an increase in network lifetime. The proposed algorithm uses a predefined region for the aggregation of packets at the cluster head for minimizing computation and communication cost. MHCDA exploits correlation of data packets generated by nodes with a variable packet generation rate to reduce energy consumption by 8.66 %. Also, it prolongs the network life by 23.53 % as compared to with and without mobility of the sink and state of the-art solutions.

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Section: Related Workmentioning

confidence: 99%

Mobility and Heterogeneity Aware Cluster-Based Data Aggregation for Wireless Sensor Network

Mantri

Prasad

2015

Wireless Pers Commun

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“…It deliberates the network with heterogeneous nodes based on the energy and dynamic sink to gather the data packets. The optimality was attained by inter-cluster and intra-cluster aggregation on the randomly disseminated nodes with the adaptable data generation rate [11]. Rout et al formulated an analytical approach for adaptive data aggregation.…”

Section: Related Workmentioning

confidence: 99%

SAC-TA: A Secure Area Based Clustering for Data Aggregation Using Traffic Analysis in WSN

Gopalakrishnan¹,

Arumugam²,

Lakshmi³

et al. 2016

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Clustering is the most significant task characterized in Wireless Sensor Networks (WSN) by data aggregation through each Cluster Head (CH). This leads to the reduction in the traffic cost. Due to the deployment of the WSN in the remote and hostile environments for the transmission of the sensitive information, the sensor nodes are more prone to the false data injection attacks. To overcome these existing issues and enhance the network security, this paper proposes a Secure Area based Clustering approach for data aggregation using Traffic Analysis (SAC-TA) in WSN. Here, the sensor network is clustered into small clusters, such that each cluster has a CH to manage and gather the information from the normal sensor nodes. The CH is selected based on the predefined time slot, cluster center, and highest residual energy. The gathered data are validated based on the traffic analysis and One-time Key Generation procedures to identify the malicious nodes on the route. It helps to provide a secure data gathering process with improved energy efficiency. The performance of the proposed approach is compared with the existing Secure Data Aggregation Technique (SDAT). The proposed SAC-TA yields lower average energy consumption rate, lower end-to-end delay, higher average residual energy, higher data aggregation accuracy and false data detection rate than the existing technique.

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“…S. Mantri et al [17] have proposed a Bandwidth Efficient Cluster-based Data Aggregation (BECDA) algorithm which provides effective data gathering with in-network aggregation. It uses the correlation of data within the packet for performing data aggregation.…”

Section: Literature Reviewmentioning

confidence: 99%

Cluster Based Compressed Data Aggregation and Routing in WSN

Jothi¹,

Chandrasekaran²

2016

IJIES

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Due to non uniform distribution of nodes, there is an imbalance of energy consumption among the nodes in cluster-based wireless sensor networks. Based on this problem, we propose an efficient data aggregation tree for communication and routing based on the previous clustering architecture. Here based on the parameters such as Residual Energy, Node Density and Load cluster heads are elected using fuzzy logic technique. The inter-cluster routing algorithm balances the energy consumption among cluster heads by adjusting inter-cluster energy consumption. Then data compression is applied for reducing the energy consumption using data correlation model.

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Bandwidth efficient cluster-based data aggregation for Wireless Sensor Network

Cited by 37 publications

References 15 publications

Mobility and Heterogeneity Aware Cluster-Based Data Aggregation for Wireless Sensor Network

Mobility and Heterogeneity Aware Cluster-Based Data Aggregation for Wireless Sensor Network

SAC-TA: A Secure Area Based Clustering for Data Aggregation Using Traffic Analysis in WSN

Cluster Based Compressed Data Aggregation and Routing in WSN

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