A lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks

Abstract

Despite unique energy-saving dispositions of cluster-based routing protocols, clustered wireless sensor networks with static sinks typically have problems of unbalanced energy consumptions, as the cluster head nodes around the sink are typically loaded with traffic from upper levels of clusters. This results in reduced lifetimes of the nodes and deterioration of other crucial performances. Meanwhile, it has been inferred from current literature that dedicated relay cooperation in cluster-based wireless sensor networks guarantees longer lifetime of the nodes and more improved performance. Therefore, to attain further enhanced performance among the current schemes, a lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks is proposed in this article. The proposed lifetime-enhancing cooperative data gathering and relaying algorithm shares the nodes into clusters using a hybrid K-means clustering algorithm that combines K-means clustering and Huffman coding algorithms. It makes full use of dedicated relay cooperative multi-hop communication with network coding mechanisms to achieve reduced data propagation cost from the various cluster sections to the central base station. The relay node selection is framed as a NP-hard problem, with regard to communication distances and residual energy metrics. Furthermore, to resolve the problem, a gradient descent algorithm is proposed. Simulation results endorse the proposed scheme to outperform related schemes in terms of latency, lifetime, and energy consumption and delivery rates.

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

“…At each time slot, the scheduled nodes work on behalf of their redundant nodes to ensure that no two nodes concurrently end up sensing the same area, thereby preventing energy waste. This approach is also called the topology control scheme [119], [120] as it controls the topological structure of the network by reducing the number of activated sensor nodes. Duty cycling-based approaches incur control overheads, making them less energy-efficient and scalable compared to other topology-level duty cycling approaches.…”

ZIZO: A Zoom-In Zoom-Out Mechanism for Minimizing Redundancy and Saving Energy in Wireless Sensor Networks

“…The aim of the proposed algorithm is to minimize the intra-cluster distance in order to determine the optimal partition at every sensor node. The authors of [29] propose a cluster-based data gathering algorithm for WSN called lifetime-enhancing cooperative data gathering and relaying (LCDGRA). Basically, LCDGRA works on three phases: the first phase aims to group the sensor nodes into clusters based on K-means clustering and Huffman coding algorithms.…”

Orchestration‐based mechanism for sampling adaptation in sensing‐based applications

“…The authors in [18][19][20][21][22][23] dedicated their works to reducing the amount of data circulated in the network along the path to the sink, for example, at intermediates nodes. In [19], the authors propose a cluster-based data gathering algorithm for WSN called lifetime-enhancing cooperative data gathering and relaying (LCDGRA). LCDGRA works on three phases: the first phase aims to group the sensor nodes into clusters based on K-means clustering and Huffman coding algorithms.…”