Abstract
Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).
Highlights
Typical sensor nodes are able to carry out sensing, data processing and communicating components, making them feasible for a wide range of promising applications, such as: environmental monitoring, disaster, healthcare, military, etc. [1]
The research in data-centric wireless sensors networks (WSNs) is concentrated on clustering by reducing the number of transmissions to the sink, by selection of a proper MAC layer and an energy-efficient data aggregation mechanism to alleviate the challenges of WSNs
We proposed the cross-layer cluster-based energy-efficient algorithms (CCBE) algorithm to extend the network lifetime and to reduce the energy consumption in end-to-end packet transmission
Summary
Typical sensor nodes are able to carry out sensing, data processing and communicating components, making them feasible for a wide range of promising applications, such as: environmental monitoring (e.g., humidity, temperature), disaster, healthcare, military, etc. [1]. The critically-located sensors are those located near the sink, which carry the burden of relaying large amounts of data traffic, especially when multiple high-rate routes pass through these nodes. Avoiding the failure of such nodes caused by early energy depletion is critical for improving the network lifetime. Another important challenge occurs, when each and every node wants to simultaneously transmit and receive data at the same time. This will lead to a lot of data collisions and congestion. The research in data-centric WSNs is concentrated on clustering by reducing the number of transmissions to the sink, by selection of a proper MAC layer and an energy-efficient data aggregation mechanism to alleviate the challenges of WSNs
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