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Local efficiency of a node is therefore calculated as the harmonic mean for neighbour-neighbour distances.
Closeness (in or out) is a metric representing the independence and efficiency of a node in communication.
It can be considered as the efficiency of a node (individual) in spreading information to others in the network.
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Thus, the energy efficiency of a sensor node can increase without requiring any specific power management hardware.
Third, based on the previous analysis, a network optimization deployment algorithm is proposed, which not only maximizes the energy efficiency of a single node but also maximizes the network lifetime and the total network energy efficiency.
The local efficiency of an individual node i (Eloc(i)) defines the efficiency of information transfer within the subgraph Gi of nodes directly connected to node i: <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0016510.e078.PNG" class= inline-graphic"/> where the degree ki equals the number of nodes directly neighboring node i.
In this work, we focus on energy efficiency of a wearable sensor node in an Internet-of-Things (IoT) based fall detection system.
We mainly propose a simple heuristic algorithm to improve the energy efficiency of each node in a clustering based EH-WSN.
By improving power consumption efficiency of sensor node operations, a sensor node's lifetime can be significantly extended.
To achieve the most efficiency parallel computation inside of a node, we modified MPI library into assembly coded library.
This metric assesses the efficiency standing in the perspective of a node.
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