Long-Lifetime and Low Latency Data Aggregation Scheduling for Wireless Sensor Network
TL;DR: The steps proposed in this article ensure an increase in the network lifetime and decrease in the energy utilization.
Abstract: Wireless Sensor Networks contain an incredible number of hubs with limited registering, detecting, and wireless communication capacities. These systems have been utilized as a part of a wide zone of utilizations, such as human services, contamination checking, and target-following frameworks. The dynamic clustering of sensors into bunches is a prevalent procedure to expand the system lifetime and increment adaptability. To accomplish this, in this article the sensor hubs are adjusted to ensure a long lifetime and the activities are arranged into rounds that use fixed time intervals. In the first phase, a clustering topology is found, and a group head is picked in view of the outstanding energy level. Then the cluster head screens the network energy threshold value to identify the energy drain rate of all its cluster members. In the second stage, the Long-Lifetime and Low-Latency Data Aggregation Scheduling method is used. This scheduling method assigns schedule openings to group part information parcels. Here, congestion occurrence is completely kept away from the scenario. In the third stage, an Energy-Efficient Distributed Schedule–based convention is used to keep up greatest residual energy level over the network. The experimental outcome shows the steps proposed in this article ensure an increase in the network lifetime and decrease in the energy utilization.
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01 Feb 2020
TL;DR: This paper presents a comparative study on cluster-based protocols being utilized to conserve node's energy, and discovered various mechanisms for energy conservation with respect to the power component.
Abstract: Research conversation about Wireless Sensor Networks (WSNs) has been creating a buzz in the network universe for quite some time now. Over the years, this exploratory research has found its applications in a variety of domains. Sensor nodes equipped with inadequate power, processing capability, storage, and energy are deployed in remote areas that remain unattended by humans. As a result, energy conservation of nodes is a challenging parameter that affects the lifespan of the node resulting in network degradation. In this paper, the challenges of sensor nodes, their actions causing energy wastage are studied in detail. Further, this paper presents a comparative study on cluster-based protocols being utilized to conserve node's energy. The review discovered various mechanisms for energy conservation with respect to the power component. Comparative analyses of various node metrics are graphically depicted. Although, many strategies improve energy conservation, but it was observed via this survey that these strategies might also negatively impact other important factors in overall network.
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01 Nov 2019
TL;DR: It has been revealed that DDC technique outperforms DCP both in terms of energy and delay, when operating under bursty traffic.
Abstract: Media Access Control (MAC) layer has been regarded as the crucial component for optimizing energy performance in Low Power Devices and Wireless Sensor Networks (WSN) operating in Internet of Things (IoT) environment. As evident from the literature, Dynamic Duty-Cycling (DDC) and Dynamic Channel Polling (DCP) are major schemes deployed at the MAC layer targeted at achieving energy efficiency. This paper compares the energy and delay performance of these two schemes for the bursty traffic applications. The protocols Adaptive and Dynamic Polling-MAC (ADP-MAC) and Traffic Auto-ADaptive mechanism, T-AAD have been selected from each category of DDC and DCP respectively. Mica2 sensor motes and Avrora emulator have been used for conducting experiments. Effect of varying burst generation intervals and wake up duration of nodes have been studied over the energy and delay performance. ADP-MAC has shown to outperform T-AAD due to having efficient match between the channel polling and packet generation instants. Although, T-AAD adjusts the duty-cycle in accordance with the traffic pattern, the preamble transmission cost and delay still remains significantly higher as compared to ADP-MAC. Hence, it has been revealed that DDC technique outperforms DCP both in terms of energy and delay, when operating under bursty traffic.
1 citations
Cites methods from "Long-Lifetime and Low Latency Data ..."
...Dynamic Duty-Cycling (DDC) [11] and Dynamic Channel Polling (DCP) [12] have been widely used in MAC protocols for performance optimization of WSN in terms of energy [13] as well as delay [14]....
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