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Proceedings ArticleDOI

A new battery and redundancy aware node scheduling protocol for Wireless Sensor Networks

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TLDR
This work proposes a node scheduling protocol for sensor networks that exploits the battery charge recovery property and node level redundancy with respect to sensing, in order to maximize the network lifetime.
Abstract
Wireless Sensor Networks demand energy conserving protocols at all layers of protocol stack in order to achieve increased network lifetime. In this work, we propose a node scheduling protocol for sensor networks that exploits the battery charge recovery property and node level redundancy with respect to sensing, in order to maximize the network lifetime. The protocol forms a virtual grid and periodically elects the active node in a given grid. The primary battery sources of the remaining redundant nodes are completely switched off. The periodic election of active nodes ensures that every redundant node recovers its battery charges during their inactive period. We compare the performance of our protocol with baseline approaches like Strict Alternation, Periodic Alternation which are redundancy aware and also with the standard IEEE 802.11 and T-MAC protocols. The simulation results reveal that our protocol achieves network lifetime as high as 20% to 40% than the other schemes, with un-interrupted sensing and reporting of the events to sink.

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Citations
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Patent

Systems and Methods for Operation Mode Transition In Wireless Communications

TL;DR: In this article, a method for a base station to instruct a mobile station to perform an operation mode transition was proposed, where the base station receives battery level information from the mobile station, and the battery level is included in a signaling header.
Journal ArticleDOI

Service redundancy and cluster‐based routing protocols for wireless sensor and mobile ad hoc networks: A survey

TL;DR: The various issues and challenges facing the design and selection of the appropriate service discovery and cluster‐based mechanism are discussed, and attention has been drawn to the cross‐layer solution by discussing different clustering techniques used to solve the redundancy problems.
Proceedings ArticleDOI

Optimum Partition for Distant Charging in Wireless Sensor Networks

TL;DR: This work designs and analyzes three network partition methods, namely the tier-based partition, the sector- based partition, and the mixed partition, for charging scheduling with mobile charging machines so that the resulting sub-networks exhibits approximately the same total energy consumption rate.
Patent

Low duty cycle transmission scheme for nb iot devices

Thomas Fliess
TL;DR: In this article, the authors proposed a transmission scheme for mobile communication devices scheduled in a cell of a network by a base station, whereas a user equipment (UE) powered by a power supply transmits a block of payload information defined by a limited transmission power over a contiguous total transmission time.
References
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Journal ArticleDOI

A survey on sensor networks

TL;DR: The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections.
Journal Article

An Energy-Efficient MAC Protocol for Wireless Sensor Networks

TL;DR: S-MAC as discussed by the authors is a medium access control protocol designed for wireless sensor networks, which uses three novel techniques to reduce energy consumption and support self-configuration, including virtual clusters to auto-sync on sleep schedules.
Proceedings ArticleDOI

An energy-efficient MAC protocol for wireless sensor networks

TL;DR: S-MAC uses three novel techniques to reduce energy consumption and support self-configuration, and applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network.
Proceedings ArticleDOI

An adaptive energy-efficient MAC protocol for wireless sensor networks

TL;DR: T-MAC, a contention-based Medium Access Control protocol for wireless sensor networks, introduces an adaptive duty cycle in a novel way: by dynamically ending the active part of it to handle load variations in time and location.
Proceedings ArticleDOI

Coverage problems in wireless ad-hoc sensor networks

TL;DR: This work establishes the main highlight of the paper-optimal polynomial time worst and average case algorithm for coverage calculation, which answers the questions about quality of service (surveillance) that can be provided by a particular sensor network.
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