Network Lifetime Maximization with Adjustable Node Transmission Range

Adu-Manu, Kofi Sarpong; Katsriku, Ferdinand Apietu; Abdulai, Jamal-Deen; Gómez, Jorge Marx; Heinzelmann, Wendi

doi:10.1007/978-3-658-25210-6_54

Cited by 7 publications

(6 citation statements)

References 15 publications

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“…The MPR reduces the control overhead of flooding since only MPRs generate link-state information. Therefore, the flooding of the network with control overhead messages reduces when OLSR is employed [27]. OLSR only transmits partial linkstate information between MPRs and their MPR selectors for route calculations.…”

Section: Wsn Protocol Stackmentioning

confidence: 99%

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WSN Protocols and Security Challenges for Environmental Monitoring Applications: A Survey

et al. 2022

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In recent years, communication technology has improved exponentially, partly owing to the locations and nature of the deployment of sensor nodes. Wireless sensor networks (WSNs) comprise these sensor nodes and can provide real-time physical and environmental measurements. The sensor nodes have limited power, which reduces their lifespan, especially when placed in human-inaccessible locations. This paper reviews energy-efficient protocols for environmental monitoring applications and energy harvesting-wireless sensor networks. The dynamic deployment and communication challenges associated with environmental monitoring applications (EMAs) make this paper take into account the WSN protocol stack, focusing on the physical layer, network layer (routing), and medium access control (MAC). The paper will delve deeper into the security challenges of deploying sensor nodes for environmental monitoring applications (EMAs). The paper further describes scientific approaches that churn out innovative and engineering applications that must be followed to improve environmental monitoring applications.

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Section: Wsn Protocol Stackmentioning

confidence: 99%

“…It is also suitable for applications that do not allow for long delays and operate in dense networks. However, it is disadvantageous in mobile networks where the frequent change in topology increases the exchange of control overhead messages, increasing the cost of energy and memory use [27].…”

Section: Wsn Protocol Stackmentioning

confidence: 99%

WSN Protocols and Security Challenges for Environmental Monitoring Applications: A Survey

et al. 2022

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“…The internal battery in most cases is unable to meet the energy budget; hence, in WSN for environmental applications such as WQM, the energy budget may be improved by designing algorithms and protocols that are capable of regulating and reducing the amount of energy consumed and the frequency of data transmission when the measured parameter is transmitted to the cloud. Also, the energy budget may be compensated by harvesting energy from ambient sources to extend the lifetime of the battery during its operation [33].…”

Section: Data Transmission (Communication)mentioning

confidence: 99%

Smart River Monitoring Using Wireless Sensor Networks

Adu-Manu

Katsriku

Abdulai

et al. 2020

Wireless Communications and Mobile Computing

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Water quality monitoring (WQM) systems seek to ensure high data precision, data accuracy, timely reporting, easy accessibility of data, and completeness. The conventional monitoring systems are inadequate when used to detect contaminants/pollutants in real time and cannot meet the stringent requirements of high precision for WQM systems. In this work, we employed the different types of wireless sensor nodes to monitor the water quality in real time. Our approach used an energy-efficient data transmission schedule and harvested energy using solar panels to prolong the node lifetime. The study took place at the Weija intake in the Greater Accra Region of Ghana. The Weija dam intake serves as a significant water source to the Weija treatment plant which supplies treated water to the people of Greater Accra and parts of Central regions of Ghana. Smart water sensors and smart water ion sensor devices from Libelium were deployed at the intake to measure physical and chemical parameters. The sensed data obtained at the central repository revealed a pH value of 7. Conductivity levels rose from 196 S/cm to 225 S/cm. Calcium levels rose to about 3.5 mg/L and dropped to about 0.16 mg/L. The temperature of the river was mainly around 35°C to 36°C. We observed fluoride levels between 1.24 mg/L and 1.9 mg/L. The oxygen content rose from the negative DO to reach 8 mg/L. These results showed a significant effect on plant and aquatic life.

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“…Understanding these sources of energy dissipation in WSNs is essential because it enables researchers to propose and implement techniques/algorithms to reduce energy wastage in WSNs and extend network lifetime [37,38]. As a result, various solutions have been proposed and implemented over the last decade to address this problem.…”

Section: Introductionmentioning

confidence: 99%

SMAC-Based WSN Protocol-Current State of the Art, Challenges, and Future Directions

Amengu

Abdulai

Katsriku

et al. 2022

Journal of Computer Networks and Communications

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Wireless Sensor Networks (WSNS) have become an indispensable tool in this epoch of technological advancements, particularly for progress made in the Internet of things. Wireless sensor nodes are deployed to collect and transmit vital data from the environment to a base station for analysis. Nevertheless, the limited battery power of the sensor nodes is rapidly drained when they stay awake for an extended period. Research has shown that significant sources of energy dissipation of sensor nodes are idle listening, packet collision, control overhead, and overhearing. One optimal solution is employing a low duty cycle mac protocol, particularly the sensor mac (SMAC) protocol. It is essential to have a detailed knowledge of the challenges identified in SMAC and solutions suggested to mitigate these challenges and the future directions. In this paper, we review techniques in SMAC protocols implemented in WSNS. In particular, we provide highlights of recent developments in the schemes used in SMAC for mitigating the challenges in SMAC and present research gaps in SMAC protocol. Finally, we discuss open issues that need to be addressed to advance the design and implementation of SMAC in WSN applications.

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Network Lifetime Maximization with Adjustable Node Transmission Range

Cited by 7 publications

References 15 publications

WSN Protocols and Security Challenges for Environmental Monitoring Applications: A Survey

WSN Protocols and Security Challenges for Environmental Monitoring Applications: A Survey

Smart River Monitoring Using Wireless Sensor Networks

SMAC-Based WSN Protocol-Current State of the Art, Challenges, and Future Directions

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