Network Lifetime Maximization in Wireless Sensor Networks with a Path-Constrained Mobile Sink

Huynh, Thong; Hwang, Won-Joo

doi:10.1155/2015/679093

Cited by 6 publications

(2 citation statements)

References 33 publications

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“…In addition, the fact that drones typically operate in geographically challenging areas is often ignored. Note that in our paper, the lifetime of the drone fleet is defined as the time of the first drone running out of power, which is widely adopted [ 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Dynamic 3D Placement of Multi-Drone Sensing Fleet

Luo

Chen

2021

Sensors

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Unmanned Aerial Vehicles (UAVs, also known as drones) have become increasingly appealing with various applications and services over the past years. Drone-based remote sensing has shown its unique advantages in collecting ground-truth and real-time data due to their affordable costs and relative ease of operability. This paper presents a 3D placement scheme for multi-drone sensing/monitoring platforms, where a fleet of drones are sent for conducting a mission in a given area. It can range from environmental monitoring of forestry, survivors searching in a disaster zone to exploring remote regions such as deserts and mountains. The proposed drone placing algorithm covers the entire region without dead zones while minimizing the number of cooperating drones deployed. Naturally, drones have limited battery supplies which need to cover mechanical motions, message transmissions and data calculation. Consequently, the drone energy model is explicitly investigated and dynamic adjustments are deployed on drone locations. The proposed drone placement algorithm is 3D landscaping-aware and it takes the line-of-sight into account. The energy model considers inter-communications within drones. The algorithm not only minimizes the overall energy consumption, but also maximizes the whole drone team’s lifetime in situations where no power recharging facilities are available in remote/rural areas. Simulations show the proposed placement scheme has significantly prolonged the lifetime of the drone fleet with the least number of drones deployed under various complex terrains.

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Section: Introductionmentioning

confidence: 99%

Energy-Aware Dynamic 3D Placement of Multi-Drone Sensing Fleet

Luo

Chen

2021

Sensors

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“…• Network lifetime. Defined as the time until the first sensor's energy runs out, energy conservation to prolong the network lifetime is one of the major issues in sensor networks [28,29]. Nodes can typically use batteries with a reduced energy life which influences the network lifetime.…”

Section: Acoustic Sensor Network (Asn)mentioning

confidence: 99%

Distributed and Collaborative Processing of Audio Signals: Algorithms, Tools and Applications

Manuel¹

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This thesis fits into the field of Information and Communications Technology (ICT), especially in the area of digital signal processing. Nowadays and due in part to the rise of the Internet of Things (IoT), there is a growing interest in wireless sensor networks (WSN), that is, networks composed of different types of devices specifically distributed in some area to perform different signal processing tasks. These devices, also referred to as nodes, are usually equipped with electroacoustic transducers, such as sensors or actuators, as well as powerful and efficient processors with communication capability. In the particular case of acoustic sensor networks (ASN), nodes are dedicated to solving different acoustic signal processing tasks, such as environmental sound monitoring, immersive audio, binaural hearing aids, noise-cancelling systems as well as audio teleconferencing. These audio signal processing applications have been undergone a major development in recent years due in part to the advances made in computer hardware and software. This has led to the development of powerful centralized processing systems that allow the number of audio channels to be increased, the control area to be extended or more complex algorithmms to be implemented, thereby improving audio quality or creating independent control over several personal sound zones. In most cases, a distributed ASN topology can be desirable due to several factors such as the limited number of channels used by the sound acquisition and reproduction devices, the convenience of a scalable system or the high computational demands of a centralized fashion. All these aspects may lead to the use of novel distributed signal processing techniques with the aim to be applied over ASNs. To this end, one of the main contributions of this dissertation is the development of adaptive filtering algorithms for multichannel sound systems over distributed networks.Note that, for sound field control (SFC) applications, such as active noise control (ANC) or active noise equalization (ANE), acoustic nodes must be not only equipped with sensors but also with actuators in order to control and modify the sound field. However, most of the adaptive distributed networks approaches used to solve soundfield control problems do not take into account that the nodes may interfere or modify the behaviour of the rest. This is an important issue which is tackled throughout this thesis. Therefore, other important contribution of this thesis is focused on analyzing

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