Dynamic multi-channel packet scheduling in an underwater acoustic sensor network

Ramezani, Hamid; Leus, Geert

doi:10.1109/acssc.2013.6810238

Cited by 3 publications

(6 citation statements)

References 9 publications

(16 reference statements)

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“…where t M p is the packet duration if M subchannels are employed, t 1 p is the packet duration for the single-channel case (whole bandwidth is used), and α M is the penalty that the system suffers from splitting the channel into M subchannels [2]. In underwater acoustic communication, the signals which are transmitted at higher frequencies are attenuated more.…”

Section: Dynamic Multi-channel Packet Schedulingmentioning

confidence: 99%

“…In contrast to the above works on underwater MAC protocols, in our previous papers, we have focused on designing a scheduling protocol for the specific task of anchor-based partially-connected single channel [1] and multi-channel underwater localization [2]. To do that, we have utilized the information about the relative positions of the anchors and their maximum transmission range to minimize the duration of the localization task.…”

Section: Introductionmentioning

confidence: 97%

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Localization Packet Scheduling for Underwater Acoustic Sensor Networks

Ramezani

Leus

2015

IEEE J. Select. Areas Commun.

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Medium access control (MAC) determines how sensor nodes share the channel for packet exchanging. To obtain the maximum network efficiency for accomplishing a specific task, the network has to adapt its parameters accordingly. In other words, different MAC protocols are required for different tasks. Localization is a crucial task of an underwater acoustic sensor network (UASN) which requires multiple packet exchanges. This article concerns the problem of designing a MAC protocol for a UASN which efficiently schedules the localization packets of the anchors. Knowing the relative positions of the anchors and their maximum transmission range, the scheduling protocol takes advantage of the long propagation delay of underwater communications to minimize the duration of the localization task. First, we formulate the concept of collision-free packet transmission for localization, and we show how the optimum solution can be obtained. Furthermore, we model the problem as a mixed integer linear program both in single-channel and multi-channel scenarios. Then, we propose two low-complexity algorithms, and through comprehensive simulations we compare their performances with the optimal solution as well as with other existing methods. Numerical results show that the proposed algorithms perform near optimum and better than alternative solutions.

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Section: Dynamic Multi-channel Packet Schedulingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Localization Packet Scheduling for Underwater Acoustic Sensor Networks

Ramezani

Leus

2015

IEEE J. Select. Areas Commun.

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“…Many channel allocation techniques for UASNs have been studied extensively, and a number of optimal and suboptimal solutions have been presented [ 46 , 47 , 48 , 49 , 50 , 51 , 52 ]. In [ 46 ], a channel sharing technique that takes advantage of long delays of underwater channel was presented, and it resulted in an improved spectrum efficiency compared to the conventional spectrum reuse scheme.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the authors of [ 49 ] studied a joint channel and power allocation algorithm for cognitive UASNs that aim at providing efficient spectrum utilization while avoiding harmful interference to other UASNs. In [ 50 ], the problem of minimization of total collision-free transmission time was demonstrated as NP-hard, and therefore the authors proposed a suboptimal algorithm which could work much better than the conventional scheduling algorithms. In [ 51 ], a joint channel and power allocation algorithm was developed to maximize the network capacity.…”

Section: Introductionmentioning

confidence: 99%

Distributed Learning for Dynamic Channel Access in Underwater Sensor Networks

Shin

Kim

Baek

et al. 2020

Entropy

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In this study, the problem of dynamic channel access in distributed underwater acoustic sensor networks (UASNs) is considered. First, we formulate the dynamic channel access problem in UASNs as a multi-agent Markov decision process, wherein each underwater sensor is considered an agent whose objective is to maximize the total network throughput without coordinating with or exchanging messages among different underwater sensors. We then propose a distributed deep Q-learning-based algorithm that enables each underwater sensor to learn not only the behaviors (i.e., actions) of other sensors, but also the physical features (e.g., channel error probability) of its available acoustic channels, in order to maximize the network throughput. We conduct extensive numerical evaluations and verify that the performance of the proposed algorithm is similar to or even better than the performance of baseline algorithms, even when implemented in a distributed manner.

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“…Nodes reserve channel resources through handshaking exchange message before initiating data communication [11,12]. The multichannel MAC protocols transmit handshaking exchange message via independent channels, initiates information transmission among multinode pairs concurrently, utilizes network bandwidth and reduces the consumption when network load is heavy [13][14][15], and attracts attention of the researchers recently. The prospective of the multichannel MAC protocols is solving new problems which are faced with multichannel protocols, especially the collision problem in control channel.…”

Section: Introductionmentioning

confidence: 99%

The Control Packet Collision Avoidance Algorithm for the Underwater Multichannel MAC Protocols via Time-Frequency Masking

Shi²,

He³

et al. 2016

Discrete Dynamics in Nature and Society

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Establishing high-speed and reliable underwater acoustic networks among multiunmanned underwater vehicles (UUVs) is basic to realize cooperative and intelligent control among different UUVs. Nevertheless, different from terrestrial network, the propagation speed of the underwater acoustic network is 1500 m/s, which makes the design of the underwater acoustic network MAC protocols a big challenge. In accordance with multichannel MAC protocols, data packets and control packets are transferred through different channels, which lowers the adverse effect of acoustic network and gradually becomes the popular issues of underwater acoustic networks MAC protocol research. In this paper, we proposed a control packet collision avoidance algorithm utilizing time-frequency masking to deal with the control packets collision in the control channel. This algorithm is based on the scarcity of the noncoherent underwater acoustic communication signals, which regards collision avoiding as separation of the mixtures of communication signals from different nodes. We first measure the W-Disjoint Orthogonality of the MFSK signals and the simulation result demonstrates that there exists time-frequency mask which can separate the source signals from the mixture of the communication signals. Then we present a pairwise hydrophones separation system based on deep networks and the location information of the nodes. Consequently, the time-frequency mask can be estimated.

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Dynamic multi-channel packet scheduling in an underwater acoustic sensor network

Cited by 3 publications

References 9 publications

Localization Packet Scheduling for Underwater Acoustic Sensor Networks

Localization Packet Scheduling for Underwater Acoustic Sensor Networks

Distributed Learning for Dynamic Channel Access in Underwater Sensor Networks

The Control Packet Collision Avoidance Algorithm for the Underwater Multichannel MAC Protocols via Time-Frequency Masking

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