Topology-Efficient Discovery: A Topology Discovery Algorithm for Underwater Acoustic Networks

Diamant, Roee; Francescon, Roberto; Zorzi, Michele

doi:10.1109/joe.2017.2716238

Cited by 26 publications

(26 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The set of PHYs is arranged in the N × T technology matrix T such that T i,n = 1 if node i has PHY n. Call M the adjacency matrix, where M i, j,n = 1 if node i is connected to node j via PHY n. The number of neighbors of i through technology n is D i,n = j M i, j,n . We assume that T is given, and that M can be obtained via preliminary link probing [6]. We remark that the difference between the communication and interference range is limited in underwater networks, due to the very fast power decay incurred for increasing range by any PHY technology [4].…”

Section: The Oms Algorithm a System Modelmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Transmission Scheduling in Small Multimodal Underwater Networks

Campagnaro

Casari

Zorzi

et al. 2019

IEEE Wireless Commun. Lett.

Self Cite

View full text Add to dashboard Cite

Section: The Oms Algorithm a System Modelmentioning

confidence: 99%

“…The schedule also considers collisions among neighboring nodes and facilitates the forwarding of packets across multiple hops. OMS requires the knowledge of the adjacency matrix M obtained, e.g., via [6]. This includes the existing connections and the available per-node PHY technologies.…”

Section: B Oms Scheduling Solutionmentioning

confidence: 99%

Optimal Transmission Scheduling in Small Multimodal Underwater Networks

Campagnaro

Casari

Zorzi

et al. 2019

IEEE Wireless Commun. Lett.

Self Cite

View full text Add to dashboard Cite

“…The nodes can be randomly deployed or in the form of a grid and tree-structure. Firstly, to provide reliable communication, each sensor node has computational, communication, and intelligence capabilities to deal with a smart environment, as in smart cities [3,4]. Secondly, node sense the data and flood it towards the destination node.…”

Section: Introductionmentioning

confidence: 99%

A Secure Communication in IoT Enabled Underwater and Wireless Sensor Network for Smart Cities

Ali

Irfan

Shaf

et al. 2020

Sensors

View full text Add to dashboard Cite

Nowadays, there is a growing trend in smart cities. Therefore, the Internet of Things (IoT) enabled Underwater and Wireless Sensor Networks (I-UWSN) are mostly used for monitoring and exploring the environment with the help of smart technology, such as smart cities. The acoustic medium is used in underwater communication and radio frequency is mostly used for wireless sensor networks to make communication more reliable. Therefore, some challenging tasks still exist in I-UWSN, i.e., selection of multiple nodes’ reliable paths towards the sink nodes; and efficient topology of the network. In this research, the novel routing protocol, namely Time Based Reliable Link (TBRL), for dynamic topology is proposed to support smart city. TBRL works in three phases. In the first phase, it discovers the topology of each node in network area using a topology discovery algorithm. In the second phase, the reliability of each established link has been determined while using two nodes reliable model for a smart environment. This reliability model reduces the chances of horizontal and higher depth level communication between nodes and selects next reliable forwarders. In the third phase, all paths are examined and the most reliable path is selected to send data packets. TBRL is simulated with the help of a network simulator tool (NS-2 AquaSim). The TBRL is compared with other well known routing protocols, i.e., Depth Based Routing (DBR) and Reliable Energy-efficient Routing Protocol (R-ERP2R), to check the performance in terms of end to end delay, packet delivery ratio, and energy consumption of a network. Furthermore, the reliability of TBRL is compared with 2H-ACK and 3H-RM. The simulation results proved that TBRL performs approximately 15% better as compared to DBR and 10% better as compared to R-ERP2R in terms of aforementioned performance metrics.

show abstract

“…Ocean covers more than 70% of the earth. UWSN is gaining lots of attention because oceans are playing vital role in transportation, ocean exploration, defense, obtaining valuable minerals, oil and gas, surveillance data collection and adventurous means [1] [2] [3]. It also helps in avoidance of different disasters i.e.…”

Section: Introductionmentioning

confidence: 99%

“…Disaster Prevention: In UWSNs, research is conducting in the area of disaster prevention and recovery [2]. With the help of UWSNs, early warnings of the tsunami can be provided to coastal.…”

Section: Introductionmentioning

confidence: 99%

Angle Adjustment for Vertical and Diagonal Communication in Underwater Sensor

Anum¹,

Ali²,

Akbar³

et al. 2020

IJACSA

View full text Add to dashboard Cite

Underwater wireless sensor network has been an area of interest for a few previous decades. UWSNs consists of tiny sensors responsible for monitoring different underwater events and transmit the collected data to the sink node. In the harsh and continuously changing environment of water, gaining better communication and performance is a difficult task as compared to networks available on land because of different underwater characteristics such as end-to-end delays, node movement, and energy constraints. In this paper, a novel routing technique named angle adjustment for vertical and diagonal communication was proposed, which doesn't use any location information of nodes. It is also efficient in terms of energy and end-to-end delays. In this approach, the source node evaluates the flooding zone based on the angle by using the basic formula for forwarding the packet to the sink. After evaluating the flooding zone, the angles of each node are compared and the packet is sent to the node closest to the vertical line. The proposed approach is evaluated with the help of NS-2 with AquaSim. The results show better results performance in data delivery, end-to-end delays, and energy consumption than DBR.

show abstract

Topology-Efficient Discovery: A Topology Discovery Algorithm for Underwater Acoustic Networks

Cited by 26 publications

References 35 publications

Optimal Transmission Scheduling in Small Multimodal Underwater Networks

Optimal Transmission Scheduling in Small Multimodal Underwater Networks

A Secure Communication in IoT Enabled Underwater and Wireless Sensor Network for Smart Cities

Angle Adjustment for Vertical and Diagonal Communication in Underwater Sensor

Contact Info

Product

Resources

About