An adaptive routing protocol in underwater sparse acoustic sensor networks

Yu, Haitao; Yao, Nianmin; Liu, Jun

doi:10.1016/j.adhoc.2014.09.016

Cited by 139 publications

(103 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This enhancement is applicable in all dense networks with different routing protocols. For future work, we can create an adaptive version of EELD-DBR by use of component adaptation concept [7], i.e. a protocol that in it, each router node can select a specific scalable parameter (α) for itself; this value can be different from other each node's scalable parameter.…”

Section: Discussionmentioning

confidence: 99%

A Solution for Scalable Routing in Depth Divisions-Based DUSNs via Adding a Scalable Parameter to Control Depth Clusters: Creating an Energy Efficient and Low Delay NI-Independent Communication Protocol

Khosravi¹,

Salari²,

Rostami³

2016

JCC

View full text Add to dashboard Cite

Due to effectiveness of network layer on general performance of networks, designing routing protocols is very important for lifetime and traffic efficiency in wireless sensor networks. So in this paper, we are going to represent an efficient and scalable version of depth-based routing (DBR) protocol that is limited by depth divisions-policy. In fact the new version is a network information independent routing protocol for acoustic communications. Proposed method by use of depth clustering is able to reduce consumed energy and end-to-end delay in dense underwater sensor networks (DUSNs) and this issue is proved by simulation.

show abstract

Section: Discussionmentioning

confidence: 99%

A Solution for Scalable Routing in Depth Divisions-Based DUSNs via Adding a Scalable Parameter to Control Depth Clusters: Creating an Energy Efficient and Low Delay NI-Independent Communication Protocol

Khosravi¹,

Salari²,

Rostami³

2016

JCC

View full text Add to dashboard Cite

show abstract

“…MI ¼ ; (26) in which MI is the mutual information used for comparing a pair of clusters. Sn i a is the number of sensor nodes in cluster Ca, Sn j b is the number of sensor nodes in cluster Cb, and n is a constant set to 1.…”

Section: Evolutionary Cluster-head Selection Algorithm (Chsa)mentioning

confidence: 99%

LRP: Link quality‐aware queue‐based spectral clustering routing protocol for underwater acoustic sensor networks

Faheem

Tuna

Güngör

2016

Int J Communication

View full text Add to dashboard Cite

Summary Recently, underwater acoustic sensor networks (UASNs) have been considered as a promising approach for monitoring and exploring the oceans in lieu of traditional underwater wireline instruments. As a result, a broad range of applications exists ranging from oil industry to aquaculture and includes oceanographic data collection, disaster prevention, offshore exploration, assisted navigation, tactical surveillance, and pollution monitoring. However, the unique characteristics of underwater acoustic communication channels, such as high bit error rate, limited bandwidth, and variable delay, lead to a large number of packet drops, low throughput, and significant waste of energy because of packets retransmission in these applications. Hence, designing an efficient and reliable data communication protocol between sensor nodes and the sink is crucial for successful data transmission in underwater applications. Accordingly, this paper is intended to introduce a novel nature‐inspired evolutionary link quality‐aware queue‐based spectral clustering routing protocol for UASN‐based underwater applications. Because of its distributed nature, link quality‐aware queue‐based spectral clustering routing protocol successfully distributes network data traffic load evenly in harsh underwater environments and avoids hotspot problems that occur near the sink. In addition, because of its double check mechanism for signal to noise ratio and Euclidean distance, it adopts opportunistically and provides reliable dynamic cluster‐based routing architecture in the entire network. To sum up, the proposed approach successfully finds the best forwarding relay node for data transmission and avoids path loops and packet losses in both sparse and densely deployed UASNs. Our experimental results obtained in a set of extensive simulation studies verify that the proposed protocol performs better than the existing routing protocols in terms of data delivery ratio, overall network throughput, end‐to‐end delay, and energy efficiency.

show abstract

“…Radio signal is generally utilized as remote transmission media as a part of the physical sensor system, yet in submerged remote sensor systems, radio signs can't function admirably because of fast weakening, bringing about short propagation delay [25]. The submerged sensor systems send the utilization of acoustic signs in light of the fact that these signs have high propagation delays and require low transmission capacity.…”

Section: Figure 3 Architecture Of the Mobile Uwsn [25]mentioning

confidence: 99%

Parametric Comparative Analysis of Underwater Wireless Sensor Networks Routing Protocols

Garg¹,

Waraich²

2015

IJCA

View full text Add to dashboard Cite

The underwater wireless sensor networks have found many applications in today's world as they are used in medical applications, sea exploration, military applications and many more. With the advancement in the underwater wireless sensor networks technology, new research challenges are found that are to be resolved like how efficient routing can be done without sacrificing energy consumption of the sensor nodes, how the deployment of the sensor nodes should be done and so on. Due to the movement of sensor nodes with the water currents, the deployment and routing becomes a difficult task. In this paper, various routing protocols like Information Carrying routing protocol, Depth Based routing protocol, Constraint Based Depth based routing protocol, Directional flooding routing protocol are discussed and a comparative analysis of these routing protocols on the basis of various parameters like localization information, network topology, and use of control packets, network architecture used is presented.

show abstract

An adaptive routing protocol in underwater sparse acoustic sensor networks

Cited by 139 publications

References 26 publications

A Solution for Scalable Routing in Depth Divisions-Based DUSNs via Adding a Scalable Parameter to Control Depth Clusters: Creating an Energy Efficient and Low Delay NI-Independent Communication Protocol

A Solution for Scalable Routing in Depth Divisions-Based DUSNs via Adding a Scalable Parameter to Control Depth Clusters: Creating an Energy Efficient and Low Delay NI-Independent Communication Protocol

LRP: Link quality‐aware queue‐based spectral clustering routing protocol for underwater acoustic sensor networks

Parametric Comparative Analysis of Underwater Wireless Sensor Networks Routing Protocols

Contact Info

Product

Resources

About