An Evidence Theory Based Opportunistic Routing Protocol for Underwater Acoustic Sensor Networks

Jin, Zhigang; Ji, Zhihua; Su, Yishan

doi:10.1109/access.2018.2881473

Cited by 27 publications

(18 citation statements)

References 24 publications

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“…. Thus, the position set S m is got from (6). For each of the other two-hop links in area I, we record the link as n i − n ip − n ipq where n ip is assumed to exhaust its energy.…”

Section: St C1 Tl N I N Auv < Tl Th1mentioning

confidence: 99%

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Routing Void Prediction and Repairing in AUV-Assisted Underwater Acoustic Sensor Networks

2020

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Underwater Acoustic Sensor Networks have attracted much attention due to various applications. However, routing voids lead performance degradation of UASNs in terms of network connectivity and packet delivery ratio. In this paper, we propose a Routing Void Prediction and Repairing (RVPR) algorithm in AUV-assisted UASNs, which utilizes AUVs to carry sensor nodes to repair the routing voids when foreseeing the occurrence of voids. First, the repair position is calculated based on Particle Swarm Optimization algorithm by maximizing the connectivity of the void area and minimizing the AUV moving distance. Then, the routing void prediction based on Markov chain model is proposed to ensure that the AUVs come to the repair task before the voids have already formed. Next, we design a task selecting rule to let the AUVs choose the most important and urgent repair task. Lastly, RVPR applies an energy-efficient interaction mechanism among nodes and AUVs, which guarantees reliable operation of the algorithm. In the simulation, the RVPR algorithm is applied in several different types of routing protocols (HHVBF, QELAR, EAVARP). The simulation results show that RVPR algorithm improves the protocol performances in terms of the packet delivery ratio and the link connection. More specifically, when there are 100 nodes deployed in the network, the packet delivery ratio of HHVBF, EAVAPR and QELAR employing RVPR are increased by 29.4%,79% and 65% respectively. INDEX TERMS Underwater acoustic sensor networks, routing voids, autonomous underwater vehicle.

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“…. Thus, the position set S m is got from (6). For each of the other two-hop links in area I, we record the link as n i − n ip − n ipq where n ip is assumed to exhaust its energy.…”

Section: St C1 Tl N I N Auv < Tl Th1mentioning

confidence: 99%

“…Another reason is the limited energy of nodes. In UASNs, nodes deployed underwater are difficult to be charged or replaced batteries [6]. When individual nodes are exhausted due to uneven energy consumption, there will be routing voids in the network.…”

Section: Introductionmentioning

confidence: 99%

Routing Void Prediction and Repairing in AUV-Assisted Underwater Acoustic Sensor Networks

2020

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“…BUBBLE [20] algorithm considers social position of nodes and uses node community and centrality information to forward data. In EBOR [21] the source node considers both residual energy and packet delivery probability as evidence to determine an optimal next hop in underwater acoustic sensor networks. With trust-based computation, the number of neighbors participating in forwarding is optimized to reduce energy consumption.…”

Section: • Replica Based Routingmentioning

confidence: 99%

Design of Routing Protocol for Opportunistic Network Based on Adaptive Motion

et al. 2020

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Opportunistic network takes advantage of the contact opportunities introduced by node movement for data transmission. Data is usually piggybacked during the movement of the carrier, which guarantees its independence, however, the system performance is impaired. Inspired from the motion nature of nodes, this paper proposes an adaptive motion based opportunistic routing protocol to address the problem. It develops a data forwarding priority model from the perspective of data communication and determines data transmission rules in combination with node activity range partition scheme. A differential replica transfer strategy is thus proposed to achieve a tradeoff between transmission efficiency and system overhead. A free motion degree model is constructed based on which a utility function is deduced to choose appropriate nodes for data relaying. The simulation results show that the proposed algorithm achieves higher packet delivery ratio and less transmission latency while satisfying application requirements and restraining network overhead. INDEX TERMS Data forwarding priority, free motion degree, opportunistic routing, utility function, activity range partition.

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“…About OR metric objectives, moving towards more complex networks requires the merits of the relaying nodes to be a compromise between more than one not-necessarily-congruent basic objectives. A new research direction can involve devising hybrid metrics as either a function of multiple single-objective metrics [83] [174] [175] [7] or a single multi-objective metric. Conventional wireless networks are homogeneous in type and limited in size.…”

Section: B Formulation Developmentmentioning

confidence: 99%

Opportunistic routing metrics: A timely one-stop tutorial survey

Abdollahi

Eshghi

Kelarestaghi

et al. 2020

Journal of Network and Computer Applications

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High-speed, low latency, and heterogeneity features of 5G, as the common denominator of many emerging and classic wireless applications, have put wireless technology back in the spotlight. Continuous connectivity requirement in low-power and wide-reach networks underlines the need for more efficient routing over scarce wireless resources, in multi-hp scenarios. In this regard, Opportunistic Routing (OR), which utilizes the broadcast nature of wireless media to provide transmission cooperation amongst a selected number of overhearing nodes, has become more promising than ever. Crucial to the overall network performance, which nodes to participate and where they stand on the transmission-priority hierarchy, are decided by userdefined OR metrics embedded in OR protocols. Therefore, the task of choosing or designing an appropriate OR metric is a critical one. The numerousness, proprietary notations, and the objective variousness of OR metrics can cause the interested researcher to lose insight and become overwhelmed, making the metric selection or design effort-intensive. While there are not any comprehensive OR metrics surveys in the literature, those who partially address the subject are non-exhaustive and lacking in detail. Furthermore, they offer limited insight regarding related taxonomy and future research recommendations. In this paper, starting with a custom tutorial with a new look to OR and OR metrics, we devise a new framework for OR metric design. Introducing a new taxonomy enables us to take a structured, investigative, and comparative approach to OR metrics, supported by extensive simulations. Exhaustive coverage of OR metrics, formulated in a unified notation, is presented with sufficient details. Self-explanatory, easy-to-grasp, and visual-friendly quick references are provided, which can be used independently from the rest of the paper. Finally, a new insightful framework for future research directions is developed. This tutorial-survey has been organized to benefit both generalists and OR specialists equally, and to be used not only in its entirety but selectively as well.

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An Evidence Theory Based Opportunistic Routing Protocol for Underwater Acoustic Sensor Networks

Cited by 27 publications

References 24 publications

Routing Void Prediction and Repairing in AUV-Assisted Underwater Acoustic Sensor Networks

Routing Void Prediction and Repairing in AUV-Assisted Underwater Acoustic Sensor Networks

Design of Routing Protocol for Opportunistic Network Based on Adaptive Motion

Opportunistic routing metrics: A timely one-stop tutorial survey

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