AAEERP: Advanced AUV-Aided Energy Efficient Routing Protocol for Underwater WSNs

Ilyas, Naveed; Javaid, Nadeem; Iqbal, Zafar; Imran, Muhammad; Khan, Zahoor Ali; Qasim, Umar; Shoaib, Muhammad

doi:10.1109/aina.2015.169

Cited by 11 publications

(9 citation statements)

References 17 publications

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“…Moreover for balance of sensor nodes energy consumption, researchers also introduced schemes that have the concept of mobile sensor nodes in which the neighbors of static sink is rapidly changes. The other case where sink is mobile also exists but it is not fit for delay sensitive cases [7]. The data gathering of UWSNs is increases by mobile motes or sinks hence to maximize the data collection many schemes nowadays deploying mobile sensors and/or mobile sinks but the cost of these nodes and sink deployment is high and difficult to handle, due to this many application not use it [8].…”

Section: Introductionmentioning

confidence: 99%

Depth-based Adaptive and Energy-aware (DAE) Routing Scheme for UWSNs

Rahim¹,

Ahmed²,

Hadi³

et al. 2018

EAI Endorsed Transactions on Energy Web

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A successful development of UWSN in different areas is going on where a continuous and remote examining, detection and monitoring required under the water. Ample of research papers have been available that emphasis on different parameters such as energy consumption, throughput, stability period, end-to-end delay in UWSNs. In our research, we focus on the decrease of endto-delay, increase its stability period and throughput as well as load balancing of motes. In order to attain our objective we propose a scheme called DAE with major goal to implement the technique of anycasting. Finally we compared DAE with two existing protocols DBR and AMCTD. The performance of DAE is much efficient than these schemes in various parameters. Outcomes shows that the throughput and stability period of DAE are much better than DBR as well as AMCTD and these results are achieved with minimum delay.

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Section: Introductionmentioning

confidence: 99%

Depth-based Adaptive and Energy-aware (DAE) Routing Scheme for UWSNs

Rahim¹,

Ahmed²,

Hadi³

et al. 2018

EAI Endorsed Transactions on Energy Web

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“…The earth planet covers 75% by sea and ocean [1]. UWSN provides promising solutions for discovering aqueous environment efficiently for military, emergency and commercial purposes [2]. Unmanned or Autonomous Underwater Vehicles (UUVs, AUVs), equipped with underwater sensors, are also envisioned to find application in exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions [3].…”

Section: Introductionmentioning

confidence: 99%

Review on Localization based Routing Protocols for Underwater Wireless Sensor Network

Ahmed¹,

Salleh²,

Channa³

et al. 2017

IJECE

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<span>Underwater Wireless Sensor Network (UWSN) can enable many scientific, military, safety, commercial and environmental applications. Majority of the network models has been introduced for the deployment of sensor nodes through routing schemes and methodologies along with different algorithms but still the design of routing protocol for underwater environment is a challenging issue due to distinctive characteristics of underwater medium. The majority of the issues are also needed to fulfill the appropriate approach for the underwater medium like limited bandwidth, high bit error rates, propagation delay, and 3D deployment. This paper focuses the comparative analysis of the localization based routing protocols for UWSN. This comparative analysis plays a significant attention to construct a reliable routing protocol, which provides the effectual discovery of the route between the source node and the sink node. In addition this comparative analysis also focuses the data packets forwarding mechanism, the deployment of sensor nodes and location based routing for UWSN in different conditions.</span>

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“…According to the experimental parameters of the horizontal polling architecture AAEERP [14], the compared parameters of the simulation experiment are as follows: the underwater sensor nodes and AUV are deployed in the 1500m * 2000m area. A different number of sensor nodes are deployed to demonstrate the utility of the data collection algorithm in the underwater acoustic sensor networks of different sizes.…”

Section: Simulation Experimentsmentioning

confidence: 99%

“…In order to validate the versatility and validity of the model, the model is applied to the representative AAEERP [14] horizontal polling architecture, and 4 groups of experiments are designed with its original model for comparison from sensor node energy consumption, network throughput, packet transmission rate, end-to-end delay design. a) Energy consumption: during the network monitoring, the total amount of energy consumed by all sensor nodes is mainly for data transmission and reception.…”

Section: Simulation Experimentsmentioning

confidence: 99%

“…As the two-dimensional network for the level of polling method is more mature, there are more ways to optimize this. AAEERP [14] has been improved on the basis of AEERP, and it is considered that the staying time of AUVs in each gateway should be different. Because the shortest path trees generated by different underwater gateway nodes are not the same, the more member nodes are, the more data should be collected.…”

Section: Related Workmentioning

confidence: 99%

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2017

IRATJ

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The communication process in Underwater Acoustic Sensor Networks (UASNs) is susceptible to interference, which leads to higher latency and Bit Error Ratio (BER). The Autonomous Underwater Vehicle (AUV) polling to collect data has been used to provide reliable transmission of data and extend the network lifecycle. The target events underwater are random appeared. In order to effectively capture the target event, an algorithm for the AUV polling to collect data with online prediction is proposed, namely RCAP (Reliable Collection based on AUV with Prediction). Firstly, the polling objects to AUV should be determined. The clustered network structure is established. The cluster head will be polled by the AUV to transfer the data from the cluster. Secondly, the forecast model is build. The first N rounds of data collected are the historical data. Using the historical data, the data of the N+1th round is predicted based on the regression method. Then, the N+1 to 2N rounds of data are used to calibrate the predicted values, and the prediction model is optimized. Finally, the AUV polling trajectory would be plan. All the cluster head have storage threshold. According to the data volume prediction of each cluster head, the AUV polling objects of each round can be determined to maximize the amount of data collection and to improve network efficiency. The simulation results show that the algorithm can adapt to the prediction of target events in a variety of distributions. Especially, when the target events obey the linear distribution, compared with AAEERP, RCAP has a great optimization in network energy consumption, throughput, data transmission efficiency. It increases nearly 10% throughput especially. Keywords: IntroductionThe underwater acoustic sensor networks (UASNs) is a kind of new marine measurement and control technology that combines autonomous data acquisition, data fusion and transmission applications in oceanographic data collection, water pollution monitoring, earthquake and tsunami prediction, marine navigation and underwater military surveillance, enemy target tracking and other aspects of the potential application value. So that the military and scientific research departments attach great importance to it. In recent years, China has proposed the strategic requirements of building a strong marine power, and the key technologies of the underwater acoustic sensor network are listed as the key research directions. The related researches mainly focus on the fields of MAC protocol, routing protocol, clock synchronization location, target recognition tracking and so on. However, the main problem affecting the performance of the underwater acoustic network is that the energy of the underwater nodes is limited and easy to disappear. Although the current research scholars have adopted a variety of routing protocols to minimize node energy consumption, such as the choice of the next hop node, the node between the rotation of the cluster head to balance the energy, the communication between the network nodes...

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AAEERP: Advanced AUV-Aided Energy Efficient Routing Protocol for Underwater WSNs

Cited by 11 publications

References 17 publications

Depth-based Adaptive and Energy-aware (DAE) Routing Scheme for UWSNs

Depth-based Adaptive and Energy-aware (DAE) Routing Scheme for UWSNs

Review on Localization based Routing Protocols for Underwater Wireless Sensor Network

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