scholarly journals W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1377 ◽  
Author(s):  
Rajkumar Singh Rathore ◽  
Suman Sangwan ◽  
Sukriti Mazumdar ◽  
Omprakash Kaiwartya ◽  
Kabita Adhikari ◽  
...  
Keyword(s):  
Optimization Model ◽  
Relay Node ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Relay Nodes ◽  
Node Selection ◽  
Comparative Performance ◽  
Whale Optimization ◽  
Relay Node Selection ◽  
Network Environments

Underwater sensor networks (UWSNs) have witnessed significant R&D attention in both academia and industry due to their growing application domains, such as border security, freight via sea or river, natural petroleum production and the fishing industry. Considering the deep underwater-oriented access constraints, energy-centric communication for the lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network relying on geolocation and the quality of service-centric underwater relay node selection, without paying much attention to the dynamic underwater network environments. To this end, this paper presents an adapted whale and wolf optimization-based energy and delay-centric green underwater networking framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale-centric optimization in relay node selection. Firstly, an underwater relay node optimization model is mathematically derived, focusing on underwater whale dynamics for incorporating realistic underwater characteristics in networking. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm for selecting optimal and stable relay nodes for centric underwater communication paths. Thirdly, a complete workflow of the W-GUN framework is presented with an optimization flowchart. The comparative performance evaluation attests to the benefits of the proposed framework and is compared to state-of-the-art techniques considering various metrics related to underwater network environments.

scholarly journals Cooperation between Trust and Routing Mechanisms for Relay Node Selection in Hybrid MANET-DTN

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Jan Papaj ◽  
Lubomir Dobos
Keyword(s):  
Mobile Networks ◽  
Network Performance ◽  
Ad Hoc ◽  
Main Idea ◽  
Relay Node ◽  
Critical Factor ◽  
Relay Nodes ◽  
Node Selection ◽  
Relay Node Selection ◽  
Hoc Networks

Today’s mobile networks require integration of the different networks in order to transport data between mobile devices. The main problems of all networks occur if the communication paths are disconnected for a short time. The hybrid MANET-DTN is an evolution of the Mobile Ad Hoc Networks (MANET) and Delay/Disruption Tolerant Network (DTN) and it gives the possibilities of data transport between the disconnected islands of the nodes. The key problem is how to select reliable and secure nodes to transport messages between isolated islands with limited connectivity. The selection of the relay nodes is a critical factor because the data are transported via these devices in hostile environments. Two algorithms for a relay node selection based on trust are introduced. These algorithms are activated if the connections are disrupted. The selected relay nodes transport data across the disconnected environment via store-carry-forward mode. The proposed algorithms enable selecting reliable relay nodes based on collecting routing information and contact history. We introduce the network performance analyses of these algorithms. The main idea of the analyses is studying how the algorithms can affect the behaviour of the routing and forwarding mechanisms in the simulator OPNET modeler.

scholarly journals Joint Next-Hop/Relay Selection for Distributive Multihop Cooperative Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Ahmed Alkhayyat
Keyword(s):  
Spectral Efficiency ◽  
Relay Selection ◽  
Relay Node ◽  
Cooperative Networks ◽  
Channel Fading ◽  
Relay Nodes ◽  
Effective Technique ◽  
Node Selection ◽  
Relay Node Selection ◽  
Selection For

Cooperative networks that use adjacent nodes to relay hearing data are employed as an effective technique to deal with channel fading, thereby enhancing the network performances. Next-hop and relay nodes selection schemes determine the optimal next-hop node toward the destination and relay node between the source and the optimal next-hop and/or destination. Offering joint next-hop and relay node selection in distributive multihop cooperative networks will enable the source to select the optimal next-hop node and relay node that can improve the system performance. In this paper, we propose a joint next-hop node and relay node selection (JNRS) protocol for wireless distributive multihop cooperative networks. The goal of JNRS is to reduce the spectral efficiency loss and outage probability. Analysis results show that JNRS can enhance the cooperative networks performance under general conditions compared to cooperative networks without the JNRS protocol.

scholarly journals An adaptive relay node selection algorithm based on opportunity

2017 ◽  
Vol 2017 (1) ◽  
Author(s):  
Baoju Zhang ◽  
Cuiping Zhang ◽  
Jiasong Mu ◽  
Wei Wang ◽  
Jiazu Xie
Keyword(s):  
Relay Node ◽  
Selection Algorithm ◽  
Node Selection ◽  
Relay Node Selection

scholarly journals Bayesian Compressive Sensing Based Optimized Node Selection Scheme in Underwater Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2568 ◽  
Author(s):  
Ruisong Wang ◽  
Gongliang Liu ◽  
Wenjing Kang ◽  
Bo Li ◽  
Ruofei Ma ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Compressed Sensing ◽  
Bayesian Estimation ◽  
Sensor Node ◽  
Optimization Problem ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Node Selection ◽  
Selection Scheme ◽  
Error Covariance

Information acquisition in underwater sensor networks is usually limited by energy and bandwidth. Fortunately, the received signal can be represented sparsely on some basis. Therefore, a compressed sensing method can be used to collect the information by selecting a subset of the total sensor nodes. The conventional compressed sensing scheme is to select some sensor nodes randomly. The network lifetime and the correlation of sensor nodes are not considered. Therefore, it is significant to adjust the sensor node selection scheme according to these factors for the superior performance. In this paper, an optimized sensor node selection scheme is given based on Bayesian estimation theory. The advantage of Bayesian estimation is to give the closed-form expression of posterior density function and error covariance matrix. The proposed optimization problem first aims at minimizing the mean square error (MSE) of Bayesian estimation based on a given error covariance matrix. Then, the non-convex optimization problem is transformed as a convex semidefinite programming problem by relaxing the constraints. Finally, the residual energy of each sensor node is taken into account as a constraint in the optimization problem. Simulation results demonstrate that the proposed scheme has better performance than a conventional compressed sensing scheme.

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