A Cluster Sleep-Wake Scheduling Algorithm Based on 3D Topology Control in Underwater Sensor Networks

Zhang, Wenbo; Wang, Jing; Han, Guangjie; Zhang, Xinyue; Feng, Yongxin

doi:10.3390/s19010156

Cited by 28 publications

(22 citation statements)

References 30 publications

(29 reference statements)

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“…They engaged multiple mobile sinks for the data collection from the network partitions. In [41], authors have segmented the network space into 3D small cubes to form clusters. The size of the cube and cluster dimensions are calculated based on the qualityof-service and energy metrics.…”

Section: B Network Division Techniquesmentioning

confidence: 99%

Anchor Nodes Assisted Cluster-Based Routing Protocol for Reliable Data Transfer in Underwater Wireless Sensor Networks

et al. 2021

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Reliable data transfer seems a quite challenging task in Underwater Wireless Sensor Networks (UWSN) in comparison with Terrestrial Wireless Sensor Networks due to the peculiar attributes of UWSN communication. However, the reliable data transmission in UWSN is very limited. Yet, there is a way to achieve reliable data transfer metrics through the design of routing protocols by considering the exceptional features of UWSN communications. With this aim, we propose two schemes with multiple sinks-based network architecture: Anchor Nodes assisted Cluster-based Routing Protocol (ANCRP) to achieve reliable data transfer metrics and Void Handling technique in ANCRP (VH-ANCRP) to cope with the local maximum nodes. For which, the network space is divided into small cubes to form clusters. Then, each cube is assigned with an anchor node as a cluster head (CH). All cluster heads are supposed to be anchored at the centroid of a cube via a string, while source nodes are randomly distributed. In ANCRP, the source nodes are liable to send the sensed data to their designated CH. The CH transmits the sensed data to the next-hop CH and continues this procedure till the successful delivery of the data packets at the surface sinks. In VH-ANCRP, a void handling technique of making the ad-hoc CH is used by the void nodes to reconnect with the network operations. We perform extensive simulations in NS3 to validate our schemes. The simulation outcomes expel that both proposed schemes have improved the network performance when compared with the baseline schemes. INDEX TERMS Underwater wireless sensor networks, reliable data transfer, routing protocol, anchor nodes, clustering technique, void handling. I. INTRODUCTION Currently, Underwater Wireless Sensor Networks (UWSNs) are gaining pivotal considerations in both industrial and academia sector because of their wide and comprehensive implementation areas, such as resource exploration, navigation assisting, military surveillance, calamity preventions, etc. [1]. The underwater WSNs also assist in finding the unexplored underwater resources and aquatic data collection with the help of different computational intelligence approaches [2]. The underwater wireless sensor nodes are supposed to be deployed sparsely from surface-layer to seabedlayer for fetching the data from the underwater harsh environments by using an acoustic modem [3], [4]. Underwater communication through optical signals is not feasible due to absorption loss and rapid attenuation. Thus, underwater communication is carried out in acoustic signals [5]. The

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Section: B Network Division Techniquesmentioning

confidence: 99%

Anchor Nodes Assisted Cluster-Based Routing Protocol for Reliable Data Transfer in Underwater Wireless Sensor Networks

et al. 2021

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“…During the election of two types of heterogeneous cluster heads according to eqs. (2) and (3), a phenomenon in which one node becomes the cluster head of two types of heterogeneous clusters at the same time may occur, and it is allowed in DCHUC. However, in order to avoid data transmission between two heterogeneous cluster heads in one cluster, DCHUC does not allow a cluster head of one type to become a member node of the other type.…”

Section: ) Clustering Of Ordinary Nodesmentioning

confidence: 99%

QSDN-WISE: A New QoS-Based Routing Protocol for Software-Defined Wireless Sensor Networks

et al. 2019

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Today, a wide variety of applications with different requirements are rapidly developed in industrial wireless sensor networks, and providing the Quality of Service (QoS) for this kind of communication network is inevitable. It is difficult to solve the problems of poor adaptability and difficulty in the implementation of the QoS-based network configuration and management in traditional network architecture. We present a hierarchical software-defined network architecture for wireless sensor networks, which makes the complex network management possible and the system more adaptable. Furthermore, we propose a QoS-based routing protocol, called QSDN-WISE, which consists of a clustering algorithm, a routing algorithm, and local network maintenance. A double-cluster head-based uneven clustering algorithm, called DCHUC, avoids the energy hole phenomenon and reduces the workload of a single cluster head. The centralized QSDN-WISE routing algorithm constructs two heterogeneous forwarding paths for nodes, which meets the requirements for different data levels. Local network maintenance reduces the number of control messages in the network. The simulation results indicate that the QSDN-WISE can provide the QoS support for data with different requirements, balance the network energy consumption, and prolong the network's lifetime. INDEX TERMS Wireless sensor networks, QSDN-WISE, DCHUC, clustering algorithm, energy hole, routing algorithm, network lifetime.

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“…Pressure routing can achieve high delivery ratios and low end-to-end delay, but it consumes more energy because of the use of opportunistic routing and the repeated transmission of the copies of same packets. The cluster sleep-wake scheduling algorithm in UWSNs was proposed by Zhang et al in [30], which shows the rotating temporary control nodes that control the sleep-wake scheduling, thus minimizing the energy dissipation. The energy optimization clustering algorithm (EOCA) was put forward by Yu et al in [11], where the number of neighboring nodes, the remaining energy of nodes, the motion of nodes, and the distance factor are taken into account.…”

Section: Introductionmentioning

confidence: 99%

A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks

Xiao

Huang

2020

Algorithms

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Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UWSNs), this paper proposes an energy-efficient clustering routing algorithm based on an improved ant colony optimization (ACO) algorithm. In clustering routing algorithms, the network is divided into many clusters, and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs). This paper optimizes the CHN selection based on the residual energy of nodes and the distance factor. The selected CHN gathers data sent by the CMNs and transmits them to the sink node by multiple hops. Optimal multi-hop paths from the CHNs to the SN are found by an improved ACO algorithm. This paper presents the ACO algorithm through the improvement of the heuristic information, the evaporation parameter for the pheromone update mechanism, and the ant searching scope. Simulation results indicate the high effectiveness and efficiency of the proposed algorithm in reducing the energy consumption, prolonging the network lifetime, and decreasing the packet loss ratio.

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A Cluster Sleep-Wake Scheduling Algorithm Based on 3D Topology Control in Underwater Sensor Networks

Cited by 28 publications

References 30 publications

Anchor Nodes Assisted Cluster-Based Routing Protocol for Reliable Data Transfer in Underwater Wireless Sensor Networks

Anchor Nodes Assisted Cluster-Based Routing Protocol for Reliable Data Transfer in Underwater Wireless Sensor Networks

QSDN-WISE: A New QoS-Based Routing Protocol for Software-Defined Wireless Sensor Networks

A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks

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