Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks

Lin, Haifeng; Dan, Bai; Gao, Demin; Liu, Yunfei

doi:10.3390/s16081201

Cited by 29 publications

(17 citation statements)

References 64 publications

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“…In this approach, the optimal path node selected using one parameter edge weight. However, network packet transmission depends upon multiple parameters, like delay [13], energy consumption [14][15][16][17][18][19][20], Bandwidth, Data Rate [21], Traffic [22][23][24], Travelling cost and Link Quality [25].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Manickavasagam¹,

Amutha²,

Priyanka³

2020

IJECE

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<span lang="EN-US">The packet forwarding node selection is one of the main constraints in the Software Defined Network (SDN). To improve the network performance, the SDN controller has to choose the shortest and optimised path between source and destination in routine and emergency packet transmission. In e-health service, information of the emergency patient has to be transferred immediately to remote hospitals or doctors by using efficient packet routing approach in Wireless Body Area Network (WBAN). In WBAN, to improve the packet transmission, the optimal packet routing policy developed based on packets priority with the support of a greedy algorithm for SDN. The SDN Controller selects the forwarding node based on node propagation delay and available bandwidth between two forwarding nodes. The mesh network topology network created for implementation, implementation results are compared with existing research works. Finally, this algorithm implemented in our institution, Software defined communication testbed laboratory (SDCTestbed Lab) with the support of 13 Zodiac-Fx (Forwarding device), 2 Raspberry-Pi3 B+ Model (host) and Arduino kit (sensor node).</span>

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Section: Literature Reviewmentioning

confidence: 99%

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Manickavasagam¹,

Amutha²,

Priyanka³

2020

IJECE

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“…Currently, mobile Ad hoc sensor network is widely utilized and obtains extensive applications for its rapid development, which results in the large quantities of problems emerged for the bad working condition [35][36][37]. For example, nodes in the network are likely to suffer from battery out of charge for the increasing power consuming rate and the link failure in the network.…”

Section: Fault Detection Algorithmmentioning

confidence: 99%

A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

Liu

Xiao

et al. 2018

Algorithms

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In an Ad hoc sensor network, nodes have characteristics of limited battery energy, self-organization and low mobility. Due to the mobility and heterogeneity of the energy consumption in the hierarchical network, the cluster head and topology are changed dynamically. Therefore, topology control and energy consumption are growing to be critical in enhancing the stability and prolonging the lifetime of the network. In order to improve the survivability of Ad hoc network effectively, this paper proposes a new algorithm named the robust, energy-efficient weighted clustering algorithm (RE2WCA). For the homogeneous of the energy consumption; the proposed clustering algorithm takes the residual energy and group mobility into consideration by restricting minimum iteration times. In addition, a distributed fault detection algorithm and cluster head backup mechanism are presented to achieve the periodic and real-time topology maintenance to enhance the robustness of the network. The network is analyzed and the simulations are performed to compare the performance of this new clustering algorithm with the similar algorithms in terms of cluster characteristics, lifetime, throughput and energy consumption of the network. The result shows that the proposed algorithm provides better performance than others.

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“…Each link of E is an ordered pair of two different vertices in V . In [ 40 ], if two nodes i and j could transmit data to each other with the power lower than the maximum transmission power, these two nodes were connected to each other. The maximum transmission range of each node depended on its maximum transmission power.…”

Section: Network Model and Data Collectionmentioning

confidence: 99%

Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks

Zhong

Liu

et al. 2017

Sensors

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In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs’ movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.

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Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks

Cited by 29 publications

References 64 publications

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks

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