scholarly journals A Multi-Objective Mathematical Model, a Markov Chains and a Deep Learning approaches for mobility prediction to reduce Energy Consumption and Delay in Mobile Wireless Sensor Networks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
German A. Montoya ◽  
Carlos Lozano-Garzon ◽  
Yezid Donoso
Keyword(s):  
Mathematical Model ◽  
Wireless Sensor Networks ◽  
Deep Learning ◽  
Energy Consumption ◽  
Wireless Sensor ◽  
Mobility Prediction ◽  
Learning Approaches ◽  
Mobile Wireless ◽  
Reduce Energy Consumption ◽  
Mobile Wireless Sensor

An Efficient Sleeping Scheduling for Saving Energy Consumption in Wireless Sensor Networks

2012 ◽  
Vol 229-231 ◽  
pp. 1261-1264
Author(s):  
Li Peng Lu ◽  
Ming Yue Zhai ◽  
Ying Liu ◽  
Xiao Da Sun
Keyword(s):  
Mathematical Model ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Reduce Energy Consumption ◽  
Battery Energy ◽  
Sleep Mechanism

Wireless Sensor Networks (WSNs) has been widely recognized as a promising technology in smart grid. However, sensor nodes have limited battery energy. So, we present a mathematical model which is to reduce energy consumption and prolong the lifetime of WSNs. Because of the high density of sensor nodes deployment, a sleep mechanism is proposed to make all sensor nodes work by turns while all service requests can be satisfied. And then, an Improved Sleep Mechanism is put forward to remove redundant active nodes. The simulation result indicates that energy consumption adopting the ISNSS is lower than or equal to the energy consumption adopting SNSS. The SNSS and ISNSS all can save some energy of WSNs to some extent and when the redundant active nodes are removed, the network energy consumption is further reduced based on the SNSS.

Genetic optimization of hybrid clustering algorithm in mobile wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (4) ◽  
pp. 526-533 ◽  
Author(s):  
Sangeetha M. ◽  
Sabari A.
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Content Type ◽  
Mobile Wireless Sensor

Purpose This paper aims to provide a prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). MWSNs have characteristics of dynamic topology due to the factors such as energy consumption and node movement that lead to create a problem in lifetime of the sensor network. Node clustering in wireless sensor networks (WSNs) helps in extending the network life time by reducing the nodes’ communication energy and balancing their remaining energy. It is necessary to have an effective clustering algorithm for adapting the topology changes and improve the network lifetime. Design/methodology/approach This work consists of two centralized dynamic genetic algorithm-constructed algorithms for achieving the objective in MWSNs. The first algorithm is based on improved Unequal Clustering-Genetic Algorithm, and the second algorithm is Hybrid K-means Clustering-Genetic Algorithm. Findings Simulation results show that improved genetic centralized clustering algorithm helps to find the good cluster configuration and number of cluster heads to limit the node energy consumption and enhance network lifetime. Research limitations/implications In this work, each node transmits and receives packets at the same energy level throughout the solution. The proposed approach was implemented in centralized clustering only. Practical implications The main reason for the research efforts and rapid development of MWSNs occupies a broad range of circumstances in military operations. Social implications The research highly gains impacts toward mobile-based applications. Originality/value A new fitness function is proposed to improve the network lifetime, energy consumption and packet transmissions of MWSNs.

Coverage Maximization and Energy Conservation for Mobile Wireless Sensor Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 43-63 ◽  
Author(s):  
Nor Azlina Ab. Aziz ◽  
Ammar W. Mohemmed ◽  
Mohamad Yusoff Alias ◽  
Kamarulzaman Ab. Aziz ◽  
Syabeela Syahali
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Conservation ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
Coverage Maximization ◽  
Mobile Wireless Sensor

WSN is a group of low-cost, low-power, multifunctional and small size wireless sensor nodes that work together to sense the environment, perform simple data processing and communicate wirelessly over a short distance. Mobile wireless sensor networks (WSN) coverage can be enhanced by moving the sensors so that a better arrangement is achieved. However, movement is a high energy consumption task. To maximize coverage the sensors need to be placed not too close to each other so that the sensing capability of the network is fully utilised; however they must not be located too far from each other to avoid coverage holes. It is desired to achieve optimal coverage and at the same time not to relax the mobility energy consumption issue due to the fact that sensors have a limited energy supply. This research is interested in solving the coverage and energy conservation issues of mobile wireless sensors using PSO. In this paper the WSN coverage maximization problem is considered by taking into account the energy spent for sensor repositioning. Thus there are two objectives to be optimized, namely maximizing the coverage and conserving the energy. The two objectives are tackled one by one, starting with the coverage maximization followed by energy conservation. Hence a two-phase PSO approach is proposed. The results show that the proposed algorithm successfully achieves its objectives to reduce the energy usage while at the same time improve the coverage. The energy usage is reduced by cutting down the maximum distance moved.

scholarly journals Energy Efficient Cross-Layer Transmission Model for Mobile Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xin Yang ◽  
Ling Wang ◽  
Jian Xie
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Transmission Model ◽  
Cross Layer ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
Mobile Wireless Sensor

The performance of mobile wireless sensor networks (MWSN) witnessed a significant improvement in recent years, such as throughput, transmission delay, and collision detection. However, MWSN still suffers from high energy consumption, since most of the sensors or users in MWSN are based on passive devices. In order to remedy this problem, in this paper we present a Cross-layer Energy Efficiency (CEE) model for MWSN. CEE is a cross-layer model which contains three layers. It utilizes nodes location information in network layer, medium access control (MAC) protocol in MAC layer (sublayer of data link layer), and full-duplex interfaces in physical (PHY) layer. The CEE model offers a number of advantages in regard to energy efficiency, throughput improvement, low delay, and power control compared to existing models. According to the performance evaluation, the proposed transmission model effectively reduces energy consumption and improves other transmission performances. Also, it has been proved that the proposed model can be used in practical MWSN as Internet of things (IoT).

scholarly journals Clustering Routing Protocol for Mobile Wireless Sensor Networks Based on Dynamic Network Partition

2018 ◽  
Vol 14 (11) ◽  
pp. 103
Author(s):  
Luzhou Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Dynamic Network ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Leach Protocol ◽  
Mobile Wireless Sensor

<p class="0abstract"><span lang="EN-US">To prolong the network life and improve the network performance, a new clustering routing protocol which uses dynamic network to divide and consider the residual energy of sensor nodes is proposed. The design and simulation of the clustering scheme for mobile wireless sensor networks are also studied. The results show that the protocol controls the number of cluster heads by region division of the network and balances its distribution in wireless sensor networks according to the latest location of the sink node. At the same time, the residual energy of nodes is considered to balance the energy consumption of the network when the cluster head is elected. The protocol effectively solves the problem of uneven distribution of cluster heads in time and space and energy consumption of each node in the LEACH protocol. Compared with the LEACH protocol, M-LEACH effectively prolongs the network life. From this, it is seen that the application of M-LEACH protocol in mobile wireless sensor network clustering routing is effective.</span></p>

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