scholarly journals Efficient Data Collection using Mobile Sink Scheme in IoT

Wireless sensor networks (WSNs) have become increasingly important in the informative development of communication technology. The growth of Internet of Things (IoT) has increased the use of WSNs in association with large scale industrial applications. The integration of WSNs with IoT is the pillar for the creation of an inescapable smart environment. A huge volume of data is being generated every day by the deployment of WSNs in smart infrastructure. The collaboration is applicable to environmental surveillance, health surveillance, transportation surveillance and many more other fields. A huge quantity of data which is obtained in various formats from varied applications is called big data. The Energy efficient big data collection requires new techniques to gather sensor-based data which is widely and densely distributed in WSNs and spread over wider geographical areas. In view of the limited range of communication and low powered sensor nodes, data gathering in WSN is a tedious task. The energy hole is another considerable issue that requires attention for efficient handling in WSN. The concept of mobile sink has been widely accepted and exploited, since it is able to effectively alleviate the energy hole problem. Scheduling a mobile sink with energy efficiency is still a challenge in WSNs time constraint implementation due to the slow speed of the mobile sink. The paper addresses the above issues and the proposal contains four-phase data collection model; the first phase is the identification of network subgroups, which are formed due to a restricted range of communication in sensor nodes in a wide network, second is clustering which is addressed on each identified subgroup for reducing energy consumption, third is efficient route planning and fourth is based on data collection. The two time-sensitive route planning schemes are presented to build a set of trajectories which satisfy the deadline constraint and minimize the overall delay. We have evaluated the performance of our schemes through simulation and compared them with the generic enhanced expectation-maximization (EEM) mobility based scenario of data collection. Simulation results reveal that our proposed schemes give much better results as compared to the generic EEM mobility approach in terms of selected performance metrics such as energy consumption, delay, network lifetime and packet delivery ratio.

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Aparna Ashok Kamble ◽  
Balaji Madhavrao Patil

Abstract Wireless networks involve spatially extended independent sensor nodes, and it is associated with each other’s to preserve and identify physical and environmental conditions of the particular application. The sensor nodes batteries are equipped with restricted energy for working with an energy source. Consequently, efficient energy consumption is themain important challenge in wireless networks, and it is outfitted witharestricted power storage capacity battery. Therefore, routing protocol with energy efficiency is essential in wireless sensor network (WSN) to offer data transmission and connectivity with less energy consumption. As a result, the routing scheme is the main factor for decreasing energy consumption and the network's lifetime. The energy-aware routing model is mainly devised for WSN with high network performance when transmitting data to a sink node. Hence, in this paper, the effectiveness of energy-aware routing protocols in mobile sink-based WSNs is analyzed and justified. Some energy-aware routing systems in mobile sink-based WSN techniques, such as optimizing low-energy adaptive clustering hierarchy (LEACH) clustering approach, hybrid model using fuzzy logic, and mobile sink. The fuzzy TOPSIS-based cluster head selection (CHS) technique, mobile sink-based energy-efficient CHS model, and hybrid Harris Hawk-Salp Swarm (HH-SS) optimization approach are taken for the simulation process. Additionally, the analytical study is executed using various conditions, like simulation, cluster size, nodes, mobile sink speed, and rounds. Moreover, the performance of existing methods is evaluated using various parameters, namely alive node, residual energy, delay, and packet delivery ratio (PDR).


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jia Xu ◽  
Chuan Ping Wang ◽  
Hua Dai ◽  
Da Qiang Zhang ◽  
Jing Jie Yu

TheMobile Sinkbased data collection in wireless sensor network can reduce energy consumption efficiently and has been a new data collection paradigm. In this paper, we focus on exploring polynomial algorithm to compute the constrained trajectory of theMobile Sinkfor data collection. We first present a universal system model for designing constrained trajectory in large-scale wireless sensor networks and formulate the problem as theMaximizing Energy Reduction for Constrained Trajectory(MERC) problem. We show that the MERC problem is NP-hard and design an approximation algorithm (CTMER), which follows the greedy approach to design the movement trajectory of theMobile Sinkby maximizing theeffective average energy reduction. Through both rigid theoretical analysis and extensive simulations, we demonstrate that our algorithm achieves high computation efficiency and is superior to otherMobile Sinkbased data collection methods in aspects of energy consumption and network lifetime.


Author(s):  
Aizat Faiz Ramli ◽  
Muhammad Ikram Shabry ◽  
Mohd Azlan Abu ◽  
Hafiz Basarudin

LoRaWAN is one of the leading Low power wide area network (LPWAN) LPWAN technologies that compete for the formation of big scale Internet of Things (IoT). It uses LoRa protocol to achieve long range, low bit rate and low power communication. Large scale LoRaWAN based IoT deployments can consist of battery powered sensor nodes. Therefore, the energy consumption and efficiency of these nodes are crucial factors that can influence the lifetime of the network. However, there is no coherent experimental based research which identifies the factors that influence the LoRa energy efficiency at various nodes density. In this paper, results on measuring the packet delivery ratio, packet loss, data rate and energy consumption ratio ECR to gauge the energy efficiency of LoRa devices at various nodes density are presented. It is shown that the ECR of LoRa is inversely proportional to the nodes density and that the ECR of the network is smaller at higher traffic indicating better network energy efficiency. It is also demonstrated that at high node density, spreading factor SF of 7 and 9 can improve the energy efficiency of the network by 5 and 3 times, respectively, compare to SF 11.


Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3150 ◽  
Author(s):  
Chao Sha ◽  
Qin Liu ◽  
Si-Yi Song ◽  
Ru-Chuan Wang

With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.


Author(s):  
Yaqiong Zhang ◽  
Jiyan Lin ◽  
Hui Zhang

To the characteristics of large number of sensor nodes, wide area and unbalanced energy consumption in farmland Wireless Sensor Networks, an efficient data collection strategy (GCMS) based on grid clustering and a mobile sink is proposed. Firstly, cluster is divided based on virtual grid, and the cluster head is selected by considering node position and residual energy. Then, an optimal mobile path and residence time allocation mechanism for mobile sink are proposed. Finally, GCMS is simulated and compared with LEACH and GRDG. Simulation results show that GCMS can significantly prolong the network lifetime and increase the amount of data collection, especially suitable for large-scale farmland Wireless Sensor Networks.


2018 ◽  
Vol 7 (3.12) ◽  
pp. 531
Author(s):  
R Shanmugavalli ◽  
P Subashini

Wireless Sensor Networks (WSNs) is a collection of devices and sensor nodes connected with wireless network and communicate with one another via radio signals. Sensor in WSN is an autonomous (self-configuring) device used to sense the light, heat, motion, moisture and pressure etc that communicate with their neighbor nodes. Node placement is a technique that places the nodes effectively in the specified network environment. In WSN basically, wireless sensor network includes different topologies namely star, point-to-point, ring, bus, mesh and hybrid. In recent years, research has been carried out on different node placement strategies and produced different results based on its performance that includes power distribution and energy consumption of sensors. Energy consumption and network lifetime are considered to be the critical issues as the nodes are powered by the batteries which have finite energy reservoirs. In this paper, three different node placements namely Random, Uniform and Grid with respect to AODV (Ad hoc On-Demand Distance Vector) protocol is evaluated in order to analyze the energy factor during wireless communication. The performance metrics used to measure the analysis are Energy Consumption Average Jitter, Average End-to-End Delay, Average Throughput and Average Packet Delivery Ratio. The comparison results suggests that Grid node placement performs well in grid scenarios and shows best for specific performance metrics.  


2010 ◽  
Vol 44-47 ◽  
pp. 772-776
Author(s):  
Shi Qiang Ma ◽  
Xiao Gang Qi

Mobile sink can be used to balance energy consumption of sensor nodes in Wireless Sensor Networks (WSNs). Sink is required to inform sensors about its new location information whenever necessary. However, frequent location updates of mobile sink can lead to both rapid energy consumption of sensor nodes and increased collisions in wireless transmissions. We propose ALUPS (A New Solution with Adaptive Location Update and Propagation Scheme) for mobile sinks to resolve this problem. When a sink moves, it only needs to broadcast its location information within a local adaptive area other than among the entire network. The overhearing feature of wireless transmission is employed when the adaptive location information is transferred. Compared with LURP (Local update-based routing protocol in wireless sensor networks with mobile sinks) and SLPS (Simple Location Propagation Scheme for Mobile Sink in Wireless Sensor Networks), ALUPS performs better both in low energy consumption and success delivery ratio.


Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.


2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jian Chen ◽  
Jie Jia ◽  
Yingyou Wen ◽  
Dazhe Zhao

Energy hole is an inherent problem caused by heavier traffic loads of sensor nodes nearer the sink because of more frequent data transmission, which is strongly dependent on the topology induced by the sensor deployment. In this paper, we propose an autonomous sensor redeployment algorithm to balance energy consumption and mitigate energy hole for unattended mobile sensor networks. First, with the target area divided into several equal width coronas, we present a mathematical problem modeling sensor node layout as well as transmission pattern to maximize network coverage and reduce communication cost. And then, by calculating the optimal node density for each corona to avoid energy hole, a fully distributed movement algorithm is proposed, which can achieve an optimal distribution quickly only by pushing or pulling its one-hop neighbors. The simulation results demonstrate that our algorithm achieves a much smaller average moving distance and a much longer network lifetime than existing algorithms and can eliminate the energy hole problem effectively.


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