scholarly journals Green Data Gathering under Delay Differentiated Services Constraint for Internet of Things

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Mingfeng Huang ◽  
Anfeng Liu ◽  
Tian Wang ◽  
Changqin Huang
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Data Gathering ◽  
Differentiated Services ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensitive Data ◽  
Delay Sensitive ◽  
Delay Tolerant

Energy-efficient data gathering techniques play a crucial role in promoting the development of smart portable devices as well as smart sensor devices based Internet of Things (IoT). For data gathering, different applications require different delay constraints; therefore, a delay Differentiated Services based Data Routing (DSDR) scheme is creatively proposed to improve the delay differentiated services constraint that is missed from previous data gathering studies. The DSDR scheme has three advantages: first, DSDR greatly reduces transmission delay by establishing energy-efficient routing paths (E2RPs). Multiple E2RPs are established in different locations of the network to forward data, and the duty cycles of nodes on E2RPs are increased to 1, so the data is forwarded by E2RPs without the existence of sleeping delay, which greatly reduces transmission latency. Secondly, DSDR intelligently chooses transmission method according to data urgency: the direct-forwarding strategy is adopted for delay-sensitive data to ensure minimum end-to-end delay, while wait-forwarding method is adopted for delay-tolerant data to perform data fusion for reducing energy consumption. Finally, DSDR make full use of the residual energy and improve the effective energy utilization. The E2RPs are built in the region with adequate residual energy and they are periodically rotated to equalize the energy consumption of the network. A comprehensive performance analysis demonstrates that the DSDR scheme has obvious advantages in improving network performance compared to previous studies: it reduces transmission latency of delay-sensitive data by 44.31%, reduces transmission latency of delay-tolerant data by 25.65%, and improves network energy utilization by 30.61%, while also guaranteeing the network lifetime is not lower than previous studies.

Advanced Energy Efficient Master/Slave Algorithm in Wireless Sensor Networks

2021 ◽  
Vol 9 (VI) ◽  
pp. 3320-3327
Author(s):  
Vageesh Kattimani
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Data Gathering ◽  
Residual Energy ◽  
Base Station ◽  
Delivery Ratio ◽  
Energy Distance ◽  
Packet Drop

The nodes in WSNs are densely deployed and lots of redundancy exists during the data gathering and sending perceived data straightforwardly to the base station, which leading to consumption of energy in nodes. Existing Clustering algorithms in WSN selects just one group head in the each cluster, where it devours more energy at Cluster head(CH) quickly and which condenses lifetime of the network incredibly. The paper proposes the Advanced and Energy Efficient Master/Slave algorithm to solve this problem. The algorithm reduces the energy consumption of each node by minimizing the direct communication of the nodes with the Base station or CHs by changing the hierarchy in WSN. The moto of the algorithm is to select one master Cluster Head and remaining slave CHs. The algorithm will select Master Cluster Head based on more residual energy, distance, and low packet drop; the remaining become Slave Cluster Heads. The simulation results prove that the Advanced and Energy Efficient Master/Slave algorithm improves throughput and packet delivery ratio(PDR) by decreasing the energy consumption.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

Wearable energy efficient fitness tracker for sports person health monitoring application

2021 ◽  
pp. 1-10
Author(s):  
Yongyue Huang ◽  
Min Hu ◽  
BalaAnand Muthu ◽  
R. Gayathri
Keyword(s):  
Energy Consumption ◽  
Data Storage ◽  
Energy Efficient ◽  
Consumer Satisfaction ◽  
Form Factors ◽  
Recognition System ◽  
Energy Utilization ◽  
Biologically Inspired Algorithms ◽  
Enhance Efficiency ◽  
Fitness Tracker

Continuous evaluation of biological and physiological metrics of sports personalities, evaluating general health status, and alerting for life-saving treatments, is supposed to enhance efficiency and healthy performance. Wearable devices with acceptable form factors compact, flexibility, minimal power consumption, etc., are needed for continuous monitoring to avoid affecting everyday operations, thereby retaining functional effectiveness and consumer satisfaction. This research focuses on the acceleration tracker for particularizing the work. Acceleration data is typically collected on battery-powered sensors for activity detection, referring to an exchange between high-precision detection and energy-efficient processing. From a feature selection perspective, the paper explores this trade-off. It suggests an Energy-Efficient Behavior Recognition System with a comprehensive energy utilization model and the Multi-objective Algorithm of Particle Swarm Optimization (EEBRS-MPSO). Therefore, using Random Forest (RF) classifiers, the model and algorithm are tested to measure the precision of identification and obtain the task’s best performance with the lowest energy consumption, among other biologically-inspired algorithms. The findings indicate that energy consumption for data storage and data processing is minimized with magnitude relative to the raw data method by choosing suitable groups of attributes. Thus, the platform allows a scalable range of feature clusters that require the authors to provide an adequate power adjustment for given target use.

scholarly journals Energy Efficient and Reliable Routing Algorithm for Wireless Sensors Networks

2020 ◽  
Vol 10 (5) ◽  
pp. 1885 ◽  
Author(s):  
Liangrui Tang ◽  
Zhilin Lu ◽  
Bing Fan
Keyword(s):  
Energy Efficient ◽  
Routing Algorithm ◽  
Evidence Theory ◽  
Fusion Rule ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Entropy Weight ◽  
Reliable Routing ◽  
Index Value

In energy-constrained wireless sensor networks, low energy utilization and unbalanced energy distribution are seriously affecting the operation of the network. Therefore, efficient and reasonable routing algorithms are needed to achieve higher Quality of Service (QoS). For the Dempster–Shafer (DS) evidence theory, it can fuse multiple attributes of sensor nodes with reasonable theoretical deduction and has low demand for prior knowledge. Based on the above, we propose an energy efficient and reliable routing algorithm based on DS evidence theory (DS-EERA). First, DS-EERA establishes three attribute indexes as the evidence under considering the neighboring nodes’ residual energy, traffic, the closeness of its path to the shortest path, etc. Then we adopt the entropy weight method to objectively determine the weight of three indexes. After establishing the basic probability assignment (BPA) function, the fusion rule of DS evidence theory is applied to fuse the BPA function of each index value to select the next hop. Finally, each node in the network transmits data through this routing strategy. Theoretical analysis and simulation results show that DS-EERA is promising, which can effectively prolong the network lifetime. Meanwhile, it can also reach a lower packet loss rate and improve the reliability of data transmission.

scholarly journals A Fast Neighbor Discovery Algorithm in WSNs

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3319 ◽  
Author(s):  
Liangxiong Wei ◽  
Weijie Sun ◽  
Haixiang Chen ◽  
Ping Yuan ◽  
Feng Yin ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Rapid Development ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Wireless Sensor ◽  
Neighbor Discovery ◽  
Low Duty Cycle ◽  
Discovery Algorithms

With the quick development of Internet of Things (IoT), one of its important supporting technologies, i.e., wireless sensor networks (WSNs), gets much more attention. Neighbor discovery is an indispensable procedure in WSNs. The existing deterministic neighbor discovery algorithms in WSNs ensure that successful discovery can be obtained within a given period of time, but the average discovery delay is long. It is difficult to meet the need for rapid discovery in mobile low duty cycle environments. In addition, with the rapid development of IoT, the node densities of many WSNs greatly increase. In such scenarios, existing neighbor discovery methods fail to satisfy the requirement in terms of discovery latency under the condition of the same energy consumption. This paper proposes a group-based fast neighbor discovery algorithm (GBFA) to address the issues. By carrying neighbor information in beacon packet, the node knows in advance some potential neighbors. It selects more energy efficient potential neighbors and proactively makes nodes wake up to verify whether these potential neighbors are true neighbors, thereby speeding up neighbor discovery, improving energy utilization efficiency and decreasing network communication load. The evaluation results indicate that, compared with other methods, GBFA decreases the average discovery latency up to 10 . 58 % at the same energy budget.

scholarly journals Novel Energy-Efficient Data Gathering Scheme Exploiting Spatial-Temporal Correlation for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ying Zhou ◽  
Lihua Yang ◽  
Longxiang Yang ◽  
Meng Ni
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Data Gathering ◽  
Temporal Correlation ◽  
Wireless Sensor ◽  
Selection Scheme ◽  
Efficient Data ◽  
Transmission Energy Consumption

A novel energy-efficient data gathering scheme that exploits spatial-temporal correlation is proposed for clustered wireless sensor networks in this paper. In the proposed method, dual prediction is used in the intracluster transmission to reduce the temporal redundancy, and hybrid compressed sensing is employed in the intercluster transmission to reduce the spatial redundancy. Moreover, an error threshold selection scheme is presented for the prediction model by optimizing the relationship between the energy consumption and the recovery accuracy, which makes the proposed method well suitable for different application environments. In addition, the transmission energy consumption is derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the existing schemes, and the sink can recover measurements with reasonable accuracy by using the proposed method.

A Location Based Energy Proficient Path Routing for Internet of Things and Its Applications

2020 ◽  
pp. 6-10
Author(s):  
Arulanantham D ◽  
Pradeepkumar G ◽  
Palanisamy C ◽  
Dineshkumar Ponnusamy
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Network Architecture ◽  
Base Station ◽  
Consumer Electronics ◽  
The Internet ◽  
Energy Efficient Routing ◽  
The Internet Of Things

The Internet of Things (IoT) is an establishment with sensors, base station, gateway, and network servers. IoT is an efficient and intellectual system that minimizes human exertion as well as right to use to real devices. This method also has an autonomous control property by which any device can control without any human collaboration. IoT-based automation has become very reasonable and it has been applied in several sectors such as manufacturing, transport, health care, consumer electronics, etc. In WSN’s smaller energy consumption sensors are expected to run independently for long phases. So much ongoing researches on implementing routing protocols for IoTbased WSNs.Energy consciousness is an essential part of IoT based WSN design issue. Minimalizing Energy consumption is well-thought-out as one of the key principles in the Expansion of routing protocols for the Internet of things. In this paper, we propose a Location based Energy efficient path routing for Internet of things and its applications its sensor position and clustering based finding the shortest path and real time implementation of Arduino based wireless sensor network architecture with the ESP8266 module. Finally, analyze the principles of Location-based energy-efficient routing and performance of QoS parameters, and then implemented automatic gas leakage detection and managing system.

Energy-Efficient Routing Protocol on Mobile Sink in Wireless Sensor Network

2013 ◽  
Vol 787 ◽  
pp. 1050-1055 ◽  
Author(s):  
Zhi Gui Lin ◽  
Hui Qi Zhang ◽  
Xu Yang Wang ◽  
Fang Qin Yao ◽  
Zhen Xing Chen
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Model Simulation ◽  
Cluster Head ◽  
Mobile Sink ◽  
High Energy ◽  
Residual Energy ◽  
Energy Efficient Routing ◽  
Simulation Results

To the disadvantages, such as high energy consumption and the energy consumption imbalance, we proposed an energy-efficient routing protocol on mobile sink (MSEERP) in this paper. In the MSEERP, the network is divided into several square virtual grids based on GAF, each grid is called a cluster, and the cluster head election method of GAF is improved. In addition, the MSEERP introduces a mobile sink in the network, the sink radios in limited number of hops and uses control moving strategy, namely the sink does not collect the information until it moves to a cluster with highest residual energy. We applied NS2 to evaluate its performance and analyze the simulation results by the energy model. Simulation results show that the MSEERP balances the energy consumption of the network, saves nodes energy and extends the network lifetime.

scholarly journals Power Aware Chain Routing Protocol for Data Gathering in Sensor Networks

2005 ◽  
Vol 1 (2) ◽  
pp. 253-267 ◽  
Author(s):  
Minh-Long Pham ◽  
Daeyoung Kim ◽  
Seong-Eun Yoo ◽  
Yoonmee Doh
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Data Gathering ◽  
Minimum Cost ◽  
Cost Calculation ◽  
Transmission Power ◽  
Global Knowledge ◽  
Transmission Cost

To prolong the network lifetime, we propose an energy efficient chain-based routing scheme and a distributed algorithm for constructing the routing chain based on the minimum cost tree. The chain construction algorithm calculates the transmission cost based on optimal transmission power. Therefore, it does not require global knowledge of location information of notes and provides more accurate communication cost calculation among nodes under different practical deployment environments. The proposed power aware mechanism for leader node election in the chain ensures more uniform energy consumption among nodes. The simulation shows the new scheme provides more uniform energy consumption among nodes and better active network lifetime in different network settings as compared to previous chain-based protocols.

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