Energy balanced data gathering approaches in wireless sensor networks using mixed-hop communication

Kulshrestha, Jagrati; Mishra, Manas Kumar

doi:10.1007/s00607-018-0597-6

Cited by 16 publications

(9 citation statements)

References 26 publications

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“…In this case, computer-assisted teaching systems supported by multimedia technology and network technology are developing rapidly. This teaching method aims to combine traditional classroom teaching with modern information technology, and implement the complementary advantages of online courses and traditional classrooms [25]. For students from different starting points, strengthen the cultivation of independent learning ability, pay attention to personality differences, and develop students' potential.…”

Section: Methodsmentioning

confidence: 99%

“…With Teaching evaluation is not only an activity to judge the value of teaching process and teaching results and serve for teaching decision-making, but also the process of studying the teaching of teachers and the learning of students. For example, Peng-Kyat Pek and Kim-Lang Pooh use Bayesian networks to build student models, and perform probabilistic inferences based on the evidence that student's feedback to the system during the learning process, predict the next behavior of students, and choose the most appropriate Teaching content [6]. Dietrich Albert and Cord Hackneyed obtained the structural similarity between hypertext and knowledge space through the analysis of knowledge space theory, and modeled knowledge [7].…”

Section: Introductionmentioning

confidence: 99%

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Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

Zhang

Huang

2020

Preprint

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With the popularization of computers and various mobile intelligent terminals, intelligent teaching systems based on learners are becoming more and more popular among learners. The above phenomenon has greatly affected and changed the current teaching quality diagnosis methods and models. However, the author found through investigation that the current intelligent teaching quality diagnosis still has different degrees of deficiencies in the design and implementation. In response to the above problems, this paper proposes a teaching quality intelligent diagnosis model based on the combination of wireless sensor networks and fuzzy comprehensive evaluation algorithms. First of all, this article is based on the wireless sensor network to link various levels of intelligent teaching systems, and constructs the information transmission structure of the teaching intelligent diagnosis system. Secondly, this article uses fuzzy comprehensive evaluation and convolutional neural network algorithms to evaluate and excavate intelligent teaching information. Finally, the model successfully passed the simulation test and simulation application, which can provide intelligent diagnosis of teaching quality for modern intelligent teaching system.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

Zhang

Huang

2020

Preprint

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“…From the perspective of data transmission, the overall energy loss of the UPIoT can be effectively suppressed by selecting the optimal route from the original nodes to the target node [12]. From the angle of power control of each sensor node, the energy consumption of each node can be reduced if its transmitting and receiving powers are determined based on the size of the local cluster and the distance to its adjacent nodes [13].…”

Section: Overviewmentioning

confidence: 99%

Energy Efficiency Management and Route Optimization for Wireless Sensor Network under the Ubiquitous Power Internet of Things

Zhang¹

2019

EJEE

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The traditional routing algorithms for data transmission in the wireless sensor network (WSN) under the ubiquitous power Internet of Things (UPIoT) are faced with two common defects, namely, the imbalance between the nodes in energy consumption and the premature death of many nodes. To solve the problems, this paper puts forward a method to manage the energy efficiency and optimize the route for the WSN under the UPIoT. Firstly, an energy consumption model of network nodes was established after analyzing the causes of node energy loss, which effectively reduces the energy consumed by each node during the clustering process. Next, the author designed a way to compute node quality, and selected cluster heads by node quality, such that the energy consumption is balanced across the WSN. On this basis, a node clustering routing algorithm was presented to dynamically adjust the communication radii of cluster heads and general nodes, thus extending the lifecycle of the WSN under the UPIoT. The simulation results show that our method outperformed the traditional clustering routing algorithm in controlling energy loss of nodes and enhancing network reliability and stability. The research findings provide a valuable reference for the efficient data transmission of the WSN under the UPIoT.

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“…As identical sensors are placed to capture identical physical variables, there is a possibility of large data redundancy and, therefore, large savings can be achieved if compression techniques are applied. In fact, Data Gathering is combined with Compressed Sensing (CS) [ 5 , 6 ] to produce Compressive Data Gathering (CDG) [ 7 , 8 , 9 ]. This hybrid scheme interconnects the well-established foundations of CS, based on the representation of a sparse dimensional signal according to fewer projections of the same signal, and DG to collect data efficiently.…”

Section: Introductionmentioning

confidence: 99%

D2R-TED: Data—Domain Reduction Model for Threshold-Based Event Detection in Sensor Networks

León‐García

Muñoz

Olivares

2018

Sensors

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The reduction of sensor network traffic has become a scientific challenge. Different compression techniques are applied for this purpose, offering general solutions which try to minimize the loss of information. Here, a new proposal for traffic reduction by redefining the domains of the sensor data is presented. A configurable data reduction model is proposed focused on periodic duty–cycled sensor networks with events triggered by threshold. The loss of information produced by the model is analyzed in this paper in the context of event detection, an unusual approach leading to a set of specific metrics that enable the evaluation of the model in terms of traffic savings, precision, and recall. Different model configurations are tested with two experimental cases, whose input data are extracted from an extensive set of real data. In particular, two new versions of Send–on–Delta (SoD) and Predictive Sampling (PS) have been designed and implemented in the proposed data–domain reduction for threshold–based event detection (D2R-TED) model. The obtained results illustrate the potential usefulness of analyzing different model configurations to obtain a cost–benefit curve, in terms of traffic savings and quality of the response. Experiments show an average reduction of 76% of network packages with an error of less than 1%. In addition, experiments show that the methods designed under the proposed D2R–TED model outperform the original event–triggered SoD and PS methods by 10% and 16% of the traffic savings, respectively. This model is useful to avoid network bottlenecks by applying the optimal configuration in each situation.

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Energy balanced data gathering approaches in wireless sensor networks using mixed-hop communication

Cited by 16 publications

References 26 publications

Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

Design of Intelligent Diagnosis System for Teaching Quality Based on Wireless Sensor Network and Data Mining

Energy Efficiency Management and Route Optimization for Wireless Sensor Network under the Ubiquitous Power Internet of Things

D2R-TED: Data—Domain Reduction Model for Threshold-Based Event Detection in Sensor Networks

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