Energy Efficient Data Collection in Large-Scale Internet of Things via Computation Offloading

Li, Guorui; He, Jingsha; Peng, Sancheng; Jia, Weijia; Wang, Cong; Niu, Jianwei; Yu, Shui

doi:10.1109/jiot.2018.2875244

Cited by 34 publications

(7 citation statements)

References 43 publications

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“…Then, a data acquisition tree is established to collect compressed data in a mixed manner. Finally, the data reconstruction problem is modeled as a set of sparse problems and solved by ADMM algorithm [57].…”

Section: Development Trendsmentioning

confidence: 99%

An Overview of Digital Twin Concept for Key Components of Renewable Energy Systems

2021

Int. J. Robot. Autom. Technol.

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Renewable energy (RE) is green and low-carbon energy, which can not only protect the environment, promote the technological diversification of the energy supply system, accelerate the adjustment of energy structure, but also has important significance for the sustainable development of economy. With the increasing complexity of the problems of renewable energy system asset management and ensuring the operational reliability of electric power equipment, it's necessary to establish remote, online, reliable monitoring and inspection techniques for the state evaluation of electrical equipment during the full life cycle. In order to meet these demands, the digital twin is a very suitable technology. In recent years, there are numerous scientific papers demonstrating DT's capabilities in virtual simulation, condition monitoring (CM), power optimization and fault diagnosis for RE generation systems, transmission and transformation equipment and storage systems. The majority of the research focusing on product design, maintenance of operation, condition monitoring and fault decision-making has provided many valuable contributions to academia and industrial fields. Nevertheless, all this valuable information is scattered over many literatures and it is lack of systematic generalization. In this article, different applications of DT technology in RE system are analyzed, advanced methods and theories are summarized comprehensively, and the development trend of DT technology in renewable energy system in the future is introduced.

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Section: Development Trendsmentioning

confidence: 99%

An Overview of Digital Twin Concept for Key Components of Renewable Energy Systems

2021

Int. J. Robot. Autom. Technol.

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“…Besides the above achievements about data transmission in WSN, Li et al [10], Yue et al [11] and Le and Vo [12] respectively propose data reconstruction algorithm, data fusion algorithm and data compression algorithm to improve the transmission efficiency. Shukla et al [13] and Majumdar et al [14] pay their attention to data packets in WSN.…”

Section: Related Workmentioning

confidence: 99%

“…The overview of SDSM is shown as in Hybrid transmission component solves subproblem (10) and derives the optimal value of D i (t) and D ij (t). In physical sense, this component determines the amount of data to be transmitted through transmission approach j (j ∈ M) in sensor i (i ∈ N ) at each time slot.…”

Section: A Sdsm Designmentioning

confidence: 99%

Stochastic Optimization of Data Access and Hybrid Transmission in Wireless Sensor Network

et al. 2020

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In recent years, the rapid advancements in Internet of Things boost the utilization of Wireless Sensor Network (WSN). Through WSN, a huge amount of various kinds of data can be acquired from different environments, which further facilitate us to harness the world we live. However, the error-prone and unpredictable natures of wireless links significantly impair the quality of data transmission and the utility of acquired data in WSN. Therefore, to solve this crucial problem, this paper focuses on data access control and hybrid transmission control of WSN. Based on the mathematical models of the two control operations, an intractable optimization problem is first formulated with numerous considerations, including data utility, energy consumption, network stability and data loss rate. Because of the complexity and intractability of the originally formulated problem, a Lyapunov function-based network optimization theory is utilized to transform and decompose it into three relatively simple subproblems. Stochastic Data Scheduling Mechanism (SDSM) is designed based on the solutions to the three subproblmes. The optimality and implementation of SDSM are also analyzed. Finally, the performance of SDSM is demonstrated through extensive evaluations. INDEX TERMS Wireless sensor network, data access, hybrid transmission, stochastic scheduling.

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“…In order to achieve efficient data collection, more and more people exploit Unmanned Aerial Vehicles (UAVs) to collect data from sensors, which will probably be a prospective technology for realizing the future IoT [6,7]. The heterogeneity and multi-domain nature of UAVs are indispensable in the IoT environment [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning for Data Collection of Energy-Constrained Heterogeneous UAVs

Qin

Dong

Wang

et al. 2019

Sensors

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Nowadays, Unmanned Aerial Vehicles (UAVs) have received growing popularity in the Internet-of-Things (IoT) which often deploys many sensors in a relatively wide region. Since the battery capacity is limited, sensors cannot transmit over a long distance. It is necessary for designing efficient sensor data collection mechanisms to prolong the lifetime of the IoT and enhance data collection efficiency. In this paper, we consider a UAV-enabled data collection scenario, where multiple heterogeneous UAVs with different energy constraints are employed to collect data from sensors. The value of data depends on the importance of the monitoring area of the sensor and the freshness of collected data. Our objective is to maximize the data collection utility by jointly optimizing the communication scheduling and trajectory of each UAV. The data collection utility is determined by the amount and value of the collected data. This problem is a variant of multiple knapsack problem, which is a classical NP-hard problem. First, we transform the initial problem into a submodular function maximization problem under energy constraints, and then we design a novel trajectory planning algorithm to maximize the data collection utility, while accounting for different values of data and different energy constraints of heterogeneous UAVs. Finally, under different network settings, the performance of the proposed trajectory planning algorithm is evaluated via extensive simulations. The results show that the proposed algorithm can obtain maximum data collection utility.

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Energy Efficient Data Collection in Large-Scale Internet of Things via Computation Offloading

Cited by 34 publications

References 43 publications

An Overview of Digital Twin Concept for Key Components of Renewable Energy Systems

An Overview of Digital Twin Concept for Key Components of Renewable Energy Systems

Stochastic Optimization of Data Access and Hybrid Transmission in Wireless Sensor Network

Trajectory Planning for Data Collection of Energy-Constrained Heterogeneous UAVs

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