Article
Computer Science, Information Systems
Theofanis Xifilidis, Kostas E. Psannis
Summary: This paper investigates the performance of Wireless Sensor Networks in environmental monitoring by examining metrics such as normalized reconstruction error and energy estimation error, considering temporal, spatial, and spatiotemporal correlations. The study thoroughly examines both independent and correlated cases for dense measurement scenarios, and proposes applications in topology and routing for fifth generation sensor networks and IoT deployment scenarios.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Pengcheng Wei, Fangcheng He
Summary: This study combines compressed sensing technology with wireless networks to expand compression algorithms spatially, improving data processing capabilities and accuracy.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Information Systems
Jinho Choi
Summary: This study investigates data-aided sensing for distributed detection in wireless sensor networks, proposing a node selection criterion based on J-divergence to ensure reliable decision-making with minimal decision delay. Simulation results confirm that the J-divergence based DAS can provide reliable decisions with fewer sensors compared to other approaches.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Xin Tian, Guoliang Wei, Jianhua Wang
Summary: This paper proposes a target localization method based on compressive sensing and Hidden semi-Markov Model (HsMM), which can solve some problems in indoor localization. The method achieves both coarse and precise positioning by combining compressive sensing and HsMM, and introduces some parameter training methods and indices to improve the localization performance.
Article
Multidisciplinary Sciences
Muhammad Talha Rahim, Awais Khan, Uman Khalid, Junaid ur Rehman, Haejoon Jung, Hyundong Shin
Summary: Quantum secure metrology protocols utilize quantum effects to achieve enhanced precision and security in probing remote systems. This paper proposes a QSM scheme that employs Bell pairs for unconditional security and offers precision scaling beyond the standard quantum limit. The comparative analysis demonstrates the superiority of the controlled encoding strategy over the parallel encoding of multi-partite entangled states in terms of parameter secrecy. Additionally, a trade-off relationship between maximum achievable precision and security under limited resource availability is identified and characterized. The dynamic scalability of the proposed protocol makes it suitable for large-scale network sensing scenarios.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Information Systems
Tongxin Zhu, Jianzhong Li, Hong Gao, Yingshu Li
Summary: A novel network called battery-free wireless sensor network (BF-WSN) is proposed to overcome the limitations of battery-powered wireless sensor networks. In BF-WSNs, battery-free sensor nodes harvest energy from the environment instead of relying on batteries, allowing them to have unlimited energy consumption. However, they still face challenges in terms of energy harvesting rates and capacities. This paper focuses on the Minimum-Latency Aggregation Scheduling problem in BF-WSNs, which is proved to be NP-hard. A Data Aggregation Scheduling algorithm is proposed to address the problem, and theoretical analysis and extensive simulations are conducted to evaluate its performance.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Engineering, Multidisciplinary
Yan Ouyang, Anfeng Liu, Naixue Xiong, Tian Wang
Summary: The paper proposes two data aggregation schemes for IoT, one based on an advance notification mechanism and the other combining advance notification mechanism and convergence routings. These schemes aim to optimize energy consumption, improve network lifetime, and reduce transmission latency in data collection.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Chemistry, Analytical
Cuicui Lv, Linchuang Yang, Xinxin Zhang, Xiangming Li, Peijin Wang, Zhenbin Du
Summary: This paper addresses the challenge of handling large data volumes and minimizing energy consumption in wireless sensor networks through the use of data compression technology and a UAV-assisted compressed data acquisition algorithm. The algorithm reduces energy consumption and experimental results show promising performance.
Article
Engineering, Electrical & Electronic
Liu Yang, Haifeng Wang, Hua Qian
Summary: Data collection is a basic application of wireless sensor networks (WSNs), and data recovery from incomplete sensing data is vital to WSNs. This paper proposes an ADMM-ResNet framework based on residual networks for spatio-temporal correlated data recovery, significantly reducing the number of iterations compared with traditional ADMM algorithm, and theoretically proving global convergence to a fixed-point.
DIGITAL SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Van-Vi Vo, Tien-Dung Nguyen, Duc-Tai Le, Moonseong Kim, Hyunseung Choo
Summary: This paper analyzes the problem of time-efficient data aggregation in multichannel duty-cycled IoT sensor networks. A novel approach called LInk-delay-aware REinforcement (LIRE) is proposed, which accelerates aggregation by leveraging active slots of sensors, reducing aggregation delay.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Tien-Dung Nguyen, Duc-Tai Le, Hyunseung Choo
Summary: This paper proposes a period-driven pipeline scheduling approach, which effectively solves the problem of data aggregation scheduling in sensor networks with high efficiency and performance. Experimental results show that compared with the latest algorithms, this approach has a shorter aggregation time and significantly improved network throughput and time utilization.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Telecommunications
Gholamreza Imanian, Mohammad Ali Pourmina, Ahmad Salahi
Summary: This study introduces a new Information-Based Deterministic Node Selection method for data aggregation in Wireless Sensor Networks. By using a specific type of shrinkage estimator, energy savings in sensor nodes can be achieved while maintaining the same accuracy in data correlations as the standard estimator.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Geethu Joseph, Pramod K. Varshney
Summary: This paper focuses on the recovery of sparse vectors in sensor networks with missing data, utilizing random sampling approaches from compressed sensing for accurate reconstruction. A sufficient condition is derived for the required number of measurements to ensure faithful recovery of sparse signals under the Bernoulli erasure channel model. The minimum required number of measurements for recovery is analyzed in relation to network parameters, random measurement matrix properties, and the recovery algorithm. Through numerical simulations, the theoretical results are validated as the minimum required number of measurements vary with different system parameters.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Shuang Zhai, Xinyu Yang, Shuzhuang Li, Xingang Guo
Summary: In this study, a data aggregation method based on game theory is proposed to address the problems of uneven load distribution and high energy consumption in wireless sensor networks. The algorithm adjusts the clusters and optimizes the number of nodes in each cluster to maximize network life. Different data collection schemes are designed based on the functions of nodes in different positions in the cluster. Moreover, a method for judging and selecting redundant nodes is proposed to improve the accuracy of cluster head fusion data.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Ebin M. Manuel, Vinod Pankajakshan, Manil T. Mohan
Summary: Conventional wireless sensor networks use sensors with continuous transmission range, but future low-power sensor networks prefer sensors with discrete transmission ranges due to certain functional advantages. The discrete transmission ranges introduce connectivity constraints in transmitting sensor data. In this study, we address the data aggregation problem in networks with sensors of discrete transmission ranges and propose a graphical framework and a polynomial-time approximation technique to solve the problem in large networks.
IEEE SENSORS JOURNAL
(2022)
