An IoT-Based Services Infrastructure for Utility-Scale Distributed Solar Farms

Internet of Things (IoT) provides large-scale solutions for efficient resource monitoring and management. As such, the technology has been heavily integrated into domains such as manufacturing, healthcare, agriculture, and utilities, which led to the emergence of sustainable smart cities. The success of smart cities depends on the availability of data, as well as the quality of the data management infrastructure. IoT introduced numerous new software, hardware, and networking technologies designed for efficient and low-cost data transport, storage, and processing. However, proper selection and integration of the correct technologies is crucial to ensuring a positive return on investment for such systems. This paper presents a novel end-to-end infrastructure for solar energy analysis and prediction via edge-based analytics.

Energy Consumption Delay Evaluation of NB-IoT Terminal Based on Markov Model

The energy consumption of terminal of Internet of Things has attracted much attention in the study of smart Internet of Things. How to simulate the energy consumption process of the terminal from the theoretical level, so as to analyze the energy consumption and delay of the terminal are important issues. In this paper, taking the power monitoring terminal as an example, a Markov model is established for the Narrow-Band Internet of Things (NB-IoT) terminal with periodic automatic reporting. The working state of the terminal includes PSM (Power Saving Mode), random access (RACH), data transport and receive (Tx/Rx), short eDRX (Extended Discontinuous Reception), long eDRX and terminal disconnection (ERROR). According to the proposed model, the effects of network quality, maximum possible number of RACH request times (Rmax ) and data retransmission times (N1, N2) on terminal energy consumption and delay are analyzed. The numerical results show that network quality, maximum number of random access and maximum number of data retransmission directly affect the energy consumption and service quality of the terminal. Reasonable configuration of the above indicators can effectively improve the service life of the terminal and meet the customer’s requirements for the terminal service quality under the condition of maximum power saving. The model provides a reference for energy consumption and delay optimization of NB-IoT terminal.

Exploring Coupling Relationship between Urban Connection and High-quality Development Using the Case of Lanzhou-Xining Urban Agglomeration

Based on socioeconomic statistical data, transport data, and network big data, the urban connection index (UCI) was constructed in terms of industry, transportation, information, and innovation, and the high-quality development index (HDI) was established from five aspects: innovation, coordination, green development, openness, and sharing. Taking Lanzhou-Xining urban agglomeration as a case, the urban connection intensity and high-quality development level were measured to analyze the relationship between them. From 2012 to 2018, the UCI and HDI of each city showed different degrees of growth. Note that there exist significant regional differences, with Lanzhou and Xining having the largest difference. The biggest gap among cities lies in the innovative connection intensity. Moreover, urban external connections are closely related to high-quality development, especially innovation and green development. For every 1% increase in industrial and transport connection, the HDI will increase by 0.317% and 0.159%, respectively. This study provides a methodological reference for measuring urban connectivity and provides decision support for high-quality development in China and other countries.

A Robust Data-Driven Method for Multiseasonality and Heteroscedasticity in Time Series Preprocessing

Internet of Things (IoT) is emerging, and 5G enables much more data transport from mobile and wireless sources. The data to be transmitted is too much compared to link capacity. Labelling data and transmit only useful part of the collected data or their features is a promising solution for this challenge. Abnormal data are valuable due to the need to train models and to detect anomalies when being compared to already overflowing normal data. Labelling can be done in data sources or edges to balance the load and computing between sources, edges, and centres. However, unsupervised labelling method is still a challenge preventing to implement the above solutions. Two main problems in unsupervised labelling are long-term dynamic multiseasonality and heteroscedasticity. This paper proposes a data-driven method to handle modelling and heteroscedasticity problems. The method contains the following main steps. First, raw data are preprocessed and grouped. Second, main models are built for each group. Third, models are adapted back to the original measured data to get raw residuals. Fourth, raw residuals go through deheteroscedasticity and become normalized residuals. Finally, normalized residuals are used to conduct anomaly detection. The experimental results with real-world data show that our method successfully increases receiver-operating characteristic (AUC) by about 30%.

Tension-free Dirac strings and steered magnetic charges in 3D artificial spin ice

Abstract3D nano-architectures presents a new paradigm in modern condensed matter physics with numerous applications in photonics, biomedicine, and spintronics. They are promising for the realization of 3D magnetic nano-networks for ultra-fast and low-energy data storage. Frustration in these systems can lead to magnetic charges or magnetic monopoles, which can function as mobile, binary information carriers. However, Dirac strings in 2D artificial spin ices bind magnetic charges, while 3D dipolar counterparts require cryogenic temperatures for their stability. Here, we present a micromagnetic study of a highly frustrated 3D artificial spin ice harboring tension-free Dirac strings with unbound magnetic charges at room temperature. We use micromagnetic simulations to demonstrate that the mobility threshold for magnetic charges is by 2 eV lower than their unbinding energy. By applying global magnetic fields, we steer magnetic charges in a given direction omitting unintended switchings. The introduced system paves the way toward 3D magnetic networks for data transport and storage.

Governing the Internet

This chapter describes some of the controversies around the large US influence on Internet governance, and the attempts by the International Telecommunication Union Working Group on Internet Governance to exert more influence on behalf of other national governments, not least China and Russia. Internet governance multistakeholderism is described, with its mix of governments, NGOs and private sector organizations, using technology (code), regulation, and norms, and we see how the Internet decomposes into a stack of protocols. The discussion is exemplified by ICANN’s governance of the Domain Name System (DNS), and by the difficulties of the move from IPv4 to IPv6. The dual functions of openness as both an engineering standard and a moral standard are described. Openness implies transparency, bottom-up, permissionless innovation, the end-to-end principle, efficient data transport, resilience, redundancy, interoperability, scalability, and generativity.

Tension-free Dirac strings and steered magnetic charges in 3D artificial spin ice

3D nano-architectures present a new paradigm in modern condensed matter physics with numerous applications in photonics, biomedicine, and spintronics. They are promising for the realisation of 3D magnetic nano-networks for ultra-fast and low-energy data storage. Frustration in these systems can lead to magnetic charges or magnetic monopoles, which can function as mobile, binary information carriers. However, Dirac strings in 2D artificial spin ices bind magnetic charges, while 3D dipolar counterparts require cryogenic temperatures for their stability. Here, we present a micromagnetic study of a highly-frustrated 3D artificial spin ice harboring tension-free Dirac strings with unbound magnetic charges at room temperature. We use micromagnetic simulations to demonstrate that the mobility threshold for magnetic charges is by 2 eV lower than their unbinding energy. By applying global magnetic fields, we steer magnetic charges in a given direction omitting unintended switchings. The introduced system paves a way towards 3D magnetic networks for data transport and storage.

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

In this paper, we analyze the performance of different node density of Wireless Sensor Network (WSN) operating under the IEEE Standard 802.15.4 in the beacon-enabled mode. The motivation for evaluating the beacon-enabled mode is due to its flexibility for WSN applications as compared to the non-beacon enabled mode. The analysis is based on an accurate OPNET simulation model which supports slotted Carrier Sense Multiple Access Mechanism with Collision Avoidance (CSMA/CA) mechanism and Guaranteed Time Slot (GTS). The performance of the slotted CSMA/CA sensor network is evaluated and analyzed for different network settings to understand the impact of the protocol attributes, including super-frame order (SO), beacon order (BO), data packet size and maximum back-off number. Through the simulation results, high SO provides better network throughput, otherwise results in lower average latency. We also found that the MAC overheads on small MAC Service Data Unit (MSDU) are more significant than the overheads on large MSDU. And the back-off mechanism results in longer delays when the network traffic is heavy.