Enabling Cross-technology Communication from LoRa to ZigBee in the 2.4 GHz Band

IEEE 802.15.4-based wireless sensor-actuator networks have been widely adopted by process industries in recent years because of their significant role in improving industrial efficiency and reducing operating costs. Today, industrial wireless sensor-actuator networks are becoming tremendously larger and more complex than before. However, a large, complex mesh network is hard to manage and inelastic to change once the network is deployed. In addition, flooding-based time synchronization and information dissemination introduce significant communication overhead to the network. More importantly, the deliveries of urgent and critical information such as emergency alarms suffer long delays, because those messages must go through the hop-by-hop transport. A promising solution to overcome those limitations is to enable the direct messaging from a long-range radio to an IEEE 802.15.4 radio. Then messages can be delivered to all field devices in a single-hop fashion. This article presents our study on enabling the cross-technology communication from LoRa to ZigBee using the energy emission of the LoRa radio as the carrier to deliver information. Experimental results show that our cross-technology communication approach provides reliable communication from LoRa to ZigBee with the throughput of up to 576.80 bps and the bit error rate of up to 5.23% in the 2.4 GHz band.

InPhase: Phase-based Ranging and Localization

Ranging and subsequent localization have become more and more critical in today’s factories and logistics. Tracking goods precisely enables just-in-time manufacturing processes. We present the InPhase system for ranging and localization applications. It employs narrowband 2.4 GHz IEEE 802.15.4 radio transceivers to acquire the radio channel’s phase response. In comparison, most other systems employ time-of-flight schemes with Ultra Wideband transceivers. Our software can be used with existing wireless sensor network hardware, providing ranging and localization for existing devices at no extra cost. The introduced Complex-valued Distance Estimation algorithm evaluates the phase response to compute the distance between two radio devices. We achieve high ranging accuracy and precision with a mean absolute error of 0.149 m and a standard deviation of 0.104 m. We show that our algorithm is resilient against noise and burst errors from the phase-data acquisition. Further, we present a localization algorithm based on a particle filter implementation. It achieves a mean absolute error of 0.95 m in a realistic 3D live tracking scenario.

DADC: A Novel Duty-cycling Scheme for IEEE 802.15.4 Cluster-tree-based IoT Applications

The IEEE 802.15.4 standard is one of the widely adopted specifications for realizing different applications of the Internet of Things. It defines several physical layer options and Medium Access Control (MAC) sub-layer for devices with low-power operating at low data rates. As devices implementing this standard are primarily battery-powered, minimizing their power consumption is a significant concern. Duty-cycling is one such power conserving mechanism that allows a device to schedule its active and inactive radio periods effectively, thus preventing energy drain due to idle listening. The standard specifies two parameters, beacon order and superframe order, which define the active and inactive period of a device. However, it does not specify a duty-cycling scheme to adapt these parameters for varying network conditions. Existing works in this direction are either based on superframe occupation ratio or buffer/queue length of devices. In this article, the particular limitations of both the approaches mentioned above are presented. Later, a novel duty-cycling mechanism based on MAC parameters is proposed. Also, we analyze the role of synchronization schemes in achieving efficient duty-cycles in synchronized cluster-tree network topologies. A Markov model has also been developed for the MAC protocol to estimate the delay and energy consumption during frame transmission.

Efficient energy for one node and multi-nodes of wireless body area network

<span>Compression sensing approaches have been used extensively with the idea of overcoming the limitations of traditional sampling theory and applying the concept of pressure during the sensing procedure. Great efforts have been made to develop methods that would allow data to be sampled in compressed form using a much smaller number of samples. Wireless body area networks (WBANs) have been developed by researchers through the creation of the network and the use of miniature equipment. Small structural factors, low power consumption, scalable data rates from kilobits per second to megabits per second, low cost, simple hardware deployment, and low processing power are needed to hold the wireless sensor through lightweight, implantable, and sharing communication tools wireless body area network. Thus, the proposed system provides a brief idea of the use of WBAN using IEEE 802.15.4 with compression sensing technologies. To build a health system that helps people maintain their health without going to the hospital and get more efficient energy through compression sensing, more efficient energy is obtained and thus helps the sensor battery last longer, and finally, the proposed health system will be more efficient energy, less energy-consuming, less expensive and more throughput.</span>

Design and Performance Analysis of Hybrid Energy Harvesting and WSN Application for More Life Time and High Throughput

the technology of wireless sensor-actuator networks (WSANs) is widely employed in the applications of IoT due to its wireless nature and it does not involve any wired structure. The wireless systems that are battery-driven can easily reconfigure the existing devices and sensors efficiently in the manufacturing units without employing any cable for power operation as well as for communication. The wireless sensor-actuator networks that are based on IEEE 802.15.4 consumes significantly less power. These networks are designed and built cost-effectively by considering the capacity of battery and expense so that they can be employed for many applications. The application of a typical wireless Autonomous Scheduling and Distributed Graph Routing (DDSR) has illustrated the reliability of employing its basic approaches for almost ten years and it consists of the accurate plot for routing and time-slotted channel hopping therefore ensuring accurate low-power wireless communication in the processing site. Officially declared by the controversial statements associated with the government of Greek experiences fourth industrialization. There is a huge requirement for sensor nodes link via WSAN in the industrial site. Also, reduced computational complexity is one of the drawbacks faced by the existing standards of WSAN which is caused because of their highly centralized traffic management systems and thereby significantly improves the consistency and accessibility of network operations at the expense of optimization. This research work enables the study of efficient Wireless DGR network management and also introduces an alternative for DDSR by enabling the sensor nodes to determine their data traffic routes for the transmission of data. When compared to the above two physical routing protocols, the proposed technique can drastically improve the performance of a network, throughput, and energy consumption under various aspects. Energy harvesting (EH) plays a significant role in the implementation of large IoT devices. The requirement for subsequent employment of power sources is eliminated by The efficient approach of Energy Harvesting and thereby providing a relatively close- perpetual working environment for the network. The structural concept of routing protocols that are designed for the IoT applications which are based on the wireless sensor has been transformed into "energy-harvesting-aware" from the concept of "energy-aware" because of the development in the Energy harvesting techniques. The main objective of the research work is to propose a routing protocol that is energy-harvesting-aware for the various network of IoT in case of acoustic sources of energy. A novel algorithm for routing called Autonomous Scheduling and Distributed Graph Routing (DDSR) has been developed and significantly improved by incorporating a new “energy back-off” factor. The proposed algorithm when integrated with various techniques of energy harvesting enhances the longevity of nodes, quality of service of a network under increased differential traffic, and factors influencing the accessibility of energy. The research work analyses the performance of the system for various constraints of energy harvesting. When compared to previous routing protocols the proposed algorithm achieves very good energy efficiency in the network of distributed IoT by fulfilling the requirements of QoS.

Development of Niederriter crypto-code design models on LDPC-codes

The development of mobile technologies and computing resources has expanded the range of digital services and practically outstripped the development of computer technologies. This approach ensures the use of mobile and wireless networks in almost all areas of smart technologies, provides a further synthesis of cyberspace and the mobile Internet. However, the absence of security service protocols: confidentiality and integrity, initially when they are formed in the structure of LTE technologies, provides cyber attackers with the opportunity to use mobile Internet channels to implement targeted (APT) attacks. The development and emergence of a full-scale quantum computer with Shor and Grover algorithms can lead to a sharp decrease in the level of security of cryptosystems based on symmetric and asymmetric cryptography (including cryptography on elliptic curves). In addition, modern cyber threats have signs of synergy and hybridity, and their integration with social engineering methods practically does not allow providing the required level of preventive measures (protection). The article proposes post-quantum cryptosystems based on the Niederreiter crypto-code construction on low-density parity-check codes (LDPC-codes). This approach makes it easy to integrate into wireless networks based on IEEE 802.16 and IEEE 802.15.4 standards, as well as LTE mobile technologies. At the same time, the required level of resistance to modern threats ensured.

Kinerja Jaringan Sensor Nirkabel untuk Model Smart Building

Penggunaan energi pada jaringan sensor nirkabel saat ini bisa dikatakan sangat boros, sehingga dibutuhkan sebuah metode komputasi pada teknologi Internet of Things (IoT) dengan sumber yang terbatas. Konsep penggunaan energi pada IoT perlu diawasi dan dikelola supaya terdapat peningkatan efisensi penggunaan energi sehingga dapat menekan biaya tanpa harus mengurangi kinerjanya. Dalam penelitian ini dibuatlah sebuah prototype sistem kontrol penggunaan energi pada IoT yang nantinya digunakan untuk model Smart Building dalam upaya penghematan energi. Konsep prototipe yang dibuat adalah hybrid network. Pada prototipe digunakan beberapa sensor berfungsi untuk membaca, mengontrol, dan mengirimkan informasi secara realtime dengan protokol zigbee IEEE 802.15.4 dan Wi-Fi ESP8266-01. Model ini diamati dan dianalisis konsumsi energi dan Quality of Service (QoS) transmisi pengiriman data dengan metode clustering. Kinerja pada jaringan bekerja dengan baik dilihat dari kondisi pada lingkungan indoor maupun outdoor. Pengujian konsumsi energi seluruh proses pengiriman data sensor yaitu 0.32 Watt sampai dengan 0.64 Watt dalam waktu 10 Menit, dapat dikatakan komunikasi jaringan pada pengembangan hybrid network ini mengonsumsi energi yang sangat rendah. Total durasi waktu pengujian dengan baterai 12 Volt hingga batas tegangan minimum didapatkan 70 Menit dan tegangan minimal mencapai 7 Volt.

ECTS: Enhanced Centralized TSCH Scheduling with Packet Aggregation for Industrial IoT

The Industrial Internet of Things (IoT) has gained a lot of momentum thanks to the introduction of Time Slotted Channel Hopping (TSCH) in IEEE 802.15.4. At last, we can enjoy collision-free, low-latency wireless communication in challenging environments. Nevertheless, the fixed size of time slots in TSCH provides an opportunity for further enhancements. In this paper, we propose an enhanced centralized TSCH scheduling (ECTS) algorithm with simple packet aggregation while collecting data over a tree topology. Having in mind that the payload of a sensor node is rather short, we attempt to put more than one payload in one packet. Thus, we occupy just one cell to forward them. We investigated the schedule compactness of ECTS in Matlab, and we evaluated its operation, after implementing it in Contiki-NG, using Cooja. Our results show that ECTS with packet aggregation outperforms TASA in terms of slotframe duration and imposes fairness among the nodes in terms of latency. A validation exercise using real motes confirms its successful operation in real deployments.

ECTS: Enhanced Centralized TSCH Scheduling with Packet Aggregation for Industrial IoT

The Industrial Internet of Things (IoT) has gained a lot of momentum thanks to the introduction of Time Slotted Channel Hopping (TSCH) in IEEE 802.15.4. At last, we can enjoy collision-free, low-latency wireless communication in challenging environments. Nevertheless, the fixed size of time slots in TSCH provides an opportunity for further enhancements. In this paper, we propose an enhanced centralized TSCH scheduling (ECTS) algorithm with simple packet aggregation while collecting data over a tree topology. Having in mind that the payload of a sensor node is rather short, we attempt to put more than one payload in one packet. Thus, we occupy just one cell to forward them. We investigated the schedule compactness of ECTS in Matlab, and we evaluated its operation, after implementing it in Contiki-NG, using Cooja. Our results show that ECTS with packet aggregation outperforms TASA in terms of slotframe duration and imposes fairness among the nodes in terms of latency. A validation exercise using real motes confirms its successful operation in real deployments.