Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive IoT Communication In LoRa Networks

We are about to enter a new world with sixth sense ability – “Network as a sensor -6G”. The driving force behind digital sensing abilities is IoT. Due to their capacity to work in high frequency, 6G devices have voracious energy demand. Hence there is a growing need to work on green solutions to support the underlying 6G network by making it more energy efficient. Low cost, low energy, and long-range communication capability make LoRa the most adopted and promising network for IoT devices. Since LoRaWAN uses ALOHA for multi-access of channels, collision management is an important task. Moreover, in massive IoT, due to the increased number of devices and their Adhoc transmissions, collision becomes and concern. Furthermore, in long-range communication, such as in forests, agriculture, and remote locations, the IoT devices need to be powered using a battery and cannot be attached to an energy grid. LoRaWAN originally has a star network wherein IoT devices communicated to a single gateway. Massive IoT causes increased traffic at a single gateway. To address Massive IoT issues of collision and gateway load handling, we have designed a reinforcement learning-based scheduling algorithm, a Deep Deterministic policy gradient algorithm with channel activity detection (CAD) to optimize the energy efficiency of LoRaWAN in cross-layer architecture in massive IoT with star topology. We also design a CAD-based simulator for evaluating any algorithms with channel sensing. We compare energy efficiency, packet delivery ratio, latency, and signal strength with existing state of art algorithms and prove that our proposed solution is efficient for massive IoT LoRaWAN with star topology

Connecting the World of Embedded Mobiles: The RIOT Approach to Ubiquitous Networking for the Internet of Things

The Internet of Things (IoT) is rapidly evolving based on low-power compliant protocol standards that extend the Internet into the embedded world. Pioneering implementations have proven it is feasible to inter-network very constrained devices, but had to rely on peculiar cross-layered designs and offer a minimalistic set of features. In the long run, however, professional use and massive deployment of IoT devices require full-featured, cleanly composed, and flexible network stacks. This paper introduces the networking architecture that turns RIOT into a powerful IoT system, to enable low-power wireless scenarios. RIOT networking offers (i) a modular architecture with generic interfaces for plugging in drivers, protocols, or entire stacks, (ii) support for multiple heterogeneous interfaces and stacks that can concurrently operate, and (iii) GNRC, its cleanly layered, recursively composed default network stack. We contribute an in-depth analysis of the communication performance and resource efficiency of RIOT, both on a micro-benchmarking level as well as by comparing IoT communication across different platforms. Our findings show that, though it is based on significantly different design trade-offs, the networking subsystem of RIOT achieves a performance equivalent to that of Contiki and TinyOS, the two operating systems which pioneered IoT software platforms

Long-Term Stable Communication in Centrally Scheduled Low-Power Wireless Networks

With the emergence of the Internet of Things (IoT), more devices are connected than ever before. Most of these communicate wirelessly, forming Wireless Sensor Networks. In recent years, there has been a shift from personal networks, like Smart Home, to industrial networks. Industrial networks monitor pipelines or handle the communication between robots in factories. These new applications form the Industrial Internet of Things (IIoT). Many industrial applications have high requirements for communication, higher than the requirements of common IoT networks. Communications must stick to hard deadlines to avoid harm, and they must be highly reliable as skipping information is not a viable option when communicating critical information. Moreover, communication has to remain reliable over longer periods of time. As many sensor locations do not offer a power source, the devices have to run on battery and thus have to be power efficient. Current systems offer solutions for some of these requirements. However, they especially lack long-term stable communication that can dynamically adapt to changes in the wireless medium.In this thesis, we study the problem of stable and reliable communication in centrally scheduled low-power wireless networks. This communication ought to be stable when it can dynamically adapt to changes in the wireless medium while keeping latency at a minimum. We design and investigate approaches to solve the problem of low to high degrees of interference in the wireless medium. We propose three solutions to overcome interference: MASTER with Sliding Windows brings dynamic numbers of retransmissions to centrally scheduled low-power wireless networks, OVERTAKE allows to skip nodes affected by interference along the path, and AUTOBAHN combines opportunistic routing and synchronous transmissions with the Time-Slotted Channel Hopping (TSCH) MAC protocol to overcome local wide-band interference with the lowest possible latency. We evaluate our approaches in detail on testbed deployments and provide open-source implementations of the protocols to enable others to build their work upon them

IoT protocols, architectures, and applications

The proliferation of embedded systems, wireless technologies, and Internet protocols have made it possible for the Internet-of-things (IoT) to bridge the gap between the physical and the virtual world and thereby enabling monitoring and control of the physical environment by data processing systems. IoT refers to the inter-networking of everyday objects that are equipped with sensing, computing, and communication capabilities. These networks can collaborate to autonomously solve a variety of tasks. Due to the very diverse set of applications and application requirements, there is no single communication technology that is able to provide cost-effective and close to optimal performance in all scenarios. In this chapter, we report on research carried out on a selected number of IoT topics: low-power wide-area networks, in particular, LoRa and narrow-band IoT (NB-IoT); IP version 6 over IEEE 802.15.4 time-slotted channel hopping (6TiSCH); vehicular antenna design, integration, and processing; security aspects for vehicular networks; energy efficiency and harvesting for IoT systems; and software-defined networking/network functions virtualization for (SDN/NFV) IoT

Performance analysis of feedback-free collision resolution NDMA protocol

To support communications of a large number of deployed devices while guaranteeing limited signaling load, low energy consumption, and high reliability, future cellular systems require efficient random access protocols. However, how to address the collision resolution at the receiver is still the main bottleneck of these protocols. The network-assisted diversity multiple access (NDMA) protocol solves the issue and attains the highest potential throughput at the cost of keeping devices active to acquire feedback and repeating transmissions until successful decoding. In contrast, another potential approach is the feedback-free NDMA (FF-NDMA) protocol, in which devices do repeat packets in a pre-defined number of consecutive time slots without waiting for feedback associated with repetitions. Here, we investigate the FF-NDMA protocol from a cellular network perspective in order to elucidate under what circumstances this scheme is more energy efficient than NDMA. We characterize analytically the FF-NDMA protocol along with the multipacket reception model and a finite Markov chain. Analytic expressions for throughput, delay, capture probability, energy, and energy efficiency are derived. Then, clues for system design are established according to the different trade-offs studied. Simulation results show that FF-NDMA is more energy efficient than classical NDMA and HARQ-NDMA at low signal-to-noise ratio (SNR) and at medium SNR when the load increases.Peer ReviewedPostprint (published version

An Energy Model Using Sleeping Algorithms for Wireless Sensor Networks under Proactive and Reactive Protocols: A Performance Evaluation

The continuous evolution of the Internet of Things (IoT) makes it possible to connect everyday objects to networks in order to monitor physical and environmental conditions, which is made possible due to wireless sensor networks (WSN) that enable the transfer of data. However, it has also brought about many challenges that need to be addressed, such as excess energy consumption. Accordingly, this paper presents and analyzes wireless network energy models using five different communication protocols: Ad Hoc On-Demand Distance Vector (AODV), Multi-Parent Hierarchical (MPH), Dynamic Source Routing (DSR), Low Energy Adaptive Clustering Hierarchy (LEACH) and Zigbee Tree Routing (ZTR). First, a series of metrics are defined to establish a comparison and determine which protocol exhibits the best energy consumption performance. Then, simulations are performed and the results are compared with real scenarios. The energy analysis is conducted with three proposed sleeping algorithms: Modified Sleeping Crown (MSC), Timer Sleeping Algorithm (TSA), and Local Energy Information (LEI). Thereafter, the proposed algorithms are compared by virtue of two widely used wireless technologies, namely Zigbee and WiFi. Indeed, the results suggest that Zigbee has a better energy performance than WiFi, but less redundancy in the topology links, and this study favors the analysis with the simulation of protocols with different nature. The tested scenario is implemented into a university campus to show a real network running

MAC Protocols for Industrial Delay-Sensitive Applications in Industry 4.0: Exploring Challenges, Protocols, and Requirements

The Industrial Internet of Things (IIoT) is expected to enable Industry 4.0 through the extensive deployment of low-power devices. However, industrial applications require, most of the time, high reliability close to 100% and low end-to-end delays. This corresponds to very challenging objectives in wireless (lossy) environments. This delay can be disastrous in time-sensitive industrial IoT deployments where immediate detection and actions impact security, safety, and machine failures. With an efficient MAC protocol, data will be provided quickly to enable the IoT to be fully effective for mission-critical applications. Efficient medium sharing is even more difficult in IIoT due to ultra-low latency, high reliability, and high quality of service (QoS) compared to best-effort for IoT. This article does not survey all existing MAC protocols for IoTs, which was already done in other works. The goal of this paper is to analyze existing MAC protocols that are more suitable for IIoT

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors