The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey toward the fifth generation of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of multi-access edge computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC’s ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultralow latency and high quality of service due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

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Survey on Multi-Access Edge Computing for Internet of Things Realization

This paper presents PLoRa, an ambient backscatter design that enables long-range wireless connectivity for batteryless IoT devices. PLoRa takes ambient LoRa transmissions as the excitation signals, conveys data by modulating an excitation signal into a new standard LoRa "chirp" signal, and shifts this new signal to a different LoRa channel to be received at a gateway faraway. PLoRa achieves this by a holistic RF front-end hardware and software design, including a low-power packet detection circuit, a blind chirp modulation algorithm and a low-power energy management circuit. To form a complete ambient LoRa backscatter network, we integrate a light-weight backscatter signal decoding algorithm with a MAC-layer protocol that work together to make coexistence of PLoRa tags and active LoRa nodes possible in the network. We prototype PLoRa on a four-layer printed circuit board, and test it in various outdoor and indoor environments. Our experimental results demonstrate that our prototype PCB PLoRa tag can backscatter an ambient LoRa transmission sent from a nearby LoRa node (20 cm away) to a gateway up to 1.1 km away, and deliver 284 bytes data every 24 minutes indoors, or every 17 minutes outdoors. We also simulate a 28-nm low-power FPGA based prototype whose digital baseband processor achieves 220 μW power consumption.

https://dl.acm.org/doi/pdf/10.1145/3230543.3230567

PLoRa: a passive long-range data network from ambient LoRa transmissions

Wireless networks have been widely deployed for many Internet-of-Things (IoT) applications, like smart cities and precision agriculture. Low Power Wide Area Networking (LPWAN) is an emerging IoT networking paradigm to meet three key requirements of IoT applications, i.e., low cost, large scale deployment and high energy efficiency. Among all available LPWAN technologies, LoRa networking has attracted much attention from both academia and industry, since it specifies an open standard and allows us to build autonomous LPWAN networks without any third-party infrastructure. Many LoRa networks have been developed recently, e.g., managing solar plants in Carson City, Nevada, USA and power monitoring in Lyon and Grenoble, France. However, there are still many research challenges to develop practical LoRa networks, e.g., link coordination, resource allocation, reliable transmissions and security. This article provides a comprehensive survey on LoRa networks, including the technical challenges of deploying LoRa networks and recent solutions. Based on our detailed analysis of current solutions, some open issues of LoRa networking are discussed. The goal of this survey paper is to inspire more works on improving the performance of LoRa networks and enabling more practical deployments.

A Survey on LoRa Networking: Research Problems, Current Solutions, and Open Issues

LoRaWAN is a flagship Low-Power Wide Area Network (LPWAN) technology that has highly attracted much attention from the community in recent years. Many LoRaWAN end-devices, such as sensors or actuators, are expected not to be powered by the electricity grid; therefore, it is crucial to investigate the energy consumption of LoRaWAN. However, published works have only focused on this topic to a limited extent. In this paper, we present analytical models that allow the characterization of LoRaWAN end-device current consumption, lifetime and energy cost of data delivery. The models, which have been derived based on measurements on a currently prevalent LoRaWAN hardware platform, allow us to quantify the impact of relevant physical and Medium Access Control (MAC) layer LoRaWAN parameters and mechanisms, as well as Bit Error Rate (BER) and collisions, on energy performance. Among others, evaluation results show that an appropriately configured LoRaWAN end-device platform powered by a battery of 2400 mAh can achieve a 1-year lifetime while sending one message every 5 min, and an asymptotic theoretical lifetime of 6 years for infrequent communication.

https://www.mdpi.com/1424-8220/17/10/2364/pdf

Modeling the Energy Performance of LoRaWAN

The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey towards the fifth generation (5G) of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of Multi-Access Edge Computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC's ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultra low latency and high Quality of Service (QoS) due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

/pdf/survey-on-multi-access-edge-computing-for-internet-of-things-abe329bbwk.pdf

Low-Power Wide-Area Networks (LPWANs) are an emerging wireless platform which can support battery-powered devices lasting 10-years while communicating at low data-rates to gateways several kilometers away. Not all such devices will experience the promised 10 year battery life despite the high density of LPWAN gateways expected in cities. Transmission from devices located deep within buildings or in remote neighborhoods will suffer severe attenuation forcing the use of slow data-rates to reach even the closest gateway, thus resulting in battery drain. This paper presents Charm, a system that enhances both the battery life of client devices and the coverage of LPWANs in large urban deployments. Charm allows multiple LoRaWAN gateways to pool their received signals in the cloud, coherently combining them to detect weak signals that are not decodable at any individual gateway. Through a novel hardware and software design at the gateway, Charm carefully detects which chunks of the received signal need to be sent to the cloud, thereby saving uplink bandwidth. We present a scalable solution to decoding weak transmissions at city-scale by identifying the set of gateways whose signals need to be coherently combined over time. In evaluations over a test network and from simulations using traces from a large LoRaWAN deployment in Pittsburgh, Pennsylvania, Charm demonstrates a gain of up to 3x in range and 4x in client battery-life.

Charm: exploiting geographical diversity through coherent combining in low-power wide-area networks

This paper presents Millimetro, an ultra-low-power tag that can be localized at high accuracy over extended distances. We develop Millimetro in the context of autonomous driving to efficiently localize roadside infrastructure such as lane markers and road signs, even if obscured from view, where visual sensing fails. While RF-based localization offers a natural solution, current ultra-low-power localization systems struggle to operate accurately at extended ranges under strict latency requirements. Millimetro addresses this challenge by re-using existing automotive radars that operate at mmWave frequency where plentiful bandwidth is available to ensure high accuracy and low latency. We address the crucial free space path loss problem experienced by signals from the tag at mmWave bands by building upon Van Atta Arrays that retro-reflect incident energy back towards the transmitting radar with minimal loss and low power consumption. Our experimental results indoors and outdoors demonstrate a scalable system that operates at a desirable range (over 100 m), accuracy (centimeter-level), and ultra-low-power (

Millimetro: mmWave retro-reflective tags for accurate, long range localization

Infrastructure monitoring applications currently lack a cost-effective and reliable solution for supporting the last communication hop for low-power devices. The use of cellular infrastructure requires contracts and complex radios that are often too power hungry and cost prohibitive for sensing applications that require just a few bits of data each day. New low-power, sub-GHz, long-range radios are an ideal technology to help fill this communication void by providing access points that are able to cover multiple kilometers of urban space with thousands of end-point devices. These new Low-Power Wide-Area Networking (LPWAN) platforms provide a cost-effective and highly deployable option that could piggyback off of existing public and private wireless networks (WiFi, Cellular, etc). In this paper, we present OpenChirp, a prototype end-to-end LPWAN architecture built using LoRa Wide-Area Network (LoRaWAN) with the goal of simplifying the design and deployment of Internet-of-Things (IoT) devices across wide areas like campuses and cities. We present a software architecture that exposes an application layer allowing users to register devices, describe transducer properties, transfer data and retrieve historical values. We define a service model on top of LoRaWAN that acts as a session layer to provide basic encoding and syntax to raw data streams. At the device-level, we introduce and benchmark an open-source hardware platform that uses Bluetooth Low-Energy (BLE) to help provision LoRa clients that can be extended with custom transducers. We evaluate the system in terms of end-node energy consumption, radio penetration into buildings as well as coverage provided by a network currently deployed at Carnegie Mellon University.

OpenChirp: A Low-Power Wide-Area Networking architecture

Conventional wireless communication systems are typically designed assuming a single transmitter-receiver pair for each link. In Low-Power Wide-Area Networks (LP-WANs), this one-to-one design paradigm is often overly pessimistic in terms of link budget because client packets are frequently detected by multiple gateways (i.e. one-to-many). Prior work has shown massive improvement in performance when specialized hardware is used to coherently combine signals at the physical layer. In this paper, we explore the potential of using multiple receivers at the MAC and link layer where these performance gains are often neglected. We present an approach called Opportunistic Packet Recovery (OPR) that targets the most likely corrupt bits across a set of packets that suffered failed CRCs at multiple LoRa LP-WAN base-stations. We see that bit errors are often disjoint across receivers, which aids in collaborative error detection. OPR leverages this to provide increasing gain in error recovery as a function of the number of receiving gateways. Since LP-WAN networks can easily offload packet processing to the cloud, there is ample compute time per packet (order of seconds) to search for bit permutations that would restore packet integrity. Link layer corrections have the advantage of being immediately applicable to the millions of already deployed LP-WAN systems without additional hardware or expensive RF front-ends. We experimentally demonstrate that OPR can correct up to 72% of packets that would normally have failed, when they are captured by multiple gateways.

https://dl.acm.org/doi/pdf/10.1145/3386901.3388915

A cloud-optimized link layer for low-power wide-area networks

The reduction of the consumption of energy, through its efficient use, is regarded as one of the ways of reducing the impact of mankind on the environment. Buildings consume a significant amount of energy, namely for heating, cooling and illumination. Over the last decades, more energy efficient equipment, new building materials and construction techniques have enabled more energy efficient buildings. However, human behaviour has a large impact on the energy consumption of each building, with similar buildings presenting very distinct energy footprints, due to their occupants' behaviour. The problem of creating more sustainable energy consumption habits has recently received a lot of attention from the research community. Systems capable of reducing energy consumption, by enforcing more correct behaviours, may reduce costs for companies and help improve the environmental outlook. This paper proposes a novel system to address the energy consumption problem and inadequate habits of people in office buildings. It's a highly flexible distributed office management system that can scale from an individual node in an office to the whole building. The goal is to reduce global building energy consumption without significantly affecting the users' comfort level. An approach is used where the building services are adjusted to its occupancy level and users' needs based on their location. Users are driven to better energy usage habits through access to information and feedback. Our proposal is presented in detail and validated in the context of an academic institution, more specifically at the Taguspark campus of Instituto Superior Tecnico. The developed system is now operational and being used as a flexible, easily programmable, research platform.

https://artur.balanuta.com/assets/publications/PerOMAS_DCOSS2015.pdf

Artur Balanuta

Papers

Charm: exploiting geographical diversity through coherent combining in low-power wide-area networks

Millimetro: mmWave retro-reflective tags for accurate, long range localization

OpenChirp: A Low-Power Wide-Area Networking architecture

A cloud-optimized link layer for low-power wide-area networks

PerOMAS: Personal Office Management and Automation System