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The Internet of Things (IoT) is a network of devices for communicating machine to machine (M2M) based on wired and wireless Internet. IoT in agriculture is a revolutionary technology that can be applied to agricultural production year-round. The aim of this study is to summarize cases of IoT being applied to agricultural automation in the agricultural sector and to discuss the limitations and prospects for expanding the application of IoT technology in Korea. The application of IoT in agriculture was classified and analyzed based on previous data, and the sensors and communication technologies used were compared. Based on the analysis results, the limitations of and prospects for IoT in agriculture were discussed. IoT was widely used in agriculture, such as management systems, monitoring systems, control systems, and unmanned machinery. In addition, the various wireless communication technologies used in agriculture, such as Wi-Fi, long-range wide area network (LoRaWAN), mobile communication (e.g., 2G, 3G, and 4G), ZigBee, and Bluetooth, were also used in IoT-based agriculture. With the development of various communication technologies, such as 5G, it is expected that faster and broader IoT technologies will be applied to various agricultural processes in the future. IoT-based agriculture equipped with a communication system suitable for each agricultural environment can contribute to agricultural automation by increasing crop quality and production and reducing labor.

The Internet of Things (IoT) denotes a concept of connected devices that communicate seamlessly over the Internet. The wireless connectivity between IoT nodes and the Internet gateways can be realized in unlicensed frequency bands upon the low-power wide-area network (LPWAN). It is foreseen that due to a massive introduction of IoT devices the unlicensed bands will experience an increased interference level which will negatively affect the communication performance. Therefore, adaptive solutions should be considered to obtain robustness. This letter presents a time-modulated antenna array (TMAA) for LPWAN receivers and demonstrates its interoperability with a commercial of-the-shelf LoRa device. According to the conducted experimental investigation, whereby the beam-steering is obtained over the sidebands inherently generated by the TMAA, both the received signal strength and the signal-to-noise ratio (SNR) are improved by means of the progressive delay applied to the time modulation functions.

Mobile Augmented Reality (MAR) applications usually contain computation-intensive tasks which far outstrip the capability of mobile devices. One way to overcome this is offloading computation-intensive MAR tasks to remote clouds. However, the wide area network delay is hard to reduce. Thanks to edge computing, we can offload MAR tasks to nearby servers. Prior studies focus on either single-task MAR applications offloading or dependent tasks offloading for a single user. In this article, we study the offloading decision of MAR applications from multiple users, each of which is comprised of a chain of dependent tasks, over a generic cloud-edge system consisting of a group of heterogeneous edge servers and remote clouds. We formulate the Multi-user Multi-task MAR Application Scheduling (M3AS) problem, which is NP-hard. We present Mutas, an efficient scheduling algorithm that jointly optimizes server assignment and resource management. We also consider the online version of M3AS and present OnMutas. Extensive evaluations demonstrate that both Mutas and OnMutas can significantly reduce the service delays of MAR applications when compared to three other heuristics.

Providing ACID transactions under conflicts across globally distributed data is the Everest of transaction processing protocols. Transaction processing in this scenario is particularly costly due to the high latency of cross-continent network links, which inflates concurrency control and data replication overheads. To mitigate the problem, we introduce Ocean Vista—a novel distributed protocol that guarantees strict serializability. We observe that concurrency control and replication address different aspects of resolving the visibility of transactions, and we address both concerns using a multi-version protocol that tracks visibility using version watermarks and arrives at correct visibility decisions using efficient gossip. Gossiping the watermarks enables asynchronous transaction processing and acknowledging transaction visibility in batches in the concurrency control and replication protocols, which improves efficiency under high cross-data center network delays. In particular, Ocean Vista can access conflicting transactions in parallel and supports efficient write-quorum/read-one access using one round trip in the common case. We demonstrate experimentally in a multi-data center cloud environment that our design outperforms a leading distributed transaction processing engine (TAPIR) more than tenfold in terms of peak throughput, albeit at the cost of additional latency for gossip and a more restricted transaction model. The latency penalty is generally bounded by one wide area network (WAN) round trip time (RTT), and in the best case (i.e., under light load) our system nearly breaks even with TAPIR by committing transactions in around one WAN RTT.

This paper discusses how to address and overcome some of the problems related to smart data generation and visualization, such as the poor autonomy of wireless sensor devices and the flexibility of the data management platform. We described the implementation and field experiment of a modular IoT application for Smart-Farming, in which the sensor devices are powered by an on-board battery and the data management system is based on a highly flexible software stack, capable of displaying time series graphs and processing millions of data per second. The experiment shown that the power consumption of the sensor devices depends on many factors and that the lifecycle of the devices can reach years using ultra-low power processors, low power wide area network (LPWAN) such as LoRaWAN and a mix of energy saving techniques. The data management and visualization platform shown to be able to display many types of time-series graphs, deal with a wide variety of data-sources and effectively manage a large amount of data.

Software-defined networking (SDN) has evolved as an approach that allows network administrators to program and initialize, control, change and manage networking components (mostly at L2-L3 layers) of the OSI model. SDN is designed to address the programmability shortcomings of traditional networking architectures commonly used in cloud datacenters (CDC). Deployment of SDN solutions have demonstrated significant improvements in areas such as flow optimization and bandwidth allocation in a CDC. However, the benefits are significantly less explored when considering Software-Defined Wide Area Networks (SD-WAN) architectures in the context of delivering solutions by networking multiple CDCs. To support the testing and bench-marking of data-driven applications that rely on data ingestion and processing (e.g., Smart Energy Cloud, Content Delivery Networks) across multiple cloud datacenters, this paper presents the simulator, IoTSim-SDWAN. To the best of our knowledge, IoTSim-SDWAN is the first simulator that facilitates the modeling, simulating, and evaluating of new algorithms, policies, and designs in the context of SD-WAN ecosystems and SDN-enabled multiple cloud datacenters. Finally, IoTSim-SDWAN simulator is evaluated for network performance and energy to illustrate the difference between classical WAN and SD-WAN environments. The obtained results show that SD-WAN surpasses the classical WAN in terms of accelerating traffic flows and reducing power consumption. Refereed/Peer-reviewed

The ability of low-power wide area network (LPWANs) to provide low-cost wireless access to geographically spread-out devices while at the same time catering to long battery life running for several years continues to meet a vital need in the IoT/smart cities market. LoRaWAN shot to prominence as off-the-shelf availability of equipment democratized the technology for private and public use. Its reliance on the unlicensed spectrum that is shared by other competing technologies limits performance and scalability. Operation in the licensed spectrum is a promising direction. However, the techno-economic aspects surrounding this is an open question addressed for the very first time in this article. We show that even with as small a chunk as 1 MHz, significant boost in performance is possible as networks scale. We examine the impact of different parameters such as network scale, subscription models, and subscriber mix for different tariffs (based on publicly available cellular IoT pricing plans) on the economic feasibility and highlight the implications this has on spectrum pricing. This broadens the appeal of this article to cellular and non-cellular network operators of IoT/smart city applications and spectrum regulators who are keen to re-farm/allocate spectrum for different IoT applications.

WSN can be a tech in-full development with top-notch, outstanding foreseeable future. The utilization of wireless sensor network (WSN) to get a good quality observation is consists using some range of detector nodes having a network capacity which might be set up for productive effects or to get constant monitoring function. Water is critical within our own lives because of our wellbeing insurance and in different cases such as farming, marketplace, and for the animal’s presence. Diseases linked to inadequate sanitation and water states have over 200 million cases reported causing 5–10 million deaths throughout the world. Water tracking procedures are indispensable to restrain exactly the challenge is gently linked to inadequate household allocation, wasteful usage and too little decent. Wireless sensor networks also have gained fame over the study area only because they supply a promising infrastructure for both multiple monitoring and control software. For fixing the dilemma, various drinking water caliber processes were grown previously in the last ten years. The parameters included with the drinking water quality tracking would be the PH degree, turbidity, dissolved oxygen and temperature has been quantified at the true period from the detectors that ship the info into the bottom channel or control/monitoring space. This document suggests the way the tracking platform might be set up highlighting the elements of low-cost, simple setup, and effortless maintenance and handling. Using this radio platform for tracking purpose is not only going to lower the total observation procedure expenditure in the duration of centers installation and labor price tag but can even offer versatility in the duration of location or distance. In this paper, the essential layout and execution of WSN comprising Lora (wide area network) established technological innovation is suggested. The developed system is cheap and makes it possible for customization. A few preliminary links between dimension to rate the efficiency and efficiency of the machine can also be shown.

The LoRaWAN technology, an example of low power wide area network, is considered a possible IoT-derived solution for realizing private cellular (single-hop) communications in the industrial domain. However, despite LoRaWAN promises long range and dense environments with many obstacles (as the industrial ones), it may suffer from coverage issue. Additionally, the inverse relationship between data rates and range may be unacceptable for many industrial applications. In this article, an innovative LoRaWAN range extender (based on an enhanced LoRaWAN node) is described, and its integration in the infrastructure of industrial Internet of Things (IIoT)-enabled industrial wireless networks is presented. A frame relay strategy is suggested, thus avoiding to tradeoff the highest data rates against an increased sensitivity. The feasibility of the solution is formally verified and the features of the realized proof-of-concept prototype, based on commercially available hardware, are discussed. The experimental results, obtained with a purposely designed test bench, show the effectiveness of the proposed approach. In particular, the range extender is transparent for legacy LoRaWAN networks as confirmed by correct relaying of uplink and downlink for different types of LoRaWAN message.

Advanced persistent threat, network intrusions and anomalies, and invasions of location and data privacy are constantly violating edge networks, disturbing guaranteed services, and further destroying critical end devices and cyberinfrastructure. Edge gateway defense against malicious cyber threats and privacy leakage for a multitude of connected physical devices remains a significant problem. Edge computing empowered network intelligence will become a practical solution to tackle this challenge by building gateway-focused protection mechanisms, dynamically extending the edge network, and establishing a flexible and intelligent platform to perform rapid responses with the cloud and wide area network. In this article, we present the research in edge intelligence assisted gateway defense in cyber security. Specifically, we first provide the overview of edge computing, and then discuss the motivations of developing and deploying a robust and effective edge intelligence. We also present the details of edge intelligence assisted gateway defense, including major cyber threats and defense mechanisms at gateways. We further offer detailed descriptions of the emerging data-driven approaches for gateway defense. Finally, we perform an experimental study, and we demonstrate that robust edge intelligence achieves high detection accuracy and effective computational performance.

Cloud computing, despite its inherent advantages (e.g., resource efficiency), still faces several challenges. The wide area network used to connect the cloud to end users could cause high latency, which may not be tolerable for some applications, especially Internet-of-Things (IoT) applications. Fog computing can reduce this latency by extending the traditional cloud architecture to the edge of the network and by enabling the deployment of some application components on fog nodes. Application providers use Platform-as-a-Service (PaaS) to provision (i.e., develop, deploy, manage, and orchestrate) applications in cloud. However, existing PaaS solutions (including IoT PaaS) usually focus on cloud and do not enable provisioning of applications with components spanning cloud and fog. Provisioning such applications requires novel functions, such as application graph generation, that are absent from existing PaaS. Furthermore, several functions offered by existing PaaS (e.g., publication/discovery) need to be significantly extended in order to fit in a hybrid cloud/fog environment. In this article, we propose a novel architecture for PaaS for hybrid cloud/fog system. It is IoT use case driven, and its applications’ components are implemented as virtual network functions (VNFs) with execution sequences modeled as graphs with substructures, such as selection and loops. It automates the provisioning of applications with components spanning cloud and fog. In addition, it enables the discovery of existing cloud and fog nodes and generates application graphs. A proof of concept is built based on Cloudify open source. Feasibility is demonstrated by evaluating its performance when the PaaS modules and application components are placed in clouds and fogs in different geographical locations.

In this letter, a metal-frame mobile antenna for Long-Term Evolution (LTE)/wireless wide area network (WWAN) smartphone application using a novel matching network is proposed. The proposed antenna consists of two parts, a typical inverted-F antenna for the low band, and an asymmetric T-slot for the high band. By means of multibranch technology based on matching circuit, the proposed design occupies a small part of the space surrounding the ground with only 1 mm ground clearance, which makes it a very competitive solution for full-screen phones. Finally, it completes the LTE 824–960 MHz and 1710–2690 MHz. The designed procedure and working mechanism of the antenna are discussed in detail. A prototype of the proposed antenna is fabricated and measured, and both simulated and experimental results are presented and discussed.

LoRa, a Low Power Wide Area Network (LPWAN) technology, demands reduced network infrastructure to cover a large area, with low power consumption. In the context of vehicular communications, LoRa has the potential to support monitoring and cooperative navigation applications, where small amounts of data can be transmitted asynchronously through the network. Nevertheless, the literature lacks evaluations of LoRa in the context of vehicular communications. Thus, in this paper we analyze the performance of this technology operating in an urban mobility environment, using LoRa terminal devices embarked on vehicles and a LoRa receiver unit, acting as infrastructure. Moreover, we evaluate the equivalence between experimental and simulated results, obtained from the communication link between the LoRa module inside a vehicle and a LoRa receiver comparing to those produced by NS-3 simulations. Three metrics of interest are evaluated: Packet Delivery Ratio (PDR), Packet Inter-Reception (PIR) time, and Received Signal Strength Indicator (RSSI). Field experiments are performed at the campus of the Federal University of Rio de Janeiro (UFRJ), Brazil. Results revealed that all the metrics evaluated in the simulated experiments are consistent with the results of the real experiments, however, we concluded that the model can be improved by looking for a stronger correlation with real experiments.

The rapid advancement of network, communication and Internet technology resulted with always-on, always-connected, device-independent and remote online working, business, education and entertainment environment. Consequently, users are searching for solutions and technologies that enable fast and reliable wide area network connection and the typical solution is through using personal computers connected with ethernet cable to network equipment and infrastructure that supports gigabit ethernet connection. Besides the complex network infrastructure that can influence performance, the bottleneck can also be caused by insufficient hardware, operating system and software resources on clients’ machines. Therefore, in this paper a networking performance evaluation of three globally most common and most used versions of Windows operating systems; namely Windows 7TM, Windows 8.1TM and Windows 10TM, on two identical computer systems, is conducted. Networking performance measurements are performed with three different benchmarks: namely iPerf, D-ITG and NetStress. Performance evaluation results showed that a newer versions of an operating system bring certain networking performance improvements but by sacrificing other performances.

Internet of Things (IoT) is a very promising technology in forest engineering, especially for the environment and plant growth monitoring. LoRa Wide Area Network (LoRaWAN) is a prevailing choice for the Forestry IoT owing to its low-power and long-range ability. Real-world deployment and network optimization require accurate path-loss modeling, so the LoRaWAN radio channel in the forest is needed to be intensively studied. However, most of the subsistent propagation models do not involve specific forestry environmental parameters. In this paper, two parameters related with the trees are considered: the leaf area index and the tree trunk diameter. Due to the time-changing characteristics of these two items (from spring to winter), an empirical model has been developed through extensive measurement campaigns: Firstly, the channel measurement platform is designed based on a real scene of mixed forest. Secondly, the fading characteristics of the channel transmission for LoRa nodes are tested, and the corresponding model is presented and evaluated. Lastly, an energy harvesting LoRaWAN is deployed and operated in a sampled forest region of Eastern China for environment monitoring based on our propagation model. The results show that 433 MHz LoRa path loss in the mingled forest could be precisely predicted by our proposed model. Moreover, network coverage and energy consumption optimization of the LoRa nodes could be performed, which enables the perpetual development of reliable forestry evolution monitoring system.

The distributed control plane is the alternate solution to reliability and scalability like potential issues in the software-defined wide area network (SDWAN), but the static mapping between controller and switches might cause an uneven load distribution among controllers. Migration of switches from one controller to another under-loaded controller is a solution to handle the peak traffic. However, the switch migration process is a complex process that may affect the end-user quality of service (QoS), as a result, the response time of the control messages are also affected. To address this issue, the authors present RTSM, a novel strategy, that optimises the response time of the control messages during switch migration. Further, an SDWAN architecture was proposed, in which the introduction of the layer-2 controller reduces the dependency on WAN communication of the forwarding devices. The Karush–Kuhn–Tucker conditions have been applied for target controller selection, which ensures improved response time. A switch selection method was also introduced, which minimally affects the end-user QoS during device migration in SDWAN scenario. To evaluate the performance of the RTSM, Mininet simulator with the Floodlight controller has been used, and the result shows that the proposed algorithm outperforms the other existing works during load balancing.

The Internet of Things (IoT) undergoes a rapid transformation this last decade, thanks to the appearance of low-power wide area network technologies, such as LoRa/LoRaWAN, SigFox, and narrowband IoT, which allow reducing the deployment cost of sensors and other IoT devices. Many emerging services such as smart city, Industry 4.0, and autonomous driving are based on IoT devices and applications to collect and analyze data and control end devices (i.e., actuators). Among these services, several IoT applications, such as data analytics, need to be deployed at the edge to either reduce the latency to access data or treat the high amount of generated data locally. However, in the context of LoRa/LoRaWAN, most of the current IoT service deployments run the applications at a central cloud to ease the integration with existing software as a service (SaaS) platforms, without exploiting the benefits of edge computing. In this article, we propose a new framework that leverages the ETSI multi-access edge computing (MEC) model to deploy LoRabased IoT applications at the edge. In particular, the proposed model takes advantage of the ETSI MEC features, such as dynamic deployment of an IoT application at the edge and application life cycle management. In addition, the proposed framework allows running an IoT application as a 5G network slice at the edge.

IEEE Software Defined Networks (SDN) has brought a new form of network architecture that simplifies network management through innovations and programmability. But, the distributed control plane of SD-Wide Area Network is challenged by load imbalance problem due to the dynamic change of the traffic pattern. The packet_in messages are one of the major contributors of the control’s load. When such packet rate exceeds a certain threshold limit, the response time for control request increases non-linearly. In order to achieve better end-user experience, most of the previous works considered the optimal switch to controller association with an objective to minimize the response time on LAN environment but ignores the consequence of large scale network. In this regard, the proposed work realizes the necessity of layer-2 and layer-3 controller in LAN and WAN environment separately. A load prediction based alertness approach has been introduced to reduce the burden of the controllers. This approach may create an additional delay for the initial packets of the flow entry that lead to more prediction error. However, the proposed method reduces the error by selecting an optimal timeout value of the flow. Further, minimization of the response time between router to the controller has been taken care of. An extensive simulation shows the efficacy of the proposed scheme.

A low power wide area network (LPWAN) is becoming a popular technology since more and more industrial Internet of things (IoT) applications rely on it. It is able to provide long distance wireless communication with great power saving. Given the fact that an LPWAN covers a wide area where all end nodes communicate directly to a few gateways, a large number of devices have to share the gateway. In this situation, chances are many collisions could occur, leading to waste of limited wireless resources. However, many factors affecting the number of collisions that cannot be solved by traditional time series analysis algorithms. Therefore, deep learning methods can be applied here to predict collisions by analyzing these factors in an LPWAN system. In this paper, we propose long short-term memory extended Kalman filter (LSTMEKF) model for collision prediction in the LPWAN in terms of the temporal correlation which can improve the LSTM performance. The efficacies of our models are demonstrated on the data set simulated by LoRaSim.

The massive increase in the Internet of Things (IoT) has brought a diverse long-range, low-power, and low bit-rate wireless network technologies. The LoRa a low-power wide area network (LPWAN) gained popularity as radio technology for the realization of many IoT applications. LoRa is typically employed together with LoRaWAN MAC protocol and operates in the license-free ISM bands. LoRa networks have an issue with scalability when the number of end nodes connected to one network is larger than the shared number of channels, that causes a collision and packets loss through receiving a wide range of different message sizes from various application. In this paper, we describe an accurate and efficient way confirmed by simulation to calculate the probability of collision rate and packet loss in LPWANs under various circumstances. Moreover, based on the LoRaWAN specification, we consider a dense network deployment of IoT devices. In the event of collisions, our proposed algorithms is classified to two approaches. Firstly a time scheduling algorithm is proposed for LoRaWAN networks that consist of devices supporting LoRaWAN class C mode for synchronization in the beginning between the gateway and the end nodes. Afterwards these devices switch to class A to significantly decrease the collision and to enhance scalability by assigning a Guard Time to each end node. Gateway acknowledgment (ACK) messages to the end nodes are used through class C. Secondly, we also propose a distance spreading factor algorithm according to the distance of the end nodes from the gateway to reduce the probability of collision. Furthermore, many of these devices are battery powered, therefore low power consumption is required.

Due to the development of the Internet and the smart end systems such as smartphones, portable laptop, and other smart mobile devices, as well as the emergence of concepts such as cloud computing, social networks, and Internet of Things, 4G and 5G have changed network requirements. A software-defined network (SDN) is a new architecture to support new network requirements. This architecture is composed of three layers, data, control, and application plane. A lot of papers have been published in well-known journals to improve network performance, so we classify the solutions for performance improvement based on three SDN layers and three SDN-based spheres which are (a) SDN-data center, (b) wireless networks, and (c) software-defined wide area network. This paper surveys the articles which have been published by Springer, IEEE, Elsevier, and ACM. We extract the performance improvement solutions and resources which are required for performance control and the metrics to evaluate the network performance. This article can help network enthusiasts to better understand, investigate, and improve the performance of SDN-based networks.

We conducted a qualitative study to get a preliminary understanding of indigents needs. The results helped us identify system requirements that led to the design of the HELPi system, a digital bracelet to enable local agencies to provide support to indigents who used roam the city. The paper aims to present the studies conducted to inform the design of our technological approach to addressing challenges related to acceptance, coverage of users, and battery lifespan. We built a prototype using LoRa™, which is a Low Power Wide Area Network (LPWAN) technology that offers several features that make it suitable for our application domain; e.g., it enables Machine-to-Machine (M2M) communications. Thus, we have taken advantage of this feature and propose a communication protocol to allow a dynamic coverage of users. We conducted assessments to determine users’ perception about its usefulness, and to measure the performance of the LoRa’s signal propagation and the battery energy consumption for the deployment of the HELPi system. According to our results, the proposed communication protocol should work with a LoRa™ Gateway in the outside setting condition and with an SNR threshold higher than − 2 dB to guarantee the successful reception of messages transmitted.

Many fire situations have represented the loss of lives and material costs due to the lack of early fire detection through smoke or gas sensing, which can become complex and critical. Meanwhile, engineers worldwide develop and test multiple systems for smoke and gas detection, commonly based on sensor networks, digital image processing, or computer vision. Furthermore, the detection system must work thoroughly with alarms and warnings that aware of a risk situation for prompt evacuation of the population in the surroundings based on a reliable data network topology with adequate device deployments that will let us know the moment a fire outbreak. This paper presents a low-cost Internet of Things (IoT) prototype for fire detection in outdoor environments based on sensors and Low Power Wide Area Network (LPWAN), focused on the accuracy in the temperature and gas measurement at the moment a fire starts. For its achievement, we integrated wireless components, development boards, and electronic devices, following the management of information updates through a database schema for the alarm settings based on the data gathered from the sensors.

Rapid data streams are generated continuously from diverse sources including users, devices, and sensors located around the globe. This results in the need for efficient geo-distributed streaming analytics to extract timely information. A typical geo-distributed analytics service uses a hub-and-spoke model, comprising multiple edges connected by a wide-area-network (WAN) to a central data warehouse. In this paper, we focus on the widely used primitive of windowed grouped aggregation , and examine the question of how much computation should be performed at the edges versus the center . We develop algorithms to optimize two key metrics: WAN traffic and staleness (delay in getting results). We present a family of optimal offline algorithms that jointly minimize these metrics, and we use these to guide our design of practical online algorithms based on the insight that windowed grouped aggregation can be modeled as a caching problem where the cache size varies over time. We evaluate our algorithms through an implementation in Apache Storm deployed on PlanetLab. Using workloads derived from anonymized traces of a popular analytics service from a large commercial CDN, our experiments show that our online algorithms achieve near-optimal traffic and staleness for a variety of system configurations, stream arrival rates, and queries.

WPaxos is a multileader Paxos protocol that provides low-latency and high-throughput consensus across wide-area network (WAN) deployments. WPaxos uses multileaders, and partitions the object-space among these multileaders. Unlike statically partitioned multiple Paxos deployments, WPaxos is able to adapt to the changing access locality through object stealing. Multiple concurrent leaders coinciding in different zones steal ownership of objects from each other using phase-1 of Paxos, and then use phase-2 to commit update-requests on these objects locally until they are stolen by other leaders. To achieve fast phase-2 commits, WPaxos adopts the flexible quorums idea in a novel manner, and appoints phase-2 acceptors to be close to their respective leaders. We implemented WPaxos and evaluated it over WAN deployments across 5 AWS regions. The dynamic partitioning of the object-space and emphasis on zone-local commits allow WPaxos to significantly outperform both partitioned Paxos deployments and leaderless Paxos approaches.

This paper proposes for the first time the use of an Internet of Things solution for the accurate recovery of incapacitated commercial and retail delivery drones. Since the use of drones will increase in popularity for a variety of uses, the problem of locating and recovering delivery drones is necessary. Using the emerging LoRaWAN and Sigfox networks (as examples of Low Power Wide Area Network (LPWAN) technology), we investigate the opportunity to locate and recover delivery drones that have crashed either due to technical issues or outside malign intervention. Location and recovery of a test drone using LoRa technology was trialed over three distinct terrains (urban, suburban, and rural) at five different sites in each terrain. These 15 trials evaluate ease of recovery on arrival at the crash site, accuracy of location coordinates given, and a subsequent analysis of the channel statistics for the LoRa network. The experiment was repeated using the Sigfox network as a comparison. The drone was able to be recovered at 14 of the 15 tests sites for both LoRa and Sigfox; in every case the drone's location was successfully transmitted to the secure server via the LPWAN networks. The paper investigates the reported location accuracy from the drone and also uses RMSE as an accuracy metric. The paper furthermore divulges lessons learned and presents a drone recovery algorithm.

The long-range wide area network (LoRaWAN) has recently emerged as one of the most potential technologies for the mobile Internet of Things (IoT) applications. In a LoRaWAN, the network-managed adaptive data rate (ADR) method is responsible for managing resource allocation (i.e., spreading factor (SF) and transmit power (TP)) to end-devices (EDs) through ADR commands. When an ED is mobile and receives a new configuration (i.e., SF and TP) from the network server, the propagation scenario could have been dramatically changed. Hence, the SF and the link budget will no longer be valid, which results in packet loss and massive retransmissions. Therefore, we propose a mobility-aware resource (SF) assignment scheme (M-ASFA), which aims to allocate the best SF to IoT-enabled mobile EDs at each uplink transmission by considering the strength of the signals that a gateway receives from the EDs. The simulation results demonstrate that, in our proposed M-ASFA solution, the SF is assigned to mobile EDs by proactively responding to the mobility of the EDs. This proactive behavior of the proposed scheme enhances the packet success ratio by significantly reducing the impact of interference, retransmissions, and packet loss when compared with the LoRaWAN-based ADR.

Many of the Internet of Things (IoT) profit significantly from long-range connectivity with low power. Low power wide area network (LPWAN) technologies are designed to extend the coverage by minimizing the energy efficiency and less expense of data throughput. Long range WAN (LoRaWAN) is a media access control (MAC) protocol operated by the LoRa Alliance using the unlicensed LoRa radio modulation technology. LoRaWAN provides a successful innovation to meet the long–range and low-power demands. LoRaWAN offers three distinct device classes (A, B and C), providing a trade-off among effectiveness and power usage. This paper provides a comparison of these classes theoretically and the simulation of class A with reduction of duty cycle. The main contribution of this paper is to analyze the scalability of LoRaWAN and its packet deliver ratio (PDR) with maximum number of nodes. Utilizing LoRaWAN the outcomes are built up an examination of scalability and unwavering quality measure in ns-3.

The convergence of the Internet of Things (IoT) and 5G will open a range of opportunities for the deployment of enhanced sensing, actuating and interactive systems as well as the development of novel services and applications in a plethora of fields. Given the processing and communication limitations of both IoT devices and the most novel IoT transmission technologies, namely, Low Power Wide Area Network (LPWAN), there are notable concerns regarding certain security issues to be overcome in order to achieve a successful integration of LPWAN systems within 5G architectures. In this survey work, we analyze the main security characteristics of LPWANs, specially focusing on network access, and contrast them with 5G security requirements and procedures. Besides, we present a comprehensive review and analysis of research works proposing security solutions for the 5G-LPWAN integration. Finally, we explore open issues and challenges in the field and draw future research directions. From our analysis, it is evident that many efforts are being devoted from the academia, industry and Standards Developing Organizations (SDOs) for achieving the desired confluence of IoT and 5G worlds. We envision a successful integration of both ecosystems by exploiting novel lightweight security schemes addressing the stringent security requirements of 5G while being assumable by constrained IoT devices.

The poetic parallels, figurative overlaps, and thematic frictions between the pages of William Blake's dynamic Songs of Innocence and of Experience establish a local area network architecture that is both complementary and antagonistic to the traditional pathways generated by/through bookspace. While this tension between connective paradigms contributes to the revolutionary vitality of Blake's work, its full implications have been stultified by generations of reproduction that privileged the organizational paradigms related to the printed book and its circulatory systems. However, flexible and fluid digital distribution, primarily via the William Blake Archive and its participation in NINES, extends the material bounds of Blake's printed work into a wide area network. This not only transcends Blake's distributive frustrations, but the sharing and communication functions engendered by network architectures encourage a more explicit recognition, re-imagining and extension of the networked features and applications of Blake's multimedia Songs. Unfortunately, as Blake's work has migrated to the digital arena, traditional doors of print-based perception have often been reinforced by unimaginative and anachronistic interfaces. NewRadial, a data visualization application, more fully illuminates the network architecture at the heart of Blake's Romantic creativity, and demonstrates the ways in which our current technological networks can extend interpretative possibility.

In this paper, the assessment of multiple scenario cases for large-scale farm monitoring using Low-Power Wide-Area Network (LPWAN) based near-ground sensor nodes with the interaction of both tractors and farmers are presented. The proposed scenario under analysis considers multiple communication links, namely nodes to infrastructure, nodes to tractor, nodes to farmer, tractor to infrastructure and farmer to infrastructure communications. Moreover, these scenarios are proposed for tractors and agricultural equipment performance improvement and tracking, as well as resources management within the farm field. Different link type configurations are tested in order to consider the impact of ground, spatial distribution as well as infrastructure elements. The results show that LPWAN-based WSNs can provide better performance in terms of coverage and radio link quality results than ZigBee for a non-flat large-scale farm field in both cases of near-ground fixed nodes and moving tractor and farmer. The proposed systems are validated by cloud-based platforms for LoRaWAN, Sigfox and NB-IoT communications, providing flexible and scalable solutions to enable interactive farming applications. This research is supported by the 2017 Predoctoral Research Grant supported by the Xunta de Galicia and the research projects TEC2017-85529-C03-3R and RTI2018-095499-B-C31, funded by Ministerio de Ciencia, Innovación y Universidades, Gobierno de España (MCIU, AEI, FEDER, UE), as well as from European Union's Horizon 2020 research and Innovation programme under grant agreement N°774094 (Stardust-Holistic and Integrated Urban Model for Smart Cities).

Today, more and more enterprises are embarking on a digital transformation where most of their applications are hosted in the Cloud. As a result, a reliable Wide Area Network (WAN) has become a primary need to interconnect their distributed branch offices and data centers that accommodate those applications. Software-Defined Wide Area Network (SD-WAN) represents the most promising technology solution for next-generation enterprise networks, being able to increase network agility and reduce costs. In this paper, we present an experimental SD-WAN solution capable of running and optimizing delay-sensitive high-priority services, such as real-time video streaming, while minimizing downtime caused by network failures. This solution comprises a monitoring and a traffic engineering system for SD-WAN. The first consists of a Transport-layer Passive Monitoring (TPM) system based on extended Berkeley Packet Filter (eBPF) technology with the goal of monitoring TCP flows; the second consists of an application, running inside the SD-WAN controller, with the goal of orchestrating the network traffic in consideration of the monitoring measurements by ensuring rapid recovery and resilience in case of unexpected congestion events. We validate our solution over two SD-WAN testbeds: the first is hosted in our laboratory at Politecnico di Milano, while the second is deployed in a municipal network of an Italian city. Results show that our SD-WAN solution can increase the overall service availability while meeting the stringent QoS requirements of delay-sensitive services. IEEE

Vibration-based condition monitoring among all the components of the aircraft structure is an important approach to improve the flight safety before any component in aircraft reaches resonance. This paper presents multichannel and multihop low-power wide-area network (MCMHL) architecture suitable for vibration monitoring on aircraft. First, microelectro mechanical system-long Range (LoRa)-based sensor node architecture in light of hardware cross-layer algorithm is proposed for implementing the tradeoff among hardware cost, power consumption, and performance. To achieve high accuracy of synchronous acquisition, multihop slot segmenting scheduling and multichannel data communication algorithm are proposed. In addition, the beacon transmission delay, of beacon between sink and sensor nodes is calculated, and further synchronization compensation algorithm is designed. The experiments of the proposed approach in aircraft vibration test and data synchronization test on aircraft skin are validated, showing that the proposed MCMHL approach has these abilities of data synchronous collections, remote communication, and data stream uploading in a wide monitoring area.

Inter-DataCenter Wide Area Network (Inter-DC WAN) that connects geographically distributed data centers is becoming one of the most critical network infrastructures. Due to limited bandwidth and inevitable link failures, it is highly challenging to guarantee network availability for services, especially those with stringent bandwidth demands, over inter-DC WAN. We present BATE, a novel Traffic Engineering (TE) framework for bandwidth availability (BA) provision, which aims to ensure that each bandwidth demand must be satisfied with a stipulated probability, when subjected to the network capacity and possible failures of the inter-DC WAN. The three core components of BATE, i.e., admission control, traffic scheduling and failure recovery, are formulated through different mathematical models and theoretically analyzed. They are also extensively compared against state-of-the-art TE schemes, using a testbed as well as real trace driven simulations across different topologies, traffic matrices and failure scenarios. Our evaluations show that, compared with the optimal admission strategy, BATE can speed up the online admission control by 30x at the expense of less than 4% false rejections. On the other hand, compared with the latest TE schemes like FFC and TEAVAR, BATE can meet the bandwidth availability targets for 23%~60% more demands under normal loads, and when network failure causes BA targets violations.