Dew Computing

Dew computing, a new version of the computing paradigm appeared along with cloud, edge, and fog computing. Dew computing is a distributed computing framework that is deliberated as an augmentation in the cloud computing schema. Researchers and academic practitioners have explored the concept of dew computing since its germination. In dew computing, users can perform full system functionality without depending on Internet availability. Information will be warehoused on the local storage of the user’s device, and when the Internet connection is present, harmonization will be accomplished to synchronize the transmitted information on cloud-dependent applications. There have been voluminous implementations of dew computing in prevailing usages, although research achieved concerning dew computing is not as much as in erstwhile distributed computing spheres. They have even tried to integrate computing into several existing and sustainable applications, such as the Internet of Things, smart Healthcare, Indoor navigation, agriculture, and numerous human-centric paradigms. The key objective of dew computing is to enhance the efficiency and reduce the cost of personal IoT devices which further augment the productivity and scalability of any distributed computing network. In this chapter, we first briefly focus on unfolding the concept of dew computing. We illustrate a set of real-time case studies, such as the cache computing framework for dew devices, the reduced Internet dependency-induced decision-making processes, the crises, the humanitarian Internet of Music Things, and so on, where the flow of information should be abundant despite having issues with constant digital network connectivity. We would focus on providing a detailed literature survey of dew computing architecture, applications, tools, and technologies that might assist in delivering ICT-based sustainable Internet of Things applications. This chapter additionally provides a deep insight into upcoming tools and technologies that can be integrated with the conventional dew computing architecture for obtaining more efficiency in Internet-dependent distributed networks.

Computers are used as controlling and monitoring tools, especially in the industrial IoT sector. Data is born at the edge by millions of IoT devices.

Modern wireless and mobile solutions are frequently referred to as the Internet of Things (IoT) applications. The development of cloud-based systems and technological advancements give rise to the concept of a networked, Internet-based, distributed processing site-based world. This paper explains the dew environment analysis and monitoring to ensure sustainability. This approach also discusses sustainable IoT solutions and provides an overview of the dew server’s organizational and operational structure. We outline the objectives, specifications, and performance of dew servers, another computational layer in the cloud-based architecture for Sustainable IoT solutions. The dew servers are examined rigorously from an operational and performance perspective as systems that, in addition to communicating with higher-level cloud servers, gather, process, and offload streaming data from IoT sensors and devices.

Edge, fog, and Dew computing have emerged from cloud computing. The proponent of cloud computing says that this model gives a better experience to users. In order to use Dew computing a user need to install DVM (Dew virtual machine) on his system. Dew virtual machine is an isolated environment to run a Dew server or a local PC. It consists of a Dew server (DS), Dew analytic server (DAS), and artificial intelligence of Dew (AID). The Dew server is a cloud server on the local PC. Dew analytic server collects information about how DS is being used. AID takes data from DS and presents it to the user such that it enhances the user experience. Based on the real-time application, many categories of Dew computing exist, e.g., Web in Dew, Software in Dew, Database in Dew, etc. Dew computing can also be used for IoT systems; we may name “IoT-enabled Dew”. As communication in these systems takes place over a public channel, many security concerns come into the picture when we use IoT in Dew. Thus, it is required to be focused on authorization in data access, secure session establishment, user privacy to have confidence in the system and data secrecy. As data is not of computing control of cloud servers, security and authorized access laws remain a key concern in Dew. To ensure secure and authorized communication, an access control mechanism may help, which could be established between the device and the Dew server. As we include Dew in IoT systems, there is also a need to establish a secure session key between the sensor device and the user. In this chapter, we will discuss the security-related issues in Dew and present a discussion on the security concerns of Dew-assisted IoT Systems and user privacy aspects. We will also provide the status of the current Dew system security and future requirements.

Matrix-Mesh is an IM protocol that proposes a hybrid messaging architecture, combining elements from cloud-dew, client-server, and P2P, with the aim of operating even when normal connectivity is not available. Matrix-Mesh was built on top of the Matrix protocol in order to make full use of its existing network and features while additionally making use of auxiliary links such as LANs, PANs (Bluetooth), and NFC connections. The app detailed herein does this, with the primary intent of proving the deployability of Matrix-Mesh on mobile platforms. While a cross-platform implementation was chosen, for expediency the primary focus is on Android, though Matrix-Mesh and all relevant discussion is applicable to other platforms, such as iOS. Through this development, it is shown that Matrix-Mesh makes the proper use of Matrix’s layered architecture, and the additional auxiliary link to provide vital communication when the primary connection is unavailable. The code is available via GitHub.

Dew computing is cache-based computing used in areas with unreliable Internet connectivity. The Blockchain client does not need to keep the Blockchain data and also has the features of a Blockchain full node. Dewblock was developed based on Dew computing principles and the Dew-Cloud architecture. A node connection protocol, the Pair Connection Protocol, has been proposed that could be used in similar Dew-Cloud applications. Edge intelligence based on Dew computing helps to establish distributed connections when the Internet connection is interrupted/disconnected for a short period of time. When the Internet connection is interrupted, the intermediary Dew device holds the data based on the available cache memory. After the Internet connection is restored using Blockchain-based mining technology, the correct edge device can be connected based on the previous hash value. This article is about Blockchain based on the Dew computing paradigm and provides all the basic information about Dew computing and Blockchain technology.

Edge of Things (EoT) is a network of edge devices in which sensors, networks, electronics, and software are included. EoT enables uninterrupted data transfer from the cloud layer to edge devices through the Internet. In this transmission, there need strong privacy and security concerns. Although day by day throughout the universe the number of devices is increasing with new features, shapes, sizes, usage, protocol, etc., the conventional method of security and privacy systems are not sufficient to control the ubiquitous EoT. The conventional IDS system does not work on unstable Internet so to overcome this issue we will use Dew computing in the IDS system. With the assistance of the dew server, an individual has more control and adaptability to access data in the absence of an unstable Internet connection. IDS is used to detect different kinds of attacks in the edge layer. But sometimes it fails to detect the false alarm, which may create a severe problem. Various types of network attacks like Malware, MITM, Remote Code Execution, etc. in different networks are detected by Intrusion Detection System (IDS) and prevented by Intrusion Prevention System (IPS). At the time of the detection procedure, several alarms are generated, which decreases the effectiveness of IDS. Using an alarm filter can be a better solution to overcome this type of problem. An intelligent alarm filtration mechanism can be designed by a selective machine-learning-based classifier in DewIDS then DewIPS can block the attempted intrusion or remediate the incident after SOC investigation. This work aims to present a comprehensive survey of existing Dew Computing for Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) in Edge of Things.

The present chapter investigates some future research cases, themes, and directions in vehicular dew computing. Dew computing is a paradigm for organizing the software and hardware of on-premises computers in a cloud computing architecture. The on-the-spot computer offers services that work independently from the cloud. It seeks to maximize the capabilities of computers on-site and cloud services. Thus it combines the concept of cloud computing with edge computing. Cloud/Fog/Edge depends on Internet connectivity. Today’s transportation and routing decisions depend on intelligent technologies. In dynamic vehicle routing and procurement planning, the Internet connectivity problem is the most important because we make a decision depending on real time, and its availability in rural/semi-urban areas is limited. To address these challenges, this investigation proposes a novel dew-caching architecture under the cloud using the Internet of vehicular things (IoVs) in different practical applications such as smart logistic routing, disaster management, etc. Also, dew computing plays a significant role in this situation. This allows the user to access the services, files, and resources when there is disrupted Internet connectivity, and then the files and resources are synced back to the cloud server when the connection is made again. The end-user gets additional freedom to retrieve essential data using dew computing. When Internet access is available, the data is synced with the master copy at the cloud server as well as in the dew server located on the user’s device. Users can read, write, update, and remove data on their smartphone, which functions as a localized version of a real server. The present study gives some novel areas of applications in dew computing utilizing caching in the Internet of vehicular things.

The inception of global pandemic has underscored and reinforced the utility and necessity of Telerobotic applications as an important factor to augment human endeavors in future. Such applications may broadly be classified into Telepresence or Teleoperation. Both function with human in the loop as an operator or observer. However, practical deployment experiences reveal that the expected advantage from such systems is largely unrealized due to the prevalent cloud-centric architecture. The key reason is the erratic response from the end-to-end channel over the Internet which is beyond the control of the end-applications. This calls for an exploration on how the promises of Dew-computing can be leveraged to ensure performance guarantee for such systems for the end-users agnostically. Particularly we shall explore how negotiation and process sharing with cloud for opportunistic localization of decision logics and storages may help compliment the desired QoS of the multi-sensory traffic-types being exchanged through formation of optimized topology among the robot, observer, and operator nodes. It will be also explored how Dew-based approach may help reduce session establishment overhead at a system-level. We shall explore two specific broad approaches, namely, Dew-on-Robot and Dew-on-Edge, and show how they fit into different dynamics of Telerobotic applications, especially in enterprise settings.

The Internet of Things can provide promising solutions for quick, reliable, and smart healthcare services to patients and health workers. Such smart healthcare devices generate a large chunk of data continuously at a very rapid rate. These healthcare data are required to be processed and action needs to be taken to save lives in real time. However, the traditional IoT-based healthcare architectures use the remote cloud as the processing and analysing unit which increases the response time and decreases the reliability of the service. To address this problem, researchers have provided several solutions such as Edge, Fog, and Dew computing to improve the reliability and service time. Dew computing enables the IoT architectures to provide important services even in offline conditions with ultra-low latency. In this paper, a detailed analysis of Dew computing, its use-cases in healthcare, its advantages and limitations, and different service architectures are presented in detail. A comparison with other IoT computing architectures is also discussed with different parameters. The survey also presents the state-of-the-art in this domain indicating various research issues in dew computing while used in healthcare applications. Finally, different future research directions are also pointed out.

With the recent advancement of the cloud, edge, and fog computing methodology data processing and buffering become more crucial tasks. This is even more critical for real-time applications like the Internet of Drone Things. The traditional edge-fog-cloud methodology highly relays on strong Internet connectivity. In case of a mission-critical situation like UAV-based surveillance, aerial reconnaissance mission, or disaster management the network connectivity becomes extremely intermittent. As a result of that, there is a high chance of packet loss. To avoid this situation, the Dew computing methodology can be considered. In this system, the state-of-the-art Dew-enabled nodes will be taken into account as a part of the Internet of Drone Things structure to ensure Dew as a service phenomenon. This chapter primarily investigates the different components of the methodology of Dew as a Service (DewaaS). Secondly, the impact of Dew as a service intermittently connected IoDT and the technical challenges. Finally, the possible use cases of DewaaS for mission-critical Drone applications.

Traditional agriculture is the most expensive method of cultivation as it requires a lot of resources like fertilized soil, water, human labour, chemical fertilizers, pesticides, etc. For nearly a decade, research has been carried out on Dew Intelligent-enabled precision farming to benefit farmers with higher yields and lower costs. Hydroponic strategies, such as aeroponics, have several advantages over traditional agriculture and are aimed at improving agricultural efficiency and reducing environmental impact, enhancing productivity, and abating loss to the environment due to traditional cultivation. This paper proposed an idea of a hybrid Internet of Agriculture Things with the automatic and manual mode of control using 5G Narrow Band Internet of Drone Things (5GNB-IoDT) and Light Fidelity (Li-Fi), based on several parameters, such as the temperature, humidity, pH of nutrient solution, and spraying nutrients to the roots of the crops in a more energy-efficient way using Anti-siphon system.

Internet of Things has revolutionised our daily life by providing varied smart applications. Smart healthcare, smart home monitoring, smart city, smart retail, etc., are various sectors where Internet of Things serves as the principal element. Agriculture is one of the significant sectors of a country that also seeks smart solutions. The use of Internet of Things in agriculture has become popular in the last few years. In this chapter, we discuss the use of Internet of Things in smart agriculture along with the use of dew computing. The dew computing paradigm is able to provide access to the data even offline. The architecture of dew computing-based smart agriculture has been demonstrated. Various machine learning algorithms used for data analysis have been discussed. The advantage of using dew computing over the conventional cloud-only system, edge/fog computing-based system, are also highlighted in this chapter. From the simulation results, we observe that the dew computing-based paradigm has approximately 40% and 55% lower latency than the edge-based and cloud-only paradigms, respectively.

Our civilization has evolved into a global information society from the very dawn of the “computer era.” The early innovators focused on computers and information interconnectivity. We are currently living in a digitized era. This electronic development has impacted almost every industry. Even the agricultural sector is constantly evolving. The method of agriculture has undergone a significant change because of technological development and the use of industrial machinery. We will now look at the impact of the Internet of Things (IoT) on the agricultural industry. Agriculture in the modern world is integrated with cutting-edge technologies like GPS and sensors that allow us to interact with one another, assess the data, and exchange that information between them. IoT provides service in the form of cloud to agriculture. In addition to offering farmers solutions based on recommendations for cutting-edge cultivation methods, the agriculture cloud and IoT service also provide a particular skill service on crop cultivation, pricing, fertilizers, and disease diagnostic methods. In the context of cloud computing, “dew computing” refers to an on-premises computer software-hardware organization paradigm in which the on-premises computer offer capability both independent of cloud services and collaborative with them. Through automation, cloud computing and Dew computing can increase computational scientific productivity. We can use them in various IoT applications because of capabilities like sensors integration and actuators, scalability, low-power consumption, and digital transmission. Monitoring irrigation systems, farms, fertilizer use under control, soils, and water quality, among other things. In this chapter, we have tried to accumulate all these ideas in a single row to give our readers a picture of the recent IoT trends in dew-enabled agricultural consumer products.