Dew Computing

Book Title
Dew Computing

Lead Editor’s Name
Debashis De

CfC Text
The personalization aspect is indispensable for the engrossment of the users in any computing genus. Dew computing is a emerging paradigm which inherits a flexible and super hybrid methodology to afford personal information to users self-regulating of internetwork connectivity. Dew computing encompasses a set of innovative design attributes in terms of hardware and software prototype that includes the dew computer, dew server, dew site, dew database, dew domain name system, dew domain name redirection, Software-as-a-Dew Product, Infrastructure-as-a-Dew Service and super-hybrid-peer-to-peer network. The foremost indication behind the dew computing is to minimize the dependency over obtainable internetwork backhaul, thus reducing network traffic, indirect overall power consumption of the network system as well as data dependency over cloud-fog-edge services. Dew computing provides augmentations of real-time personalized services to users by means of instantaneous web-data that is surf-ready. Further, transparency and loose-coupling with the internetwork configuration is envisioned.

Most people refer to modern mobile and wireless ubiquitous solutions as an IoT application. The encroachments of the technology and establishment of cloud-based systems emerge the idea of the connected world over Internet based on distributed processing frameworks. We want to illustrate in this edited contributions the dew computing architectural approach for IoT solutions and give an organizational outline of the dew server and its connections with IoT devices in the overall cloud-based solutions. Dew servers act as another computing layer in the cloud-based architecture for IoT solutions, and we are going to demonstrate its specific goals and requirements. This is compared to the fog computing and cloudlet solutions with an overview of the overall computing trends. The dew servers are analysed from architectural and organizational aspect as devices that collect, process and offload streaming data from the IoT sensors and devices, besides the communication with higher-level servers in the cloud.

The concept to be on the edge of the Internet network means that the analysed devices and systems will work only as a part of a general common integrated system, such as in the case of cyber-physical systems and various devices that act as an Internet of connected Things. Although post-cloud architectures are most commonly associated with edge computing, a focus in this paper is set on dew computing architecture that extends this concept with a specific architecture out of the edge. The dew computing implementation in cyber-physical systems allows autonomous devices and smart systems, that can collaborate and exchange information with the environment, still be independent of other external systems or perform in a connected more complex cyber-physical system of systems.

Internet of Things is a promising paradigm that integrates additionally a plethora of heterogeneous computational devices, incorporating the crowd, frameworks, additional system elements, and infrastructure. Information sensing, modelling, retrieval, and distribution perform an emerging role in the Internet of Things network. Dew computing is a challenging research issue, which needs to demonstrate its impact on the sensor data in the domain of parallel and distributed computing. We are also going to deploy the analysing schemas of the dew-cloud computing-based mobile crowdsensing and crowdsourcing framework in this in this edited volume, to address the dew computing effectiveness in the context of the Internet of Things. The crowdsourcing paradigms are efficient to collect and analyse billions of information efficiently with a diminutive cost. In this promising paradigm, participated sound sensing devices sense acoustic information from the environment; transmit the sensor data to fog computing devices through dew repository, and eventually, cloud data centre stores the processed data for providing aggregated information and relevant services to the end-users. We have also the responsibilities to discuss the system performance metrics, in terms of information transmission time, service latency, and energy dissipation in this endeavour. The overall goal of this volume is to conceptualize, how the end-users can be benefitted from data analytics through intelligent data sensing, computing, analytics, and distributed scenario using a dew-cloud computational framework over the Internet of Things environment.


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