In analyzing project regressions, automation has emerged as a major agenda in managing changes in software which requires minimum manual intervention. For rapid testing environment, software development processes such as Agile, Scrum, and XP processes depend on continuous integration tools. There is no single tool to handle the project automation, and the main challenge is dependency on multiple tools. The proposed automation tool should support configuration, execution, and debugging facility. Integrating the project automation works such as software configuration management tools Mercurial and Git, job scheduling tools like Jenkins and Apache Continuum, test management tools like TestNG and Selenium need tight integration which is a challenge. The existing PKI infrastructure for access control does not share data among the software tools and processes increasing the complexity when an organization needs to leverage the existing cloud services. The proposed approach optimizes the execution time by taking single CSV with input test case and metadata information and efficiently group and executes the tests automatically. The proposed method includes implementation of security access control mechanism for the jobs execution platform in cloud environment.
Internet of things (IoT) defines a network of virtual reality objects, software, and other technologies for the purpose of connecting and exchanging data with other devices and applications on the internet. The 'object' may refer to a connected medical device, a biochip transponder (think livestock), a solar panel, a connected motor with sensors that notify the driver of a number of potential problems (fuel, tire pressure, necessary adjustments, and more), or any object, sensory, competent to collect and transfer data over the network. The use of IoT technology is extensive, as it is flexible in almost any technology that can provide relevant information on its performance, and even environmental conditions that need to be monitored and remotely controlled. Other uses include the integration of IoT technology in hospital beds, provided with smart beds, equipped with special sensors to detect vital signs, blood pressure, oximeter, and body temperature, among others. This chapter attempts to explore and understand as how IoT is used in the healthcare sector.
The virtual network which is regarded as a bridge between real-world applications and computerized systems is termed Internet of Things (IoT). Internet of Things can access the real-world application by considering the wireless sensor network and internet facility as its main technology. The Internet o Things (IoT) comprises a global network that connects sensors, electronic devices, and software. Fog computing requires managing services among the various fog nodes. Fog computing plays a major role in the reduction in latency and energy consumption. Traces of fog nodes help to identify the location awareness to the IoT destination. As the fog nodes are geographically distributed, they can support high availability and scalability factors in large amounts of data provided by various sensors in industries. The heterogeneity issues can be handled by the proposed cognitive fog of things system by supporting interoperability and flexibility in sensors connected to machinery. The proposed work comprises of reduction in energy efficiency and latency reduction in the industrial sector with the fault analysis from the data received from sensors in machinery. The proposed system consists of the newly developed cognitive fog of things with optimization techniques. This work determines the impact of data transmission in cloud computing with the fog computing layer to improve the energy efficiency, delay time, and throughput.
Many popular online social networks such as Twitter, LinkedIn, and Facebook have become increasingly popular. In addition, a number of multimedia networks such as Flickr have also seen an increasing level of popularity in recent years. Many such social networks are extremely rich in content, and contain tremendous amount of content and linkage data which can be leveraged for analysis. The linkage data is essentially the graph structure of the social network and the communications between entities; whereas the content data contains the text, images and other multimedia data in the network. The growth of the usage and penetration of social media in the recent years has been enormous and unprecedented. This significant increase in its usage and increased number of users, there has been trend of a substantial increase in the volume of information generated by users of social media. Irrespective of primary domain in which organization is operating in to, whether it is insurance sector, social media (including facebook, twitter etc), medical science, banking etc. Virtually a large number of varying nature and services of organizations are making significant investments in social media. But it is also true that many are not systematically analyzing the valuable information that is resulting from their investments. This chapter aims at providing a data-centric view of online social networks; a topic which has been missing from much of the literature and to draw unanswered research issues which can be further explored to strengthen this area.
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