Federated learning optimization: A computational blockchain process with offloading analysis to enhance security

The Internet of Things (IoT) technology in various applications used in data processing systems requires high security because more data must be saved in cloud monitoring systems. Even though numerous procedures are in place to increase the security and dependability of data in IoT applications, the majority of outside users can decode any transferred data at any time. Therefore, it is essential to include data blocks that, under any circumstance, other external users cannot understand. The major significance of proposed method is to incorporate an offloading technique for data processing that is carried out by using block chain technique where complete security is assured for each data. Since a problem methodology is designed with respect to clusters a load balancing technique is incorporated with data weights where parametric evaluations are made in real time to determine the consistency of each data that is monitored with IoT. The examined outcomes with five scenarios process that projected model on offloading analysis with block chain proves to be more secured thereby increasing the accuracy of data processing for each IoT applications to 89%

A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security

The most important and difficult challenge the digital society has recently faced is ensuring data privacy and security in cloud‐based Internet of Things (IoT) technologies. As a result, many researchers believe that the blockchain's Distributed Ledger Technology (DLT) is a good choice for various clever applications. Nevertheless, it encountered constraints and difficulties with elevated computing expenses, temporal demands, operational intricacy, and diminished security. Therefore, the proposed work aims to develop a Decentralized Identifiable Distributed Ledger Technology‐Blockchain (DIDLT‐BC) framework that is intelligent and effective, requiring the least amount of computing complexity to ensure cloud IoT system safety. In this case, the Rabin algorithm produces the digital signature needed to start the transaction. The public and private keys are then created to verify the transactions. The block is then built using the DIDLT model, which includes the block header information, hash code, timestamp, nonce message, and transaction list. The primary purpose of the Blockchain Consent Algorithm (BCA) is to find solutions for numerous unreliable nodes with varying hash values. The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. With proper digital signature generation, key generation, blockchain construction and validation operations, secured data storage and retrieval are enabled in the cloud‐IoT systems. By using this integrated DIDLT‐BCA model, the security performance of the proposed system is greatly improved with 98% security, less execution time of up to 150 ms, and reduced mining time of up to 0.98 s

Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms

In contemporary real-time applications, diminutive devices are increasingly employing a greater portion of the spectrum to transmit data despite the relatively small size of said data. The demand for big data in cloud storage networks is on the rise, as cognitive networks can enable intelligent decision-making with minimal spectrum utilization. The introduction of cognitive networks has facilitated the provision of a novel channel that enables the allocation of low power resources while minimizing path loss. The proposed method involves the integration of three algorithms to examine the process of big data. Whenever big data applications are examined then distance measurement, decisions mechanism and learning techniques from past data is much importance thus algorithms are chosen according to the requirements of big data and cloud storage networks. Further the effect of integration process is examined with three case studies that considers low resource, path loss and weight functions where optimized outcome is achieved in all defined case studies as compared to existing approach

Paths to Innovation in Supply Chains: The Landscape of Future Research

This chapter presents a Strategic Research and Innovation Agenda for supply chain and it is the result of an intensive work jointly performed involving a wide network of stakeholders from discrete manufacturing, process industry and logistics sector to put forward a vision to strengthen European Supply Chains for the next decade. The work is based on matching visions from literature and from experts with several iterations between desk research and workshops, focus groups and interviews. The result is a detailed analysis of the supply chain strategies identified as most relevant for the next years and definition of the related research and innovation topics as future developments and steps for the full implementation of the strategies, thus proposing innovative and cutting-edge actions to be implemented based on technological development and organisational change

Advances in Vehicular Ad-hoc Networks (VANETs): challenges and road-map for future development

Recent advances in wireless communication technologies and auto-mobile industry have triggered a significant research interest in the field of vehicular ad-hoc networks (VANETs) over the past few years. A vehicular network consists of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications supported by wireless access technologies such as IEEE 802.11p. This innovation in wireless communication has been envisaged to improve road safety and motor traffic efficiency in near future through the development of intelligent transportation system (ITS). Hence, governments, auto-mobile industries and academia are heavily partnering through several ongoing research projects to establish standards for VANETs. The typical set of VANET application areas, such as vehicle collision warning and traffic information dissemination have made VANET an interesting field of mobile wireless communication. This paper provides an overview on current research state, challenges, potentials of VANETs as well as the ways forward to achieving the long awaited ITS

The reviews and analysis of the state-of-the-art service workflow specification languages

In the globalized market and business environment, enterprises strive to cope with rapid market changes and competition. To sustain competitiveness, enterprises need to continually adapt their business processes to accommodate changes promptly. This view includes the integration of external services with their internal services for required capabilities to catch new business opportunities. A number of services with similar service functionalities are available, posing a great challenge in composing optimized business processes in a timely manner. This requires effective methodologies and tools in selecting services and composing them as service workflows for specified goals. Service workflow technology facilitates these by providing methodologies to support business process modeling and reengineering to optimize and automate processes according to workflow requirement specifications. This paper provides reviews and analysis of the state-of-the-art service workflow specification languages, including (1) Self-Adaptive Configuration based on HMS (2) BAM, (3) CTR, (4) SOLOIST, and (5) SWSpec. These languages are evaluated against the fundamental principles for general service workflow specification languages