No abstract

Cloud computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to cloud customers in a pay-as-you-go, anytime, anywhere manner. Cloud services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The cloud customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We identify and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in cloud computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the cloud computing service selections in different scenarios.

To slow down the spread of COVID-19, governments worldwide are trying to identify infected people and contain the virus by enforcing isolation and quarantine. However, it is difficult to trace people who came into contact with an infected person, which causes widespread community transmission and mass infection. To address this problem, we develop an e-government Privacy-Preserving Mobile and Fog computing framework entitled PPMF that can trace infected and suspected cases nationwide. We use personal mobile devices with contact tracing app and two types of stationary fog nodes, named Automatic Risk Checkers (ARC) and Suspected User Data Uploader Node (SUDUN), to trace community transmission alongside maintaining user data privacy. Each user's mobile device receives a Unique Encrypted Reference Code (UERC) when registering on the central application. The mobile device and the central application both generate Rotational Unique Encrypted Reference Code (RUERC), which broadcasted using the Bluetooth Low Energy (BLE) technology. The ARCs are placed at the entry points of buildings, which can immediately detect if there are positive or suspected cases nearby. If any confirmed case is found, the ARCs broadcast precautionary messages to nearby people without revealing the identity of the infected person. The SUDUNs are placed at the health centers that report test results to the central cloud application. The reported data is later used to map between infected and suspected cases. Therefore, using our proposed PPMF framework, governments can let organizations continue their economic activities without complete lockdown.

No abstract

No abstract

No abstract

Fog computing complements cloud computing by removing several limitations, such as delays and network bandwidth. It emerged to support Internet of Things (IoT) applications wherein its computations and tasks are carried out at the network's edge. Heterogeneous IoT devices interact with different users throughout a network. However, data security is a crucial concern for IoT, fog and cloud network ecosystems. Since the number of anonymous users increases and new identity disclosures occur within the IoTs, it is becoming challenging to grow mesh networks to deliver end to end communications, as the extended IoT networks resemble a mesh architecture. To reinforce data security over IoTs, we deploy a microservice-based blockchain mechanism for fogs, which works as a decentralized client-server network medium (i.e., secured end device-based communication). We implement a blockchain equipped security scheme to be used with a fog-IoT hierarchical tree-based overlay mesh architecture to address and develop the network performance issues. In this study, we consider encryption and decryption delays from IoT and fog-integrated parts to monitor data records and compare them through the developed security scheme. The blocks of a blockchain offer the desired execution results mainly in terms of the algorithmic efficiency, which correlates with the existing algorithms, namely the Advanced Encryption Standard (AES), the Rivest Shamir Adleman (RSA), and the Data Encryption Standard (DES). Our 'BFIM' scheme has an enhanced task scheduling capacity and a more efficient throughput than the AES, DES, RSA resource deliverables (i.e., tasks). Our comprehensive performance evaluation implies that the Blockchain-based Fog IoT Microservice (i.e., BFIM) architecture provides a task delivery efficiency of 78.79% (i.e., task deliverable) and a service delivery efficiency of 83.24% (i.e., task scheduling). The 'BFIM' also has an overall process delivery efficiency of 75% (i.e., time delay, throughput) in the fog layer, rather than a central cloud layer running the AES, DES, and RSA algorithms.

Recent technology has modeled VANET (vehicular adhoc network) communication well in terms of privileges to derive vehicular communication technologically to save time, energy, and money. Due to the increase in powerful technology in modern times, VANETs play a vital role in uplifting daily concerns across vehicles and vehicular identities. Hence, to tune VANETs to become compatible with traditional technologies and increase demand, VANETs require upgrading. The severity and frequency of unwanted occurrences have become a considerable concern for our day-to-day lives relating to vehicular position. Thus, verily updated methodologies or working procedures are needed for the future VANET interplay to eradicate such problems occurring through vehicular identities. This article outlines in technology related to VANETS, future developments, and coping issues by deriving comprehensive frameworks, workflow patterns, upgrading procedures including big data, fog computing, SDN (software defined networking), and SIoT (social Internet of Things). This review article previews an in-depth VANET upgrade possibility to address future problem managements under a range of acceptable scientific themes, indicators, and combinations.