In this paper, we present a discussion panel of two of the hottest topics in this area namely distributed parallel processing and distributed cloud computing. Various aspects have been discussed in this review paper such as concentrating on whether these topics are discussed simultaneously in any previous works. Other aspects that have been reviewed in this paper include the algorithms, which simulated in both distributed parallel computing and distributed cloud computing. The goal is to process the tasks over resources then readjusted the calculation among the servers for the sake of optimization. These help us to improve the system performance with the desired rates. During our review, we presented some articles which explain the designing of applications in distributed cloud computing while some others introduced the concept of decreasing the response time in distributed parallel computing.

Internet of Things (IoT) is a huge number of objects which communicate over a network or the Internet. These objects are a combination of electronics, sensors, and a software to control the way of working other parts of the object. Each object generates and collects data from its environment using sensors and transfers them to other objects or a central database through a channel. Keeping this generated data and its transformation is one of the biggest challenges in IoT today and it is one of the biggest concerns of all organizations that they use the IoT technology. In this paper, the most crucial researches related to security in the IoT field have been reviewed and discussed while taking account of the great power of the Quantum Computers. Significant attributes of these studies are compared. IoT security ranges from the software layer security, board and chip, vulnerable cryptography algorithm, protocol and network security, social engineering, malware like (viruses, ransomware, trojan horses). Due to a variety of IoT devices and the rapid emergence of new devices, it is difficult to measure the security of IoT systems and identify risks and vulnerabilities.

Nowadays, continuously accessing Internet services is vital for the most of people. However, due to Denial of Service (DoS) and its severe type `Distributed Denial of Service (DDoS), online services becomes unavailable to users in sometimes. Rather than DDoS is dangerous and has serious impact on the Internet consumers, there are multiple types of that attack such Slowrise, ping of death and UDP, ICMP, SYN flood, etc. In this paper, the effect of HTTP and SYN flood attack on the most recent and widely used web servers is studied and evaluated. Systematic performance analysis is performed on Internet Information Service 10.0 (IIS 10.0) on Windows server 2016 and Apache 2 on Linux Ubuntu 16.04 Long Term Support (LTS) server. Furthermore, the key metrics of the performance are average response time, average CPU usage and standard deviation as a responsiveness, efficiency and stability of the web servers. The results show that the IIS10.0 outperformed Apache2 web server in efficiency and responsiveness during HTTP flood attack. However, Apache2 web server achievement was more responsive and performed more stability with SYN flood attack.

The quantity of data published on the Web according to principles of Linked Data is increasing intensely. However, this data is still largely limited to be used up by domain professionals and users who understand Linked Data technologies. Therefore, it is essential to develop tools to enhance intuitive perceptions of Linked Data for lay users. The features of Linked Data point to various challenges for an easy-to-use data presentation. In this paper, Semantic Web and Linked Data technologies are overviewed, challenges to the presentation of Linked Data is stated, and LOD Explorer is presented with the aim of delivering a simple application to discover triplestore resources. Furthermore, to hide the technical challenges behind Linked Data and provide both specialist and non-specialist users, an interactive and effective way to explore RDF resources.

The ever-increasing amount of data available on the web is the result of the simplicity of sharing data over the current Web. To retrieve relevant information efficiently from this huge dataspace, a sophisticated search technology, which is further complicated due to the various data formats used, is crucial. Semantic Web (SW) technology has a prominent role in search engines to alleviate this issue by providing a way to understand the contextual meaning of data so as to retrieve relevant, high-quality results. An Exploratory Search System (ESS), is a featured data looking and search approach which helps searchers learn and explore their unclear topics and seeking goals through a set of actions. To retrieve high-quality retrievals for ESSs, Linked Open Data (LOD) is the optimal choice. In this paper, SW technology is reviewed, an overview of the search strategies is provided, and followed by a survey of the state of the art Linked Data Browsers (LDBs) and ESSs based on LOD. Finally, each of the LDBs and ESSs is compared with respect to several features such as algorithms, data presentations, and explanations.