The cloud is the best method used for the utilization and organization of data. The cloud provides many resources for us via the internet. There are many technologies used in cloud computing systems; each one uses a different kind of protocols and methods. Many tasks can execute on different servers per second, which cannot execute on their computer. The most popular technologies used in the cloud system are Hadoop, Dryad, and another map reducing framework. Also, there are many tools used to optimize the performance of the cloud system, such as Cap3, HEP, and Cloudburst. This paper reviews in detail the cloud computing system, its used technologies, and the best technologies used with it according to multiple factors and criteria such as the procedure cost, speed cons and pros. Moreover, A comprehensive comparison of the tools used for the utilization of cloud computing systems is presented.  

Cloud computing is a new technology which managed by a third party “cloud provider” to provide the clients with services anywhere, at any time, and under various circumstances. In order to provide clients with cloud resources and satisfy their needs, cloud computing employs virtualization and resource provisioning techniques.  The process of providing clients with shared virtualized resources (hardware, software, and platform) is a big challenge for the cloud provider because of over-provision and under-provision problems. Therefore, this paper highlighted some proposed approaches and scheduling algorithms applied for resource allocation within cloud computing through virtualization in the datacenter. The paper also aims to explore the role of virtualization in providing resources effectively based on clients’ requirements. The results of these approaches showed that each proposed approach and scheduling algorithm has an obvious role in utilizing the shared resources of the cloud data center. The paper also explored that virtualization technique has a significant impact on enhancing the network performance, save the cost by reducing the number of Physical Machines (PM) in the datacenter, balance the load, conserve the server’s energy, and allocate resources actively thus satisfying the clients’ requirements. Based on our review, the availability of Virtual Machine (VM) resource and execution time of requests are the key factors to be considered in any optimal resource allocation algorithm. As a results of our analyzing for the proposed approaches is that the requests execution time and VM availability are main issues and should in consideration in any allocating resource approach.

Human Resources HRs are one of the most important elements in the organizations, but it is difficult to manage a large number of human resources, especially in large companies. For this purpose, companies have tended to manage these resources taking advantages of the technology and the Internet. In this research, we will focus on human resources management in different companies and different countries and explore the factors that motivate companies to adopt Electronic Human Resource Management E-HRM as well as the factors that affect its adoption. The results showed that HRM plays a vital role in facilitating organizational processes, save cost and time, it also beneficial for competitive advantages. The findings also explored that E-HRM aspects and factors impact E-HRM adoption are varied from firm to another and from country to another. However, the companies moved towards adopting E-HRM because it mitigates the efforts of HR managers to take a decision.

In this paper, several works has been presented related to the clustering parallel computing for distributed system. The trend of the paper is to focus on the strength points of previous works in this field towards enhancing performance of the distributed systems. This concentration conducted via presenting several techniques where each of them has the weak and strong features. The most challenging points for all techniques vary from increasing the performance of the system to time responding to overcome overhead running of the system. For more specific addressing concurrent computation besides parallel computing classifications for distributed systems, this paper depended comprehensive features study and comparison between SYNC and ASYNC Modes.

Distributed systems performance is affected significantly by cache coherence protocols due to their role in data consistency maintaining. Also, cache coherent protocols have a great task for keeping the interconnection of caches in a multiprocessor environment. Moreover, the overall performance of distributed shared memory multiprocessor system is influenced by the used cache coherence protocol type. The major challenge of shared memory devices is to maintain the cache coherently. Therefore, in past years many contributions have been presented to address the cache issues and to improve the performance of distributed systems. This paper reviews in a systematic way a number of methods used for the cache-coherent protocols in a distributed system.

The Internet has caused the advent of a digital society; wherein almost everything is connected and available from any place. Thus, regardless of their extensive adoption, traditional IP networks are yet complicated and arduous to operate. Therefore, there is difficulty in configuring the network in line with the predefined procedures and responding to the load modifications and faults through network reconfiguring. The current networks are likewise vertically incorporated to make matters far more complicated: the control and data planes are bundled collectively. Software-Defined Networking (SDN) is an emerging concept which aims to change this situation by breaking vertical incorporation, promoting the logical centralization of the network control, separating the network control logic from the basic switches and routers, and enabling the network programming. The segregation of concerns identified between the policies concept of network, their implementation in hardware switching and data forwarding is essential to the flexibility required: SDN makes it less complicated and facilitates to make and introduce new concepts in networking through breaking the issue of the network control into tractable parts, simplifies the network management and facilitate the development of the network. In this paper, the SDN is reviewed; it introduces SDN, explaining its core concepts, how it varies from traditional networking, and its architecture principles. Furthermore, we presented the crucial advantages and challenges of SDN, focusing on scalability, security, flexibility, and performance. Finally, a brief conclusion of SDN is revised.

The exponential growth of the Internet of Things (IoT) technology poses various challenges to the classic centralized cloud computing paradigm, including high latency, limited capacity, and network failure. Cloud computing and Fog computing carry the cloud closer to IoT computers in order to overcome these problems. Cloud and Fog provide IoT processing and storage of IoT items locally instead of sending them to the cloud. Cloud and Fog provide quicker reactions and better efficiency in conjunction with the cloud. Cloud and fog computing should also be viewed as the safest approach to ensure that IoT delivers reliable and stable resources to multiple IoT customers. This article discusses the latest in cloud and Fog computing and their convergence with IoT by stressing deployment's advantages and complexities. It also concentrates on cloud and Fog design and new IoT technologies, enhanced by utilizing the cloud and Fog model. Finally, transparent topics are addressed, along with potential testing recommendations for cloud storage and Fog computing, and IoT.

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