Fifth-generation (5G) wireless networks are projected to bring a major transformation to the current fourth-generation network to support the billions of devices that will be connected to the Internet. 5G networks will enable new and powerful capabilities to support high-speed data rates, better connectivity and system capacity that are critical in designing applications in virtual reality, augmented reality and mobile online gaming. The infrastructure of a network that can support stringent application requirements needs to be highly dynamic and flexible. Network slicing can provide these dynamic and flexible characteristics to a network architecture. Implementing network slicing in 5G requires domain modification of the preexisting network architecture. A network slicing architecture is proposed for an existing 5G network with the aim of enhancing network dynamics and flexibility to support modern network applications. To enable network slicing in a 5G network, we established the virtualisation of the underlying physical 5G infrastructure by utilising technological advancements, such as software-defined networking and network function virtualisation. These virtual networks can fulfil the requirement of multiple use cases as required by creating slices of these virtual networks. Thus, abstracting from the physical resources to create virtual networks and then applying network slicing on these virtual networks enable the 5G network to address the increased demands for high-speed communication.

The massively increasing number of wireless communication devices has led to considerable growths in radio traffic density, resulting in a predictable shortage of the available spectrum. To address this potential shortage, the Cognitive Radio (CR) technology offers promising solutions that aim to improve the spectrum utilization. The operation of CR relies on detecting the so-called spectrum holes, i.e., the frequency bands when they are unoccupied by their licensed operators. The unlicensed users are then allowed to communicate using these spectrum holes. Consequently, the performance of CR is highly dependent on the employed spectrum sensing methods. Several sensing methods are already available or literarily proposed. However, no individual method can accommodate all possible CR operation scenarios. Hence, it is fair to ascertain that the performance of a CR device can be improved if it is capable of supporting several sensing methods. Then it should be able to effectively select the most suitable method. In this paper, several spectrum sensing methods are compared and analyzed, aiming to identify their advantages and shortcomings in different CR operating conditions. Furthermore, it identifies the factors that need to be considered while selecting a proper sensing method from the catalog of available methods.

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There is a growing interest in cloud computing due to its various benefits such as the efficient utilization of computing resources. However, privacy and security concerns are among the main obstacles facing the widespread adoption of this new technology. For instance, it is more desirable for many potential organizations and users that privacy protections and access authorizations on their data stored in the cloud remain under their control and only authorized entities can have access to the data even for the cloud server. In this paper, we propose a method that enables cloud clients more control of data security requirements on their data stored in the cloud. The data is protected by a client before it is sent to the cloud in a secure manner that only authorized users can access it. To provide a complete protection from unauthorized access, even the cloud provider is prevented from revealing the data content and access control policies. The client or data owner has complete control on what methods to use to protect the data and on who can have access on the data. The proposed method is based on a combination of cryptography techniques, including the Chines Remainder Theorem, symmetric and asymmetric encryptions. The proposed method combines access control and key sharing in one mechanism. In addition, the proposed method allows a client to use a unique key to encrypt the data and attaches it securely to its encrypted data. Only authorized users can have access to the key in order to decrypt the encrypted data. The data has all the security requirements independently attached to it including the integrity proof. The proposed method is efficient and has its computational overheard minimized. With all the security requirements and metadata stored with the data itself, the proposed method is also flexible and suitable for protecting clients’ data in the cloud computing environment

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