Abstract In this article, we propose to use shuffled frog leaping algorithm (SFLA) in order to provide the quality of service (QoS) requested by the secondary user (SU) in orthogonal frequency division multiplexing‐based cognitive radio (CR) systems. The performance of the SFLA was evaluated through three transmission modes (emergency, multimedia, and low battery). SFLA provided the best possible configuration in a multicarrier context and thus proved its effectiveness to satisfy the needed QoS for the SU in CR systems. The obtained simulation results showed that SFLA offers better performance compared with genetic algorithms.

Summary Cloud computing services are used to fulfill user requests, often expressed in the form of tasks and their execution in such environments requires efficient scheduling strategies that take into account both algorithmic and architectural characteristics. Unfortunately, this problem is known to be NP‐hard in its general form. Despite the fact that several studies have been published in the literature, there are still interesting and relevant questions to be addressed. Indeed, most of the previous studies focus on a single objective and in the case where they deal with a set of objectives, they use a simple compromise function and do not consider how each of the parameters might influence the others. To this end, we propose an efficient task scheduling algorithm which is based on the pollination behavior of flowers and makes use of both Pareto optimality principle and TOPSIS technique to improve the quality of the obtained solutions. Both single and multiobjective optimization variants are investigated. In the latter case, three optimization criteria are considered, namely, minimizing the time makespan or schedule length, the execution cost, and maximizing the overall reliability of the task mapping. Different test‐bed scenarios and QoS metrics were considered and the obtained results corroborate the merits of the proposed algorithm.

Summary With its ability to “minimize human intervention when generating, exchanging and consuming data,” the Internet of Things (IoT) is increasingly deployed in all sectors, in particular in the healthcare sector. With IoT, telehealth has become the new paradigm in healthcare, as it helps keep patients connected with wearable devices and other remote patient monitoring tools in order to help practitioners work more efficiently. However, telehealth implies that patients share their personal and physiological data remotely with the hospital staff, which can put the patient's privacy at risk. Thus, the establishment of access control is mandatory. Therefore, the objective of this article is to achieve a distributed and reliable access control for telehealth systems using smart contract‐enabled blockchain technology. To do so, we propose three different smart contract‐based access control approaches. We evaluate the three propositions and compare them with related work in terms of latency of access‐request response and gas consumption related to contract deployment, function execution and different responses, furthermore, we give a security analysis.

Summary The field of telecommunication has undergone a very rapid technological evolution, which has forced researchers to find techniques that allow better exploitation of hardware and software. Among the proposed technologies, cognitive radio, a concept that was designed after several technologies such as software radio. Cognitive radio has been widely used for opportunistic access of the shared spectrum and has defined the cognitive nodes by their ability to intelligently adapt the environment to achieve specific objectives through advanced techniques. In this context, clustering techniques were adopted in cognitive radio networks (CRNs) due to their great advantages especially for routing. In this article, we propose a parallel mode of the k‐NN algorithm. The aim is to make a fast assignment of radio nodes in CRNs organized in the form of clusters. The obtained results are very satisfactory because we have been able to reduce to about 50% the execution time of the basic algorithm (sequential).

Summary Clouds provide to users on‐demand access to large computing and storing resources and offer over on premise IT infrastructures many advantages in terms of cost, flexibility, and availability. However, this new paradigm still faces many challenges, and in this paper, we address the load balancing problem. Even though many approaches have been proposed to balance the load among the servers, most of them are too sensitive to the fluctuation in the clouds load and produce unstable systems. In this paper, we propose a new distributed load balancing algorithm, based on adaptive starvation threshold. It tries to balance the load between the servers while minimizing the response time of the cloud, maximizing the utilization rate of the servers, decreasing the overall migration cost, and maintaining the stability of the system. The performance of the proposed algorithm was compared to a well‐known load balancing algorithm, inspired from the honey bee behavior (HBB). The experimental results showed that the application of the proposed load balancing algorithm gives considerable performance gains and a significant reduction in number of migrations when compared to the performance of the HBB algorithm.

The major challenge in a mobile environment is the provisioning of quality of service (QoS) guarantees that different applications demand considering the highly dynamic nature of this environment. In this context, providing QoS to mobile terminals is a very important field of research. In the integrated networks services, the majority of research seeks to extend the RSVP protocol to a mobile environment. Another way to obtain a better use of the resources is to determine the future locations of the mobile terminal. This paper describes a resource management approach for end-to-end QoS in the mobile networks; it is based on the QoS NSLP signaling application resulting from NSIS working group. This reservation is based on an object called MSpec (mobility specification) which determines the future location of the mobile terminal. The MSpec object is a part of a user's mobility profile