The pervasiveness of wireless technology has indeed created massive opportunity to integrate almost everything into the Internet fabric. This can be seen with the advent of Internet of Things and Cyber Physical Systems, which involves cooperation of massive number of intelligent devices to provide intelligent services. Fairness amongst these devices is an important issue that can be analysed from several dimensions, e.g., energy usage, achieving required quality of services, spectrum sharing, and so on. This article focusses on these viewpoints while looking at fairness research. To generalize, mainly wireless networks are considered. First, we present a general view of fairness studies, and pose three core questions that help us delineate the nuances in defining fairness. Then, the existing fairness models are summarized and compared. We also look into the major fairness research domains in wireless networks such as fair energy consumption control, power control, topology control, link and flow scheduling, channel assignment, rate allocation, congestion control and routing protocols. We make a distinction amongst fairness, utility and resource allocation to begin with. Later, we present their inter-relation. At the end of this article, we list the common properties of fairness and give an example of fairness management. Several open research challenges that point to further work on fairness in wireless networks are also discussed. Indeed, the research on fairness is entangled with many other aspects such as performance, utility, optimization and throughput at the network and node levels. While consolidating the contributions in the literature, this article tries to explain the niceties of all these aspects in the domain of wireless networking.

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Fairness in Wireless Networks:Issues, Measures and Challenges

In the fifth-generation (5G) mobile communication system, various service requirements of different communication environments are expected to be satisfied. As a new evolution network structure, heterogeneous network (HetNet) has been studied in recent years. Compared with homogeneous networks, HetNets can increase the opportunity in the spatial resource reuse and improve users’ quality of service by developing small cells into the coverage of macrocells. Since there is mutual interference among different users and the limited spectrum resource in HetNets, however, efficient resource allocation (RA) algorithms are vitally important to reduce the mutual interference and achieve spectrum sharing. In this article, we provide a comprehensive survey on RA in HetNets for 5G communications. Specifically, we first introduce the definition and different network scenarios of HetNets. Second, RA models are discussed. Then, we present a classification to analyze current RA algorithms for the existing works. Finally, some challenging issues and future research trends are discussed. Accordingly, we provide two potential structures for 6G communications to solve the RA problems of the next-generation HetNets, such as a learning-based RA structure and a control-based RA structure. The goal of this article is to provide important information on HetNets, which could be used to guide the development of more efficient techniques in this research area.

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A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges

Reliability in wireless sensor networks

A hybrid model of Internet of Things and cloud computing to manage big data in health services applications

A comprehensive survey for scheduling techniques in cloud computing

Novel energy and SLA efficient resource management heuristics for consolidation of virtual machines in cloud data centers

Increasing demand for acquiring diverse range of services has led to the establishment of huge energy hungry cloud data centers all around the world. Cloud providers face with major concerns to reduce their energy consumption while ensuring high quality of service based on the Service Level Agreement (SLA). Consolidation is proposed as one of the most effective techniques for online energy saving in cloud environments with dynamic workloads. This paper proposes novel proactive online resource management policies to optimize energy, SLA, and number of migrations in cloud data centers. More precisely, this paper proposes new prediction algorithm for determination of overloaded hosts as well as novel multi-criteria decision making techniques to select virtual machines. The results of simulations using CloudSim simulator shows up to 98.11 % reduction in the output metric which is representative of energy consumption, SLA violation, and number of migrations, in comparison with state of the art.

Novel heuristics for consolidation of virtual machines in cloud data centers using multi-criteria resource management solutions

Novel fuzzy multi objective DVFS-aware consolidation heuristics for energy and SLA efficient resource management in cloud data centers

Mechatronic systems operating in industrial environments are subject to a variety of threats because of harsh conditions. Industrial systems usually use commercial off-the shelf (COTS) equipment which are not robust and safe against hostile conditions and therefore require fault-tolerance considerations. This paper presents a novel and efficient method for online detection of control flow errors, called software-based control flow checking (SCFC). It is implemented purely in software and does not manipulate the hardware architecture of the system. Redundant instructions and signatures are embedded into the program at compile time and are utilized for control flow checking at run time. The signatures of the basic blocks are derived from the program graph. It is shown in the paper that SCFC method can increase single detection capability to 14.7% and the fault coverage to 6.12% averagely in comparison with other methods without any increase in memory and performance overheads. In the paper, besides experimental evaluations, analytical evaluations are also carried out, based on probability principles. The detection ability of each method used is thus computed. These computations verify the experimental results and show that SCFC can detect more errors than other methods suggested in literature. Considering the memory limitations in some (such as space) applications and the trend towards the requirement for faster execution of programs, we suggest a novel metric called fitness parameter which incorporates these. It is a better measure than the previously proposed ones since it considers the fault coverage, the memory overhead and the execution time (performance overhead) of each method simultaneously, as well as the detection capability.

Software-Based Control Flow Checking Against Transient Faults in Industrial Environments

Localization is one of the most important issues in wireless sensor networks and designing accurate localization algorithms is a common challenge in recent researches. Among all localization algorithms, DV-Hop attracts more attention due to its simplicity; so, we use it as a basis for our localization algorithm in order to improve accuracy. The various evolutionary algorithms such as Genetic, Shuffled Frog Leaping and Particle Swarm Optimization are employed in different phases of the main DV-Hop localization algorithm. Simulation results prove that our proposed method decreases the localization error efficiently without additional hardware.

Hassan Taheri

Papers

Novel energy and SLA efficient resource management heuristics for consolidation of virtual machines in cloud data centers

Novel heuristics for consolidation of virtual machines in cloud data centers using multi-criteria resource management solutions

Novel fuzzy multi objective DVFS-aware consolidation heuristics for energy and SLA efficient resource management in cloud data centers

Software-Based Control Flow Checking Against Transient Faults in Industrial Environments

An improved DV-Hop localization algorithm based on evolutionary algorithms