Quality of service management in emerging wireless networks

Quality of service (QoS) of wireless networks refers to the collective service performances with respect to user expectation and network configuration. Over the years, wireless networks have not only expanded in size, such as geographical area and number of nodes, but also in the variety of services, users, and deployment environments. Small mobile devices, such as smart phones, that allow instantaneous high-speed information access and data processing have radically changed our way of life. Moreover, the development of ad hoc networks allows the easy formation of wireless networks for information sharing and data gathering. Due to various factors, wireless networks are constantly changing. For example, the service pattern, workload, available resources (power supply, bandwidth, beacons, nodes etc.) are not fixed. Therefore, it is important to be able to access and manage the QoS for ensuring the optimal performance of networks. There are basically two aspects to QoS study in wireless networks. One aspect is accessing and diagnosing the status of networks and evaluating the current level of service quality. The other aspect is to study network design to handle the changing factors of networks so that QoS is optimized under the constraint of the available resources and service pattern. This special issue aims to collect papers that study both practical and theoretical models and algorithms for ensuring high quality of service in wireless networks and the approaches for QoS evaluation and diagnosis. In this special issue, we selected four papers from around twenty submissions. A brief introduction to the contributions is presented below. The paper by Yahiya et al. addresses downlink resource allocation strategies in 3GPP long-term evolution using orthogonal frequency division access (OFDMA). The authors consider 3GPP long-term evolution (LTE) resource allocation strategies for allocating higher-layer data to the basic resource allocation units (slots) of OFDMA frames and introduce two simple allocation methods: adaptive slot allocation (ASA) and reservation-based slot allocation (RSA). Both approaches consider a fair resource allocation among different types of service data flow (SDF) by considering their QoS characteristics and their channel qualities. The ultimate objective of the proposed approaches is to maximize the capacity of the system subject to the QoS constraints for each type of SDF in terms of data rate and bit error rate (BER). The two algorithms are compared with two well-known algorithms: the maximum SNR algorithm and the OFDM-TDMA algorithm. Simulation results show that the proposed algorithms achieve good capacity gains for all types of SDFs and perform a trade-off between complexity and performance by simplifying the slot allocation into two steps. The paper by Ren et al. tackles the problem of key management in the Internet of Things (IOT), which is envisioned as the natural evolution of the Internet as heterogeneous network merges. The authors propose a compromise resilient key management scheme including key agreement schemes