Heterogeneous Statistical Quality-of-service Research Articles

Scalable Virtualization and Offloading-Based Software-Defined Architecture for Heterogeneous Statistical QoS Provisioning Over 5G Multimedia Mobile Wireless Networks

As a crucial step moving towards the next generation of super-fast wireless networks, recently the fifth-generation (5G) mobile wireless networks have received a plethora of research attention and efforts from both the academia and industry. The 5G mobile wireless networks are expected to provision distinct delay-bounded quality of service (QoS) guarantees for a wide range of multimedia services, applications, and users with extremely diverse requirements. However, how to efficiently support multimedia services over 5G wireless networks has imposed many new challenging issues not encountered before in the fourth-generation wireless networks. To overcome these new challenges, we propose a novel network-function virtualization and mobile-traffic offloading based software-defined network (SDN) architecture for heterogeneous statistical QoS provisioning over 5G multimedia mobile wireless networks. Specifically, we develop the novel SDN architecture to scalably virtualize wireless resources and physical infrastructures, based on user’s locations and requests, into three types of virtual wireless networks: virtual networks without offloading, virtual networks with WiFi offloading, and virtual networks with device-to-device offloading. We derive the optimal transmit power allocation schemes to maximize the aggregate effective capacity, overall spectrum efficiency, and other related performances for these three types of virtual wireless networks. We also derive the scalability improvements of our proposed three integrated virtual networks. Finally, we validate and evaluate our developed schemes through numerical analyses, showing significant performance improvements as compared with other existing schemes.

Heterogeneous Statistical QoS Provisioning Over Airborne Mobile Wireless Networks

Airborne mobile wireless networks (AMWNs), which use spacecrafts and aircrafts such as satellites, airships, airplanes, unmanned aerial vehicles, and other high/medium/low-altitude platforms (HAPs/MAPs/LAPs) can efficiently support high dynamic network topologies and weakly connected communication links. Due to the dramatic dynamics of the AMWNs, it is very difficult to provide the deterministic delay-bounded quality of service (QoS) provisioning for time-sensitive real-time traffics (such as video and audio) over the AMWNs. Alternatively, the statistical delay-bounded QoS provisioning provides an efficient way for guaranteeing delay-bounded QoS requirements for real-time traffics over the AMWNs. On the other hand, because of the diversity of real-time traffics, it is highly demanded to consider the heterogeneity of delay-bounded QoS requirements for distinct real-time services under different HAPs/MAPs/LAPs in the AMWNs. In this paper, we establish the heterogeneous statistical QoS provisioning framework to support the diverse real-time services over the AMWNs. In particular, we formulate the optimization problem to maximize the aggregate effective capacity subject to heterogeneous statistical delay-bounded QoS requirements for both downlink and uplink transmissions-based AMWNs groups (AMWNGs) in the AMWNs. We solve the aggregate effective capacity maximization problems and derive the optimal heterogeneous statistical QoS-driven power allocation schemes for the AMWNs. The numerical analyses we obtained verify that our developed optimal heterogeneous statistical QoS-driven power allocation schemes can significantly increase the aggregate effective capacity for the AMWNs than the other existing schemes.

Heterogeneous Statistical QoS Provisioning Over Wireless Powered Sensor Networks

The wireless energy transfer, which is a promising technology for the wireless sensor networks (WSNs), can efficiently solve the energy scarcity that results from the application boosting. However, not only the energy scarcity, but also the quality of service (QoS) guarantees need to be taken into account for the WSNs. Different types of applications in the WSNs impose the new challenge on heterogeneous QoS provisioning for the WSNs. To solve the above problem, in this paper, we develop the joint downlink energy assignment and uplink power control scheme with the heterogeneous statistical QoS provisioning (HeP) for wireless powered sensor networks (WPSNs). In particular, we build up the HeP model, where the aggregate effective capacity (AEC) is defined as the aggregate throughput under the statistical QoS constraints for the WPSNs. Based on the mode, we formulate the AEC maximization problems for uniformed time division and dynamic time allocation scenarios, respectively. For the uniformed time division scenario, we divide the AEC maximization problem into the hybrid access point determined downlink energy assignment problem and the sensor node determined uplink power control problem. Then, we solve these problems and obtain the corresponding closed-form solutions. For the dynamic time allocation scenario, we develop the joint time allocation, downlink energy assignment, and uplink power control scheme to maximize the AEC and iteratively derive the scheme. Extensive simulations are conducted to demonstrate the effect of heterogeneous statistical QoS on our developed resource allocation schemes for WPSNs. The results show that the HeP resource allocation schemes are superior to the schemes with homogeneous statistical QoS guarantees.