Tshiamo Sigwele

Energy-efficient cloud radio access networks by cloud based workload consolidation for 5G

Next-generation cellular systems like fifth generation (5G) are expected to experience tremendous traffic growth. To accommodate such traffic demand, there is a need to increase the network capacity that eventually requires the deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a lot of energy. With growing complexity of signal processing, baseband units are now consuming a significant amount of energy. As a result, cloud radio access networks (C-RAN) have been proposed as an energy efficient (EE) architecture that leverages cloud computing technology where baseband processing is performed in the cloud. This paper proposes an energy reduction technique based on baseband workload consolidation using virtualized general purpose processors (GPPs) in the cloud. The rationale for the cloud based workload consolidation model is to switch off idle baseband units (BBUs) to reduce the overall network energy consumption. The power consumption model for C-RAN is also formulated with considering radio side, fronthaul and BS cloud power consumption. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution (LTE) RAN system. The proposed scheme saves up to 80% of energy during low traffic periods and 12% during peak traffic periods compared to baseline LTE system. Moreover, the proposed scheme saves 38% of energy compared to the baseline system on a daily average.

Evaluating Energy-Efficient Cloud Radio Access Networks for 5G

Next-generation cellular networks such as fifth-generation (5G) will experience tremendous growth in traffic. To accommodate such traffic demand, there is a necessity to increase the network capacity that eventually requires the deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a significant amount of energy. Meanwhile, cloud radio access networks (C-RAN) has been proposed as an energy-efficient architecture that leverages cloud computing technology where baseband processing is performed in the cloud, i.e., the computing servers or baseband processing units (BBUs) are located in the cloud. With such an arrangement, more energy saving gains can be achieved by reducing the number of BBUs used. This paper proposes a bin packing scheme with three variants such as First-fit (FT), First-fit decreasing (FFD) and Next-fit (NF) for minimizing energy consumption in 5G C-RAN. The number of BBUs are reduced by matching the right amount of baseband computing load with traffic load. In the proposed scheme, BS traffic items that are mapped into processing requirements, are to be packed into computing servers, called bins, such that the number of bins used are minimized and idle servers can then be switched off to save energy. Simulation results demonstrate that the proposed bin packing scheme achieves an enhanced energy performance compared to the existing distributed BS architecture.

Call Admission Control in Cloud Radio Access Networks

Over the past decade, wireless communications has experienced tremendous growth, and this growth is likely to multiply in the near future. The proliferation of mobile users and an ever increasing demand for multimedia services has resulted in greater capacity requirements. Radio frequency spectrum is scarce and cannot meet this ever increasing demand and the required Quality of Service (QoS) will no longer be achieved if efficient Radio Resource Management (RRM) solutions are not found. Conventional Radio Access Networks (RAN) have standalone Base Stations (BS) with capacity preconfigured for peak loads. These RANs have high call blocking and dropping rates since BSs resources cannot be shared. Cloud based RANs (C-RAN) have been proposed as a cost and energy efficient way of meeting high capacity demand of future wireless access networks by consolidating BSs to the cloud. Instead of relying on rejection of new call requests due to limited BS resources, C-RAN takes benefit of the cloud elasticity, which allows dynamic provisioning of cloud BS resources. This paper presents a novel C-RAN Call Admission Control (C-RAN CAC) to ensure Grade of Service (GoS) by improving blocking probability and improvement of call waiting times. Call blocking probability, call average waiting time and system utilization are used to evaluate the performance of the proposed CAC algorithm.

iTREE: Intelligent Traffic and Resource Elastic Energy Scheme for Cloud-RAN

By 2020, next generation (5G) cellular networks are expected to support a 1000 fold traffic increase. To meet such traffic demands, Base Station (BS) densification through small cells are deployed. However, BSs are costly and consume over half of the cellular network energy. Meanwhile, Cloud Radio Access Networks (C-RAN) has been proposed as an energy efficient architecture that leverage cloud computing technology where baseband processing is performed in the cloud. With such an arrangement, more energy gains can be acquired through statistical multiplexing by reducing the number of BBUs used. This paper proposes a green Intelligent Traffic and Resource Elastic Energy (iTREE) scheme for C-RAN. In iTREE, BBUs are reduced by matching the right amount of baseband processing with traffic load. This is a bin packing problem where items (BS aggregate traffic) are to be packed into bins (BBUs) such that the number of bins used are minimized. Idle BBUs can then be switched off to save energy. Simulation results show that iTREE can reduce BBUs by up to 97% during off peak and 66% at peak times with RAN power reductions of up to 27% and 18% respectively compared with conventional deployments.

Saving Energy in Mobile Devices Using Mobile Device Cloudlet in Mobile Edge Computing for 5G

In the future, the next generation cellular networks like fifth generation (5G) will comprise of billions of devices with various applications running on the devices. These applications are computer intensive and drain a lot of battery when executed in the mobile device itself. Mobile Edge Computing (MEC) has been proposed to solve these problems by offloading computation tasks of an application to the edge server in the radio access network (RAN). The conventional MEC framework suffer greater delays which is not suitable for 5G. In this paper, a new MEC framework in heterogeneous networks (HetNet) called MECH is proposed where a mobile device with limited resources has an option of offloading some of its tasks to a group of nearby mobile devices while considering the transmission power, quality of service (QoS) and state of charge (SoC) of the mobile battery. The simulation results demonstrates that the proposed framework extend battery life and reduces delays compared to the traditional MEC paradigm.

DoS Attack Impact Assessment on Software Defined Networks

Software Defined Networking (SDN) is an evolving network paradigm which promises greater interoperability, more innovation, flexible and effective solutions. Although SDN on the surface provides a simple framework for network programmability and monitoring, few has been said about security measures to make it resilient to hitherto security flaws in traditional network and the new threats the architecture is ushering in. One of the security weaknesses the architecture is ushering in due to separation of control and data plane is Denial of Service (DoS) attack. The main goal of this attack is to make network resources unavailable to legitimate users or introduce large delays. In this paper, the effect of DoS attack on SDN is presented using Mininet, OpenDaylight (ODL) controller and network performance testing tools such as iperf and ping. Internet Control Message Protocol (ICMP) flood attack is performed on a Transmission Control Protocol (TCP) server and a User Datagram Protocol (UDP) server which are both connected to OpenFlow switches. The simulation results reveal a drop in network throughput from 233 Mbps to 87.4 Mbps and the introduction of large jitter between 0.003 ms and 0.789 ms during DoS attack.

Security Aware Virtual Base Station Placement in 5G Cloud Radio Access Networks

In fifth generation (5G) cloud radio access networks (C-RAN), baseband processing of base stations (BS’s) will be processed on virtual machines called virtual BSs (VBS) in the centralized cloud architecture. The existing researches mostly focus on how to maximize resource utilization and reduce energy consumption in 5G C-RAN using VBS placement. However, security issues in the context of VBS placement within 5G C-RAN have been rarely addressed. In this paper, a security aware VBS placement (SAV) scheme within 5G C-RAN is proposed where the placement of VBSs to physical machines (PMs) considers the security levels of both the VBS and the PM. A rigorous simulation study is conducted for validating the proposed scheme, which shows a significant security improvement of 16% compared to the heuristic simulated annealing scheme (HSA).

On the Energy Minimization of Heterogeneous Cloud Radio Access Networks

Next-generation 5G networks is the future of information networks and it will experience a tremendous growth in traffic. To meet such traffic demands, there is a necessity to increase the network capacity, which requires the deployment of ultra dense heterogeneous base stations (BSs). Nevertheless, BSs are very expensive and consume a significant amount of energy. Meanwhile, cloud radio access networks (C-RAN) has been proposed as an energy-efficient architecture that leverages the cloud computing technology where baseband processing is performed in the cloud. In addition, the BS sleeping is considered as a promising solution to conserving the network energy. This paper integrates the cloud technology and the BS sleeping approach. It also proposes an energy-efficient scheme for reducing energy consumption by switching off remote radio heads (RRHs) and idle BBUs using a greedy and first fit decreasing (FFD) bin packing algorithms, respectively. The number of RRHs and BBUs are minimized by matching the right amount of baseband computing load with traffic load. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution advanced (LTE-A) system.

Elastic Call Admission Control Using Fuzzy Logic in Virtualized Cloud Radio Base Stations

Conventional Call Admission Control (CAC) schemes are based on stand-alone Radio Access Networks (RAN) Base Station (BS) architectures which have their independent and fixed spectral and computing resources, which are not shared with other BSs to address their varied traffic needs, causing poor resource utilization, and high call blocking and dropping probabilities. It is envisaged that in future communication systems like 5G, Cloud RAN (C-RAN) will be adopted in order to share this spectrum and computing resources between BSs in order to further improve the Quality of Service (QoS) and network utilization. In this paper, an intelligent Elastic CAC scheme using Fuzzy Logic in C-RAN is proposed. In the proposed scheme, the BS resources are consolidated to the cloud using virtualization technology and dynamically provisioned using the elasticity concept of cloud computing in accordance to traffic demands. Simulations shows that the proposed CAC algorithm has high call acceptance rate compared to conventional CAC.