Juergen Rochol

Software-defined networking: management requirements and challenges

SDN is an emerging paradigm currently evidenced as a new driving force in the general area of computer networks. Many investigations have been carried out in the last few years about the benefits and drawbacks in adopting SDN. However, there are few discussions on how to manage networks based on this new paradigm. This article contributes to this discussion by identifying some of the main management requirements of SDN. Moreover, we describe current proposals and highlight major challenges that need to be addressed to allow wide adoption of the paradigm and related technology.

Resource sharing in heterogeneous cloud radio access networks

Heterogeneous cloud radio access networks incorporate the heterogeneous network and cloud radio access network concepts for next generation cellular networks. H-CRANs exploit the heterogeneity of macro and small cells from HetNets, enabling cellular networks to achieve higher spectral efficiency. Meanwhile, concepts from C-RANs involving baseband units and remote radio heads enable H-CRANs to insert a centralized point of processing for cellular networks, reducing capital and operational expenditures. In this article, we investigate resource sharing in H-CRANs at three levels: spectrum, infrastructure, and network. For each level, we discuss the benefits and challenges, highlighting key enabling technologies that make resource sharing feasible in H-CRANs, such as software defined radio, virtualization, network function virtualization, and software defined networking. Through these technologies, H-CRANs can be virtualized in an overlay network capable of achieving enhanced infrastructure and spectrum sharing.

Interactive monitoring, visualization, and configuration of OpenFlow-based SDN

Software-Defined Networking (SDN) is an emerging paradigm that arguably facilitates network innovation and simplifies network management. However, in the context of SDN, management activities, such as monitoring, visualization, and configuration can be considerably different from traditional networks. An SDN controller, for example, can be customized by network administrators according to their needs. Such customizations might pose an impact on resource consumption and traffic forwarding performance, which is difficult to assess without an SDN-devoted management system. In this paper, we initially present an analysis of control traffic in SDN aiming to better understand the impact of the communication between the controller and forwarding devices. Afterwards, we propose an interactive approach to SDN management through monitoring, visualization, and configuration that includes the administrator in the management loop. To show the feasibility of our approach a prototype has been developed. The results obtained with this prototype show that our approach can help the administrator to better understand the impact of configuring SDN-related parameters on the overall network performance.

Improving reinforcement learning algorithms for dynamic spectrum allocation in cognitive sensor networks

Cognitive Radio Networks enable a higher number of users to access the spectrum of frequency simultaneously. This access is possible due to the implementation of dynamic spectrum allocation algorithms. In this context, one of the main algorithms found in the literature is the reinforcement learning based approach called Q-Learning. Although been widely applied, this algorithm does not take into account accurate information about the behavior of users neither the channel propagation conditions. In this sense, we propose three improvements to the dynamic spectrum allocation algorithms based on reinforcement learning for cognitive sensor networks. Simulation results show that all the proposed algorithms allow allocating channels with up to 6dB better quality and 4% higher efficiency than Q-Learning.

Managing mobile cloud computing considering objective and subjective perspectives

Mobile Cloud Computing enables mobile devices to augment constrained resources such as processing, storage, and battery autonomy by using the cloud infrastructure. As the network is a key element in integrating mobile devices to the cloud, a proper management of the mobile cloud computing environment is necessary. Such a management must take into account two main perspectives: administrators and end-users perspectives. The administrator is usually concerned with a more objective perspective based on Quality of Service parameters, such as throughput, delay, and jitter. On the other hand, the end-user has a more subjective perspective, observing his/her Quality of Experience when using a mobile cloud application or service. In this article, we introduce a management model and architecture for mobile cloud computing, exploiting both objective and subjective perspectives. As a proof of concept, we prototyped the architecture in a management system called CoLisEU, which allowed us to investigate this architecture and we discuss the benefits of the combined objective and subjective perspectives in our management architecture.

On the impact of hybrid errors on mobile WiMAX networks

Burst and AWGN errors affect mobile WiMAX networks because of propagation conditions generally resulting from the mobility characteristics. Mobile WiMAX networks are inherently vulnerable to transmission errors due to propagation conditions such as multipath fading, shadowing, and Doppler spectrum. To ensure reliable communications, even in adverse physical conditions, errors must be detected and corrected by the receiver device. The traditional approach to deal with this problem is the employment of forward error correction techniques along with bit interleaving during the phase called channel encoding. In this article we propose an hybrid errors model where both burst and AWGN errors are considered. Moreover, we present an error sequence generator, used to simulate and evaluate the use of forward error correction techniques and bit interleaving applied to nomadic (fixed) and mobile WiMAX systems affected by hybrid errors. Simulation results show that using a hybrid error model better reflects the realistic behavior of RF channels, than models which consider only AWGN.

MPLS backbones and QOS enabled networks interoperation

It is believed that in the future the telecommunication and data networks will be integrated into one single network, based on IP switching. One of the technologies that certainly will be adopted in the core of this new network is MPLS. Together with MPLS, other QoS architectures, such as IntServ and DiffServ will be used. As a result of this, a framework that allows the interoperability of the different existing architectures is needed. In this paper, an integration model based on MPLS and DiffServ is presented. The model was tested in the ns2 simulator and the results certify its applicability as the presented model showed better performance in all analyzed QoS parameters: delay, jitter, packet loss and bandwidth.

Evaluating management architectures for Internet of Things devices

The Internet of Things (IoT) is foreseen as a global network infrastructure that provides wireless communication among any kind of objects. One immediate challenge holds: how to manage these objects, considering that they may have limited computational resources. This management can be achieved through the use of gateways, i.e., devices that intermediate wireless communications, minimizing resource consumption of the restrained objects. The communication between gateways and objects can be performed over many architectures. Among these architectures, we highlight the Simple Network Management Protocol (SNMP), the Service Oriented Architecture (SOA), and the Resource Oriented Architecture (ROA). However, there is a lack of deeper investigations to define which is the best architecture to model the communication between gateways and objects. Therefore, the main contribution of this paper is a quantitative evaluation of SNMP, SOA, and ROA as means for the communication between gateways and objects. Results analysis pointed ROA as the most interesting architecture to model the management communication.

A self-adapting connection admission control solution for mobile WiMAX: Enabling dynamic switching of admission control algorithms based on predominant network usage profiles

WiMAX is a connection-oriented wireless network that provides QoS in metropolitan broadband communications. One important component in WiMAX QoS provisioning and management is the Connection Admission Control (CAC), which must be aware of the network conditions (e.g., user traffic demands and physical aspects). In our research, we define the association between a particular user traffic demand and a specific physical condition as a network usage profile. State-of-the-art proposals focus on optimizing CAC algorithms considering a single network usage profile; the adaptation of CAC algorithms when the predominant network usage profile changes is partially or fully neglected. In this article, we introduce a self-adapting CAC solution that, using a library of CAC algorithms, is able to switch the running algorithm according to the current network usage profile. The evaluation results, obtained through simulations, demonstrate that our self-adapting CAC solution is able to detect the changes on the predominant network usage profile. In addition, the results show how much different profiles can impact on the efficiency of CAC algorithms, thus confirming the need of switching the running CAC algorithm so that QoS can be guaranteed for the ongoing connections.

Specification and design of an Ethernet Interface soft IP

The IP (Intellectual Property) for Ethernet Interface is a hardware module designed to execute the MAC (media access control) service on the Ethernet standard. The goal of this IP module is to provide an easy way to develop new devices with connection to an Ethernet LAN (Local Area Network). The standard protocols used make this IP module reusable for different designs with an interface to Ethernet LANs. The Ethernet Interface IP is described and simulated in VHDL.