Luisa Caeiro

OConS: Towards Open Connectivity Services in the Future Internet

The recent advances on networking technologies (both at the access and the core realms) together with the ever-increasing requirements of the end-users and their applications/services call for an open approach, yet with a clear migration strategy, so as to avoid the well-known shortcomings and limitations of clean-slate approaches. These requirements have streamlined the design of a novel (yet not revolutionary) architecture framework based on the identification of functional entities and their interfaces. The most distinguishing feature is its flexibility, allowing its adaptation to already existing protocols/technologies/algorithms as well as to novel solutions.

OConS Supported on Demand Radio Resource Allocation for Virtual Connectivity

With the increase of mobile network utilisation, the virtualisation of wireless resources becomes an important issue in the overall Virtual Networks (VNets) process. In this paper, the On Demand Virtual Network Radio Resource Allocation (OnDemand VRRA) mechanism is proposed to take advantage of the set of shared resources available within a cluster of wireless resources from different Radio Access Technologies (RATs) for wireless virtualisation. Optimising resource utilisation satisfying the VNet contracted capacity is its main objective. Furthermore, the mechanism is modelled according to the Open Connectivity Services (OConS) architecture, in order to demonstrate the advantages of its use within the OConS framework. Simulation results show that the introduction of OnDemand VRRA allows supporting the minimum bandwidth requirement in a wireless cluster, composed of several physical base stations from different RATs. The percentage of operation out of contract (i.e., below the virtual operator’s contracted capacity) for a VNet with guaranteed minimum service is zero for a number of end users in the VNet up to 80% of the total, which is higher than in other circumstances. One also observes that VNets providing guaranteed services can achieve the contracted data rate independently of the number of end users in other VNets.

Open connectivity services for the future internet

In this paper we present an Open Connectivity Services architecture, which has been conceived such as to cope with the challenges posed by the Future Internet. By relying on currently working solutions and establishing a trustworthy migration strategy, the proposed architecture provides a flexible framework that supports both legacy and enhanced connectivity mechanisms. It is able to dynamically adapt the operation of the involved mechanisms according to the particular requirements of the services and applications. This open architecture is based on three main modules (information gathering, decision taking and decision enforcement) which mimic the basic functionalities of any connectivity mechanism. By having a common way of representing current and future mechanisms, the OConS operation eases the instantiation, launch and interconnection of mechanisms by the specified orchestration procedures. A challenging flash crowd scenario is presented for validation of the architecture, where enhanced connectivity mechanisms support both cloud networking and network of information use cases.

A Service-Oriented Approach for Radio Resource Management in Virtual RANs

Virtualisation, as a key role player of future mobile communications, promotes the idea of service-oriented architectures. This paper proposes a model of Radio Resource Management (RRM) for emerging Virtual Radio Access Networks, based on the interaction between two separated management entities: Common-RRM (CRRM) to coordinate the radio resources among the Radio Access Technologies (RATs) and a centralised virtualisation platform on top of it, called Virtual-RRM (VRRM), which is responsible for service orchestration among Virtual Network Operators, enabling the definition of various services and policies, separately from vendors and underlying RATs. The main objective of VRRM is to satisfy the Service Level Agreements associated with different service classes to the highest possible level, within the framework of proportional fairness. On the other hand, CRRM is in charge of mapping the demanded capacity of each service onto the most suitable RATs. The model is further extended to deal with extreme situations of resource shortage, resulting from high traffic loads, by introducing delay to lower priority services. The performance of the proposed model is evaluated in a practical multi-RAT scenario. Results confirm that the isolation of service classes is consistent with the introduced serving weights, while all the demanded capacities from different services are responded by the most suitable RATs. Finally, independent of the variation of traffic load, 100% of the aggregated capacity is used.

A modified proportional fair radio resource management scheme in virtual RANs

This paper proposes a model for radio resource management in virtualised radio access networks, based on the criterion of proportional fairness, which is also adapted to deal with the situations when there is not enough capacity to serve all subscribers with an acceptable level of service, the so-called the extreme case. A single virtual network operator providing four different classes of services negotiates the required capacity to serve its subscribers, from a centralised entity called Virtual Radio Resource Management (VRRM). The main goals of VRRM are to maximise the utilisation of resources, while maintaining a level of fairness in the allocation of data rate among different services. However, under extreme situations, the algorithm is modified to react differently, according to the offered traffic load. In general, it keeps serving a number of users having the stringiest Quality of Service (QoS), with the minimum guaranteed data rate, while the rest of users performing lowest QoS priority services are increasingly delayed. The performance of the proposed algorithm is evaluated through a practical heterogeneous network scenario and different evaluation metrics. Results show that when there is enough capacity, the algorithm is capable of satisfying the predefined service level agreements, while keeping fairness, whereas under extreme situations, it delays just enough number of users to free capacity for high priority services. In both cases, the algorithm is capable of maximising the utilisation of resources.