No abstract

In this paper we address the problem of virtual network reconfiguration. In our previous work on virtual network embedding strategies, we found that most virtual network rejections were caused by bottlenecked substrate links while peak resource use is equal to 18%. These observations lead us to propose a new greedy Virtual Network Reconfiguration algorithm, VNR. The main aim of our proposal is to 'tidy up' substrate network in order to minimise the number of overloaded substrate links, while also reducing the cost of reconfiguration. We compare our proposal with the related reconfiguration strategy VNA-Periodic, both of them are incorporated in the best existing embedding strategies VNE-AC and VNE-Greedy in terms of rejection rate. The results obtained show that VNR outperforms VNA-Periodic. Indeed, our research shows that the performances of VNR do not depend on the virtual network embedding strategy. Moreover, VNR minimises the rejection rate of virtual network requests by at least ≃ 83% while the cost of reconfiguration is lower than with VNA-Periodic.

International audienceCloud-Radio Access Network (C-RAN) is a new emerging technology that holds alluring promises for Mobile network operators regarding capital and operation cost savings. However, many challenges still remain before full commercial deployment of C-RAN solutions. Dynamic resource allocation algorithms are needed to cope with significantly fluctuating traffic loads. Those algorithms must target not only a better quality of service delivery for users, but also less power consumption and better interference management, with the possibility to turn off RRHs that are not transmitting. To this end, we propose in this paper a dynamic two-stage design for downlink OFDMA resource allocation and BBU-RRH assignment in C-RAN. Specifically, we first model the resource and power allocation problem in a mixed integer linear problem for real-time fluctuating traffic of mobile users. Then, we propose a Knapsack formulation to model the BBU-RRH assignment problem. Simulation results show that our proposal achieves not only a high satisfaction rate for mobile users, but also minimal power consumption and significant BBUs savings, compared to state-of-the-art schemes

International audienceRecently, operators have resorted to femtocell networks in order to enhance indoor coverage and quality of service since macro-antennas fail to reach these objectives. Nevertheless, they are confronted to many challenges to make a success of femtocells deployment. In this paper, we address the issue of resources allocation in femtocell networks using OFDMA technology (e.g., WiMAX, LTE). Specifically, we propose a hybrid centralized/distributed resource allocation strategy namely Femtocell Cluster-based Resource Allocation (FCRA). Firstly, FCRA builds disjoint femtocell clusters. Then, within a cluster the optimal resource allocation for each femtocell is performed by its cluster-head. Finally, the contingent collisions among different clusters are fixed. To achieve this, we formulate the problem mathematically as Min-Max optimization problem. Performance analysis shows that FCRA converges to the optimal solution in small-sized networks and outperforms two prominent related schemes (C-DFP and DRA) in large-sized ones. The results concern the throughput satisfaction rate, the spectrum spatial reuse, and the convergence time metrics