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In network virtualisation, which enables multiple virtual routers to share one physical router, how to ensure the scalability and performance of concurrent virtual routers is a challenging problem in virtual router design. Since physical router only has limited memory resource, it is significant to efficiently store multiple forwarding tables for virtual routers. Motivated by the idea of diminishing the dissimilarities in forwarding tables, the authors propose a novel trie shifting scheme with depth adjusting, and finally obtain a memory-efficient shared trie for all forwarding tables. In this scheme, by diminishing the dissimilarity in the depth and in the shape, memory is saved by reducing the trie nodes needed in the shared trie. In the simulation, the scheme needs only 10% of trie nodes, compared with storing forwarding tables separately. Extensive simulation based on three sets of forwarding tables, which are collected from five backbone routers, shows that the scheme saves memory by reducing the number of trie nodes between 4.7 and 7.8%, compared with the latest scheme in related work. Moreover, this scheme achieves more improvement when the dissimilarity is increasing. [ABSTRACT FROM AUTHOR]

In guaranteed-type applications the bandwidth planning and cost management are two important issues in deployment of optical core networks. A two-stage fuzzy-based approach is proposed for accommodating long-term demand uncertainties in dense wavelength division multiplexing optical networks. Here, the uncertainties are modelled using the Gaussian fuzzy membership functions. First, the forecasted part of demand matrix is introduced to Dijkstra shortest path-based routing algorithm. Then, the available wavelengths are assigned to demand uncertainties. Unlike existing algorithms, different bandwidth cost factors are assigned to the links of a lightpath according to network and links state information. The performance of proposed approach is evaluated on a typical optical link for uncertain traffic loads in Erlang mode. Simulation results show that the proposed fuzzy-based approach is up to 29% cost-effective for accommodating network demands in real-world applications comparing to existing algorithms. [ABSTRACT FROM AUTHOR]

In this study, the authors propose a new method for constructing irregular low-density parity-check codes (LDPC codes) with midterm or short block lengths. It is a Monte-Carlo simulation-based optimisation procedure called downhill simplex which uses progressive edge growth method for Tanner graph construction in cost function evaluations. It outperforms the density evolution (DE) method in both efficiency and performance. The efficiency of the authors' proposal mostly depends on the Monte-Carlo simulation time which owing to the midterm block lengths is relatively small compared to the time delay of the conventional DE method. Simulation results show that for block length of 3200 and a relatively low code rate 3/8, LDPC codes constructed using the authors' proposal noticeably outperform those constructed with DE method by more than 0.2 dB in the entire signal to noise ratio (SNR) range under AWGN channel. [ABSTRACT FROM AUTHOR]

In order to overcome the negotiation procedure bottleneck of the standard DCF in wireless mesh networks, the authors propose a new channel reservation function (CRF) that reduces the negotiation overhead of the DCF, which as a result reduces the overall transmission delay effectively without of any extra bandwidth consumption. Furthermore, the authors provide an analytical model for the proposed scheme for which the simulation results measure the amount that the new method can reduce the average total delay for both regular and fragmented mesh topologies demonstrating superiority of the new method over the classic 802.11 solution. Additionally, the authors extend the scheme to multichannel CRF upon which the proposed method can be used for multichannel applications. [ABSTRACT FROM AUTHOR]