Abstract-The increasing number of disasters around the world calls for a new direction in building the networks; this direction is known as disaster-resilient networks. In this paper, we consider the effect of post-disaster traffic on the core network performance. We evaluate the network blocking during single node flooding with different flood sizes. Then we study four mitigation approaches to maximally serve the traffic floods using the excess capacity, traffic filtering, rerouting and DifferentiatedServices. The results show that the studied approaches reduce blocking by 50% in the worst cases.

In this paper, we investigate the energy efficiency that can be achieved by using traffic scheduling in IP over WDM networks. A mixed integer linear programming model is developed to optimize routing and scheduling in dynamically arriving demands, where part of the demands can be allocated within a sliding window. The results show that scheduling improves the energy efficiency of non-bypass IP/WDM networks, with traffic grooming by up to 25% and blocking is reduced by 30%.

In this paper, we present three heuristics for mitigating post-disaster traffic floods. First exploiting the excess capacity, second rerouting backup paths, finally redistributing the whole traffic by rerouting the working and protection paths to accommodate more floods. Using these mitigation approaches can reduce the blocking by up to 30%.

Epilepsy is one of the widespread disorders. It is a noncommunicable disease that affects the human nerve system. Seizures are abnormal patterns of behavior in the electricity of the brain which produce symptoms like losing consciousness, attention or convulsions in the whole body. This paper demonstrates an effective electroencephalogram (EEG) based seizure detection method using discrete wavelet transformation (DWT) for signal decomposition to extract features. An automatic channel selection method was proposed by the researcher to select the best channel from 23 channels based on maximum variance value. The records were segmented into a nonoverlapping segment with long 1-S. The support vector machine (SVM) model was used to automatically detect segments that contain seizures, using both frequency and time domain statistical moment features. The experimental result was obtained from 24 patients in CHB-MIT database. The average accuracy is 94.1, sensitivity is 93.5, specificity is 94.6 and the false positive rate average is 0.054.

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As the Internet grows in capacity, the energy consumption of Information and Communication Technologies (ICT) are significantly increasing. Significant research efforts on energy conservation have been devoted to devise different technological solutions to address raised concerns surrounding the power consumption of networking equipment and its impact firstly on the emission of greenhouse gases and secondly on electricity bills. In this work, we investigate energy-efficient physical topologies for NSF IP over wavelength-division multiplexing (WDM) network for the purpose of minimizing energy consumption by redesigning its current physical connectivity. We implement different network topologies, such as implementing the small-world, scale-free (SFN), and random networks on the NSF network, then evaluate and compare its physical properties and network power consumption with the current NSF topology design using a mixed-integer linear programming model, all with the aim of minimizing the network total power consumption. The evaluation shall optimize and minimize the embodied energy consumption of network equipment in the IP and optical layers. Results have demonstrated that the implementation of the proposed energy-minimized topology designs can significantly improve the node’s clustering coefficient, reduce network’s diameter, and reduce energy consumption of the NSF IP over WDM network to 28% if compared with the current design implementation.

A disaster may not necessarily demolish the telecommunications infrastructure, but instead it might affect the national grid and cause blackouts, consequently disrupting the network operation unless there is an alternative power source(s). In this paper, power outages are considered, and the telecommunication network performance is evaluated during a blackout. Two approaches are presented to minimize the impact of power outage and maximize the survival time of the blackout node. A mixed integer linear programming (MILP) model is developed to evaluate the network performance under a single node blackout scenario. The model is used to evaluate the network under the two proposed scenarios. The results show that the proposed approach succeeds in extending the network life time while minimizing the required amount of backup energy.INDEX TERMS -blackout, core network, disaster-resilient, IP/WDM, power outage.

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