8 research outputs found
Energy-efficiency versus resilience: risk awareness view on dimensioning of optical networks with a sleep mode
Energy Conservation for Wireless Mesh Networks: A PSO Approach with Throughput-Energy Consumption Scheme Using Solar Energy
Part 4: Neural Computing and Swarm IntelligenceInternational audienceA basic problem in the design of Wireless Mesh Networks (WMNs) is presented by the choice of renewable energy for the communication problems in remote regions and post-disaster reconstruction areas. Since the cost and performance are take into consideration as the needs to address the inadequate capacities of links and time-varying traffic demands. In this paper, we aim to find a trade-off between the higher time-varying traffic throughput and lower energy consumption. We propose an optimal approach using particle swarm optimization (PSO) method by formulating this problem into a numerical optimization problem which takes the battery’s charge-discharge constraint into consideration firstly. As a further study, an accelerated approximation that computes this optimal problem for larger cases is put forward. Finally, the efficiency of our proposition is proved by numerical results
Big data analytics in healthcare: A cloud based framework for generating insights
With exabytes of data being generated from genome sequencing, a whole new science behind genomic big data has emerged. As technology improves, the cost of sequencing a human genome has gone down considerably increasing the number of genomes being sequenced. Huge amounts of genomic data along with a vast variety of clinical data cannot be handled using existing frameworks and techniques. It is to be efficiently stored in a warehouse where a number of things have to be taken into account. Firstly, the genome data is to be integrated effectively and correctly with clinical data. The other data sources along with their formats have to be identified. Required data is then extracted from these other sources (such as clinical datasets) and integrated with the genome. The main challenge here is to be able to handle the integration complexity as a large number of datasets are being integrated with huge amounts of genome. Secondly, since the data is captured at disparate locations individually by clinicians and scientists, it brings the challenge of data consistency. It has to be made sure that the data consistency is not compromised as it is passed along the warehouse. Checks have to be put in place to make sure the data remains consistent from start to finish. Thirdly, to carry this out effectively, the data infrastructure has to be in the correct order. How frequently the data is accessed plays a crucial role here. Data in frequent use will be handled differently than data which is not in frequent use. Lastly, efficient browsing mechanisms have to put in place to allow the data to be quickly retrieved. The data is then iteratively analysed to get meaningful insights. The challenge here is to perform analysis very quickly. Cloud Computing plays an important role as it is used to provide scalability.N/
Satellite networking in the context of green, flexible and programmable networks
In order to support heterogeneous services, using the information generated by a huge number of communicating devices, the Future Internet should be more energy-efficient, scalable and flexible than today\u2019s networking platforms, and it should allow a tighter integration among heterogeneous network segments (fixed, cellular wireless, and satellite). Flexibility and in-network programma- bility brought forth by Software Defined Networking (SDN) and Network Functions Virtualization (NFV) appear to be promising tools for this evolution, together with architectural choices and techniques aimed at improving the net- work energy efficiency (Green Networking). As a result, optimal dynamic resource allocation strategies should be readily available to support the current workload generated by applications at the required Quality of Service/Quality of Experience (QoS/QoE) levels, with minimum energy expenditure. In this framework, we briefly explore the above-mentioned paradigms, and describe their potential application in a couple of satellite networking related use cases, regarding traffic routing and gateway selection, and satellite swarms, respectively