DTN Trustworthiness for Permafrost Telemetry IoT Network

The SHETLAND-NET research project aims to build an Internet of Things (IoT) telemetry service in Antarctica to automatize the data collection of permafrost research studies on interconnecting remote wireless sensor networks (WSNs) through near vertical incidence skywave (NVIS) long fat networks (LFN). The proposed architecture presents some properties from challenging networks that require the use of delay tolerant networking (DTN) opportunistic techniques that send the collected data during the night as a bulk data transfer whenever a link comes available. This process might result in network congestion and packet loss. This is a complex architecture that demands a thorough assessment of the solution’s viability and an analysis of the transport protocols in order to find the option which best suits the use case to achieve superior trustworthiness in network congestion situations. A heterogeneous layer-based model is used to measure and improve the trustworthiness of the service. The scenario and different transport protocols are modeled to be compared, and the system’s trustworthiness is assessed through simulations.

Design and Evaluation of Bulk Data Transfer Extensions for the NFComms Framework

We present the design and implementation of an indirect messaging extension for the existing NFComms framework that provides communication between a network flow processor and host CPU. This extension addresses the bulk throughput limitations of the framework and is intended to work in conjunction with existing communication mediums. Testing of the framework extensions shows an increase in throughput performance of up to 268x that of the current direct message passing framework at the cost of increased single message latency of up to 2x. This trade-off is considered acceptable as the proposed extensions are intended for bulk data transfer only while the existing message passing functionality of the framework is preserved and can be used in situations where low latency is required for small messages.

A Dynamic Programmable Network for Large-Scale Scientific Data Transfer Using AmoebaNet

Large scientific experimental facilities currently are generating a tremendous amount of data. In recent years, the significant growth of scientific data analysis has been observed across scientific research centers. Scientific experimental facilities are producing an unprecedented amount of data and facing new challenges to transfer the large data sets across multi continents. In particular, these days the data transfer is playing an important role in new scientific discoveries. The performance of distributed scientific environment is highly dependent on high-performance, adaptive, and robust network service infrastructures. To support large scale data transfer for extreme-scale distributed science, there is the need of high performance, scalable, end-to-end, and programmable networks that enable scientific applications to use the networks efficiently. We worked on the AmoebaNet solution to address the problems of a dynamic programmable network for bulk data transfer in extreme-scale distributed science environments. A major goal of the AmoebaNet project is to apply software-defined networking (SDN) technology to provide “Application-aware” network to facilitate bulk data transfer. We have prototyped AmoebaNet’s SDN-enabled network service that allows application to dynamically program the networks at run-time for bulk data transfers. In this paper, we evaluated AmoebaNet solution with real world test cases and shown that how it efficiently and dynamically can use the networks for bulk data transfer in large-scale scientific environments.

Transferências de Dados em Massa Sensíveis ao Consumo Energético em Redes Ópticas Elásticas

O consumo energético nas redes de núcleo atualmente é impactado pelas aplicações de Bulk Data Transfer (BDT) entre os principais Centros de Dados (CDs) da Internet. Isso ocorre porque essas aplicações consomem a maior parte dos recursos disponíveis e o fazem por longos períodos de tempo. Devido ao aumento do tráfego na rede, que ocorre a cada ano, um dos principais desafios para os provedores de serviço em nuvem é a eficiência energética. Para servir à crescente demanda, o paradigma das Redes Ópticas Elásticas (EON) têm sido proposto com o objetivo de atender requisições com maior flexibilidade, aproveitando melhor o espectro de frequência. Este artigo propõe a solução Energy Efficient Aware-BDT in EON (EEABE), um algoritmo de Roteamento e Alocação de Espectro (RSA) ciente de eficiência energética para realizar BDT inter-CD (ICD), que é capaz de escalonar requisições BDT e implementar a técnica de sleep mode para reduzir o consumo energético dos elementos comutadores na rede óptica.