Decentralized Solutions for Monitoring Large-Scale Software-Defined Networks

Software-Defined Networking (SDN) technologies offer the possibility to automatically and frequently reconfigure the network resources by enabling simple and flexible network programmability. One of the key challenges to address when developing a new SDN-based solution is the design of a monitoring framework that can provide frequent and consistent updates to heterogeneous management applications. To cope with the requirements of large-scale networks (i.e. large number of geographically dispersed devices), a distributed monitoring approach is required. This PhD aims at investigating decentralized solutions for resource monitoring in SDN. The research will focus on the design of monitoring entities for the collection and processing of information at different network locations and will investigate how these can efficiently share their knowledge in a distributed management environment

Accuracy-Aware Adaptive Traffic Monitoring for Software Dataplanes

Network operators have recently been developing multi-Gbps traffic monitoring tools on commodity hardware, as part of the packet-processing pipelines realizing software dataplanes. These solutions allow the execution of sophisticated per-packet monitoring using the processing power available on servers. Although advances in packet capture have enabled the interception of packets at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive monitoring framework, →ol, which is resilient to bottlenecks while maintaining the accuracy of monitoring reports above a user-specified threshold. →ol dynamically reduces the measurement task sets under adverse conditions, and reconfigures them to recover potential accuracy degradations. To quantify the monitoring accuracy at run time, →ol adopts a novel task-independent technique that generates accuracy estimates according to recently observed traffic characteristics. With a prototype implementation based on a generic packet-processing pipeline, and using well-known measurements tasks, we show that →ol achieves lossless traffic monitoring for a wide range of conditions, significantly enhances the level of monitoring accuracy, and performs adaptations at the time scale of milliseconds with limited overhead

A Northbound Interface for Software-based Networks

The current shift from traditional network architectures to software-based solutions is offering new opportunities to allow network functionality to be managed in a flexible way. Substantial efforts have been invested in the recent years in the development of new network management approaches taking advantage of emerging paradigms such as software-defined networking and network function virtualization. Until now however there has not been much progress in the development of a northbound interface (NBI) linking high-level requirements (HLRs) capturing business objectives to management operations. This is a crucial functionality to facilitate faster service deployment and realization of business objectives. In this paper we extend the efforts towards the development of a NBI and propose a novel approach for the automatic decomposition of HLRs to network management operations. We demonstrate its functionality based on representative use cases and evaluate its feasibility through prototype implementation. The results obtained show that our solution can translate new technical requirements to network configurations in the order of a few seconds, thus enabling the management of network functionality and services in short timescales

A Northbound Interface for Software-based Networks

The current shift from traditional network architectures to software-based solutions is offering new opportunities to allow network functionality to be managed in a flexible way. Substantial efforts have been invested in the recent years in the development of new network management approaches taking advantage of emerging paradigms such as software-defined networking and network function virtualization. Until now however there has not been much progress in the development of a northbound interface (NBI) linking high-level requirements (HLRs) capturing business objectives to management operations. This is a crucial functionality to facilitate faster service deployment and realization of business objectives. In this paper we extend the efforts towards the development of a NBI and propose a novel approach for the automatic decomposition of HLRs to network management operations. We demonstrate its functionality based on representative use cases and evaluate its feasibility through prototype implementation. The results obtained show that our solution can translate new technical requirements to network configurations in the order of a few seconds, thus enabling the management of network functionality and services in short timescales

Self-Adaptive Decentralized Monitoring in Software-Defined Networks

The Software-Defined Networking (SDN) paradigm can allow network management solutions to automatically and frequently reconfigure network resources. When developing SDNbased management architectures, it is of paramount importance to design a monitoring system that can provide timely and consistent updates to heterogeneous management applications. To support such applications operating with low latency requirements, the monitoring system should scale with increasing network size and provide precise network views with minimum overhead on the available resources. In this paper we present a novel, self-adaptive, decentralized framework for resource monitoring in SDN. Our framework enables accurate statistics to be collected with limited burden on the network resources. This is realized through a self-tuning, adaptive monitoring mechanism that automatically adjusts its settings based on the traffic dynamics. We evaluate our proposal based on a realistic use case scenario, where a content distribution service and an on-demand gaming platform are deployed within an ISP network. The results show that reduced monitoring latencies are obtained with the proposed framework, thus enabling shorter reconfiguration control loops. In addition, the proposed adaptive monitoring method achieves significant gain in terms of monitoring overhead, while preserving the performance of the services considered

Spring Deposits and Lakeshore Layered Sediments Inside the Vernal Crater (SW Arabia Terra): A Resource-Rich and Engineering Safe Mars Human Landing Site

We here present the scientific rationale, the resource analysis and the engineering requirements evaluation performed on the Vernal crater and its closest surroundings in SW Arabia Terra, Mars, as a possible future human landing site

Chromosome 20p11.2 deletions cause congenital hyperinsulinism via the loss of FOXA2 or its regulatory elements

This is the final version. Available on open access from Springer Nature via the DOI in this recordData availability: All non-clinical data analyzed during this study are included in this article (and its Supplementary Information). The 20p11.2 variants reported in this study were uploaded to ClinVar (SUB14235415). Clinical and genotype data can be used to identify individuals and are therefore available only through collaboration to experienced teams working on approved studies examining the mechanisms, cause, diagnosis and treatment of diabetes and other beta cell disorders. Requests for collaboration will be considered by a steering committee following an application to the Genetic Beta Cell Research Bank (https://www.diabetesgenes.org/current-research/genetic-beta-cell-research-bank/). Contact by email should be directed to S. Flanagan ([email protected]). All requests for access to data will be responded to within 14 d. Accession codes and DOI numbers for all ChIP-seq, ATAC-seq, RNA-seq and scRNA-seq datasets are provided in Supplementary Table 2. We used the Genome Reference Consortium Human Build 37 (GRCh37) to annotate genetic data (accession number GCF_000001405.13). Details of this assembly are provided at https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.13/.Persistent congenital hyperinsulinism (HI) is a rare genetically heterogeneous condition characterised by dysregulated insulin secretion leading to life-threatening hypoglycaemia. For up to 50% of affected individuals screening of the known HI genes does not identify a disease-causing variant. Large deletions have previously been used to identify novel regulatory regions causing HI. Here, we used genome sequencing to search for novel large (>1 Mb) deletions in 180 probands with HI of unknown cause and replicated our findings in a large cohort of 883 genetically unsolved individuals with HI using off-target copy number variant calling from targeted gene panels. We identified overlapping heterozygous deletions in five individuals (range 3-8 Mb) spanning chromosome 20p11.2. The pancreatic beta-cell transcription factor gene, FOXA2, a known cause of HI was deleted in two of the five individuals. In the remaining three, we found a minimal deleted region of 2.4 Mb adjacent to FOXA2 that encompasses multiple non-coding regulatory elements that are in conformational contact with FOXA2. Our data suggests that the deletions in these three children may cause disease through the dysregulation of FOXA2 expression. These findings provide new insights into the regulation of FOXA2 in the beta-cell and confirm an aetiological role for chromosome 20p11.2 deletions in syndromic HI.Wellcome Trus

Chromosome 20p11.2 deletions cause congenital hyperinsulinism via the loss of FOXA2 or its regulatory elements

DATA AVAILABILITY : All non-clinical data analyzed during this study are included in this article (and its Supplementary Information). The 20p11.2 variants reported in this study were uploaded to ClinVar (SUB14235415). Clinical and genotype data can be used to identify individuals and are therefore available only through collaboration to experienced teams working on approved studies examining the mechanisms, cause, diagnosis and treatment of diabetes and other beta cell disorders. Requests for collaboration will be considered by a steering committee following an application to the Genetic Beta Cell Research Bank (https://www.diabetesgenes.org/current-research/genetic-beta-cell-research-bank/). Contact by email should be directed to S. Flanagan ([email protected]). All requests for access to data will be responded to within 14 d. Accession codes and DOI numbers for all ChIP-seq, ATAC-seq, RNA-seq and scRNA-seq datasets are provided in Supplementary Table 2. We used the Genome Reference Consortium Human Build 37 (GRCh37) to annotate genetic data (accession number GCF_000001405.13). Details of this assembly are provided at https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.13/.Persistent congenital hyperinsulinism (HI) is a rare genetically heterogeneous condition characterised by dysregulated insulin secretion leading to life-threatening hypoglycaemia. For up to 50% of affected individuals screening of the known HI genes does not identify a disease-causing variant. Large deletions have previously been used to identify novel regulatory regions causing HI. Here, we used genome sequencing to search for novel large (>1 Mb) deletions in 180 probands with HI of unknown cause and replicated our findings in a large cohort of 883 genetically unsolved individuals with HI using off-target copy number variant calling from targeted gene panels. We identified overlapping heterozygous deletions in five individuals (range 3–8 Mb) spanning chromosome 20p11.2. The pancreatic beta-cell transcription factor gene, FOXA2, a known cause of HI was deleted in two of the five individuals. In the remaining three, we found a minimal deleted region of 2.4 Mb adjacent to FOXA2 that encompasses multiple non-coding regulatory elements that are in conformational contact with FOXA2. Our data suggests that the deletions in these three children may cause disease through the dysregulation of FOXA2 expression. These findings provide new insights into the regulation of FOXA2 in the beta-cell and confirm an aetiological role for chromosome 20p11.2 deletions in syndromic HI.Funded in whole, or in part, by Wellcome.http://www.nature.come/jhghj2024Biochemistry, Genetics and Microbiology (BGM)SDG-03:Good heatlh and well-bein