Prediction of inter packet arrival times for enhanced NR-V2X sidelink scheduling

A significant limitation of the LTE-V2X and NR-V2X sidelink scheduling mechanisms is their difficulty coping with variations in inter packet arrival times, also known as aperiodic packets. This conflicts with the fundamental characteristics of most V2X services which are triggered based on an event. e.g. ETSI Cooperative Awareness Messages (CAMs) - vehicle kinematics, Cooperative Perception Messages (CPMs) - object sensing and Decentralised Event Notification Messages (DENMs) - event occurrences. Furthermore, network management techniques such as congestion control mechanisms can result in varied inter packet arrival times. To combat this, NR-V2X introduced a dynamic grant mechanism, which we show is ineffective unless there is background periodic traffic to stabilise the sensing history upon which the scheduler makes it decisions. The characteristics of V2X services make it implausible that such periodic application traffic will exist. To overcome this significant drawback, we demonstrate that the standardised scheduling algorithms can be made effective if the event triggered arrival rate of packets can be accurately predicted. These predictions can be used to tune the Resource Reservation Interval (RRI) parameter of the MAC scheduler to negate the negative impact of aperiodicity. Such an approach allows the scheduler to achieve comparable performance to a scenario where packets arrive periodically. To demonstrate the effectiveness of our approach, an ML model has been devised for the prediction of cooperative awareness messages, but the same principle can be abstracted to other V2X service types.Comment: 9 pages, 10 figure

A case for good defaults: pitfalls in VANET physical layer simulations

Network simulations are often the first choice to design, test, and evaluate novel applications and protocols for vehicular networks. Aiming for higher realism, simulators become increasingly complex, relying on detailed simulation models that are developed by different communities. With this trend, it also becomes difficult to understand all models in detail and researchers might lack the expert knowledge to parameterize such models properly. In this paper, we identify suboptimal default parameter values for physical layer effects in common simulation frameworks and show how they can negatively impact the results. We also review papers that use said simulation models and highlight that this is not simply a theoretical issue: We found that the majority of the papers simply copy these default parameter values or do not mention physical layer parameters at all. Both cases are clearly problematic. We thus argue that we should focus on reasonable default parameter values just as much as on the functional correctness of simulation models

Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis

peer-reviewedRapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number ofmethodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance inmicrobiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced withMiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes should optimise their protocols to accurately detect these taxa using different techniques.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2273 and 11/PI/1137 and by FP7 funded CFMATTERS (Cystic Fibrosis Microbiome-determined Antibiotic Therapy Trial in Exacerbations: Results Stratified, Grant Agreement no. 603038)

MCS adaptation within the Cellular V2X sidelink

Adaptation of the Modulation and Coding Scheme (MCS) within the Cellular Vehicle-To-Everything (C-V2X) sidelink has the potential for a wide range of applications including congestion control, support of variable packet sizes and improved support of unicast transmissions. However, the practical implementation of MCS adaptation presents a wide range of implications for the C- V2X radio resources, computation of power levels and the operation of the Sensing-Based Semi-Persistent Scheduling (SB-SPS) mechanism. This paper presents the first study that provides a detailed analysis and an imple-mented model highlighting the implications of MCS adaptation on the operation of SB-SPS. This provides the foundation for other applications of MCS adaptation within the C- V2X sidelink. To showcase the use of MCS adaptation, a quantitative evaluation of its performance for distributed congestion control is undertaken, while considering different vehicular densities. The results indicate that MCS adaptation can be useful to reduce channel congestion by decreasing resource occupation, but may not improve the overall packet delivery rate unless subchannel occupation is reduced

Draft Genome Sequences of Six Different Staphylococcus epidermidis Clones, Isolated Individually from Preterm Neonates Presenting with Sepsis at Edinburgh's Royal Infirmary

Herein, we report the draft genome sequences of six individualStaphylococcus epidermidisclones, cultivated from blood taken from different preterm neonatal sepsis patients at the Royal Infirmary, Edinburgh, Scotland, United Kingdom

Exploring NR-V2X dynamic grant limitations for aperiodic traffic

The recent 3GPP NR-V2X standard (Rel. 16) has largely built upon its precursor Cellular-V2X (Rels. 14 & 15) but has introduced new approaches for dealing with application traffic exhibiting aperiodic arrival rates in the sidelink. This is vital as safety services based on ETSI Cooperative Awareness Messages (CAMs) and Decentralised Environmental Notification Messages (DENM) exhibit such characteristics. It is further envisaged that future vehicular services will also exhibit high aperiodicity to support increased autonomy. In this paper we quantitatively evaluate the reasons why the Sensing based Semi-Peristent Scheduling (SB-SPS) mechanism performs poorly when scheduling aperiodic traffic. We then provide the first in-depth evaluation of the NR-V2X Dynamic Grant mechanism in contrast to schemes that parameterise the existing C-V2X SPS algorithm and evaluate the performance of alternative dedicated scheduling mechanisms specifically designed for aperiodicity. This paper highlights th at the level of aperiodicity exhibited by the application model greatly impacts scheduling performance, both for the default SB-SPS and dedicated approaches. As such we conclude that a novel aperiodic scheduling mechanism must be devised, or more promisingly, an approach to enable application traffic to mimic periodic characteristics allowing it to co-exist with the existing scheduling approach

Adapting the resource reservation interval for improved congestion control in NR-V2X

This paper presents a detailed quantitative evalu- ation of standardised ETSI & 3GPP Decentralised Congestion Control (DCC) and packet dropping mechanisms for Cellular V2X (C-V2X) and New Radio (NR) V2X. Based on the identified shortcomings, an Access layer scheme, RRI DCC, is then pro- posed. RRI DCC explicitly accommodates the sidelink scheduling mechanism Sensing Based Semi-Persistent Scheduling (SB-SPS), eliminating incompatibilities between current standards and the scheduling mechanism, to avoid unnecessary and recurring collisions. Three variants are proposed; one is an evolution of the ETSI Reactive DCC mechanism, the second is based on the ETSI Adaptive DCC mechanism and the final aligns with the 3GPP approach based on channel occupancy ratio (CR). All approaches are compared with current ETSI and 3GPP standards and exhibit improved performance. An evaluation of the proposed RRI DCC mechanisms and existing DCC standards, to meet the Quality of Service (QoS) requirements of vehicular cooperative awareness applications is also conducted

HBLAST: parallelised sequence similarity - A Hadoop MapReducable basic local alignment search tool

The recent exponential growth of genomic databases has resulted in the common task of sequence alignment becoming one of the major bottlenecks in the field of computational biology. It is typical for these large datasets and complex computations to require cost prohibitive High Performance Computing (HPC) to function. As such, parallelised solutions have been proposed but many exhibit scalability limitations and are incapable of effectively processing “Big Data” – the name attributed to datasets that are extremely large, complex and require rapid processing. The Hadoop framework, comprised of distributed storage and a parallelised programming framework known as MapReduce, is specifically designed to work with such datasets but it is not trivial to efficiently redesign and implement bioinformatics algorithms according to this paradigm. The parallelisation strategy of “divide and conquer” for alignment algorithms can be applied to both data sets and input query sequences. However, scalability is still an issue due to memory constraints or large databases, with very large database segmentation leading to additional performance decline. Herein, we present Hadoop Blast (HBlast), a parallelised BLAST algorithm that proposes a flexible method to partition both databases and input query sequences using “virtual partitioning”. HBlast presents improved scalability over existing solutions and well balanced computational work load while keeping database segmentation and recompilation to a minimum. Enhanced BLAST search performance on cheap memory constrained hardware has significant implications for in field clinical diagnostic testing; enabling faster and more accurate identification of pathogenic DNA in human blood or tissue samples

The t(8;9)(p22;p24) is a recurrent abnormality in chronic and acute leukemia that fuses PCM1 to JAK2

We have identified a t(8;9)(p21-23;p23-24) in seven male patients (mean age 50, range 32-74) with diverse hematologic malignancies and clinical outcomes: atypical chronic myeloid leukemia/chronic eosinophilic leukemia (n = 5), secondary acute myeloid leukemia (n = 1), and pre-B-cell acute lymphoblastic leukemia (n = 1). Initial fluorescence in situ hybridization studies of one patient indicated that the nonreceptor tyrosine kinase Janus-activated kinase 2 (JAK2) at 9p24 was disrupted. Rapid amplification of cDNA ends-PCR identified the 8p22 partner gene as human autoantigen pericentriolar material (PCM1), a gene encoding a large centrosomal protein with multiple coiled-coil domains. Reverse transcription-PCR and fluorescence in situ hybridization confirmed the fusion in this case and also identified PCM1–JAK2 in the six other t(8;9) patients. The breakpoints were variable in both genes, but in all cases the chimeric mRNA is predicted to encode a protein that retains several of the predicted coiled-coil domains from PCM1 and the entire tyrosine kinase domain of JAK2. Reciprocal JAK2–PCM1 mRNA was not detected in any patient. We conclude that human autoantigen pericentriolar material (PCM1)–JAK2 is a novel, recurrent fusion gene in hematologic malignancies. Patients with PCM1–JAK2 disease are attractive candidates for targeted signal transduction therapy