2021 version of the proposal

After the Tender selection process completes for a live and offline transcription and translation product,
help to post-process and automate the  enhancement of the lectures' backlog with subtitles.
See here categories of candidate lectures.

2020 version of the proposal (TECH approved by IT and HR, rejected by the service manager):

The CERN IT Collaboration, Devices & Applications group and in particular sections Digital Repositories (IT CDA/DR) and Integrated Collaboration (IT CDA/IC), run many highly visible and popular services, which enable researchers/institutions to share and preserve their research data, software and publications as well as meet, present and record lectures, projects, plans and decisions of academic content and very large experiment collaborations.

The CERN Document Server (CDS) is the official document repository for the laboratory and annually serves around 2 million visitors. There are thousands of videos recorded at CERN via the CDA/IC recording and transcoding infrastructure. They are uploaded and viewable via CDS or the recent videos' portal.

We need to equip all CERN-made videos with subtitles. This project is about turning the transcription software, to be selected by the relevant CERN CDA service managers, into a scalable service that automatically introduces and displays subtitles in CDS for the CERN community. The process should be well integrated with our new video player and the set-up should allow to apply text corrections by the content owner (lecture, meeting, conference organiser) in a functional way.

The group Collaboration, Devices and Applications (CDA) in CERN IT Department initiated a Documentation Project for moving static service documentation web sites containing service documentation to Markdown. For this purpose, software tools are being developed, instructions being written and  pilot testers contacted.

The student will have to:

1. apply the instructions in order to create a new web site according to the policy for site naming, hosting, authoring.
2. observe new-comer users' reactions to the procedure, the tools and the suggested rich-text editors.
3. identify shortcomings in any area of point 2 above and report to the documentation-project members.
4. document tips in form of FAQs and/or discourse articles.
5. make recommendations to the documentation-project team for an optimal user experience.
6. disseminate the instructions via alternative methods, namely online tutorials.
7. convert some of the groups' own service documentations to test the process in operation.
8. make short videos based on the Instructions.

The LHC experiments execute a significant fraction of their data reconstruction, simulation and analysis on the CERN computing batch resources. One of the most important features of these data processing jobs is their I/O pattern in accessing the local storage system, EOS, which is based on the xrootd protocol. In fact, the way experiment applications access the data can have a considerable impact on how efficiently the computing, storage and network resources are used, and has important implications on the optimisation and size of these resources.

A promising approach is to study the logs of the storage system to identify and characterise the job I/O, which is strongly dependent on
the type of jobs (simulation, digitisation, reconstruction, etc.). A direct link between the information in the storage logs and the information in the monitoring systems of the experiments (which contain detailed information about the jobs) is possible, as it can be derived from a cross analysis of the aforementioned data sources together with information from the CERN batch systems. The goal of this project is to study such connection, use it to relate I/O storage patterns to experiment job types, look for significant variations within a given job type, identify important sources of inefficiency and describe a simple model for the computer centre (batch nodes, network, disk servers) that would increase the efficiency of the resource utilisation.

In case inefficiencies are detected that could be alleviated by changes in the way experiments run their jobs, this information should be passed to the experiments.

The analysis can be initially based on the jobs of a single large LHC experiment (ATLAS or CMS) and extended to other experiments if time allows.

This proposal was materialised via the Jekyll project

The CERN IT Collaboration, Devices & Applications (CDA) group in general and the Integrated Collaboration (IC) section host services used widely at CERN and beyond. Examples from IC:

• Conference room equipment, configuration, documentation and support
• audiovisual services' support (webcast and recording)
• video conferencing (vidyo service)
• email service management and support
• IP telephony (e.g. skype for business)
• Login accounts, the CERN Single Sign-On (SSO) service, Authentication/Authorisation/Digital Certificates

In this project, we wish to understand the best way to document and promote these services with the user in mind, i.e. not considering service organisational, administrative or technical boundaries.

After getting the service managers' input, navigating through existing leaflets or web documentation and identifying out-of-date or obsolete parts in it, we shall come up with a proposal on:

1. a user-friendly information organisation, based on user stories, rather than services.
2. suggestions of quick How-Tos as the users would expect them, rather than sequencially describing each service or groups of services. The purpose here is to make our services more understandable and accessible.
3. tips for best promoting existing documentation.
4. a recommendation on how to best get feedback from users on our services or on the documentation itself...

There is already a wealth of information being assembled in  a group internal page to facilitate the investigation and enhance the student's technical experience.

The LHC experiments perform the vast majority of the data processing and analysis on the Worldwide LHC Computing Grid (WLCG), which provides a globally distributed infrastructure with more than 500k cores to analyse the tens of PB of data collected each year. Profiling of the computing infrastructure with respect to the impact of different workloads is a crucial factor to find  the most efficient match between resources and use cases.  From the current analysis it is clear that the efficiency is neither perfect nor well understood.

There is a rich amount of information collected by the communities' monitoring infrastructures. The scale and complexity of this data presents an analytics challenge on its own. So far the full potential hasn't been exploited. This data covers all the areas of the computing activities such as host monitoring, storage, network, batch system performance, user level job monitoring. Extracting useful knowledge from this data requires the use of state of the art data analytics tools and processes. The final purpose is to gain deep understanding of what determines the efficiency and how it can be improved. 

ElasticSearch is a distributed, search and analytics engine  that is used at CERN to store and process large amounts of monitoring data for several experiments.

It has been noted that differences in data access patterns lead to significantly different utilisation of the resources. However, the concrete causes and quantitative relations are still badly understood. In the same way job failures due a variety of underlying causes lead to loss of productivity, without knowing the exact causes and the concrete scale of the different issues.  

To be able to improve the overall efficiency we suggest to studying the dependency of the performance on a variety of variables. Based on these findings, which could be obtained by classical and/or machine learning based data analysis techniques, new strategies should be developed. Since the expected gains are on the order of 10-20% the outcome of this work is of great importance for the experiments and the infrastructure providers. 

The work in this project will be done in close collaboration with experts from CERN IT and the LHC experiments. 

One of the main challenges in WLCG WAN networking is the network diagnostics and advanced notifications on the issues seen in the network. LHCOPN/LHCONE as the core global networks in WLCG have more than 5000 active links between 120 sites. Currently, most of the issues are only visible by the applications and need to be debugged after the incident and performance degradation has already occurred. This is primarily due to the underlying complexity of the WLCG network (multi-domain) and difficulty to understand state of the network and how it changes over time. The project will aim to use the current open-source event processing systems to automate detection and location of the network problems using the existing data from the perfSONAR network infrastructure. The project will be done in collaboration with University of Chicago and University of Michigan.

The project will build on the standard WLCG perfSONAR network measurement infrastructure and will aim to gather and analyze complex real-world network topologies and their corresponding network metrics to identify possible signatures of the network problems. It will provide a real-time view on the existing diagnosed issues together with a list of existing downtimes from the network providers to the experiments operations teams.

The group runs a project whose goal is the dynamic federation of

• HTTP based storage systems, allowing a set of globally distributed resources to be integrated and appear via a single entry point. The task is to work on the development of this project (“dynafed”), implementing functional and performance extensions, in particular 
• Redirection monitoring, to allow the logging of federator behaviour for real-time monitorng and subsequent analytics
• Metadata integration, beginning with the incorporation of space usage information, allowing the federator to expose grid-wide storage metrics
• An endpoint status/management subsystem. The basic feature would be an interface that publishes endpoint status (up/down/degraded). Management functions could also be incorporated, including ways to add/enable/disable endpoints without having to restart the service.
• Semantic enhancements to the embedded rule-based authorization implementation, including turning the authorization subsystem into a pluggable authorization manager.
• Deployment tests and development with other Apache security plugins, to support natively Identity Federations, like the CERN SSO, Facebook, Google and others. May benefit from the previous points about authorization.
• Integration with experiment catalogues to benefit from available metadata and replica placement information.

The group maintains a framework called dmlite which is used to integrate various types of storage with different protocol frontends. It is the basis of a number of the group’s products such as the Disk Pool Manager (DPM), a grid storage system which holds over 50PB of storage in the global infrastructure. DPM/dmlite extensions
The task is to contribute to the dmlite project by working on functional extensions to the framework. Example projects include

• Exposing system data through a “procfs” style plugin
• Incorporation of new AA mechanisms, eg outh
• Creation of a web admin interface
• Work on draining and file placement within the system
• dmliteSE

Help to realise the group's vision of a “dmliteSE” by working on the gradual retirement of legacy daemons within the DPM system. In this context, tackle the modernisation of pool management and file placement, and the incorporation of new resource types (eg cluster file systems) into the system. Complete the functional development required to allow operation of a disk storage system purely through standard protocols.

The File Transfer Service (FTS) manages the global distribution
of LHC data, moving multiple petabytes per month during a run and underpinning the whole data lifecycle. Join the FTS team in their development of this critical service. Possible projects include

• authorised proxy sharing: allowing a production service to delegate a proxy and authorising others to use it
• incorporation of support for new types of endpoint, for example cloud or archival storage

Profiling of computing resources respect to WLCG experiment workloads is a crucial factor to select the most effective resources and to be able to optimise their usage.
There is a rich amount of data collected by the CERN and WLCG monitoring infrastructures just waiting to be turned into useful information. This data covers all the areas of the computing activity such as (real and/or virtual) machine monitoring, storage, network, batch system performance, experiment job monitoring.
Data gathered by those systems contain great intrinsic value, however information needs to be extracted and understood through a predictive data analytics process. The final purpose of this process is to support decisions and improve the efficiency and the reliability of the related services.
For instance, with the adoption of the remote access of data it becomes mandatory to understand the impact of this approach to the job efficiency. Here the interplay of network and CPU effects, as well as the resource usage from multi VOs needs to be studied and understood. An interesting topic of study is the performance of job processing at the WLCG distributed T0 center, which is physically split between Computer Centers in Meyrin and Wigner. The goal of the project will be to understand the difference in the performance and to suggest possible optimization.

The work will be conducted in close contact with the experts (CERN analytics working group, system managers, developers) and will provide a deep insight into the computing infrastructure of a WLCG datacenter, its design, technical requirements and operational challenges.

Cloud synchronization and sharing is an area in evolution with innovative services being built on top of different platforms. CERNBOX is a service ran at CERN to provide at the same time synchronisation services (based on the OwnCloud software) and high-performance data access and sharing (based on EOS, the CERN disk storage system for large-scale physics data analysis).

The Smashbox framework (https://github.com/cernbox/smashbox) is successfully used on Linux clients to test OwnCloud/CERNBOX installations. The plans to extend it require to port it to non-Linux platforms:
* Smashbox port to Windows platforms 
* Smashbox port to Android 
* Smashbox port to iOS 
* Smashbox orchestration (concurrent execution across platforms)

Cloud synchronization and sharing is a promising area for the preparation of powerful transformative data services. 

The goal of this project is to prepare CERNBOX to be used in connection with heavy-duty activities (large-scale batch processing) on the current LXBATCH infrastructure (LSF) and on its future evolution (HT-Condor): physicists can enable their data to move across their private workstations (like a private laptop) while the bulk of the data is directly accessed from the EOS infrastructure. At the same time, users can control the progress of their activity via mobile clients (as a smartphone) via optimised client applications or via standard browsers.
The student will participate to the preparation and validation of these use cases. The student will participate to the deployment of the necessary infrastructure (EOS Fuse access from interactive and batch services), support the alpha users (physicists) and extend the current testing and validation system to these new use cases and to new platforms (acceptance tests – in connection with other sites running CERNBOX and monitoring – using the CERN monitoring infrastructure).

An additional use case is the enabling of data viewers (ROOT tuple) in connection with the SFT team to allow seamless access to summary data (like histograms) from the CERNBOX portal directly.

Clients of the sync&share system (CERNBOX) are particularly exposed to "operational failures" due to heterogeneity of hardware, OS and network environments. 

Sync&share system operates in very heterogenous network environment: from fast, reliable network inside the computing center to unreliable, high-latency ad-hoc connections such as from air-ports etc. 
Windows filesystems have substantially different semantics (e.g. locking) from Unix filesystems -- these difference affect the synchronization process 
the goal of the R&D is to analyze the environment and identify the relevant classes of failures in order to provide a reproducible framework for injecting faults at the system level for testing client-server data transmission 
examples: 
* network slowdown or packet loss 
* local disk failure 
* checksum errors 
* failed software upgrades 
the work is supported by real monitoring and logging data: failure patterns in an existing service (CERNBOX) 
the work extends on existing testing framework (smashbox)