mrva-interconnect: existing summary

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\documentclass[11pt]{article}
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% Title, Author, and Date (or Report Number)
\title{MRVA component interconnections}
\author{Michael Hohn}
\date{Technical Report 20250524}
\hypersetup{
pdfauthor={Michael Hohn},
pdftitle={MRVA component interconnections},
pdfkeywords={},
pdfsubject={},
pdfcreator={Emacs 29.1},
pdflang={English}}
\begin{document}
\maketitle
\tableofcontents
\section{Overview}
\label{sec:overview}
The MRVA system is organized as a collection of services. On the server side, the
system is containerized using Docker and comprises several key components:
\begin{itemize}
\item {\textbf{Server}}: Acts as the central coordinator.
\item \textbf{Agents}: One or more agents that execute tasks.
\item \textbf{RabbitMQ}: Handles messaging between components.
\item \textbf{MinIO}: Provides storage for both queries and results.
\item \textbf{HEPC}: An HTTP endpoint that hosts and serves CodeQL databases.
\end{itemize}
The execution process follows a structured workflow:
\begin{enumerate}
\item A client submits a set of queries $\mathcal{Q}$ targeting a repository
set $\mathcal{R}$.
\item The server enqueues jobs and distributes them to available agents.
\item Each agent retrieves a job, executes queries against its assigned repository, and accumulates results.
\item The agent sends results back to the server, which then forwards them to the client.
\end{enumerate}
This full round-trip can be expressed as:
\begin{equation}
\text{Client} \xrightarrow{\mathcal{Q}} \text{Server}
\xrightarrow{\text{enqueue}}
\text{Queue} \xrightarrow{\text{dispatch}} \text{Agent}
\xrightarrow{\mathcal{Q}(\mathcal{R}_i)}
\text{Server} \xrightarrow{\mathcal{Q}(\mathcal{R}_i} \text{Client}
\end{equation}
\section{Symbols and Notation}
\label{sec:orgb695d5a}
We define the following symbols for entities in the system:
\begin{center}
\begin{tabular}{lll}
Concept & Symbol & Description \\[0pt]
\hline
Client & \(C\) & The source of the query submission \\[0pt]
Server & \(S\) & Manages job queue and communicates results back to the client \\[0pt]
Job Queue & \(Q\) & Queue for managing submitted jobs \\[0pt]
Agent & \(\alpha\) & Independently polls, executes jobs, and accumulates results \\[0pt]
Agent Set & \(A\) & The set of all available agents \\[0pt]
Query Suite & \(\mathcal{Q}\) & Collection of queries submitted by the client \\[0pt]
Repository List & \(\mathcal{R}\) & Collection of repositories \\[0pt]
\(i\)-th Repository & \(\mathcal{R}_i\) & Specific repository indexed by \(i\) \\[0pt]
\(j\)-th Query & \(\mathcal{Q}_j\) & Specific query from the suite indexed by \(j\) \\[0pt]
Query Result & \(r_{i,j,k_{i,j}}\) & \(k_{i,j}\)-th result from query \(j\) executed on repository \(i\) \\[0pt]
Query Result Set & \(\mathcal{R}_i^{\mathcal{Q}_j}\) & Set of all results for query \(j\) on repository \(i\) \\[0pt]
Accumulated Results & \(\mathcal{R}_i^{\mathcal{Q}}\) & All results from executing all queries on \(\mathcal{R}_i\) \\[0pt]
\end{tabular}
\end{center}
\section{Full Round-Trip Representation}
\label{sec:full-round-trip}
The full round-trip execution, from query submission to result delivery, can be summarized as:
\[
C \xrightarrow{\mathcal{Q}} S \xrightarrow{\text{enqueue}} Q
\xrightarrow{\text{poll}}
\alpha \xrightarrow{\mathcal{Q}(\mathcal{R}_i)} S \xrightarrow{\mathcal{R}_i^{\mathcal{Q}}} C
\]
\begin{itemize}
\item \(C \to S\): Client submits a query suite \(\mathcal{Q}\) to the server.
\item \(S \to Q\): Server enqueues the query suite \((\mathcal{Q}, \mathcal{R}_i)\) for each repository.
\item \(Q \to \alpha\): Agent \(\alpha\) polls the queue and retrieves a job.
\item \(\alpha \to S\): Agent executes the queries and returns the accumulated results \(\mathcal{R}_i^{\mathcal{Q}}\) to the server.
\item \(S \to C\): Server sends the complete result set \(\mathcal{R}_i^{\mathcal{Q}}\) for each repository back to the client.
\end{itemize}
\section{Result Representation}
For the complete collection of results across all repositories and queries:
\[
\mathcal{R}^{\mathcal{Q}} = \bigcup_{i=1}^{N} \bigcup_{j=1}^{M}
\left\{ r_{i,j,1}, r_{i,j,2}, \dots, r_{i,j,k_{i,j}} \right\}
\]
where:
\begin{itemize}
\item \(N\) is the total number of repositories.
\item \(M\) is the total number of queries in \(\mathcal{Q}\).
\item \(k_{i,j}\) is the number of results from executing query
\(\mathcal{Q}_j\)
on repository \(\mathcal{R}_i\).
\end{itemize}
An individual result from the \(i\)-th repository, \(j\)-th query, and \(k\)-th result is:
\[
r_{i,j,k}
\]
\[
C \xrightarrow{\mathcal{Q}} S \xrightarrow{\text{enqueue}} Q \xrightarrow{\text{dispatch}} \alpha \xrightarrow{\mathcal{Q}(\mathcal{R}_i)} S \xrightarrow{r_{i,j}} C
\]
Each result can be further indexed to track multiple repositories and result sets.
\end{document}
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