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Pavan Poudel

Publications and source records attributed to Pavan Poudel.

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LeafData: An Agentic System for Data Migration

Modern data migration relies on JSON configuration to define data connection, pipeline logic, and orchestration behavior. This requires domain knowledge from users and is time-consuming and error-prone. In this paper, we present LeafData, an agentic system that converts user intent into validated and executable JSON configuration for data migration. Specifically, LeafData comprises a frontend chatbot and the backend service. The chatbot incrementally collects required information from users and performs schema-driven validation, while the backend service processes validated inputs and generates JSON configuration artifacts. These artifacts are directly consumable by orchestration platforms, enabling end-to-end pipeline generation and execution without manual coding. LeafData supports heterogeneous data migration across various data sources and connectors including relational databases, file-based systems, document-oriented databases, and REST APIs.

cs.AI

A Poly-Log Approximation for Transaction Scheduling in Fog-Cloud Computing and Beyond

Transaction scheduling is crucial to efficiently allocate shared resources in a conflict-free manner in distributed systems. We investigate the efficient scheduling of transactions in a network of fog-cloud computing model, where transactions and their associated shared objects can move within the network. The schedule may require objects to move to transaction nodes, or the transactions to move to the object nodes. Moreover, the schedule may determine intermediate nodes where both objects and transactions meet. Our goal is to minimize the total combined cost of the schedule. We focus on networks of constant doubling dimension, which appear frequently in practice. We consider a batch problem where an arbitrary set of nodes has transactions that need to be scheduled. First, we consider a single shared object required by all the transactions and present a scheduling algorithm that gives an $O(\log n \cdot \log D)$ approximation of the optimal schedule, where $n$ is the number of nodes and $D$ is the diameter of the network. Later, we consider transactions accessing multiple shared objects (at most $k$ objects per transaction) and provide a scheduling algorithm that gives an $O(k \cdot \log n \cdot \log D)$ approximation. We also provide a fully distributed version of the scheduling algorithms where the nodes do not need global knowledge of transactions.

cs.DC

Stable Scheduling in Transactional Memory

We study computer systems with transactions executed on a set of shared objects. Transactions arrive continually subjects to constrains that are framed as an adversarial model and impose limits on the average rate of transaction generation and the number of objects that transactions use. We show that no deterministic distributed scheduler in the queue-free model of transaction autonomy can provide stability for any positive rate of transaction generation. Let a system consist of $m$ shared objects and an adversary be constrained such that each transaction may access at most $k$ shared objects. We prove that no scheduler can be stable if a generation rate is greater than $\max\bigl\{\frac{2}{k+1},\frac{2}{\lfloor \sqrt{2m} \rfloor}\bigr\}$. We develop a centralized scheduler that is stable if a transaction generation rate is at most $\max\bigl\{\frac{1}{4k}, \frac{1}{4\lceil\sqrt{m}\rceil} \bigr\}$. We design a distributed scheduler in the queue-based model of transaction autonomy, in which a transaction is assigned to an individual processor, that guarantees stability if the rate of transaction generation is less than $\max\bigl\{ \frac{1}{6k},\frac{1}{6\lceil\sqrt{m}\rceil}\bigr\}$. For each of the schedulers we give upper bounds on the queue size and transaction latency in the range of rates of transaction generation for which the scheduler is stable.

cs.DC