Consensus, replication, decentralization, fault tolerance, and distributed coordination.
31 curated papers31 papers
Introduces replica assignment that protects high-priority sessions while allowing capacity borrowing in constrained replicated database clusters.
Models quorum-formation latency and multimodal block-time distributions to diagnose heterogeneous network behavior in HotStuff-based BFT systems.
Uses decentralized monitoring and declarative actions to add self-healing, self-protection, and self-optimization to microservices.
Combines a token ring with cache-local rendezvous candidates to improve balance and lookup throughput while preserving minimal churn.
The scaling of Large-scale Language Models (LLMs) demands unprecedented computational power and bandwidth. We present UB-Mesh, an innovative AI datacenter network architecture that enhances scalability, performance, and cost-efficiency through a hierarchical nD-FullMesh topology.
Memory disaggregation has become a major trend in cloud-native databases. However, most existing memory disaggregation solutions suffer from read/write amplification, limited bandwidth, inefficient recovery, and challenges in data sharing.
Due to characteristics such as the openness and exposure of inter-satellite links, Low-Earth Orbit (LEO) satellite networks are subject to heightened vulnerability to malicious attacks compared to ground-based networks. Given various security risks, implementing trust management in LEO satellite networks becomes imperative.
Remote data structures built with one-sided Remote Direct Memory Access (RDMA) are at the heart of many disaggregated database management systems today. Concurrent access to these data structures by thousands of remote workers necessitates a highly efficient synchronization scheme.
Presents error-free, information-theoretically secure asynchronous multi-valued Byzantine agreement with near-optimal communication.
Combines reputation, outlier detection, and blockchain-backed identity to defend cross-device federated learning against poisoned updates.
As an important component of the space-air-ground integrated network, aerial base station (AeBS) systems have gained significant attention for their flexibility in mobility and cost-effective construction. Nevertheless, the scarce spectrum resources and difficulty in accessing global information bring necessity and challenges to the deployment and…
Serverless computing is renowned for its computation elasticity, yet its full potential is often constrained by the requirement for functions to operate within local and dedicated background environments, resulting in limited memory elasticity. To address this limitation, this paper introduces TrEnv, a co-designed integration of the serverless platform…
RDMA-based in-memory storage systems offer high performance but are restricted by the capacity of physical memory. In this article, we propose TeRM to extend RDMA-attached memory with SSD.
With the increasing demand for blockchain technology in various industry sectors, there has been a growing interest in the Byzantine Fault Tolerance (BFT) consensus that is the backbone of most of these blockchains. However, many state-of-the-art algorithms that require reliable connections can only offer limited throughput in wide-area networks (WANs),…
Long-running containerized workloads (e. g.
Distributed databases have become indispensable in contemporary computing and data processing, owing to their pivotal role in ensuring high availability and scalability. They effectively cater to the requirements of data management and high-concurrency access.
Relational network verification is a new approach for validating network changes. In contrast to traditional network verification, which analyzes specifications for a single network snapshot, it analyzes specifications that capture similarities and differences between two network snapshots (e.
Distributed tracing has been widely adopted in many microservice systems and plays an important role in monitoring and analyzing the system. However, trace data often come in large volumes, incurring substantial computational and storage costs.
In a geo-distributed database, data shards and their respective replicas are deployed in distinct datacenters across multiple regions, enabling regional-level disaster recovery and the ability to serve global users locally. However, transaction processing in geo-distributed databases requires multiple cross-region communications, especially during the…
Disaggregated memory separates compute and memory resources into independent pools connected by RDMA (Remote Direct Memory Access) networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. However, existing RDMA-based distributed transactions on disaggregated memory suffer from severe…
Decentralized Storage Network (DSN) is an emerging technology that challenges traditional cloud-based storage systems by consolidating storage capacities from independent providers and coordinating to provide decentralized storage and retrieval services. However, current DSNs face several challenges associated with data privacy and efficiency of the…
While modern internet services, such as chatbots, search engines, and online advertising, demand the use of large-scale deep neural networks (DNNs), distributed training and inference over heterogeneous computing systems are desired to facilitate these DNN models. Mixture-of-Experts (MoE) is one the most common strategies to lower the cost of training…
Deep Learning training jobs process large amounts of training data using many GPU devices, often running for weeks or months. When hardware or software failures happen, these jobs need to restart, losing the memory state for the Deep Neural Network (DNN) model trained so far, unless checkpointing mechanisms are used to save training state periodically.
Large language models (LLMs) have triggered tremendous success to empower our daily life by generative information. The personalization of LLMs could further contribute to their applications due to better alignment with human intents.
Byzantine fault-tolerant (BFT) state machine replication (SMR) is adopted to support blockchain consensus by tolerating arbitrarily faulty behaviours. However, the inherent complexity of BFT protocols makes existing BFT protocols hard to adapt to large-scale applications that require high scalability and performance.
Distributed protocols such as 2PC and Paxos lie at the core of many systems in the cloud, but standard implementations do not scale. New scalable distributed protocols are developed through careful analysis and rewrites, but this process is ad hoc and error-prone.
With the rapid development of blockchain and its applications, the amount of data stored on decentralized storage networks (DSNs) has grown exponentially. DSNs bring together affordable storage resources from around the world to provide robust, decentralized storage services for tens of thousands of decentralized applications (dApps).
Function-as-a-Service (FaaS) offers a fine-grained resource provision model, enabling developers to build highly elastic cloud applications. User requests are handled by a series of serverless functions step by step, which forms a multi-step workflow.
As humanity’s reach in space exploration extends beyond Earth’s orbit, the demand for robust and efficient communication systems intensifies. The traditional paradigm of isolated missions has given way to a complex network of diverse spacecraft engaged in terrestrial research, lunar exploration, and the provision of essential satellite services.
Memory disaggregation is a promising architecture for modern datacenters that separates compute and memory resources into independent pools connected by ultra-fast networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. However, existing memory disaggregation solutions based on remote…
In the modelling of distributed systems, most Model of Computations (MoCs) rely on blocking communication to preserve determinism. A prominent example is Kahn Process Networks (KPNs), which supports non-blocking writes and blocking reads, and its implementable variant Finite FIFO Platforms (FFPs) which enforces boundedness using blocking writes.