The Middleware conference debuted in 1998, and has since evolved into the premier event for presenting and discussing research and innovations in the field of middleware systems. Middleware technologies focus on the design, implementation, deployment, and evaluation of distributed systems, platforms and architectures for computing, storage, and communication.
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Precursor: a fast, client-centric and trusted key-value store using RDMA and Intel SGX
As offered by the Intel Software Guard Extensions (SGX), trusted execution enables confidentiality and integrity for off-site deployed services. Thereby, securing key-value stores has received particular attention, as they are a building block for many ...
PProx: efficient privacy for recommendation-as-a-service
- Guillaume Rosinosky,
- Simon Da Silva,
- Sonia Ben Mokhtar,
- Daniel Négru,
- Laurent Réveillère,
- Etienne Rivière
We present PProx, a system preventing recommendation-as-a-service (RaaS) providers from accessing sensitive data about the users of applications leveraging their services. PProx does not impact recommendations accuracy, is compatible with arbitrary ...
FW-KV: improving read guarantees in PSI
We present FW-KV, a novel distributed transactional in-memory key-value store that guarantees the Parallel Snapshot Isolation (PSI) correctness level. FW-KV's primary goal is to allow its read-only transactions to access more up-to-date (fresher) ...
Towards optimal placement and scheduling of DNN operations with Pesto
The increasing size of Deep Neural Networks (DNNs) has necessitated the use of multiple GPUs to host a single DNN model, a practice commonly referred to as model parallelism. The key challenge for model parallelism is to efficiently and effectively ...
Prosecutor: an efficient BFT consensus algorithm with behavior-aware penalization against Byzantine attacks
Current leader-based Byzantine fault-tolerant (BFT) protocols aim to improve the efficiency for achieving consensus while tolerating failures; however, Byzantine servers are able to repeatedly impair BFT systems as faulty servers launch attacks without ...
SeBS: a serverless benchmark suite for function-as-a-service computing
Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud services, and serverless functions have immediately become a new middleware for building scalable and cost-efficient microservices and appli cations. However, ...
Magic-Pipe: self-optimizing video analytics pipelines
Microservices-based video analytics pipelines routinely use multiple deep convolutional neural networks. We observe that the best allocation of resources to deep learning engines (or microservices) in a pipeline, and the best configuration of parameters ...
Experience Paper: sgx-dl: dynamic loading and hot-patching for secure applications
Trusted execution as offered by Intel's Software Guard Extensions (SGX) is considered as an enabler to protect the integrity and confidentiality of stateful workloads such as key-value stores and databases in untrusted environments. These systems are ...
Xar-trek: run-time execution migration among FPGAs and heterogeneous-ISA CPUs
- Edson Horta,
- Ho-Ren Chuang,
- Naarayanan Rao VSathish,
- Cesar Philippidis,
- Antonio Barbalace,
- Pierre Olivier,
- Binoy Ravindran
Datacenter servers are increasingly heterogeneous: from x86 host CPUs, to ARM or RISC-V CPUs in NICs/SSDs, to FPGAs. Previous works have demonstrated that migrating application execution at run-time across heterogeneous-ISA CPUs can yield significant ...
SHARC: improving adaptive replacement cache with shadow recency cache management
Adaptive Replacement Cache (ARC) is a state-of-the-art cache replacement policy with a constant-time complexity per request. It uses a recency list and a frequency list to balance between access recency and access frequency. In this paper, we re-examine ...
Experience Paper: Danaus: isolation and efficiency of container I/O at the client side of network storage
Containers are a mainstream virtualization technique commonly used to run stateful workloads over persistent storage. In multi-tenant hosts with high utilization, resource contention at the system kernel often leads to inefficient handling of the ...
SwitchFlow: preemptive multitasking for deep learning
Accelerators, such as GPU, are a scarce resource in deep learning (DL). Effectively and efficiently sharing GPU leads to improved hardware utilization as well as user experiences, who may need to wait for hours to access GPU before a long training job ...
FaaSTCC: efficient transactional causal consistency for serverless computing
In this paper we study mechanisms that permit to augment the FaaS middleware with support for Transactional Causal Consistency (TCC). At first glance, it may seem that offering TCC to FaaS applications can trivially be achieved, given that the FaaS ...
RamCast: RDMA-based atomic multicast
Atomic multicast is a group communication abstraction useful in the design of highly available and scalable systems. It allows messages to be addressed to a subset of the processes in the system reliably and consistently. Many atomic multicast ...
Memory at your service: fast memory allocation for latency-critical services
Co-location and memory sharing between latency-critical services, such as key-value store and web search, and best-effort batch jobs is an appealing approach to improving memory utilization in multi-tenant datacenter systems. However, we find that the ...
Gossip consensus
Gossip-based consensus protocols have been recently proposed to confront the challenges faced by state machine replication in large geographically distributed systems. It is unclear, however, to which extent consensus and gossip communication fit ...
Experience Paper: Towards enhancing cost efficiency in serverless machine learning training
Function-as-a-Service (FaaS) has raised a growing interest in how to "tame" serverless to enable domain-specific use cases such as data-intensive applications and machine learning (ML), to name a few. Recently, several systems have been implemented for ...
CAT: content-aware tracing and analysis for distributed systems
Tracing and analyzing the interactions and exchanges between nodes is fundamental to uncover performance, correctness and dependability issues almost unavoidable in any complex distributed system. Existing monitoring tools acknowledge this importance ...
Snarl: entangled merkle trees for improved file availability and storage utilization
In cryptographic decentralized storage systems, files are split into chunks and distributed across a network of peers. These storage systems encode files using Merkle trees, a hierarchical data structure that provides integrity verification and lookup ...
Sizeless: predicting the optimal size of serverless functions
Serverless functions are an emerging cloud computing paradigm that is being rapidly adopted by both industry and academia. In this cloud computing model, the provider opaquely handles resource management tasks such as resource provisioning, deployment, ...
Let's wait awhile: how temporal workload shifting can reduce carbon emissions in the cloud
Depending on energy sources and demand, the carbon intensity of the public power grid fluctuates over time. Exploiting this variability is an important factor in reducing the emissions caused by data centers. However, regional differences in the ...
Lognroll: discovering accurate log templates by iterative filtering
Modern IT systems rely heavily on log analytics for critical operational tasks. Since the volume of logs produced from numerous distributed components is overwhelming, it requires us to employ automated processing. The first step of automated log ...
Privacy preserving event based transaction system in a decentralized environment
In this paper, we present the design and implementation of a privacy preserving event based UTXO (Unspent Transaction Output) transaction system. Unlike the existing approaches that often depend on smart contracts where digital assets are first locked ...
YASMIN: a real-time middleware for COTS heterogeneous platforms
Commercial-off-the-shelf (COTS) heterogeneous platforms provide immense computational power, but are difficult to program and to correctly use when real-time requirements come into play: A sound configuration of the operating system scheduler is needed, ...
Implicit model specialization through dag-based decentralized federated learning
Federated learning allows a group of distributed clients to train a common machine learning model on private data. The exchange of model updates is managed either by a central entity or in a decentralized way, e.g. by a blockchain. However, the strong ...
A fresh look at the architecture and performance of contemporary isolation platforms
With the ever-increasing pervasiveness of the cloud computing paradigm, strong isolation guarantees and low performance overhead from isolation platforms are paramount. An ideal isolation platform offers both: an impermeable isolation boundary while ...
Highly-available and consistent group collaboration at the edge with colony
Edge applications, such as gaming, cooperative engineering, or in-the-field information sharing, enjoy immediate response, autonomy and availability by distributing and replicating data at the edge. However, application developers and users demand the ...
Montsalvat: Intel SGX shielding for GraalVM native images
- Peterson Yuhala,
- Jämes Ménétrey,
- Pascal Felber,
- Valerio Schiavoni,
- Alain Tchana,
- Gaël Thomas,
- Hugo Guiroux,
- Jean-Pierre Lozi
The popularity of the Java programming language has led to its wide adoption in cloud computing infrastructures. However, Java applications running in untrusted clouds are vulnerable to various forms of privileged attacks. The emergence of trusted ...
Lachesis: a middleware for customizing OS scheduling of stream processing queries
Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transformations of raw data into value. The performance of such applications, run by Stream Processing Engines (SPEs), can be boosted through custom CPU ...
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
Middleware '22 | 21 | 8 | 38% |
Middleware '17 | 85 | 20 | 24% |
Middleware '17 | 20 | 7 | 35% |
Middleware '17 | 17 | 12 | 71% |
Middleware Industry '15 | 20 | 4 | 20% |
Middleware '15 | 118 | 23 | 19% |
Middleware '14 | 144 | 27 | 19% |
Middleware '12 | 18 | 13 | 72% |
Middleware '08 | 117 | 21 | 18% |
Middleware '07 | 108 | 22 | 20% |
Middleware '06 | 122 | 21 | 17% |
Middleware '03 | 158 | 25 | 16% |
Overall | 948 | 203 | 21% |