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Config 2.0: towards reinforcement learning based configuration of stream processing systems
Distributed stream processing systems (DSPSs) have enabled us to build scalable, fast, and reactive applications. As faults are common in any distributed system, DSPSs allow for recovering from faults using various techniques, for example, snapshotting ...
AutoML: towards automation of machine learning systems maintainability
Machine learning systems both gained significant interest from the academic side and have seen adoption in the industry. However, one aspect that has received insufficient attention so far is the study of the lifecycle of such systems. This aspect is ...
Multi-objective evolutionary based feature selection supported by distributed multi-label classification and deep learning on image/video data
We live in an era in which a myriad of computer systems produce immense amounts of (raw) data every day. This big data must be processed efficiently to gain valuable and hidden knowledge. Complex processing pipelines need to be designed for filtering ...
Efficient parallel execution of block transactions in blockchain
Miners and validators in current blockchains serially execute block transactions. Such serial execution cannot efficiently utilize modern multi-core resources, consequently hampering system throughput. We propose three approaches to improve blockchain ...
OneOS: a distributed operating system for the internet of things
Existing Internet of Things (IoT) platforms introduce various framework-specific APIs for building user applications, which causes technology fragmentation within the IoT ecosystem and incur engineering costs. I seek to adopt standard POSIX APIs in an ...
Non-relational multi-level caching for mitigation of staleness & stragglers in distributed deep learning
For efficient distributed deep neural network design, mitigation of stale gradients and stragglers is necessary. The stale gradient problem occurs during the distribution and parallelism of the deep neural networks on the multi-cluster/nodes. The ...
Using blockchain to provide trusted interoperability to system-of-systems in smart cities context
Currently, Smart Cities use computational solutions that promote services to improve the quality of life of the entire population. However, these systems are often heterogeneous and designed in an isolated way that makes it challenging to integrate with ...
Autonomous resource management in distributed stream processing systems
Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are deployed on in-network resources to deliver query results while fulfilling the Quality of Service (QoS) requirements of the end-users. Various resource ...
Token-based incentive schemes in decentralized P2P storage networks
Token-based incentives are promising schemes to increase participation in decentralized peer-to-peer networks. They encourage peers to share resources in exchange for tokens. A concern is that decentralized services need a large number of participants ...
Using blockchain technology for software identity maintenance
Recently, the number of entities in the digital world has increased, due to technologies like 5G and the Internet of Things (IoT). Therefore, in a software application, it is important to be able to identify and maintain entities in an interoperable, ...
FlexOS: easy specialization of OS safety properties
Modern operating systems are tightly coupled to a specific isolation approach and safety mechanism. At design time, the isolation strategy is set in stone and rarely revisited later, due to prohibitive costs. This lack of flexibility hurts ...
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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% |