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FogExplorer
Fog application design is complex as it comprises not only the application architecture, but also the runtime infrastructure, and the deployment mapping from application modules to infrastructure machines. For each of these aspects, there is a variety ...
A Distributed Analysis and Benchmarking Framework for Apache OpenWhisk Serverless Platform
Serverless computing simplifies the life cycle of scalable web applications, through delegating most of the operational concerns to the cloud providers. One prominent serverless platform is Apache OpenWhisk which is employed by IBM Cloud. Despite the ...
Attack and Vulnerability Simulation Framework for Bitcoin-like Blockchain Technologies
Despite the very high volatility of the cryptocurrency markets, the interest in the development and adaptation of existing cryptocurrencies such as Bitcoin as well as new distributed ledger technologies is increasing. Therefore, understanding the ...
CIDDS: A Configurable and Distributed DAG-based Distributed Ledger Simulation Framework
Directed Acyclic Graph (DAG) based Distributed Ledger Technologies (DLT) such as IOTA Tangle has been proposed to address the inefficiencies of traditional blockchains, including the issues with scalability, high resource consumptions, and the ...
A Serverless Approach to Publish/Subscribe Systems
Building reliable and scalable publish/subscribe (pub/sub) systems require tremendous development efforts. The serverless paradigm simplifies the development and deployment of highly available applications by delegating most of the operational concerns ...
eVIBES: Configurable and Interactive Ethereum Blockchain Simulation Framework
Cryptocurrencies and Distributed Ledger Technologies, such as Ethereum have received extensive attention over the past few years. With the increasing popularity of Ethereum, comprehensive understanding of its various properties plays a critical role in ...
Applying Web-Technologies for Device State Processing in IoT Middleware
In this demo the use of web-based technologies for device state processing in IoT systems is presented. In particular, the Document Object Model (DOM) is used in conjunction with JavaScript processing to access and modify the state of heterogeneous ...
mKPAC: Kernel Packet Processing for Manycore Systems
Network Function Virtualization (NFV) has recently gained popularity due to its ability of offering high scalability and programmability using commodity servers and general-purpose operating system (OS). However, current OSes have failed to deliver the ...
A DSL for composing IoT systems
We believe that enabling services to collaborate, even if they were not designed to work together, will be important for the success of the Internet of Things (IoT). To support this we have designed a domain specific language (DSL) for service ...
Understanding the Behavior of Operator Placement Mechanisms on Large-Scale Networks
Operator Placement (OP) mechanism dictates the mapping of compute units, aka. operators on the network infrastructure based on the performance objectives requested by the end-user. The behavior of a placement is strongly influenced by the underlying ...
An Implementation Experience with SDN-enabled IoT Data Exchange Middleware
- Luca Scalzotto,
- Kyle E. Benson,
- Georgios Bouloukakis,
- Paolo Bellavista,
- Valérie Issarny,
- Sharad Mehrotra,
- Nalini Venkatasubramanian
This poster presents our prototype implementation of FireDeX [1], a cross-layer middleware that supports timely delivery of mission-critical messages (i.e. events) over an IoT data exchange service. Emergency scenarios may challenge/congest the network ...
Understanding Scheduler Workload on Non-Hyperscale Cloud Platform
Until now, research in cloud computing has mainly focused on hyperscale platforms. However, mid-size platforms represent 20%-40% of the worldwide public cloud market, and their usage under the form of on-premise cloud solutions is increasing. This ...
- Proceedings of the 19th International Middleware Conference (Posters)
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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% |