The proceedings contain 10 papers. The topics discussed include: QROSS: QUBO relaxation parameter optimization via learning solver surrogates;VPN-nonVPN traffic classification using deep reinforced naive bayes and fuz...
ISBN:
(纸本)9781665449328
The proceedings contain 10 papers. The topics discussed include: QROSS: QUBO relaxation parameter optimization via learning solver surrogates;VPN-nonVPN traffic classification using deep reinforced naive bayes and fuzzy k-means clustering;personalized federated learning by structured and unstructured pruning under data heterogeneity;effect-centric networking;joint offloading and resource allocation of UAV-assisted mobile edge computing with delay constraints;backup placement in WSNs in the network management distributed setting;AI-based robust convex relaxations for supporting diverse QoS in next-generation wireless systems;dynamic DNN decomposition for lossless synergistic inference;and joint offloading and resource allocation of UAV-assisted mobile edge computing with delay constraints.
Software Defined Systems (SDS) abstract the actual hardware at different layers with software components, layers such as networking, Storage, Security, Servers, Data Centers, Clouds etc. This abstraction facilitates c...
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In the era of cloud networking, database protection is a problem that is becoming more and more crucial, and blockchain technology is emerging as a potent remedy. Blockchain is a digital ledger technology that uses an...
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Direct memory access (RDMA) over Converged Ethernet (RoCE) allows for direct memory transfers between systems, granting minimal latency and CPU overhead. This allows low-latency applications where data collection, ana...
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ISBN:
(纸本)9798350377330;9798350377323
Direct memory access (RDMA) over Converged Ethernet (RoCE) allows for direct memory transfers between systems, granting minimal latency and CPU overhead. This allows low-latency applications where data collection, analytics and feedback to the user are distributed between different nodes, optimizing resource management. RoCE, originally designed for data center operations, has the potential to effectively support applications deployed on edge nodes, where limited resources are available and low latency is required. This demo shows the use of RoCE in support to an AI-based application for smart shopping, deployed at the edge.
Balancing robustness and computational efficiency in machine learning models is challenging, especially in settings with limited resources like mobile and IoT devices. This study introduces Adaptive and Localized Adve...
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Recently, Large Language Models (LLMs) have been a phenomenal trend in the Artificial intelligence field. However, training and fine-tuning can be challenging because of privacy concerns and limited computing resource...
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In data driven deep learning, distributed sensing and joint computing bring heavy load for computing and communication. To face the challenge, over-the-air computation (OAC) has been proposed for multi-sensor data agg...
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The proceedings contain 63 papers. The topics discussed include: post quantum communication over the internet infrastructure;efficient and resilient edge computing: algorithms, techniques and research opportunities;se...
ISBN:
(纸本)9798400716737
The proceedings contain 63 papers. The topics discussed include: post quantum communication over the internet infrastructure;efficient and resilient edge computing: algorithms, techniques and research opportunities;self-stabilizing byzantine multivalued consensus;a further study on weak byzantine gathering of mobile agents;distributed uniform partitioning of a region using opaque ASYNC luminous mobile robots;space and move-optimal arbitrary pattern formation on a rectangular grid by robot swarms;maximal independent set via mobile agents;collision-free linear time mutual visibility for asynchronous fat robots;arbitrary pattern formation on a continuous circle by oblivious robot swarm;sublinear message bounds of authenticated implicit byzantine agreement;and LightKey: lightweight and secure key agreement protocol for effective communication in internet of vehicles.
We introduce SpDISTAL, a compiler for sparse tensor algebra that targets distributed systems. SpDISTAL combines separate descriptions of tensor algebra expressions, sparse data structures, data distribution, and compu...
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Fog computing is a promising computing paradigm that provides computing services close to end-users at edge of the network. Therefore, it supports large-scale, geographically distributed and latency-sensitive applicat...
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ISBN:
(数字)9781665469753
ISBN:
(纸本)9781665469753
Fog computing is a promising computing paradigm that provides computing services close to end-users at edge of the network. Therefore, it supports large-scale, geographically distributed and latency-sensitive applications. However, due to its untrusty nature, numerous security challenges must be overcome. The integrity verification of the data in fog computing context is one of the main challenges to tackle. Indeed, most of existing solutions consider a centralized data storage context, and usually rely on a trusted third party to check data integrity. However, these approaches are not suitable for fog computing architecture, since the data is stored in a dynamic and a completely distributed manner. Motivated by these challenges, we propose in this paper, a new efficient public verification scheme that protects the integrity of the data in fog computing architecture. Our scheme secures data integrity and authenticity based on the short integer solution SIS problem and the identity-based signatures. In addition, it allows to efficiently verify the integrity of data, even when it is separately shared on multiple servers. This verification can be performed by any end-user on the architecture, and without relying on any trusted third party. Finally, we show through extensive simulation that our solution is highly effective and outperforms existing solutions.
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