Daniel E. Lucani
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View article: Touch-Augmented Gaussian Splatting for Enhanced 3D Scene Reconstruction
Touch-Augmented Gaussian Splatting for Enhanced 3D Scene Reconstruction Open
This paper presents a multimodal framework that integrates touch signals (contact points and surface normals) into 3D Gaussian Splatting (3DGS). Our approach enhances scene reconstruction, particularly under challenging conditions like low…
View article: Rage for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications
Rage for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications Open
We introduce RAGE, an image compression framework that achieves four generally conflicting objectives: 1) good compression for a wide variety of color images, 2) computationally efficient, fast decompression, 3) fast random access of image…
View article: TREAT - Two wRongs makE A righT: efficient distributed storage and queries of IoT datasets with erasure coding and compression
TREAT - Two wRongs makE A righT: efficient distributed storage and queries of IoT datasets with erasure coding and compression Open
Erasure coding in distributed multi-cloud data storage increases availability, durability and security, but it also makes data analytics inefficient since the whole dataset must be reconstructed to answer a query, even if the result set is…
View article: RAGE for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications
RAGE for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications Open
We introduce RAGE, an image compression framework that achieves four generally conflicting objectives: 1) good compression for a wide variety of color images, 2) computationally efficient, fast decompression, 3) fast random access of image…
View article: PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data Compression
PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data Compression Open
Exponential growth in data collection is creating significant challenges for data storage and analytics latency.Approximate Query Processing (AQP) has long been touted as a solution for accelerating analytics on large datasets, however, th…
View article: Zip to Zip-It: Compression to Achieve Local Differential Privacy
Zip to Zip-It: Compression to Achieve Local Differential Privacy Open
Local differential privacy techniques for numerical data typically transform a dataset to ensure a bound on the likelihood that, given a query, a malicious user could infer information on the original samples. Queries are often solely base…
View article: Zip to Zip-it: Compression to Achieve Local Differential Privacy
Zip to Zip-it: Compression to Achieve Local Differential Privacy Open
Local differential privacy techniques for numerical data typically transform a dataset to ensure a bound on the likelihood that, given a query, a malicious user could infer information on the original samples. Queries are often solely base…
View article: Change a Bit to Save Bytes: Compression for Floating Point Time-Series Data
Change a Bit to Save Bytes: Compression for Floating Point Time-Series Data Open
The number of IoT devices is expected to continue its dramatic growth in the coming years and, with it, a growth in the amount of data to be transmitted, processed and stored. Compression techniques that support analytics directly on the c…
View article: GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT
GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT Open
Exponential growth in the amount of data generated by the Internet of Things currently pose significant challenges for data communication, storage and analytics and leads to high costs for organisations hoping to leverage their data. Novel…
View article: Change a Bit to save Bytes: Compression for Floating Point Time-Series Data
Change a Bit to save Bytes: Compression for Floating Point Time-Series Data Open
The number of IoT devices is expected to continue its dramatic growth in the coming years and, with it, a growth in the amount of data to be transmitted, processed and stored. Compression techniques that support analytics directly on the c…
View article: Stream Compression of DLMS Smart Meter Readings
Stream Compression of DLMS Smart Meter Readings Open
Smart electricity meters typically upload power consumption readings once or few times a day. Utility providers aim to increase the upload frequency in order to access consumption information in near real time, but the currently used data …
View article: Bonsai: A Generalized Look at Dual Deduplication
Bonsai: A Generalized Look at Dual Deduplication Open
Cloud Service Providers (CSPs) offer a vast amount of storage space at competitive prices to cope with the growing demand for digital data storage. Dual deduplication is a recent framework designed to improve data compression on the CSP wh…
View article: Bifrost: Secure, Scalable and Efficient File Sharing System Using Dual Deduplication
Bifrost: Secure, Scalable and Efficient File Sharing System Using Dual Deduplication Open
We consider the problem of sharing sensitive or valuable files across users while partially relying on a common, untrusted third-party, e.g., a Cloud Storage Provider (CSP). Although users can rely on a secure peer-to-peer (P2P) channel fo…
View article: Energy Efficient Data Recovery from Corrupted LoRa Frames
Energy Efficient Data Recovery from Corrupted LoRa Frames Open
High frame-corruption is widely observed in Long Range Wide Area Networks (LoRaWAN) due to the coexistence with other networks in ISM bands and an Aloha-like MAC layer. LoRa's Forward Error Correction (FEC) mechanism is often insufficient …
View article: QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations
QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations Open
Mobile edge computing pushes computationally-intensive services closer to the user to provide reduced delay due to physical proximity. This has led many to consider deploying deep learning models on the edge -- commonly known as edge intel…
View article: Yggdrasil: Privacy-Aware Dual Deduplication in Multi Client Settings
Yggdrasil: Privacy-Aware Dual Deduplication in Multi Client Settings Open
This paper proposes Yggdrasil, a protocol for privacy-aware dual data deduplication in multi client settings. Yggdrasil is designed to reduce the cloud storage space while safeguarding the privacy of the client's outsourced data. Yggdrasil…
View article: Optimal Accuracy-Time Trade-off for Deep Learning Services in Edge Computing Systems
Optimal Accuracy-Time Trade-off for Deep Learning Services in Edge Computing Systems Open
With the increasing demand for computationally intensive services like deep learning tasks, emerging distributed computing platforms such as edge computing (EC) systems are becoming more popular. Edge computing systems have shown promising…
View article: Stream Compression of DLMS Smart Meter Readings
Stream Compression of DLMS Smart Meter Readings Open
Smart electricity meters typically upload readings a few times a day. Utility providers aim to increase the upload frequency in order to access consumption information in near real time, but the legacy compressors fail to provide sufficien…
View article: Correction to “Fulcrum: Flexible Network Coding for Heterogeneous Devices”
Correction to “Fulcrum: Flexible Network Coding for Heterogeneous Devices” Open
In the above article [1], in Section II-B.1)a, titled “Outer Encoding,” the first sentence of the second paragraph should be corrected to consistently use to denote the coded packets, i.e., this sentence should state: “For systematic oute…
View article: Memory-aware Online Compression of CAN Bus Data for Future Vehicular Systems
Memory-aware Online Compression of CAN Bus Data for Future Vehicular Systems Open
Vehicles generate a large amount of data from their internal sensors. This data is not only useful for a vehicle's proper operation, but it provides car manufacturers with the ability to optimize performance of individual vehicles and comp…
View article: Smart Meter Data Compression using Generalized Deduplication
Smart Meter Data Compression using Generalized Deduplication Open
Utility providers are relying more often on smart, wirelessly connected smart meters to collect consumption information of their customers. The sheer amount of connected smart meters and the growing requirements to provide more frequent re…
View article: ZipLine
ZipLine Open
Network appliances continue to offer novel opportunities to offload\nprocessing from computing nodes directly into the data plane. One popular\nconcern of network operators and their customers is to move data increasingly\nfaster. A common…
View article: Optimal Accuracy-Time Trade-off for Deep Learning Services in Edge\n Computing Systems
Optimal Accuracy-Time Trade-off for Deep Learning Services in Edge\n Computing Systems Open
With the increasing demand for computationally intensive services like deep\nlearning tasks, emerging distributed computing platforms such as edge computing\n(EC) systems are becoming more popular. Edge computing systems have shown\npromis…
View article: Side Channel Security of Smart Meter Data Compression Techniques
Side Channel Security of Smart Meter Data Compression Techniques Open
Given the large and sustained growth in the number of smart meters for different applications, e.g., electricity, water or heat, effective data compression has become increasingly important.Although smart meters tend to encrypt payloads us…
View article: Hermes
Hermes Open
With the advent of the Internet of Things (IoT), the ever growing number of\nconnected devices observed in recent years and foreseen for the next decade\nsuggests that more and more data will have to be transmitted over a network,\nbefore …
View article: A Randomly Accessible Lossless Compression Scheme for Time-Series Data
A Randomly Accessible Lossless Compression Scheme for Time-Series Data Open
We detail a practical compression scheme for lossless compression of time-series data, based on the emerging concept of generalized deduplication. As data is no longer stored for just archival purposes, but needs to be continuously accesse…
View article: Age of Information Analysis for Instantly Decompressible IoT Protocols
Age of Information Analysis for Instantly Decompressible IoT Protocols Open
Generalized deduplication (GD) has been proposed as a new approach for reducing the cost of storage. Recent work has adapted this technique to provide distributed, multi-source lossless compression to reduce the total number of bits transm…
View article: DSEP Fulcrum: Dynamic Sparsity and Expansion Packets for Fulcrum Network Coding
DSEP Fulcrum: Dynamic Sparsity and Expansion Packets for Fulcrum Network Coding Open
Fulcrum coding combines a high-field outer Random Linear Network Coding (RLNC) that generates outer coding expansion packets with a small-field inner RLNC that combines the source packets and the outer coding expansion packets. This two-la…
View article: Protocols to Reduce CPS Sensor Traffic Using Smart Indexing and Edge Computing Support
Protocols to Reduce CPS Sensor Traffic Using Smart Indexing and Edge Computing Support Open
We propose a new approach for lossless data compression to reduce the amount of data transmitted by Cyber-Physical Systems (CPS) by several-fold. Our approach uses an indexing technique inspired in the concept of generalized deduplication …