To provide compressed storage for large amounts of time series data, we present a new strategy data deduplication. Rather than attempting to deduplicate entire chunks, employ generalized approach, where each chunk is split into part worth deduplicating and that must be stored directly. This simple principle enables greater compression the often similar, non-identical, chunks case classic deduplication, while keeping benefits such as scalability, robustness, on-the-fly storage, retrieval,...

We detail a practical compression scheme for lossless of time-series data, based on the emerging concept generalized deduplication. As data is no longer stored just archival purposes, but needs to be continuously accessed in many applications, designed low-cost random access its compressed avoiding decompression. With this method, an arbitrary bit original can read by accessing only few hundred bits worst case, several orders magnitude fewer than state-of-the-art schemes. Subsequent...

We study a generalization of deduplication, which enables lossless deduplication highly similar data and show that classic with fixed chunk length is special case. provide bounds on the expected coded sequences for generalized coding has asymptotic near-entropy cost under proposed source model. More importantly, we allows multiple orders magnitude faster convergence than deduplication. This means can compression benefits much earlier key in practical systems. Numerical examples demonstrate...

The amount of data generated worldwide is expected to grow from 33 175 ZB by 2025 in part driven the growth Internet Things (IoT) and cyber-physical systems (CPS). To cope with this enormous data, new cloud storage techniques must be developed. Generalised Data Deduplication (GDD) a paradigm for reducing cost systematically identifying near identical chunks, storing their common component once, compact representation deviation original chunk each chunk. This paper presents system...

We introduce Titchy, which is a compression method for time-series data generated by the Internet of Things. Our proposed flexible and has several advantages when applied in IoT ecosystem: 1) it able to compress even only small amount memory can be allocated it; 2) compresses tiny chunks, so introduces very little latency during online operation thus, enables frequent timely updates with compressed data; 3) facilitates efficient storage retrieval enabling low-cost random access data,...

In cloud storage systems, malicious users may exploit client-side deduplication responses to infer what other are storing in the cloud. We propose CIDER, a low overhead approach mitigate this side channel by obfuscating existence status of data stored analyze scheme's ability obfuscate side-channel and discuss attacks that user still employ he could learn from such attacks. Finally, we use simulated real examine performance under realistic workloads, revealing CIDER ends up transmitting less...

This work proposes a novel design for secure cloud storage systems using third party to meet three seemingly opposing demands: reduce requirements on the cloud, protect against erasures (data loss), and maintain confidentiality of data. More specifically, we achieve cost reductions data deduplication without requiring system users trust that operates honestly. We analyze security our scheme honest-but-curious covert adversaries may collude with multiple parties show no sensitive information...

We propose and implement a technique to enable random access in any data compressor. With the transformed compressor, arbitrary requests compressed file's content can be served without decompressing large amounts of unrequested data. A comprehensive performance study is carried out: cloud storage pod used examine compression capabilities achieved with eight popular tools for three diverse types under different cache conditions. compare speed accesses uncompressed file compressed, quantify...

This paper considers benefits of coding techniques in recommendation systems operating over wireless channels with erasures. We identify scenarios where coded broadcasting can increase the overall user satisfaction at a fixed channel utilization level. Such opportunities arise both when preferences are unknown, and must be explored, they known exploited to recommend optimally. determine magnitude potential gains show that is most beneficial if users have heterogeneous preferences. Finally,...