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X-WR-CALNAME:Information Systems Group
X-ORIGINAL-URL:https://isg.ics.uci.edu
X-WR-CALDESC:Events for Information Systems Group
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DTSTART:20220313T100000
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DTSTART:20221106T090000
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DTSTART;TZID=America/Los_Angeles:20221104T123000
DTEND;TZID=America/Los_Angeles:20221104T140000
DTSTAMP:20260711T124822
CREATED:20220926T231639Z
LAST-MODIFIED:20221028T174302Z
UID:1476-1667565000-1667570400@isg.ics.uci.edu
SUMMARY:Juncheng Fang: PeloPartition- Improving Blockchain Resilience to Partitioning by Sharding
DESCRIPTION:Abstract:\nBlockchain has gained considerable traction over the last few years and plays a critical role in realizing decentralized and cryptocurrency applications. A challenge that has been overlooked in prior blockchain algorithms is that they do not consider large-scale network outages and relied on the assumption of reliable global network connectivity. In the event of a large-scale network partition\, forks may occur between partitioned regions. After the partition ends they will be discarded\, leading to the loss of many blocks and a considerable amount of wasted work.\nThis paper presents PeloPartition\, which provides a sharding mechanism to improve blockchain’s resilience to the possibility of a global internet outage. In PeloPartition we form consensus groups dynamically and consider the partitioning of the group as a hint to split the blockchain into branches and guarantee that all of them will be merged after the network is recovered. We indicate different methodologies to ensure blockchain security while partitioning occurs. Our experiments use simulations to show how this approach can improve the performance of blockchain algorithms and prevent wasted computational power during partitioning.\n\nBio:\nJuncheng Fang is a 2nd-year Ph.D. student in the Computer Science Department at UC Irvine\, supervised by Prof. Faisal Nawab. His current research focuses on blockchain and distributed systems.
URL:https://isg.ics.uci.edu/event/juncheng-fang-pelopartition-improving-blockchain-resilience-to-partitioning-by-sharding/
LOCATION:DBH 4011
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221118T123000
DTEND;TZID=America/Los_Angeles:20221118T140000
DTSTAMP:20260711T124822
CREATED:20220926T231824Z
LAST-MODIFIED:20260405T013614Z
UID:1478-1668774600-1668780000@isg.ics.uci.edu
SUMMARY:Peeyush Gupta: A Demonstration of TippersDB
DESCRIPTION:Abstract: In the talk\, I’ll present TippersDB\, a middleware system designed to build\nsensor-based smart space analytical applications. TippersDB supports a powerful data model that decouples semantic data about the application domain from sensor data using which the semantic data is derived. By supporting mechanisms to map/translate\ndata\, concepts\, and queries between the two levels\, TippersDB relieves the application developers from having to know or reason about either the type or location of sensors or write sensor-specific code. In addition\, it allows for multiple optimizations based on smart space semantics to improve query processing.\nIn the talk\, I will present TippersDB’s data model\, query-driven translation of sensor data\, a summary of the system implementation\, and a demonstration of the TippersDB system. \n \nBio: Peeyush Gupta is a Postdoc in the Computer Science Department at UC Irvine\, advised by Prof. Sharad Mehrotra. His research interests include IoT data management\, time series database systems\, and data security and privacy.
URL:https://isg.ics.uci.edu/event/peeyush-gupta-a-demonstration-of-tippersdb/
LOCATION:DBH 4011
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