Sujaya Maiyya

University of California, Santa Barbara

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Amr El Abbadi

University of California, Santa Barbara

Divyakant Agrawal

University of California, Santa Barbara

Mohammad Javad Amiri

University of Tehran

Victor Zakhary

University of California, Santa Barbara

Yuanyuan Tian

Arizona State University

Alexandra Meliou

University of Massachusetts Amherst

Yael Amsterdamer

Bar-Ilan University

Meihui Zhang

Shenyang Pharmaceutical University

FÖ

Fatma Özcan

Mi̇lli̇ Eği̇ti̇m Bakanliği

Juliana Freire

New York University

Cooperative Institutions

University of California, Santa Barbara

Centre National de la Recherche Scientifique

IBM Research - Almaden

IBM (United States)

University of California, Santa Cruz

University of Pennsylvania

National University of Singapore

Microsoft (United States)

Microsoft Research (United Kingdom)

University of California System

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Waffle: An Online Oblivious Datastore for Protecting Data Access Patterns

Proceedings of the ACM on Management of Data (2023)

Sujaya Maiyya Sharath Chandra Vemula Divyakant Agrawal Amr El Abbadi Florian Kerschbaum

We present Waffle, a datastore that protects an application's data access patterns from a passive persistent adversary. Waffle achieves this without prior knowledge of the input data access distribution, making it the first of its kind to adaptively handle input sequences under a passive persistent adversary. Waffle maintains a constant bandwidth and client-side storage overhead, which can be adjusted to suit the application owner's preferences. This flexibility allows the owner to fine-tune system parameters and strike a balance between security and performance. Our evaluation, utilizing the Yahoo! Cloud Serving Benchmark (YCSB) benchmark and Redis as the backend storage, demonstrates promising results. The insecure baseline outperforms Waffle by a mere 5-6x, whereas Waffle outperforms Pancake-a state-of-the-art oblivious datastore under passive persistent adversaries-by 45-57%, and a concurrent ORAM system, TaoStore, by 102x.

Benchmark (surveying)

Data access

10.1145/3626760

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Citations (5)

Diversity, Equity and Inclusion Activities in Database Conferences: A 2022 Report

ACM SIGMOD Record (2023)

Sihem Amer-Yahia Divyakant Agrawal Yael Amsterdamer Sourav S. Bhowmick Angela Bonifati

The Diversity, Equity and Inclusion (DEI) initiative started as the Diversity/Inclusion initiative in 2020 [4]. The current report summarizes our activities in 2022. Our responsibility as a community is to ensure that attendees of DB conferences feel included, irrespective of their scientific perspective and personal background. One of the first steps was to establish the role of the DEI chairs at DB Conferences, with the DEI team dedicated to providing leadership to help our community achieve this goal. In this leadership role, the DEI team is advising DEI chairs at DB conferences, serving as a memory of DEI events at conferences, building an agreed-upon vision, and committing to working together to devise a set of measures for achieving DEI. That is pursued via actions led by our core members (Figure 1) and liaisons of individual executive bodies (Figure 2): REACH OUT collects data and experiences from our community. INCLUDE monitors and recommends inclusion efforts. ORGANIZE focuses on in-conference organization efforts, such as adopting a code of conduct. INFORM communicates through various channels. SUPPORT coordinates DEI support from executive bodies and sponsors. SCOUT collates DEI efforts from other communities. COORDINATE manages all actions. Two new actions: MEDIA preserves and disseminates the digital media produced by DEI@DB events. ETHICS establishes and promotes ethics guidelines for publications in our community.

Equity

Executive committee

10.1145/3615952.3615964

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Ziziphus: Scalable Data Management Across Byzantine Edge Servers

2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023)

Mohammad Javad Amiri Daniel Shu Sujaya Maiyya Divyakant Agrawal Amr El Abbadi

Edge computing while bringing computation and data closer to users in order to improve response time, distributes edge servers in wide area networks resulting in increased communication latency between the servers. Synchronizing globally distributed edge servers, especially in the presence of Byzantine servers, becomes costly due to the high communication complexity of Byzantine fault-tolerant consensus protocols. In this paper, we present Ziziphus, a geo-distributed system that partitions edge servers into fault-tolerant zones where each zone processes transactions initiated by nearby clients locally. Global synchronization among zones is required only in special situations, e.g., migration of clients from one zone to another. On the one hand, the two-level architecture of Ziziphus confines the malicious behavior of nodes within zones requiring a much cheaper protocol at the top level for global synchronization. On the other hand, Ziziphus processes local transactions within zones by edge servers closer to clients resulting in enhanced performance. Ziziphus further introduces zone clusters to enhance scalability where instead of running global synchronization among all zones, only zones of a single cluster are synchronized.

10.1109/icde55515.2023.00044

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Citations (3)

KLL ^± approximate quantile sketches over dynamic datasets

Proceedings of the VLDB Endowment (2021)

Fuheng Zhao Sujaya Maiyya R. Wiener Divyakant Agrawal Amr El Abbadi

Recently the long standing problem of optimal construction of quantile sketches was resolved by K arnin, L ang, and L iberty using the KLL sketch (FOCS 2016). The algorithm for KLL is restricted to online insert operations and no delete operations. For many real-world applications, it is necessary to support delete operations. When the data set is updated dynamically, i.e., when data elements are inserted and deleted, the quantile sketch should reflect the changes. In this paper, we propose KLL ± , the first quantile approximation algorithm to operate in the bounded deletion model to account for both inserts and deletes in a given data stream. KLL ± extends the functionality of KLL sketches to support arbitrary updates with small space overhead. The space bound for KLL ± is [EQUATION], where ∈ and δ are constants that determine precision and failure probability, and α bounds the number of deletions with respect to insert operations. The experimental evaluation of KLL ± highlights that with minimal space overhead, KLL ± achieves comparable accuracy in quantile approximation to KLL.

Quantile

Sketch

10.14778/3450980.3450990

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Citations (16)

SeeMoRe: A Fault-Tolerant Protocol for Hybrid Cloud Environments

2022 IEEE 38th International Conference on Data Engineering (ICDE) (2020)

Mohammad Javad Amiri Sujaya Maiyya Divyakant Agrawal Amr El Abbadi

Large scale data management systems utilize State Machine Replication to provide fault tolerance and to enhance performance. Fault-tolerant protocols are extensively used in the distributed database infrastructure of large enterprises such as Google, Amazon, and Facebook. However, and in spite of years of intensive research, existing fault-tolerant protocols do not adequately address hybrid cloud environments consisting of private and public clouds which are widely used by enterprises. In this paper, we consider a private cloud consisting of nonmalicious nodes (crash-only failures) and a public cloud with possible malicious failures. We introduce SeeMoRe, a hybrid State Machine Replication protocol that uses the knowledge of where crash and malicious failures may occur in a public/private cloud environment to improve overall performance. SeeMoRe has three different modes that can be used depending on the private cloud load and the communication latency between the public and private clouds. SeeMoRe can dynamically transition from one mode to another. Furthermore, an extensive evaluation reveals that SeeMoRe's performance is close to the state of the art crash fault-tolerant protocols while tolerating malicious failures.

10.1109/icde48307.2020.00120

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Citations (18)

SeeMoRe: A Fault-Tolerant Protocol for Hybrid Cloud Environments.

arXiv (Cornell University) (2019)

Mohammad Javad Amiri Sujaya Maiyya Divyakant Agrawal Amr El Abbadi

Large scale data management systems utilize State Machine Replication to provide fault tolerance and to enhance performance. Fault-tolerant protocols are extensively used in the distributed database infrastructure of large enterprises such as Google, Amazon, and Facebook, as well as permissioned blockchain systems like IBM's Hyperledger Fabric. However, and in spite of years of intensive research, existing fault-tolerant protocols do not adequately address all the characteristics of distributed system applications. In particular, hybrid cloud environments consisting of private and public clouds are widely used by enterprises. However, fault-tolerant protocols have not been adapted for such environments. In this paper, we introduce SeeMoRe, a hybrid State Machine Replication protocol to handle both crash and malicious failures in a public/private cloud environment. SeeMoRe considers a private cloud consisting of nonmalicious nodes (either correct or crash) and a public cloud with both Byzantine faulty and correct nodes. SeeMoRe has three different modes which can be used depending on the private cloud load and the communication latency between the public and the private cloud. We also introduce a dynamic mode switching technique to transition from one mode to another. Furthermore, we evaluate SeeMoRe using a series of benchmarks. The experiments reveal that SeeMoRe's performance is close to the state of the art crash fault-tolerant protocols while tolerating malicious failures.

IBM

Replication

Source

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Database and Distributed Computing Foundations of Blockchains

Proceedings of the 2022 International Conference on Management of Data (2019)

Sujaya Maiyya Victor Zakhary Mohammad Javad Amiri Divyakant Agrawal Amr El Abbadi

The uprise of Bitcoin and other peer-to-peer cryptocurrencies has opened many interesting and challenging problems in cryptography, distributed systems, and databases. The main underlying data structure is blockchain, a scalable fully replicated structure that is shared among all participants and guarantees a consistent view of all user transactions by all participants in the system. In this tutorial, we discuss the basic protocols used in blockchain, and elaborate on its main advantages and limitations. To overcome these limitations, we provide the necessary distributed systems background in managing large scale fully replicated ledgers, using Byzantine Agreement protocols to solve the consensus problem. Finally, we expound on some of the most recent proposals to design scalable and efficient blockchains in both permissionless and permissioned settings. The focus of the tutorial is on the distributed systems and database aspects of the recent innovations in blockchains.

Distributed database

Distributed ledger

Distributed data store

10.1145/3299869.3314030

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Citations (14)

Diversity and Inclusion Activities in Database Conferences

ACM SIGMOD Record (2022)

Sihem Amer-Yahia Yael Amsterdamer Sourav S. Bhowmick Angela Bonifati Philippe Bonnet

Diversity and Inclusion (D&I) are core to fostering innovative thinking. Existing theories demonstrate that to facilitate inclusion, multiple types of exclusionary dynamics, such as self-segregation, communication apprehension, and stereotyping and stigmatizing, must be overcome [11]. A diverse group of people tends to surface different perspectives, which help to understand and address D&I. Fostering D&I in research communities must address issues related to inclusive interpersonal and small group dynamics, rules and codes of conduct, increasing diversity in under-represented groups and disciplines, and organizing D&I events, and longterm efforts to champion change [15].

Champion

Inclusion–exclusion principle

Apprehension

10.1145/3552490.3552510

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Citations (2)

Unifying consensus and atomic commitment for effective cloud data management

Proceedings of the VLDB Endowment (2019)

Sujaya Maiyya Faisal Nawab Divyakant Agrawal Amr El Abbadi

Data storage in the Cloud needs to be scalable and fault-tolerant. Atomic commitment protocols such as Two Phase Commit (2PC) provide ACID guarantees for transactional access to sharded data and help in achieving scalability. Whereas consensus protocols such as Paxos consistently replicate data across different servers and provide fault tolerance. Cloud based datacenters today typically treat the problems of scalability and fault-tolerance disjointedly. In this work, we propose a unification of these two different paradigms into one framework called Consensus and Commitment (C&C) framework. The C&C framework can model existing and well known data management protocols as well as propose new ones. We demonstrate the advantages of the C&C framework by developing a new atomic commitment protocol, Paxos Atomic Commit (PAC), which integrates commitment with recovery in a Paxos-like manner. We also instantiate commit protocols from the C&C framework catered to different Cloud data management techniques. In particular, we propose a novel protocol, Generalized PAC (G-PAC) that integrates atomic commitment and fault tolerance in a cloud paradigm involving both sharding and replication of data. We compare the performance of G-PAC with a Spanner-like protocol, where 2PC is used at the logical data level and Paxos is used for consistent replication of logical data. The experimental results highlight the benefits of combining consensus along with commitment into a single integrated protocol.

Commit

Two-phase commit protocol

Replication

Atomicity

10.14778/3303753.3303765

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Citations (20)

Blockchains and Databases: Opportunities and Challenges for the Permissioned and the Permissionless

Lecture notes in computer science (2020)

Divyakant Agrawal Amr El Abbadi Mohammad Javad Amiri Sujaya Maiyya Victor Zakhary

10.1007/978-3-030-54832-2_1

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