arXiv subjects

Amr El Abbadi

Publications and source records attributed to Amr El Abbadi.

24 records · Page 2Linked to original sources

arXiv2019

Towards Global Asset Management in Blockchain Systems

Permissionless blockchains (e.g., Bitcoin, Ethereum, etc) have shown a wide success in implementing global scale peer-to-peer cryptocurrency systems. In such blockchains, new currency units are generated through the mining process and are used in addition to transaction fees to incentivize miners to maintain the blockchain. Although it is clear how currency units are generated and transacted on, it is unclear how to use the infrastructure of permissionless blockchains to manage other assets than the blockchain's currency units (e.g., cars, houses, etc). In this paper, we propose a global asset management system by unifying permissioned and permissionless blockchains. A governmental permissioned blockchain authenticates the registration of end-user assets through smart contract deployments on a permissionless blockchain. Afterwards, end-users can transact on their assets through smart contract function calls (e.g., sell a car, rent a room in a house, etc). In return, end-users get paid in currency units of the same blockchain or other blockchains through atomic cross-chain transactions and governmental offices receive taxes on these transactions in cryptocurrency units.

cs.DB↗

arXiv2019

ParBlockchain: Leveraging Transaction Parallelism in Permissioned Blockchain Systems

Many existing blockchains do not adequately address all the characteristics of distributed system applications and suffer from serious architectural limitations resulting in performance and confidentiality issues. While recent permissioned blockchain systems, have tried to overcome these limitations, their focus has mainly been on workloads with no-contention, i.e., no conflicting transactions. In this paper, we introduce OXII, a new paradigm for permissioned blockchains to support distributed applications that execute concurrently. OXII is designed for workloads with (different degrees of) contention. We then present ParBlockchain, a permissioned blockchain designed specifically in the OXII paradigm. The evaluation of ParBlockchain using a series of benchmarks reveals that its performance in workloads with any degree of contention is better than the state of the art permissioned blockchain systems.

cs.DC↗

arXiv2018

A Distributed Collaborative Filtering Algorithm Using Multiple Data Sources

Collaborative Filtering (CF) is one of the most commonly used recommendation methods. CF consists in predicting whether, or how much, a user will like (or dislike) an item by leveraging the knowledge of the user's preferences as well as that of other users. In practice, users interact and express their opinion on only a small subset of items, which makes the corresponding user-item rating matrix very sparse. Such data sparsity yields two main problems for recommender systems: (1) the lack of data to effectively model users' preferences, and (2) the lack of data to effectively model item characteristics. However, there are often many other data sources that are available to a recommender system provider, which can describe user interests and item characteristics (e.g., users' social network, tags associated to items, etc.). These valuable data sources may supply useful information to enhance a recommendation system in modeling users' preferences and item characteristics more accurately and thus, hopefully, to make recommenders more precise. For various reasons, these data sources may be managed by clusters of different data centers, thus requiring the development of distributed solutions. In this paper, we propose a new distributed collaborative filtering algorithm, which exploits and combines multiple and diverse data sources to improve recommendation quality. Our experimental evaluation using real datasets shows the effectiveness of our algorithm compared to state-of-the-art recommendation algorithms.

cs.IR↗

arXiv2012

Serializability, not Serial: Concurrency Control and Availability in Multi-Datacenter Datastores

We present a framework for concurrency control and availability in multi-datacenter datastores. While we consider Google's Megastore as our motivating example, we define general abstractions for key components, making our solution extensible to any system that satisfies the abstraction properties. We first develop and analyze a transaction management and replication protocol based on a straightforward implementation of the Paxos algorithm. Our investigation reveals that this protocol acts as a concurrency prevention mechanism rather than a concurrency control mechanism. We then propose an enhanced protocol called Paxos with Combination and Promotion (Paxos-CP) that provides true transaction concurrency while requiring the same per instance message complexity as the basic Paxos protocol. Finally, we compare the performance of Paxos and Paxos-CP in a multi-datacenter experimental study, and we demonstrate that Paxos-CP results in significantly fewer aborted transactions than basic Paxos.

cs.DB↗

arXiv2010

ElasTraS: An Elastic Transactional Data Store in the Cloud

Over the last couple of years, "Cloud Computing" or "Elastic Computing" has emerged as a compelling and successful paradigm for internet scale computing. One of the major contributing factors to this success is the elasticity of resources. In spite of the elasticity provided by the infrastructure and the scalable design of the applications, the elephant (or the underlying database), which drives most of these web-based applications, is not very elastic and scalable, and hence limits scalability. In this paper, we propose ElasTraS which addresses this issue of scalability and elasticity of the data store in a cloud computing environment to leverage from the elastic nature of the underlying infrastructure, while providing scalable transactional data access. This paper aims at providing the design of a system in progress, highlighting the major design choices, analyzing the different guarantees provided by the system, and identifying several important challenges for the research community striving for computing in the cloud.

cs.DB↗

arXiv2010

Anonimos: An LP based Approach for Anonymizing Weighted Social Network Graphs

The increasing popularity of social networks has initiated a fertile research area in information extraction and data mining. Anonymization of these social graphs is important to facilitate publishing these data sets for analysis by external entities. Prior work has concentrated mostly on node identity anonymization and structural anonymization. But with the growing interest in analyzing social networks as a weighted network, edge weight anonymization is also gaining importance. We present Anónimos, a Linear Programming based technique for anonymization of edge weights that preserves linear properties of graphs. Such properties form the foundation of many important graph-theoretic algorithms such as shortest paths problem, k-nearest neighbors, minimum cost spanning tree, and maximizing information spread. As a proof of concept, we apply Anónimos to the shortest paths problem and its extensions, prove the correctness, analyze complexity, and experimentally evaluate it using real social network data sets. Our experiments demonstrate that Anónimos anonymizes the weights, improves k-anonymity of the weights, and also scrambles the relative ordering of the edges sorted by weights, thereby providing robust and effective anonymization of the sensitive edge-weights. Additionally, we demonstrate the composability of different models generated using Anónimos, a property that allows a single anonymized graph to preserve multiple linear properties.

cs.DB↗