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Register a new userTowards Application Portability on Blockchains
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Added by
Kazuyuki Shudo
Publication date
2018
fields
Informatics Engineering
and research's language is
English
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We discuss the issue of what we call {em incentive mismatch}, a fundamental problem with public blockchains supported by economic incentives. This is an open problem, but one potential solution is to make application portable. Portability is desirable for applications on private blockchains. Then, we present examples of middleware designs that enable application portability and, in particular, support migration between blockchains.
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We improve the fundamental security threshold of eventual consensus Proof-of-Stake (PoS) blockchain protocols under the longest-chain rule by showing, for the first time, the positive effect of rounds with concurrent honest leaders. Current security analyses reduce consistency to the dynamics of an abstract, round-based block creation process that is determined by three events associated with a round: (i) event $A$: at least one adversarial leader, (ii) event $S$: a single honest leader, and (iii) event $M$: multiple, but honest, leaders. We present an asymptotically optimal consistency analysis assuming that an honest round is more likely than an adversarial round (i.e., $Pr[S] + Pr[M] > Pr[A]$); this threshold is optimal. This is a first in the literature and can be applied to both the simple synchronous communication as well as communication with bounded delays. In all existing consistency analyses, event $M$ is either penalized or treated neutrally. Specifically, the consistency analyses in Ouroboros Praos (Eurocrypt 2018) and Genesis (CCS 2018) assume that $Pr[S] - Pr[M] > Pr[A]$; the analyses in Sleepy Consensus (Asiacrypt 2017) and Snow White (Fin. Crypto 2019) assume that $Pr[S] > Pr[A]$. Moreover, all existing analyses completely break down when $Pr[S] < Pr[A]$. These thresholds determine the critical trade-off between the honest majority, network delays, and consistency error. Our new results can be directly applied to improve the security guarantees of the existing protocols. We also provide an efficient algorithm to explicitly calculate these error probabilities in the synchronous setting. Furthermore, we complement these results by analyzing the setting where $S$ is rare, even allowing $Pr[S] = 0$, under the added assumption that honest players adopt a consistent chain selection rule.
Every organisation today wants to adopt cloud computing paradigm and leverage its various advantages. Today everyone is aware of its characteristics which have made it so popular and how it can help the organisations focus on their core activities leaving all IT services development and maintenance to the cloud service providers. Application Programming Interfaces (APIs) act as the interface between the CSPs and the consumers. This paper proposes an improved access control mechanism for securing the Cloud APIs.
Existing blockchain systems scale poorly because of their distributed consensus protocols. Current attempts at improving blockchain scalability are limited to cryptocurrency. Scaling blockchain systems under general workloads (i.e., non-cryptocurrency applications) remains an open question. In this work, we take a principled approach to apply sharding, which is a well-studied and proven technique to scale out databases, to blockchain systems in order to improve their transaction throughput at scale. This is challenging, however, due to the fundamental difference in failure models between databases and blockchain. To achieve our goal, we first enhance the performance of Byzantine consensus protocols, by doing so we improve individual shards throughput. Next, we design an efficient shard formation protocol that leverages a trusted random beacon to securely assign nodes into shards. We rely on trusted hardware, namely Intel SGX, to achieve high performance for both consensus and shard formation protocol. Third, we design a general distributed transaction protocol that ensures safety and liveness even when transaction coordinators are malicious. Finally, we conduct an extensive evaluation of our design both on a local cluster and on Google Cloud Platform. The results show that our consensus and shard formation protocols outperform state-of-the-art solutions at scale. More importantly, our sharded blockchain reaches a high throughput that can handle Visa-level workloads, and is the largest ever reported in a realistic environment.
This paper revisits the ubiquitous problem of achieving state machine replication in blockchains based on repeated consensus, like Tendermint. To achieve state machine replication in blockchains built on top of consensus, one needs to guarantee fairness of user transactions. A huge body of work has been carried out on the relation between state machine replication and consensus in the past years, in a variety of system models and with respect to varied problem specifications. We systematize this work by proposing novel and rigorous abstractions for state machine replication and repeated consensus in a system model that accounts for realistic blockchains in which blocks may contain several transactions issued by one or more users, and where validity and order of transactions within a block is determined by an external application-dependent function that can capture various approaches for order-fairness in the literature. Based on these abstractions, we propose a reduction from state machine replication to repeated consensus, such that user fairness is achieved using the consensus module as a black box. This approach allows to achieve fairness as an add-on on top of preexisting consensus modules in blockchains based on repeated consensus.
An increasingly large number of HPC systems rely on heterogeneous architectures combining traditional multi-core CPUs with power efficient accelerators. Designing efficient applications for these systems has been troublesome in the past as accelerators could usually be programmed using specific programming languages threatening maintainability, portability and correctness. Several new programming environments try to tackle this problem. Among them, OpenACC offers a high-level approach based on compiler directive clauses to mark regions of existing C, C++ or Fortran codes to run on accelerators. This approach directly addresses code portability, leaving to compilers the support of each different accelerator, but one has to carefully assess the relative costs of portable approaches versus computing efficiency. In this paper we address precisely this issue, using as a test-bench a massively parallel Lattice Boltzmann algorithm. We first describe our multi-node implementation and optimization of the algorithm, using OpenACC and MPI. We then benchmark the code on a variety of processors, including traditional CPUs and GPUs, and make accurate performance comparisons with other GPU implementations of the same algorithm using CUDA and OpenCL. We also asses the performance impact associated to portable programming, and the actual portability and performance-portability of OpenACC-based applications across several state-of-the- art architectures.
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