The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
여러 하위 작업으로 구성된 대규모 컴퓨팅 작업을 수행하려는 클라이언트를 생각해 보십시오. 이때 스토리지와 계산은 모두 타사 서비스 제공업체에 의해 아웃소싱됩니다. 클라이언트는 계산 결과의 무결성과 완전성을 어떻게 보장할 수 있습니까? 한편, 보증 메커니즘이 어떻게 서비스 제공자나 클라이언트가 그러한 계획에 참여하는 데 과도한 통신 비용과 같은 방해 요인을 발생시키지 않을 수 있습니까? 우리는 이 문제를 자세히 설명하고 대규모 컴퓨팅 작업에 대한 실행 보증의 일반적인 모델을 제시합니다. 일련의 주요 기능은 우리 작업을 기존 작업과 구별합니다. a) 신뢰할 수 없는 제XNUMX자가 저장과 계산을 모두 제공하고 고객이 데이터를 소유하지 않는 상황을 고려합니다. b) 우리는 데이터 인증 및 컴퓨터 개인 정보 검색(cPIR) 기계의 새로운 통합을 기반으로 하는 간단하면서도 효과적인 보증 모델을 제안합니다. c) 우리는 검증 정확도와 계산, 저장 및 통신 비용 간의 내재적인 균형에 대한 분석 연구를 수행합니다.
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Ting WANG, Ling LIU, "Execution Assurance for Massive Computing Tasks" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 6, pp. 1343-1351, June 2010, doi: 10.1587/transinf.E93.D.1343.
Abstract: Consider a client who intends to perform a massive computing task comprsing a number of sub-tasks, while both storage and computation are outsourced by a third-party service provider. How could the client ensure the integrity and completeness of the computation result? Meanwhile, how could the assurance mechanism incur no disincentive, e.g., excessive communication cost, for any service provider or client to participate in such a scheme? We detail this problem and present a general model of execution assurance for massive computing tasks. A series of key features distinguish our work from existing ones: a) we consider the context wherein both storage and computation are provided by untrusted third parties, and client has no data possession; b) we propose a simple yet effective assurance model based on a novel integration of the machineries of data authentication and computational private information retrieval (cPIR); c) we conduct an analytical study on the inherent trade-offs among the verification accuracy, and the computation, storage, and communication costs.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1343/_p
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@ARTICLE{e93-d_6_1343,
author={Ting WANG, Ling LIU, },
journal={IEICE TRANSACTIONS on Information},
title={Execution Assurance for Massive Computing Tasks},
year={2010},
volume={E93-D},
number={6},
pages={1343-1351},
abstract={Consider a client who intends to perform a massive computing task comprsing a number of sub-tasks, while both storage and computation are outsourced by a third-party service provider. How could the client ensure the integrity and completeness of the computation result? Meanwhile, how could the assurance mechanism incur no disincentive, e.g., excessive communication cost, for any service provider or client to participate in such a scheme? We detail this problem and present a general model of execution assurance for massive computing tasks. A series of key features distinguish our work from existing ones: a) we consider the context wherein both storage and computation are provided by untrusted third parties, and client has no data possession; b) we propose a simple yet effective assurance model based on a novel integration of the machineries of data authentication and computational private information retrieval (cPIR); c) we conduct an analytical study on the inherent trade-offs among the verification accuracy, and the computation, storage, and communication costs.},
keywords={},
doi={10.1587/transinf.E93.D.1343},
ISSN={1745-1361},
month={June},}
부
TY - JOUR
TI - Execution Assurance for Massive Computing Tasks
T2 - IEICE TRANSACTIONS on Information
SP - 1343
EP - 1351
AU - Ting WANG
AU - Ling LIU
PY - 2010
DO - 10.1587/transinf.E93.D.1343
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2010
AB - Consider a client who intends to perform a massive computing task comprsing a number of sub-tasks, while both storage and computation are outsourced by a third-party service provider. How could the client ensure the integrity and completeness of the computation result? Meanwhile, how could the assurance mechanism incur no disincentive, e.g., excessive communication cost, for any service provider or client to participate in such a scheme? We detail this problem and present a general model of execution assurance for massive computing tasks. A series of key features distinguish our work from existing ones: a) we consider the context wherein both storage and computation are provided by untrusted third parties, and client has no data possession; b) we propose a simple yet effective assurance model based on a novel integration of the machineries of data authentication and computational private information retrieval (cPIR); c) we conduct an analytical study on the inherent trade-offs among the verification accuracy, and the computation, storage, and communication costs.
ER -