Minimizing Redundancy to Satisfy Reliability Requirement for a Parallel Application on Heterogeneous Service-Oriented Systems

Xie, Guoqi; Zeng, Gang; Chen, Yuekun; Bai, Yang; Zhou, Zhili; Li, Renfa; Li, Keqin

doi:10.1109/tsc.2017.2665552

Cited by 59 publications

(23 citation statements)

References 31 publications

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“…Xie et al [25] proposed three hardware cost optimization algorithms for functional safety-critical parallel applications on heterogeneous distributed embedded systems during the design phase. Xie et al [13] designed enough replication for the redundancy minimization (ERRM) algorithm to satisfy the application's reliability requirement with low time complexity.…”

Section: Related Workmentioning

confidence: 99%

“…When the exposure level is rising, the corresponding reliability requirement is going down, which increases the risk of failures in the system. As noted in IEC 61508, the occurrence frequency of the transient failure follows a Poisson distribution during the hardware lifecycle [13]. Thus, let λ j denotes the failure rate (constant failure rate per unit time) of the processor s j .…”

Section: E Reliability Modelmentioning

confidence: 99%

“…However, this approach not only takes a lot of time but also causes energy waste, which is not a good way for the UE whose energy resources are limited [11], [12]. For that, according to references [13], [14], we mainly consider the reliability during execution, for which the task of an application is divided into multiple sub-tasks. It would reduce the complexity of running the entire application and decrease execution latency by the parallel processing, and then the sub-tasks will be offloaded to the various MEC servers or performed locally to guarantee the task's overall reliability.…”

Section: Introductionmentioning

confidence: 99%

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A Fast Algorithm for Energy-Saving Offloading With Reliability and Latency Requirements in Multi-Access Edge Computing

et al. 2020

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Multi-Access Edge Computing (MEC) is a promising paradigm that providing cloud-like service for handling the high-complexity and latency-sensitive applications on user equipment (UE) via computation offloading. However, the execution reliability is rarely considered in current MEC studies, which is an important factor to guarantee the quality of service (QoS). For that, this paper considers an energy-saving offloading to satisfy the reliability and latency requirements of the application. Specifically, we formulate an optimization problem to minimize the UE's energy consumption with reliability and latency constraints. To tackle this NP-hard problem, we first divide the entire application into multiple directed-acyclic-graph-(DAG)-based subtasks, where the subtask can be executed on the UE locally or MEC server remotely. Then, we decompose the overall reliability and latency requirements into multiple constraints for each subtask. Finally, we propose a fast heuristic algorithm to find a solution satisfying the constraints. Simulation results demonstrate the proposed algorithm obtains lower energy consumption compared with the local execution and random assignment and costs less runtime compared with the greedy algorithm. INDEX TERMS Multi-access edge computing, computation offloading, energy consumption minimization, reliability guarantee.

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Section: Related Workmentioning

confidence: 99%

Section: E Reliability Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Fast Algorithm for Energy-Saving Offloading With Reliability and Latency Requirements in Multi-Access Edge Computing

et al. 2020

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“…HEFT [8] is the most popular DAG scheduling algorithm and widely believed to achieve the shortest makespan in many cases. There are other methods that take energy cost and reliability into account, such as LEC (Least Energy Cost) [6] and MR (Maximum Reliability) [21].…”

Section: Related Workmentioning

confidence: 99%

Dynamic DAG Scheduling on Multiprocessor Systems: Reliability, Energy, and Makespan

Huang

Jiao

et al. 2020

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Multiprocessor systems are increasingly deployed in real-time applications, where reliability, energy consumption, and makespan are often the main scheduling objectives. In this work, we investigate dynamic scheduling of tasks modelled by directed acyclic graphs (DAGs), which is an NP-hard problem with all existing methods being heuristics. Our contributions have two steps: (i) Assuming that the allocation of DAG nodes to processors is given, we propose OEA (Optimal Energy Allocation) and SOEA (Search-based OEA)-the first optimal methods that minimise the energy consumption whilst satisfying the reliability requirement-for homogeneous and heterogeneous systems, respectively; (ii) We present a novel scheduling algorithm ODS (Out-Degree Scheduling) that allocates the DAG nodes according to their out-degrees, and considering energy consumption, reliability, as well as dynamic finish time. ODS dominates the widely applied HEFT (Heterogeneous Earliest Finish Time) in makespan. Combining SOEA with ODS makes a complete solution to the problem of dynamic DAG scheduling on multiprocessor systems, and achieves generally better results compared to the existing approaches. Specifically, in most cases, we are better on all the three objectives, i.e., reliability, energy as well as makespan, and in other cases we are better on some of the objectives.

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“…Services computing, known as service‐oriented computing, and cloud computing are two mainly coexisting paradigms that are widely demanded at present software systems, and most works focus on the problem of satisfying the one or multiple quality of service requirements for users while keeping satisfactory performance of the software systems . However, with the merging, sharing, and integration of different software systems, multidatabases have become the most important storage of current services computing and cloud computing software systems .…”

Section: Introductionmentioning

confidence: 99%

An integration approach of hybrid databases based on SQL in cloud computing environment

2018

Softw Pract Exp

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As the applications with big data in cloud computing environment grow, many existing systems expect to expand their service to support the dramatic increase of data, and modern software development for services computing and cloud computing software systems is no longer based on a single database but on existing multidatabases and this convergence needs new software architecture design. This paper proposes an integration approach to support hybrid database architecture, including MySQL, MongoDB, and Redis, to make it possible of allowing users to query data simultaneously from both relational SQL systems and NoSQL systems in a single SQL query. Two mechanisms are provided for constructing Redis's indexes and semantic transforming between SQL and Mon-goDB API to add the SQL feature for these NoSQL databases. With the proposed approach, hybrid database systems can be performed in a flexible manner, ie, access can be either relational database or NoSQL, depending on the size of data. The approach can effectively reduce development complexity and improve development efficiency of the software systems with multidatabases. This is the result of further research on the related topic, which fills the gap ignored by relevant scholars in this field to make a little contribution to the further development of NoSQL technology. /journal/spe 401 402 LI AND GU applications of NoSQL (not only SQL) database systems become more and more popular, it also poses a greater challenge to the development methods and technical architecture of software systems. A dramatic change, or called a revolution, is taking place in the field of database management technology as the growing of applications with big data in cloud computing environment. In June 1970, Edgar Frank Codd, a researcher of IBM company, published the famous paper, ie, A Relational Model of Data for Large Shared Data Banks, in Communications of ACM, which established the theoretical model of relational database. After decades of development, the relational database management system has gradually become mature, and the SQL (structured query language) used to access the relational database system also has been developed into the standard of all relational databases. However, big data and hybrid database system are becoming popular as cloud service blooms, and NoSQL database systems, such as Redis, 9 MongoDB, 10 HBase, 11 and Neo4J, 12 also have been developed rapidly.NoSQL systems have been developed to support applications not well served by relational systems, often involving big data processing. 13 Therefore, related research works have academic significance and practical values. Typical applications of NoSQL databases involve many important areas, such as the Internet, 14 mobile computation, 15 telecommunications, 16 bioinformatics, 17 education, 18 and energy. 19 Major NoSQL databases can be classified into four categories, [20][21][22] including key-value store, column-oriented store, document-oriented store, and graph store. Representative NoSQL database products include...

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Minimizing Redundancy to Satisfy Reliability Requirement for a Parallel Application on Heterogeneous Service-Oriented Systems

Cited by 59 publications

References 31 publications

A Fast Algorithm for Energy-Saving Offloading With Reliability and Latency Requirements in Multi-Access Edge Computing

A Fast Algorithm for Energy-Saving Offloading With Reliability and Latency Requirements in Multi-Access Edge Computing

Dynamic DAG Scheduling on Multiprocessor Systems: Reliability, Energy, and Makespan

An integration approach of hybrid databases based on SQL in cloud computing environment

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