The Experts below are selected from a list of 1611 Experts worldwide ranked by ideXlab platform
Guoqi Xie - One of the best experts on this subject based on the ideXlab platform.
-
Price Performance-Driven Hardware Cost Optimization under Functional Safety Requirement in Large-Scale Heterogeneous Distributed Embedded Systems
IEEE Transactions on Industrial Electronics, 2021Co-Authors: Guoqi Xie, Hao PengAbstract:The problem of optimizing hardware cost un- der Functional Safety Requirement is a desirable work for a Safety-critical embedded application. The state-of-the- art algorithms called enhanced explorative hardware cost optimization (EEHCO) and simplified EEHCO (SEEHCO) have been used to study this problem for a distributed embedded application by iteratively removing some pro- cessors from opened processors (i.e., open-to-close). How- ever, EEHCO has powerful cost optimization capability but inferior time efficiency, and vice versa for SEEHCO in large- scale heterogeneous distributed embedded systems. This study presents a price performance-driven hardware cost optimization (PPHCO) method, which is the combination of PPHCO1 and PPHCO2, to achieve powerful cost optimiza- tion capability and superior time efficiency simultaneously. PPHCO1 iteratively selects the processor with the maxi- mum price performance to open and overcomes the inferior time efficiency (i.e., close-to-open). PPHCO2 iteratively se- lects the processor with the minimum price performance to close and further optimizes the hardware cost on the basis of PPHCO1 without losing time efficiency (i.e., open-to- close). Through significantly reducing the iteration count, PPHCO overcomes the inferior time efficiency of the open- to-close method. Through adopting union fast Functional Safety verification (UFFSV), PPHCO achieves powerful cost optimization capability. Experiments confirm that PPHCO not only achieves stronger cost optimization capability but also has better time efficiency than state-of-the-art EEHCO and SEEHCO algorithms.
-
risk assessment and development cost optimization in software defined vehicles
IEEE Transactions on Intelligent Transportation Systems, 2020Co-Authors: Guoqi Xie, Gang ZengAbstract:Vehicle design has entered a new stage, namely, Software Defined Vehicles (SDV), where Functional Safety is required to be guaranteed for risk control, and development cost needs to be optimized for profit maximization. This paper targets to optimize the development cost under the Functional Safety Requirement for a Safety-aware SDV, based on the automotive Safety integrity level (ASIL) decomposition defined in ISO 26262. For this, a two-stage solution is proposed, which includes Functional Safety risk assessment and development cost optimization. The first stage develops a new fast risk assessment (FRA) algorithm to assess the Functional Safety risk, including the joint reliability risk and the real-time risk, of the SDV Functionality. The second stage proposes a dual Requirement guarantee (DRG) algorithm to optimize the development cost considering reliability and real-time Requirements jointly. Our experiments demonstrate that the proposed two-stage solution guarantees the Functional Safety Requirement while reducing the development cost by 20%-24%.
-
Reliability-Aware Fault-Tolerant Scheduling
Scheduling Parallel Applications on Heterogeneous Distributed Systems, 2019Co-Authors: Guoqi Xie, Gang ZengAbstract:Reliability is widely identified as an increasingly relevant issue on heterogeneous distributed cloud systems because processor failure affects the quality of service for users. Replication-based fault-tolerance is a common approach to satisfy the application’s reliability Requirement. This chapter solves the problem of minimizing redundancy to satisfy reliability Requirement for a parallel application on heterogeneous distributed cloud systems. In addition, this chapter also focuses on heterogeneous distributed embedded systems such as ACPS, which are Safety critical systems. And response time is an another Safety attribution on ACPS. So this chapter further solves the problem of cost optimization when satisfying Safety Requirement including reliability and response time Requirement on heterogeneous distributed embedded systems such as APCS. We first propose the enough replication for redundancy minimization (ERRM) algorithm to satisfy an application’s reliability Requirement, and then propose heuristic replication for redundancy minimization (HRRM) to satisfy an application’s reliability Requirement with low time complexity. ERRM can generate the least redundancy followed by HRRM, and the state-of-the-art MaxRe and RR algorithm. In addition, HRRM implements approximate minimum redundancy with a short computation time. Considering that a minimum number of replicas does not necessarily lead to the minimum execution cost and shortest schedule length in a heterogeneous distributed cloud systems, we further propose the quantitative fault-tolerance with minimum execution cost (QFEC) & QFEC+ algorithms and the quantitative fault-tolerance with minimum schedule length (QFSL) & QFSL+ algorithms while satisfying the reliability Requirement of the workflow. Next, we present a Safety-aware fault-tolerant methodology towards the resource cost optimization for end-to-end Functional Safety computation on ACPS. The proposed design methodology involves early Functional Safety Requirement verification and late resource cost design optimization. We first propose the Functional Safety Requirement verification (FSRV) algorithm to verify the Functional Safety Requirement consisting of reliability and response time Requirements of the distributed automotive function for the early design phase. And then we propose the resource cost-aware fault-tolerant optimization (RCFO) algorithm to reduce the resource cost while satisfying the Functional Safety Requirement of the function for the late design phase. Finally, this chapter presents different experiments toward different application environments such as CPCS and ACPS. We first do the experiments for the redundancy cost optimization on real and randomly generated parallel applications at different scales, parallelism to validate the performance of ERRM and HRRM on heterogeneous distributed systems. We then do the experiments for the execution cost and scheduling length optimization on heterogeneous distributed cloud systems to validate the efficiency of QFEC, QFEC+, QFSL and QFSL+. We finally do the experiments for the resource cost optimization with real-life automotive and synthetic automotive applications on heterogeneous distributed embedded systems to validate the performance and efficiency of RCFO and VFSR.
-
Resource-Cost-Aware Fault-Tolerant Design Methodology for End-to-End Functional Safety Computation on Automotive Cyber-Physical Systems
ACM Transactions on Cyber-Physical Systems, 2019Co-Authors: Guoqi Xie, Gang ZengAbstract:Automotive Functional Safety standard ISO 26262 aims to avoid unreasonable risks due to systematic failures and random hardware failures caused by malfunctioning behavior. Automotive functions involve distributed end-to-end computation in automotive cyber-physical systems (ACPSs). The automotive industry is highly cost-sensitive to the mass market. This study presents a resource-cost-aware fault-tolerant design methodology for end-to-end Functional Safety computation on ACPSs. The proposed design methodology involves early Functional Safety Requirement verification and late resource cost design optimization. We first propose the Functional Safety Requirement verification (FSRV) method to verify the Functional Safety Requirement consisting of reliability and response time Requirements of the distributed automotive function during the early design phase. We then propose the resource-cost-aware fault-tolerant optimization (RCFO) method to reduce the resource cost while satisfying the Functional Safety Requirement of the function during the late design phase. Finally, we perform experiments with real-life automotive and synthetic automotive functions. Findings reveal that the proposed RCFO and VFSR methods demonstrate satisfactory resource cost reduction compared with other methods while satisfying the Functional Safety Requirement.
-
Toward Effective Reliability Requirement Assurance for Automotive Functional Safety
ACM Transactions on Design Automation of Electronic Systems, 2018Co-Authors: Guoqi Xie, Na YuanAbstract:Automotive Functional Safety Requirement includes response time and reliability Requirements learning from the Functional Safety standard ISO 26262. These two Requirements must be simultaneously satisfied to assure automotive Functional Safety Requirement. However, increasing reliability increases the response time intuitively. This study proposes a method to find the solution with the minimum response time while assuring reliability Requirement. Pre-assigning reliability values to unassigned tasks by transferring the reliability Requirement of the function to each task is a useful reliability Requirement assurance approach proposed in recent years. However, the pre-assigned reliability values in state-of-the-art studies have unbalanced distribution of the reliability of all tasks, thereby resulting in a limited reduction in response time. This study presents the geometric mean-based non-fault-tolerant reliability pre-assignment (GMNRP) and geometric mean-based fault-tolerant reliability pre-assignment (GMFRP) approaches, in which geometric mean-based reliability values are pre-assigned to unassigned tasks. Geometric mean can make the pre-assigned reliability values of unassigned tasks to the central tendency, such that it can distribute the reliability Requirements in a more balanced way. Experimental results show that GMNRP and GMFRP can effectively reduce the response time compared with their individual state-of-the-art counterparts.
Keqin Li - One of the best experts on this subject based on the ideXlab platform.
-
Energy-Efficient Functional Safety Design Methodology Using ASIL Decomposition for Automotive Cyber-Physical Systems
IEEE Transactions on Reliability, 2019Co-Authors: Hao Peng, Renfa Li, Jing Huang, Keqin LiAbstract:Automotive cyber-physical systems (ACPS) are typical cyber-physical systems because of the joint interaction between the cyber part and physical part. Functional Safety Requirement (including response time and reliability Requirements) for an ACPS function must be assured for safe driving. Auto industry is cost-sensitive, power-sensitive, and environment-friendly. Energy consumption affects the development efficiency of the ACPS and the living environment of people. This paper solves the problem of optimizing the energy consumption for an ACPS function while assuring its Functional Safety Requirement (i.e., energy-efficient Functional Safety for ACPS). However, implementing minimum response time, maximum reliability, and minimum energy consumption is a conflicting problem. Consequently, solving the problem is a challenge. In this paper, we propose a three-stage design process toward energy-efficient Functional Safety for ACPS. The topic problem is divided into three sub-problems, namely, response time Requirement verification (first stage), Functional Safety Requirement verification (second stage), and Functional Safety-critical energy consumption optimization (third stage). The proposed energy-efficient Functional Safety design methodology is implemented by using automotive Safety integrity level decomposition, which is defined in the ACPS Functional Safety standard ISO 26262. Experiments with real-life and synthetic ACPS functions reveal the advantages of the proposed design methodology toward energy-efficient Functional Safety for ACPS compared with state-of-the-art algorithms.
-
Hardware Cost Design Optimization for Functional Safety-Critical Parallel Applications on Heterogeneous Distributed Embedded Systems
IEEE Transactions on Industrial Informatics, 2018Co-Authors: Yuekun Chen, Renfa Li, Keqin LiAbstract:Industrial embedded systems are cost sensitive, and hardware cost of industrial production should be reduced for high profit. The Functional Safety Requirement must be satisfied according to industrial Functional Safety standards. This study proposes three hardware cost optimization algorithms for Functional Safety-critical parallel applications on heterogeneous distributed embedded systems during the design phase. The explorative hardware cost optimization (EHCO), enhanced EHCO (EEHCO), and simplified EEHCO (SEEHCO) algorithms are proposed step by step. Experimental results reveal that EEHCO can obtain minimum hardware cost, whereas SEEHCO is efficient for large-scale parallel applications compared with the existing algorithms.
-
Resource Consumption Cost Minimization of Reliable Parallel Applications on Heterogeneous Embedded Systems
IEEE Transactions on Industrial Informatics, 2017Co-Authors: Yuekun Chen, Renfa Li, Keqin LiAbstract:Heterogeneous processors are increasingly being used in embedded systems where parallel applications with precedence-constrained tasks widely exist. Reliability is an important Functional Safety Requirement and reliability goal should be satisfied for Safety-critical parallel applications; meanwhile, resource is limited in embedded systems and it should be minimized. This study solves the problem of resource consumption cost minimization of a reliable parallel application on heterogeneous embedded systems without using fault tolerance. The problem is decomposed into two subproblems, namely, satisfying reliability goal and minimizing resource consumption cost. The first subproblem is solved by transferring the reliability goal of the application to that of each task, and the second subproblem is solved by heuristically assigning each task to the processor with the minimum resource consumption cost while satisfying its reliability goal. Experiments with real parallel applications verify that the proposed algorithm obtains minimum resource consumption costs compared with the state-of-the-art algorithms.
Yuekun Chen - One of the best experts on this subject based on the ideXlab platform.
-
Energy-Efficient Fault-Tolerant Scheduling of Reliable Parallel Applications on Heterogeneous Distributed Embedded Systems
IEEE Transactions on Sustainable Computing, 2018Co-Authors: Guoqi Xie, Yuekun Chen, Xiongren XiaoAbstract:Dynamic voltage and frequency scaling (DVFS) is a well-known energy consumption optimization technique in embedded systems and dynamically scaling down the voltage of a chip has been developed to achieve energy-efficient optimization. However, this operation may lead to a sharp rise in transient failures of processors and consequently weaken the reliability of systems. Reliability goal is an important Functional Safety Requirement and must be satisfied for Safety-critical applications. In this study, we aim to implement energy-efficient fault-tolerant scheduling for a reliable parallel application on heterogeneous distributed embedded systems, where the parallel application is described by a directed acyclic graph (DAG). An energy-efficient scheduling with a reliability goal (ESRG) algorithm is presented to reduce the energy consumption while satisfying the reliability goal for the parallel application. Considering that the application's reliability goal is unreachable if its reliability goal exceeds a certain threshold via ESRG, we further propose an energy-efficient fault-tolerant scheduling with a reliability goal (EFSRG) algorithm to reduce the energy consumption while satisfying the reliability goal based on an active replication scheme. Experimental results confirm that the energy consumption reduced by the proposed EFSRG algorithm is higher than those reduced by other approaches under different scale conditions.
-
Hardware Cost Design Optimization for Functional Safety-Critical Parallel Applications on Heterogeneous Distributed Embedded Systems
IEEE Transactions on Industrial Informatics, 2018Co-Authors: Yuekun Chen, Renfa Li, Keqin LiAbstract:Industrial embedded systems are cost sensitive, and hardware cost of industrial production should be reduced for high profit. The Functional Safety Requirement must be satisfied according to industrial Functional Safety standards. This study proposes three hardware cost optimization algorithms for Functional Safety-critical parallel applications on heterogeneous distributed embedded systems during the design phase. The explorative hardware cost optimization (EHCO), enhanced EHCO (EEHCO), and simplified EEHCO (SEEHCO) algorithms are proposed step by step. Experimental results reveal that EEHCO can obtain minimum hardware cost, whereas SEEHCO is efficient for large-scale parallel applications compared with the existing algorithms.
-
Resource Consumption Cost Minimization of Reliable Parallel Applications on Heterogeneous Embedded Systems
IEEE Transactions on Industrial Informatics, 2017Co-Authors: Yuekun Chen, Renfa Li, Keqin LiAbstract:Heterogeneous processors are increasingly being used in embedded systems where parallel applications with precedence-constrained tasks widely exist. Reliability is an important Functional Safety Requirement and reliability goal should be satisfied for Safety-critical parallel applications; meanwhile, resource is limited in embedded systems and it should be minimized. This study solves the problem of resource consumption cost minimization of a reliable parallel application on heterogeneous embedded systems without using fault tolerance. The problem is decomposed into two subproblems, namely, satisfying reliability goal and minimizing resource consumption cost. The first subproblem is solved by transferring the reliability goal of the application to that of each task, and the second subproblem is solved by heuristically assigning each task to the processor with the minimum resource consumption cost while satisfying its reliability goal. Experiments with real parallel applications verify that the proposed algorithm obtains minimum resource consumption costs compared with the state-of-the-art algorithms.
-
Resource Consumption Cost Minimization of Reliable Parallel Applications on Heterogeneous Embedded Systems
IEEE Transactions on Industrial Informatics, 2017Co-Authors: Guoqi Xie, Yuekun Chen, Yan Liu, Yehua WeiAbstract:Heterogeneous processors are increasingly being used in embedded systems where parallel applications with precedence-constrained tasks widely exist. Reliability is an important Functional Safety Requirement and reliability goal should be satisfied for Safety-critical parallel applications; meanwhile, resource is limited in embedded systems and it should be minimized. This study solves the problem of resource consumption cost minimization of a reliable parallel application on heterogeneous embedded systems without using fault tolerance. The problem is decomposed into two subproblems, namely, satisfying reliability goal and minimizing resource consumption cost. The first subproblem is solved by transferring the reliability goal of the application to that of each task, and the second subproblem is solved by heuristically assigning each task to the processor with the minimum resource consumption cost while satisfying its reliability goal. Experiments with real parallel applications verify that the proposed algorithm obtains minimum resource consumption costs compared with the state-of-the-art algorithms.
Renfa Li - One of the best experts on this subject based on the ideXlab platform.
-
Energy-Efficient Functional Safety Design Methodology Using ASIL Decomposition for Automotive Cyber-Physical Systems
IEEE Transactions on Reliability, 2019Co-Authors: Hao Peng, Renfa Li, Jing Huang, Keqin LiAbstract:Automotive cyber-physical systems (ACPS) are typical cyber-physical systems because of the joint interaction between the cyber part and physical part. Functional Safety Requirement (including response time and reliability Requirements) for an ACPS function must be assured for safe driving. Auto industry is cost-sensitive, power-sensitive, and environment-friendly. Energy consumption affects the development efficiency of the ACPS and the living environment of people. This paper solves the problem of optimizing the energy consumption for an ACPS function while assuring its Functional Safety Requirement (i.e., energy-efficient Functional Safety for ACPS). However, implementing minimum response time, maximum reliability, and minimum energy consumption is a conflicting problem. Consequently, solving the problem is a challenge. In this paper, we propose a three-stage design process toward energy-efficient Functional Safety for ACPS. The topic problem is divided into three sub-problems, namely, response time Requirement verification (first stage), Functional Safety Requirement verification (second stage), and Functional Safety-critical energy consumption optimization (third stage). The proposed energy-efficient Functional Safety design methodology is implemented by using automotive Safety integrity level decomposition, which is defined in the ACPS Functional Safety standard ISO 26262. Experiments with real-life and synthetic ACPS functions reveal the advantages of the proposed design methodology toward energy-efficient Functional Safety for ACPS compared with state-of-the-art algorithms.
-
Hardware Cost Design Optimization for Functional Safety-Critical Parallel Applications on Heterogeneous Distributed Embedded Systems
IEEE Transactions on Industrial Informatics, 2018Co-Authors: Yuekun Chen, Renfa Li, Keqin LiAbstract:Industrial embedded systems are cost sensitive, and hardware cost of industrial production should be reduced for high profit. The Functional Safety Requirement must be satisfied according to industrial Functional Safety standards. This study proposes three hardware cost optimization algorithms for Functional Safety-critical parallel applications on heterogeneous distributed embedded systems during the design phase. The explorative hardware cost optimization (EHCO), enhanced EHCO (EEHCO), and simplified EEHCO (SEEHCO) algorithms are proposed step by step. Experimental results reveal that EEHCO can obtain minimum hardware cost, whereas SEEHCO is efficient for large-scale parallel applications compared with the existing algorithms.
-
Resource Consumption Cost Minimization of Reliable Parallel Applications on Heterogeneous Embedded Systems
IEEE Transactions on Industrial Informatics, 2017Co-Authors: Yuekun Chen, Renfa Li, Keqin LiAbstract:Heterogeneous processors are increasingly being used in embedded systems where parallel applications with precedence-constrained tasks widely exist. Reliability is an important Functional Safety Requirement and reliability goal should be satisfied for Safety-critical parallel applications; meanwhile, resource is limited in embedded systems and it should be minimized. This study solves the problem of resource consumption cost minimization of a reliable parallel application on heterogeneous embedded systems without using fault tolerance. The problem is decomposed into two subproblems, namely, satisfying reliability goal and minimizing resource consumption cost. The first subproblem is solved by transferring the reliability goal of the application to that of each task, and the second subproblem is solved by heuristically assigning each task to the processor with the minimum resource consumption cost while satisfying its reliability goal. Experiments with real parallel applications verify that the proposed algorithm obtains minimum resource consumption costs compared with the state-of-the-art algorithms.
Gang Zeng - One of the best experts on this subject based on the ideXlab platform.
-
risk assessment and development cost optimization in software defined vehicles
IEEE Transactions on Intelligent Transportation Systems, 2020Co-Authors: Guoqi Xie, Gang ZengAbstract:Vehicle design has entered a new stage, namely, Software Defined Vehicles (SDV), where Functional Safety is required to be guaranteed for risk control, and development cost needs to be optimized for profit maximization. This paper targets to optimize the development cost under the Functional Safety Requirement for a Safety-aware SDV, based on the automotive Safety integrity level (ASIL) decomposition defined in ISO 26262. For this, a two-stage solution is proposed, which includes Functional Safety risk assessment and development cost optimization. The first stage develops a new fast risk assessment (FRA) algorithm to assess the Functional Safety risk, including the joint reliability risk and the real-time risk, of the SDV Functionality. The second stage proposes a dual Requirement guarantee (DRG) algorithm to optimize the development cost considering reliability and real-time Requirements jointly. Our experiments demonstrate that the proposed two-stage solution guarantees the Functional Safety Requirement while reducing the development cost by 20%-24%.
-
Reliability-Aware Fault-Tolerant Scheduling
Scheduling Parallel Applications on Heterogeneous Distributed Systems, 2019Co-Authors: Guoqi Xie, Gang ZengAbstract:Reliability is widely identified as an increasingly relevant issue on heterogeneous distributed cloud systems because processor failure affects the quality of service for users. Replication-based fault-tolerance is a common approach to satisfy the application’s reliability Requirement. This chapter solves the problem of minimizing redundancy to satisfy reliability Requirement for a parallel application on heterogeneous distributed cloud systems. In addition, this chapter also focuses on heterogeneous distributed embedded systems such as ACPS, which are Safety critical systems. And response time is an another Safety attribution on ACPS. So this chapter further solves the problem of cost optimization when satisfying Safety Requirement including reliability and response time Requirement on heterogeneous distributed embedded systems such as APCS. We first propose the enough replication for redundancy minimization (ERRM) algorithm to satisfy an application’s reliability Requirement, and then propose heuristic replication for redundancy minimization (HRRM) to satisfy an application’s reliability Requirement with low time complexity. ERRM can generate the least redundancy followed by HRRM, and the state-of-the-art MaxRe and RR algorithm. In addition, HRRM implements approximate minimum redundancy with a short computation time. Considering that a minimum number of replicas does not necessarily lead to the minimum execution cost and shortest schedule length in a heterogeneous distributed cloud systems, we further propose the quantitative fault-tolerance with minimum execution cost (QFEC) & QFEC+ algorithms and the quantitative fault-tolerance with minimum schedule length (QFSL) & QFSL+ algorithms while satisfying the reliability Requirement of the workflow. Next, we present a Safety-aware fault-tolerant methodology towards the resource cost optimization for end-to-end Functional Safety computation on ACPS. The proposed design methodology involves early Functional Safety Requirement verification and late resource cost design optimization. We first propose the Functional Safety Requirement verification (FSRV) algorithm to verify the Functional Safety Requirement consisting of reliability and response time Requirements of the distributed automotive function for the early design phase. And then we propose the resource cost-aware fault-tolerant optimization (RCFO) algorithm to reduce the resource cost while satisfying the Functional Safety Requirement of the function for the late design phase. Finally, this chapter presents different experiments toward different application environments such as CPCS and ACPS. We first do the experiments for the redundancy cost optimization on real and randomly generated parallel applications at different scales, parallelism to validate the performance of ERRM and HRRM on heterogeneous distributed systems. We then do the experiments for the execution cost and scheduling length optimization on heterogeneous distributed cloud systems to validate the efficiency of QFEC, QFEC+, QFSL and QFSL+. We finally do the experiments for the resource cost optimization with real-life automotive and synthetic automotive applications on heterogeneous distributed embedded systems to validate the performance and efficiency of RCFO and VFSR.
-
Resource-Cost-Aware Fault-Tolerant Design Methodology for End-to-End Functional Safety Computation on Automotive Cyber-Physical Systems
ACM Transactions on Cyber-Physical Systems, 2019Co-Authors: Guoqi Xie, Gang ZengAbstract:Automotive Functional Safety standard ISO 26262 aims to avoid unreasonable risks due to systematic failures and random hardware failures caused by malfunctioning behavior. Automotive functions involve distributed end-to-end computation in automotive cyber-physical systems (ACPSs). The automotive industry is highly cost-sensitive to the mass market. This study presents a resource-cost-aware fault-tolerant design methodology for end-to-end Functional Safety computation on ACPSs. The proposed design methodology involves early Functional Safety Requirement verification and late resource cost design optimization. We first propose the Functional Safety Requirement verification (FSRV) method to verify the Functional Safety Requirement consisting of reliability and response time Requirements of the distributed automotive function during the early design phase. We then propose the resource-cost-aware fault-tolerant optimization (RCFO) method to reduce the resource cost while satisfying the Functional Safety Requirement of the function during the late design phase. Finally, we perform experiments with real-life automotive and synthetic automotive functions. Findings reveal that the proposed RCFO and VFSR methods demonstrate satisfactory resource cost reduction compared with other methods while satisfying the Functional Safety Requirement.
