A. Ferreira, B. Childers, R. Melhem, D. Mossé, Mazin S. Yousif
Dynamic RAM (DRAM) has been the best technology for main memory for over thirty years. In embedded space applications, radiation hardened DRAM is needed because gamma rays cause transient errors; such rad-hard memories are extremely expensive and power hungry, leading to lower life (or increased battery weight) for satellite and other devices operating in space. Despite these problems, DRAM has been the technology of choice because it has better performance and it scales well. New, more energy efficient, non-volatile, scalable, radiation resistant memory technologies are now available, namely phase-change memory (PCM), making the DRAM choice much less compelling. However, current approaches require changes to PCM device internal circuitry, the operating system and/or the CPU cache-memory organization/interface. This paper presents a new, practical, detailed architecture, called PMMA, to effectively use PCM for main memory in next-generation embedded space systems. We designed PMMA avoiding changes to commodity PCM devices, the operating system, and the existing CPU cache-memory interface, enabling plug-in replacement of a conventional DRAM main memory by one constructed with PMMA. Our architecture incorporates novel mechanisms to address PCM’s limitations including expensive write operations, asymmetric read/write latency, and limited endurance. In our evaluation we show that PMMA achieves a 60% improvement in energy-delay over a conventional DRAM main memory.
{"title":"Using PCM in Next-generation Embedded Space Applications","authors":"A. Ferreira, B. Childers, R. Melhem, D. Mossé, Mazin S. Yousif","doi":"10.1109/RTAS.2010.40","DOIUrl":"https://doi.org/10.1109/RTAS.2010.40","url":null,"abstract":"Dynamic RAM (DRAM) has been the best technology for main memory for over thirty years. In embedded space applications, radiation hardened DRAM is needed because gamma rays cause transient errors; such rad-hard memories are extremely expensive and power hungry, leading to lower life (or increased battery weight) for satellite and other devices operating in space. Despite these problems, DRAM has been the technology of choice because it has better performance and it scales well. New, more energy efficient, non-volatile, scalable, radiation resistant memory technologies are now available, namely phase-change memory (PCM), making the DRAM choice much less compelling. However, current approaches require changes to PCM device internal circuitry, the operating system and/or the CPU cache-memory organization/interface. This paper presents a new, practical, detailed architecture, called PMMA, to effectively use PCM for main memory in next-generation embedded space systems. We designed PMMA avoiding changes to commodity PCM devices, the operating system, and the existing CPU cache-memory interface, enabling plug-in replacement of a conventional DRAM main memory by one constructed with PMMA. Our architecture incorporates novel mechanisms to address PCM’s limitations including expensive write operations, asymmetric read/write latency, and limited endurance. In our evaluation we show that PMMA achieves a 60% improvement in energy-delay over a conventional DRAM main memory.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123006180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sangeeta Bhattacharya, Abusayeed Saifullah, Chenyang Lu, G. Roman
Wireless sensor networks are evolving from dedicated application-specific platforms to integrated infrastructure shared by multiple applications. Shared sensor networks offer inherent advantages in terms of flexibility and cost since they allow dynamic resource sharing and allocation among multiple applications. Such shared systems face the critical need for allocation of nodes to contending applications to enhance the overall Quality of Monitoring (QoM) under resource constraints. To address this need, this paper presents Utility-based Multi-application Allocation and Deployment Environment (UMADE), an integrated application deployment system for shared sensor networks. In sharp contrast to traditional approaches that allocate applications based on cyber metrics (e.g., computing resource utilization), UMADE adopts a cyber-physical system approach that dynamically allocates nodes to applications based on their QoM of the physical phenomena. The key novelty of UMADE is that it is designed to deal with the inter-node QoM dependencies typical in cyber-physical applications. Furthermore, UMADE provides an integrated system solution that supports the end-to-end process of (1) QoM specification for applications, (2) QoM-aware application allocation, (3) application deployment over multi-hop wireless networks, and (4) adaptive reallocation of applications in response to network dynamics. UMADE has been implemented on TinyOS and Agilla virtual machine for Telos motes. The feasibility and efficacy of UMADE have been demonstrated on a 28-node wireless sensor network testbed in the context of building automation applications.
{"title":"Multi-Application Deployment in Shared Sensor Networks Based on Quality of Monitoring","authors":"Sangeeta Bhattacharya, Abusayeed Saifullah, Chenyang Lu, G. Roman","doi":"10.1109/RTAS.2010.20","DOIUrl":"https://doi.org/10.1109/RTAS.2010.20","url":null,"abstract":"Wireless sensor networks are evolving from dedicated application-specific platforms to integrated infrastructure shared by multiple applications. Shared sensor networks offer inherent advantages in terms of flexibility and cost since they allow dynamic resource sharing and allocation among multiple applications. Such shared systems face the critical need for allocation of nodes to contending applications to enhance the overall Quality of Monitoring (QoM) under resource constraints. To address this need, this paper presents Utility-based Multi-application Allocation and Deployment Environment (UMADE), an integrated application deployment system for shared sensor networks. In sharp contrast to traditional approaches that allocate applications based on cyber metrics (e.g., computing resource utilization), UMADE adopts a cyber-physical system approach that dynamically allocates nodes to applications based on their QoM of the physical phenomena. The key novelty of UMADE is that it is designed to deal with the inter-node QoM dependencies typical in cyber-physical applications. Furthermore, UMADE provides an integrated system solution that supports the end-to-end process of (1) QoM specification for applications, (2) QoM-aware application allocation, (3) application deployment over multi-hop wireless networks, and (4) adaptive reallocation of applications in response to network dynamics. UMADE has been implemented on TinyOS and Agilla virtual machine for Telos motes. The feasibility and efficacy of UMADE have been demonstrated on a 28-node wireless sensor network testbed in the context of building automation applications.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126582242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) techniques form the basis of numerous energy management schemes proposed for real-time embedded systems. DVS targets reducing the dynamic CPU energy consumption, while DPM attempts to reduce theenergy consumption of idle devices by putting them to low-power states over sufficiently long intervals. It is imperative that the system-wide energy management schemes efficiently integrate DVS and DPM while exploiting the subtle trade-off dimensions. In this paper, we develop and propose a unified framework for periodic real-time tasks where DVS and DPM are judiciously combined. The framework, called DFR-EDF, assumes a general system-level energy model and includes both static and dynamic(online) components. The static part is based on the extension of the recently proposed Device Forbidden Regions (DFRs) approach to Earliest-Deadline-First (EDF) scheduling. The online component integrates the predictive DPM techniques and offers a generalized slack reclaiming mechanism that can be used by DVS and DPMsimultaneously. Our experimental evaluation indicates significant gains of DFR-EDF at the system-level compared to the state-of-the-art solutions. Finally, this research effort makes another contribution by formally showing that optimally solving the DPM problem in periodic real-time execution settings is NP-Hard in the strong sense, even in the absence of DVS.
{"title":"DFR-EDF: A Unified Energy Management Framework for Real-Time Systems","authors":"V. Devadas, Hakan Aydin","doi":"10.1109/RTAS.2010.32","DOIUrl":"https://doi.org/10.1109/RTAS.2010.32","url":null,"abstract":"Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) techniques form the basis of numerous energy management schemes proposed for real-time embedded systems. DVS targets reducing the dynamic CPU energy consumption, while DPM attempts to reduce theenergy consumption of idle devices by putting them to low-power states over sufficiently long intervals. It is imperative that the system-wide energy management schemes efficiently integrate DVS and DPM while exploiting the subtle trade-off dimensions. In this paper, we develop and propose a unified framework for periodic real-time tasks where DVS and DPM are judiciously combined. The framework, called DFR-EDF, assumes a general system-level energy model and includes both static and dynamic(online) components. The static part is based on the extension of the recently proposed Device Forbidden Regions (DFRs) approach to Earliest-Deadline-First (EDF) scheduling. The online component integrates the predictive DPM techniques and offers a generalized slack reclaiming mechanism that can be used by DVS and DPMsimultaneously. Our experimental evaluation indicates significant gains of DFR-EDF at the system-level compared to the state-of-the-art solutions. Finally, this research effort makes another contribution by formally showing that optimally solving the DPM problem in periodic real-time execution settings is NP-Hard in the strong sense, even in the absence of DVS.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"46 40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127090633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Forget, F. Boniol, E. Grolleau, D. Lesens, C. Pagetti
This article studies the scheduling of critical embedded systems, which consist of a set of communicating periodic tasks with constrained deadlines. Currently, tasks are usually sequenced manually, partly because available scheduling policies do not ensure the determinism of task communications. Ensuring this determinism requires scheduling policies supporting task precedence constraints (which we call dependent tasks), which are used to force the order in which communicating tasks execute. We propose fixed priority scheduling policies for different classes of dependent tasks: with simultaneous or arbitrary release times, with simple precedences (between tasks of the same period) or extended precedences (between tasks of different periods). We only consider policies that do not require synchronization mechanisms (like semaphores). This completely prevents deadlocks or scheduling anomalies without requiring further proofs.
{"title":"Scheduling Dependent Periodic Tasks without Synchronization Mechanisms","authors":"J. Forget, F. Boniol, E. Grolleau, D. Lesens, C. Pagetti","doi":"10.1109/RTAS.2010.26","DOIUrl":"https://doi.org/10.1109/RTAS.2010.26","url":null,"abstract":"This article studies the scheduling of critical embedded systems, which consist of a set of communicating periodic tasks with constrained deadlines. Currently, tasks are usually sequenced manually, partly because available scheduling policies do not ensure the determinism of task communications. Ensuring this determinism requires scheduling policies supporting task precedence constraints (which we call dependent tasks), which are used to force the order in which communicating tasks execute. We propose fixed priority scheduling policies for different classes of dependent tasks: with simultaneous or arbitrary release times, with simple precedences (between tasks of the same period) or extended precedences (between tasks of different periods). We only consider policies that do not require synchronization mechanisms (like semaphores). This completely prevents deadlocks or scheduling anomalies without requiring further proofs.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128954907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yong Fu, N. Kottenstette, Yingming Chen, Chenyang Lu, X. Koutsoukos, Hongan Wang
Thermal control is crucial to real-time systems as excessive processor temperature can cause system failure or unacceptable performance degradation due to hardware throttling. Real-time systems face significant challenges in thermal management as they must avoid processor overheating while still delivering desired real-time performance. Furthermore, many real-time systems must handle a broad range of uncertainties in system and environmental conditions. To address these challenges, this paper presents Thermal Control under Utilization Bound (TCUB), a novel thermal control algorithm specifically designed for real-time systems. TCUB employs a nested feedback loop that dynamically controls both processor temperature and CPU utilization through task rate adaptation. Rigorously modeled and designed based on control theory, TCUB can maintain both desired processor temperature and CPU utilization, thereby avoiding processor overheating and maintaining desired soft real-time performance. A salient feature of TCUB lies on its capability to handle a broad range of uncertainties in terms of processor power consumption, task execution times, ambient temperature, and unexpected thermal faults. The robustness of TCUB makes it particularly suitable for real-time embedded systems that must operate in highly unpredictable environments. The advantages of TCUB are demonstrated through extensive simulations under a broad range of system and environmental uncertainties.
{"title":"Feedback Thermal Control for Real-time Systems","authors":"Yong Fu, N. Kottenstette, Yingming Chen, Chenyang Lu, X. Koutsoukos, Hongan Wang","doi":"10.1109/RTAS.2010.9","DOIUrl":"https://doi.org/10.1109/RTAS.2010.9","url":null,"abstract":"Thermal control is crucial to real-time systems as excessive processor temperature can cause system failure or unacceptable performance degradation due to hardware throttling. Real-time systems face significant challenges in thermal management as they must avoid processor overheating while still delivering desired real-time performance. Furthermore, many real-time systems must handle a broad range of uncertainties in system and environmental conditions. To address these challenges, this paper presents Thermal Control under Utilization Bound (TCUB), a novel thermal control algorithm specifically designed for real-time systems. TCUB employs a nested feedback loop that dynamically controls both processor temperature and CPU utilization through task rate adaptation. Rigorously modeled and designed based on control theory, TCUB can maintain both desired processor temperature and CPU utilization, thereby avoiding processor overheating and maintaining desired soft real-time performance. A salient feature of TCUB lies on its capability to handle a broad range of uncertainties in terms of processor power consumption, task execution times, ambient temperature, and unexpected thermal faults. The robustness of TCUB makes it particularly suitable for real-time embedded systems that must operate in highly unpredictable environments. The advantages of TCUB are demonstrated through extensive simulations under a broad range of system and environmental uncertainties.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133644515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hardware-managed caches introduce large amounts of timing variability, complicating real-time system design. One alternative is a memory system with scratchpad memories which improve system performance while eliminating such timing variability. Prior work introduced the DARTS approach, which combines static allocation of data into scratchpad memories, with task scheduling for preemptive multi-threaded, hard real-time embedded systems.This study offers several significant contributions. First, it introduces a method to split a stack frame across multiple memory units, offering fine-grain allocation of automatic memory variables with very low run-time overhead. This enables more effective use of fast memory, improving run-times. Second, it introduces the completed tool-chain based on DARTS, which reallocates static and automatic variables across multiple memory banks and now targets the ARM7 architecture. Third, it evaluates the performance improvement from DARTS using experimental results from the code running on real hardware in a preemptively scheduled RTOS-based multi-tasking environment. This hands-on experimental approach ensures a high level of confidence in the results; previous studies have generally stopped at estimating performance rather than building and measuring a real implementation.In our experiments the execution time of each task is reduced up to 24% from the baseline external SRAM configurations. We show that our methods improve task execution time to achieve 37% to 99% of the performance improvement of an ideal unlimited-capacity scratchpad memory system. Finally, we find our allocations provide on average 2/3 of the performance enhancement of the equivalently-sized cache yet with easily-predicted performance.
{"title":"DARTS: Techniques and Tools for Predictably Fast Memory Using Integrated Data Allocation and Real-Time Task Scheduling","authors":"Sangyeol Kang, A. Dean","doi":"10.1109/RTAS.2010.36","DOIUrl":"https://doi.org/10.1109/RTAS.2010.36","url":null,"abstract":"Hardware-managed caches introduce large amounts of timing variability, complicating real-time system design. One alternative is a memory system with scratchpad memories which improve system performance while eliminating such timing variability. Prior work introduced the DARTS approach, which combines static allocation of data into scratchpad memories, with task scheduling for preemptive multi-threaded, hard real-time embedded systems.This study offers several significant contributions. First, it introduces a method to split a stack frame across multiple memory units, offering fine-grain allocation of automatic memory variables with very low run-time overhead. This enables more effective use of fast memory, improving run-times. Second, it introduces the completed tool-chain based on DARTS, which reallocates static and automatic variables across multiple memory banks and now targets the ARM7 architecture. Third, it evaluates the performance improvement from DARTS using experimental results from the code running on real hardware in a preemptively scheduled RTOS-based multi-tasking environment. This hands-on experimental approach ensures a high level of confidence in the results; previous studies have generally stopped at estimating performance rather than building and measuring a real implementation.In our experiments the execution time of each task is reduced up to 24% from the baseline external SRAM configurations. We show that our methods improve task execution time to achieve 37% to 99% of the performance improvement of an ideal unlimited-capacity scratchpad memory system. Finally, we find our allocations provide on average 2/3 of the performance enhancement of the equivalently-sized cache yet with easily-predicted performance.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122284575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we are interested in mixed hard/soft real-time fault-tolerant applications mapped on distributed heterogeneous architectures. We use the Earliest Deadline First (EDF) scheduling for the hard real-time tasks and the Constant Bandwidth Server (CBS) for the soft tasks. The bandwidth reserved for the servers determines the quality of service (QoS) for soft tasks. CBS enforces temporal isolation, such that soft task overruns do not affect the timing guarantees of hard tasks. Transient faults in hard tasks are tolerated using checkpointing with rollback recovery. We have proposed a Tabu Search-based approach for task mapping and CBS bandwidth reservation, such that the deadlines for the hard tasks are satisfied, even in the case of transient faults, and the QoS for the soft tasks is maximized. Researchers have used fixed execution time models, such as the worst-case execution times for hard tasks and average execution times for soft tasks. However, we show that by using stochastic execution times for soft tasks, significant improvements can be obtained. The proposed strategy has been evaluated using an extensive set of benchmarks.
{"title":"Task Mapping and Bandwidth Reservation for Mixed Hard/Soft Fault-Tolerant Embedded Systems","authors":"P. Saraswat, P. Pop, J. Madsen","doi":"10.1109/RTAS.2010.31","DOIUrl":"https://doi.org/10.1109/RTAS.2010.31","url":null,"abstract":"In this paper we are interested in mixed hard/soft real-time fault-tolerant applications mapped on distributed heterogeneous architectures. We use the Earliest Deadline First (EDF) scheduling for the hard real-time tasks and the Constant Bandwidth Server (CBS) for the soft tasks. The bandwidth reserved for the servers determines the quality of service (QoS) for soft tasks. CBS enforces temporal isolation, such that soft task overruns do not affect the timing guarantees of hard tasks. Transient faults in hard tasks are tolerated using checkpointing with rollback recovery. We have proposed a Tabu Search-based approach for task mapping and CBS bandwidth reservation, such that the deadlines for the hard tasks are satisfied, even in the case of transient faults, and the QoS for the soft tasks is maximized. Researchers have used fixed execution time models, such as the worst-case execution times for hard tasks and average execution times for soft tasks. However, we show that by using stochastic execution times for soft tasks, significant improvements can be obtained. The proposed strategy has been evaluated using an extensive set of benchmarks.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121323985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global EDF scheduling of sporadic task systems upon uniform multiprocessor platforms is studied. A new sufficient schedulability test is presented and proved correct. Some interesting issues are discussed, that arise regarding the choice of an appropriate metric for evaluating the test quantitatively. Metrics based on processor speedup factor are proposed, and the test is quantitatively evaluated in terms of these metrics.
{"title":"An Improved Global EDF Schedulability Test for Uniform Multiprocessors","authors":"Sanjoy Baruah","doi":"10.1109/RTAS.2010.11","DOIUrl":"https://doi.org/10.1109/RTAS.2010.11","url":null,"abstract":"The global EDF scheduling of sporadic task systems upon uniform multiprocessor platforms is studied. A new sufficient schedulability test is presented and proved correct. Some interesting issues are discussed, that arise regarding the choice of an appropriate metric for evaluating the test quantitatively. Metrics based on processor speedup factor are proposed, and the test is quantitatively evaluated in terms of these metrics.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133919239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Providing QoS and performance guarantees to arbitrarily divisible loads has become a significant problem for many cluster-based research computing facilities. While progress is being made in scheduling arbitrarily divisible loads, current approaches are not efficient and do not scale well. In this paper, we propose a linear algorithm for real-time divisible load scheduling. Unlike existing approaches, the new algorithm relaxes the tight coupling between the task admission controller and the task dispatcher. By eliminating the need to generate exact schedules in the admission controller, the algorithm avoids high overhead. We experimentally evaluate the new algorithm. Simulation results demonstrate that the algorithm scales well, can schedule large numbers of tasks efficiently, and performs similarly to existing approaches in terms of providing real-time guarantees.
{"title":"An Efficient Algorithm for Real-Time Divisible Load Scheduling","authors":"A. Mamat, Ying Lu, J. Deogun, S. Goddard","doi":"10.1109/RTAS.2010.29","DOIUrl":"https://doi.org/10.1109/RTAS.2010.29","url":null,"abstract":"Providing QoS and performance guarantees to arbitrarily divisible loads has become a significant problem for many cluster-based research computing facilities. While progress is being made in scheduling arbitrarily divisible loads, current approaches are not efficient and do not scale well. In this paper, we propose a linear algorithm for real-time divisible load scheduling. Unlike existing approaches, the new algorithm relaxes the tight coupling between the task admission controller and the task dispatcher. By eliminating the need to generate exact schedules in the admission controller, the algorithm avoids high overhead. We experimentally evaluate the new algorithm. Simulation results demonstrate that the algorithm scales well, can schedule large numbers of tasks efficiently, and performs similarly to existing approaches in terms of providing real-time guarantees.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"624 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132690947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Glaubius, T. Tidwell, B. Sidoti, David Pilla, Justin Meden, C. Gill, W. Smart
Open soft real-time systems, such as mobile robots, must respond adaptively to varying operating conditions, while balancing the need to perform multiple mission specific tasks against the requirement that those tasks complete in a timely manner. Setting and enforcing a utilization target for shared resources is a key mechanism for achieving this behavior. However, because of the uncertainty and non-preempt ability of some tasks, key assumptions of classical scheduling approaches do not hold. In previous work we presented foundational methods for generating task scheduling policies to enforce proportional resource utilization for open soft real-time systems with these properties. However, these methods scale exponentially in the number of tasks, limiting their practical applicability.In this paper, we present a novel parameterized scheduling policy that scales our technique to a much wider range of systems. These policies can represent geometric features of the scheduling policies produced by our earlier methods, but only require a number of parameters that is quadratic in the number of tasks. We provide empirical evidence that the best of these policies are competitive with exact solution methods in small problems, and significantly outperform heuristic methods in larger ones.
{"title":"Scalable Scheduling Policy Design for Open Soft Real-Time Systems","authors":"R. Glaubius, T. Tidwell, B. Sidoti, David Pilla, Justin Meden, C. Gill, W. Smart","doi":"10.1109/RTAS.2010.23","DOIUrl":"https://doi.org/10.1109/RTAS.2010.23","url":null,"abstract":"Open soft real-time systems, such as mobile robots, must respond adaptively to varying operating conditions, while balancing the need to perform multiple mission specific tasks against the requirement that those tasks complete in a timely manner. Setting and enforcing a utilization target for shared resources is a key mechanism for achieving this behavior. However, because of the uncertainty and non-preempt ability of some tasks, key assumptions of classical scheduling approaches do not hold. In previous work we presented foundational methods for generating task scheduling policies to enforce proportional resource utilization for open soft real-time systems with these properties. However, these methods scale exponentially in the number of tasks, limiting their practical applicability.In this paper, we present a novel parameterized scheduling policy that scales our technique to a much wider range of systems. These policies can represent geometric features of the scheduling policies produced by our earlier methods, but only require a number of parameters that is quadratic in the number of tasks. We provide empirical evidence that the best of these policies are competitive with exact solution methods in small problems, and significantly outperform heuristic methods in larger ones.","PeriodicalId":356388,"journal":{"name":"2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116373508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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