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Leibniz Transactions on Embedded Systems, Volume 4, Issue 1
LITES, Volume 4, Issue 1
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LITES, Volume 4
Journal: Leibniz Transactions on Embedded Systems (LITES)
Publication Details
- published at: 2017-02-28
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/lites/lites4
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Complete Issue
LITES, Volume 4, Issue 1
Abstract
LITES, Volume 4, Issue 1
Cite as
LITES, Volume 4, Issue 1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
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@Article{LITES-v004-i001,
title = {{LITES, Volume 4, Issue 1}},
journal = {Leibniz Transactions on Embedded Systems},
ISSN = {2199-2002},
year = {2017},
volume = {4},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001},
doi = {10.4230/LITES-v004-i001},
annote = {Keywords: LITES, Volume 4, Issue 1}
}
Document
A Note on the Period Enforcer Algorithm for Self-Suspending Tasks
Abstract
The period enforcer algorithm for self-suspending real-time tasks is a technique for suppressing the "back-to-back" scheduling penalty associated with deferred execution. Originally proposed in 1991, the algorithm has attracted renewed interest in recent years. This note revisits the algorithm in the light of recent developments in the analysis of self-suspending tasks, carefully re-examines and explains its underlying assumptions and limitations, and points out three observations that have not been made in the literature to date: (i) period enforcement is not strictly superior (compared to the base case without enforcement) as it can cause deadline misses in self-suspending task sets that are schedulable without enforcement; (ii) to match the assumptions underlying the analysis of the period enforcer, a schedulability analysis of self-suspending tasks subject to period enforcement requires a task set transformation for which no solution is known in the general case, and which is subject to exponential time complexity (with current techniques) in the limited case of a single self-suspending task; and (iii) the period enforcer algorithm is incompatible with all existing analyses of suspension-based locking protocols, and can in fact cause ever-increasing suspension times until a deadline is missed.
Cite as
Jian-Jia Chen and Björn B. Brandenburg. A Note on the Period Enforcer Algorithm for Self-Suspending Tasks. In LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1, pp. 01:1-01:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
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@Article{chen_et_al:LITES-v004-i001-a001,
author = {Chen, Jian-Jia and Brandenburg, Bj\"{o}rn B.},
title = {{A Note on the Period Enforcer Algorithm for Self-Suspending Tasks}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {01:1--01:22},
ISSN = {2199-2002},
year = {2017},
volume = {4},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001-a001},
doi = {10.4230/LITES-v004-i001-a001},
annote = {Keywords: Period Enforcer, Deferred Execution, Self-suspension, Blocking}
}
Document
Utility-Based Scheduling of (m,k)-firm Real-Time Tasks - New Empirical Results
Abstract
The concept of a firm real-time task implies the notion of a firm deadline that should not be missed by the jobs of this task. If a deadline miss occurs, the concerned job yields no value to the system. For some applications domains, this restrictive notion can be relaxed. For example, robust control systems can tolerate that single executions of a control loop miss their deadlines, and still yield an acceptable behaviour. Thus, systems can be developed under more optimistic assumptions, e.g. by allowing overloads. However, care must be taken that deadline misses do not accumulate. This restriction can be expressed by the model of (m,k)-firm real-time tasks that require that from any k consecutive jobs at least m are executed successfully. In this article, we extend our prior work on the MKU scheduling heuristic. MKU uses history-cognisant utility functions as means for making decisions in overload situations. We present new theoretical results on MKU and on other schedulers for (m,k)-firm real-time tasks. Based on extensive simulations, we assess the performance of these schedulers. The results allow us to identify task set characteristics that can be used as guidelines for choosing a scheduler for a concrete use case.
Cite as
Florian Kluge. Utility-Based Scheduling of (m,k)-firm Real-Time Tasks - New Empirical Results. In LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1, pp. 02:1-02:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
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@Article{kluge:LITES-v004-i001-a002,
author = {Kluge, Florian},
title = {{Utility-Based Scheduling of (m,k)-firm Real-Time Tasks - New Empirical Results}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {02:1--02:25},
ISSN = {2199-2002},
year = {2017},
volume = {4},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001-a002},
doi = {10.4230/LITES-v004-i001-a002},
annote = {Keywords: Real-time Scheduling, (m, k)-Firm Real-Time Tasks}
}
Document
Quantitative Analysis of Consistency in NoSQL Key-Value Stores
Abstract
The promise of high scalability and availability has prompted many companies to replace traditional relational database management systems (RDBMS) with NoSQL key-value stores. This comes at the cost of relaxed consistency guarantees: key-value stores only guarantee eventual consistency in principle. In practice, however, many key-value stores seem to offer stronger consistency. Quantifying how well consistency properties are met is a non-trivial problem. We address this problem by formally modeling key-value stores as probabilistic systems and quantitatively analyzing their consistency properties by both statistical model checking and implementation evaluation. We present for the first time a formal probabilistic model of Apache Cassandra, a popular NoSQL key-value store, and quantify how much Cassandra achieves various consistency guarantees under various conditions. To validate our model, we evaluate multiple consistency properties using two methods and compare them against each other. The two methods are: (1) an implementation-based evaluation of the source code; and (2) a statistical model checking analysis of our probabilistic model.
Cite as
Si Liu, Jatin Ganhotra, Muntasir Raihan Rahman, Son Nguyen, Indranil Gupta, and José Meseguer. Quantitative Analysis of Consistency in NoSQL Key-Value Stores. In LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1, pp. 03:1-03:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
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@Article{liu_et_al:LITES-v004-i001-a003,
author = {Liu, Si and Ganhotra, Jatin and Rahman, Muntasir Raihan and Nguyen, Son and Gupta, Indranil and Meseguer, Jos\'{e}},
title = {{Quantitative Analysis of Consistency in NoSQL Key-Value Stores}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {03:1--03:26},
ISSN = {2199-2002},
year = {2017},
volume = {4},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001-a003},
doi = {10.4230/LITES-v004-i001-a003},
annote = {Keywords: NoSQL Key-value Store, Consistency, Statistical Model Checking, Rewriting Logic, Maude}
}
Document
How Is Your Satellite Doing? Battery Kinetics with Recharging and Uncertainty
Abstract
The kinetic battery model is a popular model of the dynamic behaviour of a conventional battery, useful to predict or optimize the time until battery depletion. The model however lacks certain obvious aspects of batteries in-the-wild, especially with respect to the effects of random influences and the behaviour when charging up to capacity limits.This paper considers the kinetic battery model with limited capacity in the context of piecewise constant yet random charging and discharging. We provide exact representations of the battery behaviour wherever possible, and otherwise develop safe approximations that bound the probability distribution of the battery state from above and below. The resulting model enables the time-dependent evaluation of the risk of battery depletion. This is demonstrated in an extensive dependability study of a nano satellite currently orbiting the earth.
Cite as
Holger Hermanns, Jan Krčál, and Gilles Nies. How Is Your Satellite Doing? Battery Kinetics with Recharging and Uncertainty. In LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1, pp. 04:1-04:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
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@Article{hermanns_et_al:LITES-v004-i001-a004,
author = {Hermanns, Holger and Kr\v{c}\'{a}l, Jan and Nies, Gilles},
title = {{How Is Your Satellite Doing? Battery Kinetics with Recharging and Uncertainty}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {04:1--04:28},
ISSN = {2199-2002},
year = {2017},
volume = {4},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001-a004},
doi = {10.4230/LITES-v004-i001-a004},
annote = {Keywords: Battery Power, Depletion Risk, Bounded Charging and Discharging, Stochastic Load, Distribution Bounds}
}
Document
Characterizing Data Dependence Constraints for Dynamic Reliability Using n-Queens Attack Domains
Abstract
As data centers attempt to cope with the exponential growth of data, new techniques for intelligent, software-defined data centers (SDDC) are being developed to confront the scale and pace of changing resources and requirements. For cost-constrained environments, like those increasingly present in scientific research labs, SDDCs also may provide better reliability and performability with no additional hardware through the use of dynamic syndrome allocation. To do so, the middleware layers of SDDCs must be able to calculate and account for complex dependence relationships to determine an optimal data layout. This challenge is exacerbated by the growth of constraints on the dependence problem when available resources are both large (due to a higher number of syndromes that can be stored) and small (due to the lack of available space for syndrome allocation). We present a quantitative method for characterizing these challenges using an analysis of attack domains for high-dimension variants of the $n$-queens problem that enables performable solutions via the SMT solver Z3. We demonstrate correctness of our technique, and provide experimental evidence of its efficacy; our implementation is publicly available.
Cite as
Eric W. D. Rozier, Kristin Y. Rozier, and Ulya Bayram. Characterizing Data Dependence Constraints for Dynamic Reliability Using n-Queens Attack Domains. In LITES, Volume 4, Issue 1 (2017). Leibniz Transactions on Embedded Systems, Volume 4, Issue 1, pp. 05:1-05:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
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@Article{rozier_et_al:LITES-v004-i001-a005,
author = {Rozier, Eric W. D. and Rozier, Kristin Y. and Bayram, Ulya},
title = {{Characterizing Data Dependence Constraints for Dynamic Reliability Using n-Queens Attack Domains}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {05:1--05:26},
ISSN = {2199-2002},
year = {2017},
volume = {4},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LITES-v004-i001-a005},
doi = {10.4230/LITES-v004-i001-a005},
annote = {Keywords: SMT, Data dependence, n-queens}
}