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- Avni, G., et al.
(författare)
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Computing scores of forwarding schemes in switched networks with probabilistic faults
- 2017
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Ingår i: Lecture Notes in Computer Science, Volume 10206. - Berlin, Heidelberg : Springer Verlag. - 9783662545799 ; , s. 169-187
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Konferensbidrag (refereegranskat)abstract
- Time-triggered switched networks are a deterministic communication infrastructure used by real-time distributed embedded systems. Due to the criticality of the applications running over them, developers need to ensure that end-to-end communication is dependable and predictable. Traditional approaches assume static networks that are not flexible to changes caused by reconfigurations or, more importantly, faults, which are dealt with in the application using redundancy. We adopt the concept of handling faults in the switches from non-real-time networks while maintaining the required predictability. We study a class of forwarding schemes that can handle various types of failures. We consider probabilistic failures. For a given network with a forwarding scheme and a constant ℓ, we compute the score of the scheme, namely the probability (induced by faults) that at least ℓ messages arrive on time. We reduce the scoring problem to a reachability problem on a Markov chain with a “product-like” structure. Its special structure allows us to reason about it symbolically, and reduce the scoring problem to #SAT. Our solution is generic and can be adapted to different networks and other contexts. Also, we show the computational complexity of the scoring problem is #P-complete, and we study methods to estimate the score. We evaluate the effectiveness of our techniques with an implementation.
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- Avni, G., et al.
(författare)
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Synthesizing time-triggered schedules for switched networks with faulty links
- 2016
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Ingår i: Proceedings of the 13th International Conference on Embedded Software, EMSOFT 2016. - New York, NY, USA : ACM. - 9781450344852
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Konferensbidrag (refereegranskat)abstract
- Time-triggered (TT) switched networks are a deterministic communication infrastructure used by real-time distributed embedded systems. These networks rely on the notion of globally discretized time (i.e. time slots) and a static TT schedule that prescribes which message is sent through which link at every time slot, such that all messages reach their destination before a global timeout. These schedules are generated offline, assuming a static network with fault-free links, and entrusting all error-handling functions to the end user. Assuming the network is static is an over-optimistic view, and indeed links tend to fail in practice. We study synthesis of TT schedules on a network in which links fail over time and we assume the switches run a very simple error-recovery protocol once they detect a crashed link. We address the problem of finding a pk; qresistant schedule; namely, one that, assuming the switches run a fixed error-recovery protocol, guarantees that the number of messages that arrive at their destination by the timeout is at least no matter what sequence of at most k links fail. Thus, we maintain the simplicity of the switches while giving a guarantee on the number of messages that meet the timeout. We show how a pk; q-resistant schedule can be obtained using a CEGAR-like approach: find a schedule, decide whether it is pk; q-resistant, and if it is not, use the witnessing fault sequence to generate a constraint that is added to the program. The newly added constraint disallows the schedule to be regenerated in a future iteration while also eliminating several other schedules that are not pk; q-resistant. We illustrate the applicability of our approach using an SMT-based implementation.
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- Olefeldt, David, et al.
(författare)
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The Boreal-Arctic Wetland and Lake Dataset (BAWLD)
- 2021
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Ingår i: Earth System Science Data. - : Copernicus Gesellschaft MBH. - 1866-3508 .- 1866-3516. ; 13:11, s. 5127-5149
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Tidskriftsartikel (refereegranskat)abstract
- Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the BorealArctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 x 0.5 degrees grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 x 10(6) km(2) (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 x 10(6) km(2). Bog, fen, and permafrost bog were the most abundant wetland classes, covering similar to 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 x 10(6) km(2) (6 % of domain). Low-methane-emitting large lakes (>10 km(2)) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km(2)) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 x 10(6) km(2). Rivers and streams were estimated to cover 0.12 x 10(6) km(2) (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of "wetscapes" that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions.
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