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Synthesis of communication schedules for TTEthernetbased mixedcriticality systems,” CODES+ISSS
, 2012
"... In this paper we are interested in safetycritical distributed systems, composed of heterogeneous processing elements interconnected using the TTEthernet protocol. We address hard realtime mixedcriticality applications, which may have different criticality levels, and we focus on the optimizati ..."
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In this paper we are interested in safetycritical distributed systems, composed of heterogeneous processing elements interconnected using the TTEthernet protocol. We address hard realtime mixedcriticality applications, which may have different criticality levels, and we focus on the optimization of the communication configuration. TTEthernet integrates three types of traffic: TimeTriggered (TT) messages, EventTriggered (ET) messages with bounded endtoend delay, also called Rate Constrained (RC) messages, and BestEffort (BE) messages, for which no timing guarantees are provided. TT messages are transmitted based on static schedule tables, and have the highest priority. RC messages are transmitted if there are no TT messages, and BE traffic has the lowest priority. TT and RC traffic can carry safetycritical messages, while BE messages are noncritical. Mixedcriticality tasks and messages can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. TTEthernet offers spatial separation for mixedcriticality messages through the concept of virtual links, and temporal separation, enforced through schedule tables for TT messages and bandwidth allocation for RC messages. Given the set of mixedcriticality messages in the system and the topology of the virtual links on which the messages are transmitted, we are interested to synthesize offline the static schedules for the TT messages, such that the deadlines for the TT and RC messages are satisfied, and the endtoend delay of the RC traffic is minimized. We have proposed a Tabu Searchbased approach to solve this optimization problem. The proposed algorithm has been evaluated using several benchmarks.
Network calculus: Application to switched realtime networking
 In 5th International ICST Conference on Performance Evaluation Methodologies and Tools, ValueTools
, 2011
"... In this paper, we show how Network Calculus can be used to determine whether a switched network may satisfy the time constraints of a realtime application. If switched architecture are interesting in the sense that they offer flexible design and may eliminate collisions in Ethernetbased network, ..."
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In this paper, we show how Network Calculus can be used to determine whether a switched network may satisfy the time constraints of a realtime application. If switched architecture are interesting in the sense that they offer flexible design and may eliminate collisions in Ethernetbased network, they are not guaranteeing endtoend performances (in particular in terms of delay), especially when crosstraffic are present. We illustrate Network Calculus usefulness by showing how the internal switching structure of an Ethernet switch simplify the analysis and which kind of traffic interdependencies are problematic.
The PEGASE project: precise and scalable temporal analysis for aerospace communication systems with network calculus
 In: 4th Intl Symp. On Leveraging Applications of Formal Methods (ISoLA 2010), LNCS
, 2010
"... Abstract. With the increase of critical data exchanges in embedded realtime systems, the computation of tight upper bounds on network traversal times is becoming a crucial industrial need especially in safety critical systems. To address this need, the French project PEGASE grouping academics and ..."
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Abstract. With the increase of critical data exchanges in embedded realtime systems, the computation of tight upper bounds on network traversal times is becoming a crucial industrial need especially in safety critical systems. To address this need, the French project PEGASE grouping academics and industrial partners from the aerospace field has been undertaken to improve some key aspects of the Network Calculus and its implementation. 1
Pay Bursts Only Once Holds for (Some) NonFIFO Systems
 In IEEE INFOCOM
, 2011
"... Abstract—NonFIFO processing of flows by network nodes is not a rare phenomenon. Unfortunately, the stateoftheart analytical tool for the computation of performance bounds in packetswitched networks, network calculus, cannot deal well with nonFIFO systems. The problem lies in its conventional s ..."
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Abstract—NonFIFO processing of flows by network nodes is not a rare phenomenon. Unfortunately, the stateoftheart analytical tool for the computation of performance bounds in packetswitched networks, network calculus, cannot deal well with nonFIFO systems. The problem lies in its conventional service curve definitions. Either the definition is too strict to allow for a concatenation and consequent beneficial endtoend analysis, or it is too loose and results in infinite delay bounds. Hence, in this paper, we propose a new service curve definition and demonstrate its strength with respect to achieving both finite delay bounds and a concatenation of systems resulting in a favorable endtoend delay analysis. In particular, we show that the celebrated pay bursts only once phenomenon is retained even without any assumptions on the processing order of packets. This seems to contradict previous work [15]; the reasons for this are discussed.
PriorityMeister: Tail Latency QoS for Shared Networked Storage
"... Meeting service level objectives (SLOs) for tail latency is an important and challenging open problem in cloud computing infrastructures. The challenges are exacerbated by burstiness in the workloads. This paper describes PriorityMeister – a system that employs a combination of perworkload priorit ..."
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Meeting service level objectives (SLOs) for tail latency is an important and challenging open problem in cloud computing infrastructures. The challenges are exacerbated by burstiness in the workloads. This paper describes PriorityMeister – a system that employs a combination of perworkload priorities and rate limits to provide tail latency QoS for shared networked storage, even with bursty workloads. PriorityMeister automatically and proactively configures workload priorities and rate limits across multiple stages (e.g., a shared storage stage followed by a shared network stage) to meet endtoend tail latency SLOs. In real system experiments and under production trace workloads, PriorityMeister outperforms most recent reactive request scheduling approaches, with more workloads satisfying latency SLOs at higher latency percentiles. PriorityMeister is also robust to misestimation of underlying storage device performance and contains the effect of misbehaving workloads. 1.
Exact Worstcase Delay for FIFOmultiplexing
"... Abstract—This paper computes the actual worstcase endtoend delay for a flow in a tandem of FIFO multiplexing service curve nodes, where flows are shaped by concave, piecewise linear arrival curves, and service curves are convex and piecewise linear. Previous works only computed bounds on the abov ..."
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Abstract—This paper computes the actual worstcase endtoend delay for a flow in a tandem of FIFO multiplexing service curve nodes, where flows are shaped by concave, piecewise linear arrival curves, and service curves are convex and piecewise linear. Previous works only computed bounds on the above quantity, which are not always tight. We show that the solution entails taking the maximum among the optimal solution of a number of Linear Programming problems. However, the number and size of LP problems grows exponentially with the tandem length. Furthermore, we present approximate solution schemes to find both upper and lower delay bounds on the worstcase delay. Both of them only require to solve just one LP problem, and they produce bounds which are generally more accurate than those found in the previous work. Finally, we elaborate on how the worstcase scenario should be constructed. I.
Boosting Sensor Network Calculus by Thoroughly Bounding CrossTraffic
"... framework for worstcase analysis of wireless sensor networks. The analysis proceeds in two steps: For a given flow, (1) the network is reduced to a tandem of nodes by computing the arrival bounds of crosstraffic; (2) the flow is separated from the crosstraffic by subtracting crossflows and conca ..."
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framework for worstcase analysis of wireless sensor networks. The analysis proceeds in two steps: For a given flow, (1) the network is reduced to a tandem of nodes by computing the arrival bounds of crosstraffic; (2) the flow is separated from the crosstraffic by subtracting crossflows and concatenating nodes on its path. While the second step has seen much treatment, the first step has not at all. This is in sharp contrast to the fact that arrival bounding takes roughly 80 % of the total analysis time and is equally crucial for the tightness of the bounds. Therefore, we turn our attention to this first SensorNC analysis step with the goal to boost the performance and applicability of the overall framework. The main technical contribution is a generalized version of the concatenation theorem within the SensorNC setting. This generalization is instrumental in simplifying and streamlining the crosstraffic arrival bound computations such that run times can be reduced by more than a factor of 5. Even more important, it enables a localization of the information necessary to execute the calculations at the node level, thus enabling a distribution of the SensorNC analysis within a selfmodeling WSN. I.
Searching for Tight Performance Bounds in FeedForward Networks
"... Abstract. Computing tight performance bounds in feedforward networks under general assumptions about arrival and server models has turned out to be a challenging problem. Recently it was even shown to be NPhard [1]. We now address this problem in a heuristic fashion, building on a procedure for ..."
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Abstract. Computing tight performance bounds in feedforward networks under general assumptions about arrival and server models has turned out to be a challenging problem. Recently it was even shown to be NPhard [1]. We now address this problem in a heuristic fashion, building on a procedure for computing provably tight bounds under simple traffic and server models. We use a decomposition of a complex problem with more general traffic and server models into a set of simpler problems with simple traffic and server models. This set of problems can become prohibitively large, and we therefore resort to heuristic methods such as Monte Carlo. This shows interesting tradeoffs between performance bound quality and computational effort. 1 Motivation and Related Work When designing or analyzing a network, one of the most important aspects is its performance under various load conditions. A number of methods for that kind of analysis have been devised, among them network calculus, which describes
The MIDdleware Assurance Substrate: Enabling Strong RealTime Guarantees in Open Systems With OpenFlow
, 2014
"... Middleware designed for use in Distributed RealTime and Embedded (DRE) systems enable cost and development time reductions by providing simple communications abstractions and hiding operating systemlevel networking API details from developers. While current middleware technologies can hide many lo ..."
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Middleware designed for use in Distributed RealTime and Embedded (DRE) systems enable cost and development time reductions by providing simple communications abstractions and hiding operating systemlevel networking API details from developers. While current middleware technologies can hide many lowlevel details, designers must provide a static configuration for the system’s underlying network in order to achieve required performance characteristics. This has not been a problem for many types of DRE systems where the configuration of the system is relatively fixed from the factory (e.g., aircraft or naval vessels). However for truly open systems (i.e., systems where end users can add or subtract components at runtime) the standard static network configuration approach cannot guarantee that required performance will be met because network resource demands are not fully known a priori. Open systems with stringent performance requirements need middleware that can dynamically manage the underlying network configuration automatically in response to changing demands. Fortunately, recent trends in networking have resulted in a wide variety of networking equipment that expose a standardized lowlevel interface to their configuration via the OpenFlow protocol. In this paper we discuss how OpenFlow can be leveraged by DRE middleware to automatically provide performance guarantees. In order to make the discussion concrete, we describe the
Analyzing Multimode Wireless Sensor Networks Using the Network Calculus
"... The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the singlemode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bou ..."
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The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the singlemode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods AMM and NMM. The method AMM models the whole network as a multimode component, and the method NMM models each node as a multimode component. We prove that the maximum delay bound computed by the method AMM is tighter than or equal to that computed by the method NMM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the largescale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.