A method of computation for worst-case delay analysis on SpaceWire networks

SpaceWire is a standard for on-board satellite networks chosen by the ESA as the basis for future data-handling architectures. However, network designers need tools to ensure that the network is able to deliver critical messages on time. Current research only seek to determine probabilistic results for end-to-end delays on Wormhole networks like SpaceWire. This does not provide sufficient guarantee for critical traffic. Thus, in this paper, we propose a method to compute an upper-bound on the worst-case end-to-end delay of a packet in a SpaceWire network

Worst-case end-to-end delays evaluation for SpaceWire networks

SpaceWire is a standard for on-board satellite networks chosen by the ESA as the basis for multiplexing payload and control traffic on future data-handling architectures. However, network designers need tools to ensure that the network is able to deliver critical messages on time. Current research fails to address this needs for SpaceWire networks. On one hand, many papers only seek to determine probabilistic results for end-to-end delays on Wormhole networks like SpaceWire. This does not provide sufficient guarantee for critical traffic. On the other hand, a few papers give methods to determine maximum latencies on wormhole networks that, unlike SpaceWire, have dedicated real-time mechanisms built-in. Thus, in this paper, we propose an appropriate method to compute an upper-bound on the worst-case end-to-end delay of a packet in a SpaceWire network

An enhanced worst-case end-to-end evaluation method for SpaceWire networks

The SpaceWire network is scheduled to be used as the sole on-board network for future ESA satellites. However, at the moment, network designers do not have tools to ensure that critical temporal deadlines are met when using best-effort wormhole networks like SpaceWire. In a previous paper, we have presented a first method to compute an upper-bound on the worst-case end-to-end delay of flows traversing such networks. However, its scope was limited by restrictive assumptions on the traffic patterns. Thus, in this paper, we propose a new network model that removes those limitations and allows worst-case delay analysis on SpaceWire networks with any traffic pattern

Modeling SpaceWire networks with network calculus

The SpaceWire network standard is promoted by the ESA and is scheduled to be used as the sole on-board network for future satellites. This network uses a wormhole routing mechanism that can lead to packet blocking in routers and consequently to variable end-to-end delays. As the network will be shared by real-time and non real-time traffic, network designers require a tool to check that temporal constraints are verified for all the critical messages. Network Calculus can be used for evaluating worst-case end-to-end delays. However, we first have to model SpaceWire components through the definition of service curves. In this paper, we propose a new Network Calculus element that we call the Wormhole Section. This element allows us to better model a wormhole network than the usual multiplexer and demultiplexer elements used in the context of usual Store-and-Forward networks. Then, we show how to combine Wormhole Section elements to compute the end-to-end service curve offered to a flow and illustrate its use on a industrial case study

Modeling a spacewire architecture using timed automata to compute worst-case end-to-end delays

International audienceSpacewire is a real-time communication network for use onboard satellites. It has been designed to transmit both payload and control/command data. To guarantee that communications respect the real-time constraints, designers use tools to compute the worst-case end-to-end delays. Among these tools, recursive flow analysis and Network Calculus approaches have been studied. This paper proposes to use the model-checking approach based on timed automata. A case study based on an industrial one is shown. Our approach is compared with recursive flow analysis and Network Calculus

Computing the exact worst-case End-to-end delays in a Spacewire network using Timed Automata

National audienceSpacewire is a real-time communication network for use onboard satellites. It has been designed to transmit both payload and control/command data. To guarantee that communications respect the real-time constraints, designers use tools to compute the worst-case end-to-end delays. Among these tools, recursive flow analysis and Network Calculus approaches have been studied. This paper proposes to use the model-checking approach based on timed automata to compute the exact worstcase end-to-end delays and two case studies are presented

Buffer-aware Worst Case Timing Analysis of Wormhole Network On Chip

A buffer-aware worst-case timing analysis of wormhole NoC is proposed in this paper to integrate the impact of buffer size on the different dependencies relationship between flows, i.e. direct and indirect blocking flows, and consequently the timing performance. First, more accurate definitions of direct and indirect blocking flows sets have been introduced to take into account the buffer size impact. Then, the modeling and worst-case timing analysis of wormhole NoC have been detailed, based on Network Calculus formalism and the newly defined blocking flows sets. This introduced approach has been illustrated in the case of a realistic NoC case study to show the trade off between latency and buffer size. The comparative analysis of our proposed Buffer-aware timing analysis with conventional approaches is conducted and noticeable enhancements in terms of maximum latency have been proved

Model Checking Message Delivery Times in SpaceWire Networks

This paper presents a model checking framework in Uppaal for finding worst-case message delivery times for periodic and event-driven message flows in a SpaceWire network with wormhole switching. In particular, we focus on segmentation of large messages into smaller packets. We present a collection of timed automata for SpaceWire links and network messages, that capture message segmentation and wormhole blocking. We evaluate our approach on a realistic example network with 4 routers and 16 message flows, two of which are large messages that need to be segmented. Our model can be used to determine the bounds on the possible segment size, and how this size affects the worst-case message delivery times. Model checking time for these experiments ranges from several minutes to several hours, and we further investigate how it depends on the number of flows, the segmentation size, and the message periods