205 research outputs found
P4CEP: Towards In-Network Complex Event Processing
In-network computing using programmable networking hardware is a strong trend
in networking that promises to reduce latency and consumption of server
resources through offloading to network elements (programmable switches and
smart NICs). In particular, the data plane programming language P4 together
with powerful P4 networking hardware has spawned projects offloading services
into the network, e.g., consensus services or caching services. In this paper,
we present a novel case for in-network computing, namely, Complex Event
Processing (CEP). CEP processes streams of basic events, e.g., stemming from
networked sensors, into meaningful complex events. Traditionally, CEP
processing has been performed on servers or overlay networks. However, we argue
in this paper that CEP is a good candidate for in-network computing along the
communication path avoiding detouring streams to distant servers to minimize
communication latency while also exploiting processing capabilities of novel
networking hardware. We show that it is feasible to express CEP operations in
P4 and also present a tool to compile CEP operations, formulated in our P4CEP
rule specification language, to P4 code. Moreover, we identify challenges and
problems that we have encountered to show future research directions for
implementing full-fledged in-network CEP systems.Comment: 6 pages. Author's versio
Just a Second -- Scheduling Thousands of Time-Triggered Streams in Large-Scale Networks
Deterministic real-time communication with bounded delay is an essential
requirement for many safety-critical cyber-physical systems, and has received
much attention from major standardization bodies such as IEEE and IETF. In
particular, Ethernet technology has been extended by time-triggered scheduling
mechanisms in standards like TTEthernet and Time-Sensitive Networking. Although
the scheduling mechanisms have become part of standards, the traffic planning
algorithms to create time-triggered schedules are still an open and challenging
research question due to the problem's high complexity. In particular,
so-called plug-and-produce scenarios require the ability to extend schedules on
the fly within seconds. The need for scalable scheduling and routing algorithms
is further supported by large-scale distributed real-time systems like smart
energy grids with tight communication requirements. In this paper, we tackle
this challenge by proposing two novel algorithms called Hierarchical Heuristic
Scheduling (H2S) and Cost-Efficient Lazy Forwarding Scheduling (CELF) to
calculate time-triggered schedules for TTEthernet. H2S and CELF are highly
efficient and scalable, calculating schedules for more than 45,000 streams on
random networks with 1,000 bridges as well as a realistic energy grid network
within sub-seconds to seconds
Availability Analysis of Redundant and Replicated Cloud Services with Bayesian Networks
Due to the growing complexity of modern data centers, failures are not
uncommon any more. Therefore, fault tolerance mechanisms play a vital role in
fulfilling the availability requirements. Multiple availability models have
been proposed to assess compute systems, among which Bayesian network models
have gained popularity in industry and research due to its powerful modeling
formalism. In particular, this work focuses on assessing the availability of
redundant and replicated cloud computing services with Bayesian networks. So
far, research on availability has only focused on modeling either
infrastructure or communication failures in Bayesian networks, but have not
considered both simultaneously. This work addresses practical modeling
challenges of assessing the availability of large-scale redundant and
replicated services with Bayesian networks, including cascading and
common-cause failures from the surrounding infrastructure and communication
network. In order to ease the modeling task, this paper introduces a high-level
modeling formalism to build such a Bayesian network automatically. Performance
evaluations demonstrate the feasibility of the presented Bayesian network
approach to assess the availability of large-scale redundant and replicated
services. This model is not only applicable in the domain of cloud computing it
can also be applied for general cases of local and geo-distributed systems.Comment: 16 pages, 12 figures, journa
Stable phase-shift despite quasi-rhythmic movements: a CPG-driven dynamic model of active tactile exploration in an insect
Harischandra N, Krause AF, Dürr V. Stable phase-shift despite quasi-rhythmic movements: a CPG-driven dynamic model of active tactile exploration in an insect. Frontiers in Computational Neuroscience. 2015;9: 107.An essential component of autonomous and flexible behaviour in animals is active exploration of the environment, allowing for perception-guided planning and control of actions. An important sensory system involved is active touch. Here, we introduce a general modelling framework of Central Pattern Generators (CPGs) for movement generation in active tactile exploration behaviour. The CPG consists of two network levels: (i) phase-coupled Hopf oscillators for rhythm generation, and (ii) pattern formation networks for capturing the frequency and phase characteristics of individual joint oscillations. The model captured the natural, quasi-rhythmic joint kinematics as observed in coordinated antennal movements of walking stick insects. Moreover, it successfully produced tactile exploration behaviour on a three-dimensional skeletal model of the insect antennal system with physically realistic parameters. The effect of proprioceptor ablations could be simulated by changing the amplitude and offset parameters of the joint oscillators, only. As in the animal, the movement of both antennal joints was coupled with a stable phase difference, despite the quasi-rhythmicity of the joint angle time courses. We found that the phase-lead of the distal scape-pedicel joint relative to the proximal head-scape joint was essential for producing the natural tactile exploration behaviour and, thus, for tactile efficiency. For realistic movement patterns, the phase-lead could vary within a limited range of 10 to 30 degrees only. Tests with artificial movement patterns strongly suggest that this phase sensitivity is not a matter of the frequency composition of the natural movement pattern. Based on our modelling results, we propose that a constant phase difference is coded into the CPG of the antennal motor system and that proprioceptors are acting locally to regulate the joint movement amplitude
A network abstraction for control systems
Networked control systems (NCS), such as the smart power grid, implement feedback control loops by connecting distributed sensors and actuators to a remote controller over a communication network. In order to avoid the costly and time-consuming installation of dedicated networks, NCS can benefit from utilizing readily available IP networks such as the Internet. However, as control systems are typically sensitive to delay and loss, the integration of such systems over best-effort networks becomes a challenge, which we address in this paper with two main contributions. First, we propose an end-to-end transport abstraction for NCS based on a novel probabilistic quality of service specification which (1) is compatible with existing control models and (2) provides the network with application-specific knowledge about the relation between system performance and network-relevant metrics. Second, we realize this abstraction at the network layer with an optimal routing algorithm, which fulfils the required QoS while minimizing the usage of network resources. We show that our approach lends itself to the implementation with state-of-the-art software-defined networking (SDN) technologies, and demonstrate its effectiveness in our evaluation
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