4,967 research outputs found
Path computation in multi-layer networks: Complexity and algorithms
Carrier-grade networks comprise several layers where different protocols
coexist. Nowadays, most of these networks have different control planes to
manage routing on different layers, leading to a suboptimal use of the network
resources and additional operational costs. However, some routers are able to
encapsulate, decapsulate and convert protocols and act as a liaison between
these layers. A unified control plane would be useful to optimize the use of
the network resources and automate the routing configurations. Software-Defined
Networking (SDN) based architectures, such as OpenFlow, offer a chance to
design such a control plane. One of the most important problems to deal with in
this design is the path computation process. Classical path computation
algorithms cannot resolve the problem as they do not take into account
encapsulations and conversions of protocols. In this paper, we propose
algorithms to solve this problem and study several cases: Path computation
without bandwidth constraint, under bandwidth constraint and under other
Quality of Service constraints. We study the complexity and the scalability of
our algorithms and evaluate their performances on real topologies. The results
show that they outperform the previous ones proposed in the literature.Comment: IEEE INFOCOM 2016, Apr 2016, San Francisco, United States. To be
published in IEEE INFOCOM 2016, \<http://infocom2016.ieee-infocom.org/\&g
Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results
This paper focuses on current control in a permanentmagnet synchronous motor (PMSM). The paper has two main objectives: The first objective is to develop a neural-network (NN) vector controller to overcome the decoupling inaccuracy problem associated with conventional PI-based vector-control methods. The NN is developed using the full dynamic equation of a PMSM, and trained to implement optimal control based on approximate dynamic programming. The second objective is to evaluate the robust and adaptive performance of the NN controller against that of the conventional standard vector controller under motor parameter variation and dynamic control conditions by (a) simulating the behavior of a PMSM typically used in realistic electric vehicle applications and (b) building an experimental system for hardware validation as well as combined hardware and simulation evaluation. The results demonstrate that the NN controller outperforms conventional vector controllers in both simulation and hardware implementation
MacShim: Compiling MATLAB to a Scheduling-Independent Concurrent Language
Nondeterminism is a central challenge in most concurrent models of computation. That programmers must worry about races and other timing-dependent behavior is a key reason that parallel programming has not been widely adopted. The SHIM concurrent language, intended for hardware/software codesign applications, avoids this problem by providing deterministic (race-free) concurrency, but does not support automatic parallelization of sequential algorithms. In this paper, we present a compiler able to parallelize a simple MATLAB-like language into concurrent SHIM processes. From a user-provided partitioning of arrays to processes, our compiler divides the program into coarse-grained processes and schedules and synthesizes inter-process communication. We demonstrate the effectiveness of our approach on some image-processing algorithms
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