4,013 research outputs found
Real-time and fault tolerance in distributed control software
Closed loop control systems typically contain multitude of spatially distributed sensors and actuators operated simultaneously. So those systems are parallel and distributed in their essence. But mapping this parallelism onto the given distributed hardware architecture, brings in some additional requirements: safe multithreading, optimal process allocation, real-time scheduling of bus and network resources. Nowadays, fault tolerance methods and fast even online reconfiguration are becoming increasingly important. All those often conflicting requirements, make design and implementation of real-time distributed control systems an extremely difficult task, that requires substantial knowledge in several areas of control and computer science. Although many design methods have been proposed so far, none of them had succeeded to cover all important aspects of the problem at hand. [1] Continuous increase of production in embedded market, makes a simple and natural design methodology for real-time systems needed more then ever
Receiver-Based Flow Control for Networks in Overload
We consider utility maximization in networks where the sources do not employ
flow control and may consequently overload the network. In the absence of flow
control at the sources, some packets will inevitably have to be dropped when
the network is in overload. To that end, we first develop a distributed,
threshold-based packet dropping policy that maximizes the weighted sum
throughput. Next, we consider utility maximization and develop a receiver-based
flow control scheme that, when combined with threshold-based packet dropping,
achieves the optimal utility. The flow control scheme creates virtual queues at
the receivers as a push-back mechanism to optimize the amount of data delivered
to the destinations via back-pressure routing. A novel feature of our scheme is
that a utility function can be assigned to a collection of flows, generalizing
the traditional approach of optimizing per-flow utilities. Our control policies
use finite-buffer queues and are independent of arrival statistics. Their
near-optimal performance is proved and further supported by simulation results.Comment: 14 pages, 4 figures, 5 tables, preprint submitted to IEEE INFOCOM
201
On Energy Allocation and Data Scheduling in Backscatter Networks with Multi-antenna Readers
In this paper, we study the throughput utility functions in buffer-equipped
monostatic backscatter communication networks with multi-antenna Readers. In
the considered model, the backscatter nodes (BNs) store the data in their
buffers before transmission to the Reader. We investigate three utility
functions, namely, the sum, the proportional and the common throughput. We
design online admission policies, corresponding to each utility function, to
determine how much data can be admitted in the buffers. Moreover, we propose an
online data link control policy for jointly controlling the transmit and
receive beamforming vectors as well as the reflection coefficients of the BNs.
The proposed policies for data admission and data link control jointly optimize
the throughput utility, while stabilizing the buffers. We adopt the
min-drift-plus-penalty (MDPP) method in designing the control policies.
Following the MDPP method, we cast the optimal data link control and the data
admission policies as solutions of two independent optimization problems which
should be solved in each time slot. The optimization problem corresponding to
the data link control is non-convex and does not have a trivial solution. Using
Lagrangian dual and quadratic transforms, we find a closed-form iterative
solution. Finally, we use the results on the achievable rates of finite
blocklength codes to study the system performance in the cases with short
packets. As demonstrated, the proposed policies achieve optimal utility and
stabilize the data buffers in the BNs
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