Assessment of visibility restriction mechanisms for RFID data Discovery Services

RFID is a technology that enables the automated capture of observations of uniquely identified physical objects as they move through supply chains. Discovery Services provide links to repositories that have traceability information about specific physical objects. Each supply chain party publishes records to a Discovery Service to create such links and also specifies access control policies to restrict who has visibility of link information, since it is commercially sensitive and could reveal inventory levels, flow patterns, trading relationships, etc. The requirement of being able to share information on a need-to-know basis, e.g. within the specific chain of custody of an individual object, poses a particular challenge for authorization and access control, because in many supply chain situations the information owner might not have sufficient knowledge about all the companies who should be authorized to view the information, because the path taken by an individual physical object only emerges over time, rather than being fully pre-determined at the time of manufacture. This led us to consider novel approaches to delegate trust and to control access to information. This paper presents an assessment of visibility restriction mechanisms for Discovery Services capable of handling emergent object paths. We compare three approaches: enumerated access control (EAC), chain-of-communication tokens (CCT), and chain-of-trust assertions (CTA). A cost model was developed to estimate the additional cost of restricting visibility in a baseline traceability system and the estimates were used to compare the approaches and to discuss the trade-offs. © 2012 IEEE.

State estimation over a communication network: Measurement or estimate communication?

In this paper we consider the problem of state estimation over a communication network. Using estimation quality as a metric, two communication schemes are studied and compared. In scheme one, each sensor node communicates its measurement data to the remote estimator, while in scheme two, each sensor node communicates its local state estimate to the remote estimator. We show that with perfect communication link, if the sensor has unlimited computation capability, the two schemes produce the same estimate at the estimator, and if the sensor has limited computation capability, scheme one is always better than scheme two. On the other hand, when data packet drops occur over the communication link, we show that if the sensor has unlimited computation capability, scheme two always outperforms scheme one, and if the sensor has limited computation capability, we show that in general there exists a critical packet arrival rate, above which scheme one outperforms scheme two. Simulations are provided to demonstrate the two schemes under various circumstances. © South China University of Technology and Academy of Mathematics and Systems Science, CAS and Springer-Verlag Berlin Heidelberg 2010.

A neuro-inspired method for data rate limited feedback control

The nervous system implements a networked control system in which the plants take the form of limbs, the controller is the brain, and neurons form the communication channels. Unlike standard networked control architectures, there is no periodic sampling, and the fundamental units of communication contain little numerical information. This paper describes a novel communication channel, modeled after spiking neurons, in which the transmitter integrates an input signal and sends out a spike when the integral reaches a threshold value. The reciever then filters the sequence of spikes to approximately reconstruct the input signal. It is shown that for appropriate choices of channel parameters, stable feedback control over these spiking channels is possible. Furthermore, good tracking performance can be achieved. The data rate of the channel increases linearly with the size of the inputs. Thus, when placed in a feedback loop, small loop gains imply a low data rate. ©2010 IEEE.

Sensor data scheduling for linear quadratic Gaussian control with full state feedback

Networked control systems (NCSs) have attracted much attention in the past decade due to their many advantages and growing number of applications. Different than classic control systems, resources in NCSs, such as network bandwidth and communication energy, are often limited, which degrade the closed-loop system performance and may even cause the system to become unstable. Seeking a desired trade-off between the closed-loop system performance and the limited resources is thus one heated area of research. In this paper, we analyze the trade-off between the sensor-to-controller communication rate and the closed-loop system performance indexed by the conventional LQG control cost. We present and compare several sensor data schedules, and demonstrate that two event-based sensor data schedules provide better trade-off than an optimal offline schedule. Simulation examples are provided to illustrate the theories developed in the paper. © 2012 AACC American Automatic Control Council).

Finite horizon LQR control with limited controller-system communication

We consider finite-horizon LQR control with limited controller-system communication. Within a time-horizon T , the controller can only communicate with the system d