RFID Application of Smart Grid for Asset Management

RFID technology research has resolved practical application issues of the power industry such as assets management, working environment control, and vehicle networking. Also it provides technical reserves for the convergence of ERP and CPS. With the development of RFID and location-based services technology, RFID is converging with a variety of sensing, communication, and information technologies. Indoor positioning applications are under rapid development. Micromanagement environment of the assets is a useful practice for the RFID and positioning. In this paper, the model for RFID applications has been analyzed in the microenvironment management of the data center and electric vehicle batteries, and the optimization scheme of enterprise asset management is also proposed

Flexible Congestion Management for Error Reduction in Wireless Sensor Networks

The dissertation is concerned with the efficient resolution of data congestion on wireless sensor networks (WSNs). WSNs are of increasing relevance due to their applications in automation, industrial processes, natural-disaster detection, weather prediction, and climate monitoring. In large WSNs where measurements are periodically made at each node in the network and sent in a multi-hop fashion via the network tree to a single base-station node, the volume of data at a node may exceed the transmission capabilities of the node. This type of congestion can negatively impact data accuracy when packets are lost in transmission. We propose flexible congestion management for sensor networks (FCM) as a data-collection scheme to reduce network traffic and minimize the error resulting from data-volume reduction. FCM alleviates all congestion by lossy data fusion, encourages opportunistic fusion with an application-specific distortion tolerance, and balances network traffic. We consider several data-fusion methods including the k-means algorithm and two forms of adaptive summarization. Additional fusion is allowed when like data may be fused with low error up to some limit set by the user of the data-collection application on the network. Increasing the error limit tends to reduce the overall traffic on the network at the cost of data accuracy. When a node fuses more data than is required to alleviate congestion, its siblings are notified that they may increase the sizes of their transmissions accordingly. FCM is further improved to re-balance the network traffic of subtrees such that subtrees whose measurements have lower variance may decrease their output rates while subtrees whose measurements have higher variance may increase their output rates, while still addressing all congestion in the network. We verify the effectiveness of FCM with extensive simulations

Design of Wireless Communication Networks for Cyber-Physical Systems with Application to Smart Grid

Cyber-Physical Systems (CPS) are the next generation of engineered systems in which computing, communication, and control technologies are tightly integrated. On one hand, CPS are generally large with components spatially distributed in physical world that has lots of dynamics; on the other hand, CPS are connected, and must be robust and responsive. Smart electric grid, smart transportation system are examples of emerging CPS that have significant and far-reaching impact on our daily life. In this dissertation, we design wireless communication system for CPS. To make CPS robust and responsive, it is critical to have a communication subsystem that is reliable, adaptive, and scalable. Our design uses a layered structure, which includes physical layer, multiple access layer, network layer, and application layer. Emphases are placed on multiple access and network layer. At multiple access layer, we have designed three approaches, namely compressed multiple access, sample-contention multiple access, and prioritized multiple access, for reliable and selective multiple access. At network layer, we focus on the problem of creating reliable route, with service interruption anticipated. We propose two methods: the first method is a centralized one that creates backup path around zones posing high interruption risk; the other method is a distributed one that utilizes Ant Colony Optimization (ACO) and positive feedback, and is able to update multipath dynamically. Applications are treated as subscribers to the data service provided by the communication system. Their data quality requirements and Quality of Service (QoS) feedback are incorporated into cross-layer optimization in our design. We have evaluated our design through both simulation and testbed. Our design demonstrates desired reliability, scalability and timeliness in data transmission. Performance gain is observed over conventional approaches as such random access