We consider the problem of resource provisioning for real-time cyber-physical applications in an open system environment where there does not exist a global resource scheduler that has complete knowledge of the real-time performance requirements of each individual application that shares the resources with the other applications. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically partition and assign various resource slices among such applications. However, previous work on RRP model only discusses uniform resource environment, where resources are implicitly assumed to be synchronized and clocked at the same frequency. The challenge is that a task utilizing multiple resources may experience unexpected delays in non-uniform environments, where resources are clocked at different frequencies. This paper extends the RRP model to non-uniform multi-resource open system environments to tackle this problem. It first introduces a novel composite resource partition abstraction and then proposes algorithms to construct and reconfigure the composite resource partitions. Specifically, the Acyclic Regular Composite Resource Partition Scheduling (ARCRP-S) algorithm constructs regular composite resource partitions and the Acyclic Regular Composite Resource Partition Dynamic Reconfiguration (ARCRP-DR) algorithm reconfigures the composite resource partitions in the run time upon requests of partition configuration changes. Our experimental results show that compared with state-of-the-art methods, ARCRP-S can prevent unexpected resource supply shortfall and improve the schedulability up to 50%. On the other hand, ARCRP-DR can guarantee the resource supply during the reconfiguration with moderate computational overhead.

We consider the problem of resource provisioning for real-time cyber-physical applications in an open system environment where there does not exist a global resource scheduler that has complete knowledge of the real-time performance requirements of each individual application that shares the resources with the other applications. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically partition and assign various resource slices among the applications. However, RRP model does not consider changes in resource requests from the applications at run time. To allow for the run time adaptation to change resource requirements, we consider in this paper the issues in online resource partition reconfiguration, including semantics issues that arise in configuration transitions that may cause application failures. Based on the reconfiguration semantics, we study the online resource reconfigurability problem under the RRP model where the availability factors of resource partitions may be reconfigured during run time. We formalize the Dynamic Partition Reconfiguration (DPR) problem and provide a solution to this problem. Extensive experiments have been conducted to evaluate the performance of the proposed approach in different scenarios. We also present a case study using the autonomous F1/10 model car; the controller of the F1/10 car requires resource adaptation to satisfy the computing needs of its PID controller and vision system under different operating conditions. Our implementation demonstrates the effectiveness and benefit of online resource partition reconfiguration using the DPR approach in a real system.

Applying wireless technologies in cyber-physical systems (CPSs) has received significant attention in recent years. In our previous work, a high-speed and flexible real-time wireless communication protocol called RT-WiFi was designed to support a wide range of CPSs, and we presented an implementation with a single access point (AP). To serve the CPS applications with communication nodes geographically distributed over a large area, multicluster RT-WiFi networks with multiple APs need to be deployed. Although effective scheduling algorithms have been designed to schedule tasks in RT-WiFi networks with a single AP, uncoordinated packet transmissions from multicluster RT-WiFi networks may suffer from cochannel interferences that cause performance degradation. The multicluster RT-WiFi network management problem is to resolve the cochannel interference through channel assignment for clusters and through phasing assignment for communication tasks. In this article, we first derive a conjunctive normal form encoding of the problem and design a TScheduler that searches feasible solutions through the SAT solver. A novel LRTree Scheduler is further designed to solve the problem in chain graphs while keeping the number of used channels small and the network management overhead low. A testbed of the multicluster RT-WiFi network is deployed to validate the design of the multicluster RT-WiFi network and evaluate the performance of the proposed scheduling algorithms compared to the contention-based methods in regular WiFi networks. Performance of these scheduling algorithms in large-scale networks is further evaluated through extensive simulations on both static and dynamic multicluster RT-WiFi networks.

With the ever-growing interests in applying wireless technologies for networked embedded systems to serve as the communication fabric, many real-time wireless technologies have been recently developed to support time-critical sensing and control applications. We proposed in previous work the RT-WiFi protocol that provides real-time high-speed predictable data delivery and enables designs to meet time-critical industrial needs. However, without explicit reliability enforcement mechanisms, our previous RT-WiFi design is either subject to uncontrolled packet loss due to noise and other interferences or may suffer from inefficient communication channel usage. In this article, we explicitly consider interference from both Wi-Fi and non-Wi-Fi based interference sources and propose two sets of effective solutions for reliable data transmissions in RT-WiFi-based networked embedded systems. To improve reliability against general non-Wi-Fi based interference, based on rate adaptation and retransmission techniques, we present an optimal real-time rate adaption algorithm together with a communication link scheduler that has low network management overhead. A novel technique called overbooking is introduced to further improve the schedulability of the communication link scheduler while maintaining the required communication reliability. For Wi-Fi-based interference, we present mechanisms that utilize virtual carrier sensing to provide reliable data transmission while co-existing with regular Wi-Fi networks. We have implemented the proposed algorithms in the RT-WiFi network management framework and demonstrated the system performance with a series of experiments.

In open systems, no global scheduler has knowledge of the complete resource requirements from all the applications. Each application has its own task group and can generate tasks on demand at run time. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically allocate resource in such environments. However, when applying the RRP model to multi-resource environments, end-to-end tasks could experience unexpected delay and miss the deadlines. The tasks might arrive at non-resource-slice boundaries because the resource slice sizes of different physical resource may vary in such non-uniform environments. This paper extends the RRP model to non-uniform multi-resource open systems. It introduces a novel composite resource partition abstraction, identifies the feasible conditions for hierarchical regular composite resource partitioning and proposes an acyclic regular composite resource partition scheduling (ARCRPS) algorithm. Simulation results show that compared with the state-of-the-art approach, ARCRPS improves the acceptance ratio by 20% and 25% in uniform and non-uniform multi-resource environments, respectively. A multi-resource scheduling framework jointly considering the CPU and network resources is also designed and implemented to evaluate the feasibility of this theoretical model in practice.

This study presents several extensions to our previous work on the PipeProbe system, a mobile sensor system for identifying the spatial topology of hidden water pipelines (i.e., non-moldable pipes such as copper and PVC) behind walls or under floors [Lai et al. 2010]. The PipeProbe system works by dropping a tiny wireless sensor capsule into the source of a water pipeline. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatiotemporal analysis of these sensor readings, the proposed algorithm locates all turning points in the pipelines and maps their 3D spatial topology. This study expands upon previous research by developing new sensing techniques that identify variable-diameter pipes and differentiate 90-degree pipe turns from 45-degree pipe bends.

This study presents TriopusNet, a mobile wireless sensor network system for autonomous sensor deployment in pipeline monitoring. TriopusNet works by automatically releasing sensor nodes from a centralized repository located at the source of the water pipeline. During automated deployment, TriopusNet runs a sensor deploy-ment algorithm to determine node placement. While a node is flowing inside the pipeline, it performs placement by extending its mechanical arms to latch itself onto the pipe's inner surface. By continuously releasing nodes into pipes, the TriopusNet system builds a wireless network of interconnected sensor nodes. When a node runs at a low battery level or experiences a fault, the TriopusNet system releases a fresh node from the repository and performs a node replacement algorithm to replace the failed node with the fresh one. We have evaluated the TriopusNet system by creating and collecting real data from an experimental pipeline testbed. Comparing with the non-automated static deployment, TriopusNet is able to use less sensor nodes to cover a sensing area in the pipes while maintaining network connectivity among nodes with high data collection rate. Experimental results also show that TriopusNet can recover from the network disconnection caused by a battery-depleted node and successfully replace the battery-depleted node with a fresh node.

Wi-Fi ingerprint-based localization is currently the most promising approach to building metropolitan-scale localization systems for both indoor and outdoor environments. A Wi-Fi fingerprint localization system makes use of a radio map that contains Wi-Fi signals received at various locations, and uses the map for location estimation. Thus, the accuracy of a Wi-Fi fingerprint localization system greatly depends on the quality of its radio map. This paper explores various properties of a metropolitan radio map that may affect the accuracy of Wi-Fi fingerprint localization systems. In this study, metropolitan-scale radio maps are obtained using war walking and war driving. These maps contain hundreds of thousands of access points and signal samples. A detailed comparison analysis of selected radio map properties reveals how different map properties affect the difference between the positional accuracies of the driving and walking radio maps in Wi-Fi fingerprint-based localization.