Time-Sensitive Networking (TSN) is widely used in Advanced Driver Assistance Systems (ADAS) owing to its high reliability, low latency, and deterministic transmission. ADAS utilizes automotive TSN switches to connect various sensors and actuators, facilitating deterministic communication for different data flows. The Time-Aware Shaper (TAS) in automotive TSN switch uses a pre-configured Gate Control List (GCL) for deterministic transmission of TSN flows. The GCL specifies the states of all gates (queues) and periodic transmission times, including Time-Triggered (TT), Audio Video Bridging (AVB), and Best-Effort (BE) queues. The widely used methods involve generating a GCL configuration file offline before scheduling, known as statically configured GCL. However, there are non-periodic but safety-critical Event-Triggered (ET) flows in ADAS, such as traffic incidents or alarms. ET flows are triggered by emergency events and require a timely response. In other words, ET flows should be transmitted immediately after TT flows. The statically configured GCL cannot provide timely scheduling for ET flows, as the time required for its reconfiguration is significantly longer than the time needed to configure ET flows. In this study, we propose a Dynamically Configurable GCL (DC-GCL) to adapt to the transmission of ET flows in automotive TSN switch for ADAS. We design a dynamic ET flow transmission solution in DC-GCL without affecting TT flows transmission. DC-GCL defines the ET flow as the second highest priority, allowing it to preempt the transmission of AVB and BE queues. We design a dynamic GCL scheduling window to calculate the queue and transmission time of ET flows. We further present a dynamic GCL configuration algorithm to initialize the GCL and enable dynamic GCL modification. We build a TSN-based ADAS prototype platform consisting of automotive-grade development boards and deploy DC-GCL in this platform. Experimental results show that DC-GCL significantly improves the scalability of GCL in different ADAS scenarios. Compared with statically configured GCL, DC-GCL reduces the end-to-end delay of TT flows by 40.9%-53.6% and ET flows by 81.1% -82.3%.

The microcomputer cluster is a group of connected microcomputers that work together to perform as a single system. Unlike high-performance computer clusters, microcomputer clusters are designed to provide reliable and efficient services for safety-critical embedded systems, which usually require low SWaP (Size, Weight, and Power) because of the high stability and cost control requirements. Considering that safety-critical systems have strict real-time constraints (i.e., deadline constraints) and resource constraints, each microcomputer usually needs to run a Real-Time Operating System (RTOS) instead of Linux to achieve precise scheduling and control, and a high-speed real-time network such as Time-Triggered Ethernet (TTE) is required for intra-cluster communication. In microcomputer clusters, a load imbalance between microcomputers usually leads to system instability, and a lightweight application distribution framework automatically migrates applications among microcomputers, thereby breaking resource isolation and improving resource utilization. However, mainstream application distribution frameworks, such as Kubernetes (K8s), MicroK8s, and K3s, can be applied neither to RTOS nor to TTE. In this study, we design a lightweight application distribution framework with automated and real-time computing and communication (ARC2). ARC2 monitors the microcomputer cluster resource state in real-time and introduces a resource hierarchical pooling method to utilize cluster resources flexibly. It employs TTE for application distribution combined with a real-time scheduling strategy, achieving low end-to-end latency and load balancing. It simplifies the existing application distribution framework and introduces a low-complexity cluster management logic to achieve low resource overhead. We conduct experimental evaluations on a heterogeneous platform. The results show that: (1) the load imbalance is reduced by at least 59.81% compared to the original system; (2) the deviation in real-time monitoring traffic is reduced by an average of 56.7 ms, with the application distribution success rate reaching 100% and an average distribution time of 393.0 ms; and (3) the CPU, memory, and bandwidth overhead are 9%, 3 MB, and 0.104 Mb/s, respectively.

5G mobile communication techniques are widely applied in ubiquitous communication scenarios (e.g., smart navigation and smart transportation), which require time synchronization among mobile devices. However, the built-in time synchronization software of Android phones presents large time offsets with hundreds of milliseconds (ms), and the mainstream time synchronization techniques have specific limitations: 1) the Network Time Protocol (NTP) has too large offset to meet the real-time information interaction among mobile devices; 2) the Linux Precision Time Protocol (LinuxPTP) exists hardware dependence and cannot be implemented on Android and 5G networks; and 3) the Global Navigation Satellite System (GNSS) requires installing a hardware receiver on each mobile device. In this study, we develop a Mobile Precision Time Protocol (MobiPTP), which is hardware-independent and compatible with various network types, including Wide-Area Network (WAN), Local-Area Network (LAN), wired and wireless networks. The main challenges include signal strength instability and uplink-downlink asymmetry. We propose a dynamic time synchronization algorithm and an asymmetry compensation strategy to overcome these challenges. Regardless of high-speed mobile or crowded conditions in 5G networks, MobiPTP demonstrates an average offset of 9 ms, outperforming the NTP-based open-source software Chrony (about 30 ms). MobiPTP has been successfully deployed in multiple real-world ubiquitous communication scenarios and always demonstrates much lower offsets than Chrony.

The network architecture that Time-Sensitive Networking (TSN) is used as the backbone network and the Controller Area Network (CAN) serves as the intra-domain network is considered as the CAN-TSN interconnection network architecture, which has gained considerable attention within industrial embedded networks, such as spacecraft, intelligent automobiles, and factory automation. The architecture employs the CAN-TSN gateway as a central hub for transmitting and managing a significant volume of communications between the CAN domains and TSN. However, the CAN-TSN gateway faces a high congestion challenge due to the rapid growth in data volume, making it difficult to effectively support different time planning mechanisms provided by TSN. In this article, we propose a two-stage mixed-criticality traffic scheduler. The scheduler in the first stage adopts a Message Optimization Algorithm (MOA) to aggregate multiple CAN messages into a single TSN message (including the aggregation of critical and non-critical CAN messages), which reduces the number of CAN messages requiring transmission. In the second stage, the scheduler proposes a Message Scheduling Optimization Algorithm (MSOA) to schedule critical TSN messages. This algorithm reassembles all the critical CAN messages (within the un-schedulable TSN messages) to generate new TSN messages for rescheduling. Experimental results show that our proposed scheduler effectively improves the acceptance ratio of critical and non-critical CAN messages and outperforms the state-of-the-art message scheduling method in terms of acceptance ratio while improving the bandwidth utilization and the number of schedule table entries. We further construct a hardware platform to evaluate the performance of MSOA. The consistency between practical results and theoretical results shows the effectiveness of MSOA.

With the advancement of intelligence and networked automotive, the domain-centralized architecture, which employs time sensitive networking (TSN) as the inter-domain backbone network and control area network with flexible data rate (CAN-FD) as the intra-domain network, has garnered significant attention. However, cross-domain end-to-end communication involves multiple components, and significant disparities between TSN and CAN-FD render response time analysis within domain-centralized architecture for mixed-critical traffic exceptionally complex. In this paper, we develop a cross-domain with TSN and CAN-FD end-to-end response time evaluation tool, which analyzes the response time of mixed-critical traffic under different design options segment by segment. We specifically analyze the waiting times of different messages in the domain control unit when faced with the design options of one-to-one and multi-to-one conversion of CAN-FD and TSN frames. The proposed evaluation tool can be easily extended to different design options to support more application scenarios. Theoretical computational analysis and real hardware measurements show the effectiveness of our tool.

Distributed storage systems introduce redundancy to protect data from node failures. After a storage node fails, the lost data should be regenerated at a replacement storage node as soon as possible to maintain the same level of redundancy. Minimizing such a regeneration time is critical to the reliability of distributed storage systems. Existing work commits to reduce the regeneration time by either minimizing the regenerating traffic, or adjusting the regenerating traffic patterns, whereas nodes participating the regeneration are generally assumed to be given beforehand. However, real-world distributed storage systems usually exhibit heterogeneous link capacities, and the regeneration time is highly related to the selection of the participating nodes. In this paper, we consider the minimization of the regeneration time by selecting the participating nodes in heterogeneous networks. We propose optimal node selection algorithms respectively for two cases: 1) the newcomer is not given, 2) both the newcomer and the providers are not given. Analysis shows that the optimal regeneration time can be achieved in each case. We then consider the effect of flexible amount of data blocks from each provider on the regeneration time, and apply this observation to enhance our schemes. Experiment results show that our node selection schemes can significantly reduce the regeneration time, especially in practical networks with heterogeneous link capacities, compared with the scheme based on random node selection.

Data access is an important and challenging issue in Mobile Social Networks (MSNs), and cooperative caching is an effective technique to improve the access performance. Most of current research efforts in data access of MSNs focus on improving the access performance while neglecting the fair treatment of users. Because fairness is considered as a major incentive for peer-to-peer service especially in infrastructure-less wireless networks, in this paper we propose a novel approach to support fairness aware cooperative caching scheme in MSNs. Through capturing close friend set of each node, we cache data prior at nodes which are overlapped by most nodes' close friend sets. Then we derive the optimal cooperative scheme by using the minimum dominating set, which is an NP-Complete problem, and we design a heuristic algorithm to handle it. Experimental results show that our scheme can effectively improve data access fairness as well as maintain nearly the same access performance compared to existing cooperative caching schemes.

Distributed storage systems provide large-scale reliable data storage services by spreading redundancy across a large group of storage nodes. In such big systems, node failures take place on a regular basis. When a node fails or leaves the system, to maintain the same level of redundancy, it is expected to regenerate the redundant data at a replacement node as soon as possible. Previous studies aim to minimize the network traffic in the regeneration process, but in practical networks, where link capacities vary in a wide range, minimizing network traffic does not always mean minimizing regeneration time. Considering the heterogeneous link capacities, Li et al. proposed a tree-structured regeneration scheme, called RCTREE, to bypass the low-capacitated link encountered in direct transmissions. However, we find that RCTREE may rapidly lose data integrity after several regenerations. In this paper, we reconsider the problem of minimizing regeneration time in networks with heterogeneous link capacities. We derive the minimum amount of data to be transmitted through each link to preserve data integrity. We prove that building an optimal regeneration tree is NP-complete and propose a heuristic algorithm for a near-optimal solution. We further introduce a flexible regeneration scheme, which allows providers to generate different amount of coded data. Simulation results show that the flexible tree-structured regeneration scheme can reduce the regeneration time significantly.