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Majid Nabi

Publications and source records attributed to Majid Nabi.

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SbDN: Source-based TSN-Grade Deterministic Networking using Commodity Switches

Deterministic networking is essential for safety-critical applications in automotive, industrial, and aerospace systems, where bounded end-to-end latency must be guaranteed for time-critical traffic. Time-Sensitive Networking (TSN) provides the mechanisms to achieve such guarantees, but its deployment requires expensive TSN-capable switches at every hop and complex per-switch configuration that hinders runtime reconfiguration. This paper presents SbDN, a Multi-Agent Source-based architecture that achieves TSN-grade determinism using commodity Ethernet switches. SbDN moves all scheduling intelligence to a centralized controller composed of three cooperating agents and enforces the computed configurations exclusively at the source endpoints, leaving switches as simple forwarding elements. We propose two methods: Temporal Network Partitioning (TNP), which provides strict temporal isolation on pure FIFO switches, and Traffic Prioritization (TP), which leverages strict-priority queuing at switches to enable work-conserving best-effort traffic. Both methods are formally proven to guarantee that all admitted time-critical flows meet their end-to-end deadlines. Evaluation across 40 benchmark configurations on two topologies shows that TNP and TP achieve 100\% admission of time-critical traffic in every scenario, with scheduling times in the low-millisecond range suitable for safe runtime reconfiguration. Compared to a standard TSN baseline, SbDN delivers superior time-critical latency at a fraction of the switch infrastructure cost, while offering competitive best-effort throughput through the choice between the two methods.

cs.NI

V-TSN: A Software-Defined TSN Overlay for General-Purpose Networks

Time-Sensitive Networking (TSN) extends Ethernet with deterministic communication for time-critical applications such as industrial automation, in-vehicle networks, and cyber-physical systems. However, realizing TSN behavior without dedicated hardware is difficult. During design and validation, offline simulation cannot run application software at real-time speed when costly specialized TSN hardware is not (yet) available. At deployment time, many systems run on general-purpose and cloud networks with no native TSN support, where provisioning full TSN hardware is unnecessary or impractical for applications that tolerate relaxed timing. In this paper, we introduce Virtual Time-Sensitive Networking (V-TSN), a software-defined overlay that realizes gPTP-based synchronization and TSN traffic shaping over general-purpose, non-deterministic networks without specialized hardware. V-TSN runs in real time alongside the unmodified application stack, serving both as a development-time emulation tool and as a cost-efficient deployment option where relaxed timing is acceptable. In a cloud-based deployment, V-TSN achieves an average clock offset below 200 microseconds, it isolates time-critical traffic through a virtual Time-Aware Shaper (TAS), and it enforces per-class bandwidth reservations through a virtual Credit-Based Shaper (CBS).

cs.NI

Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of coverage enhancement features of NB-IoT in NS-3, an end-to-end network simulator. The resource allocation and link adaptation in NS-3 are modified to comply with the new features of NB-IoT. Using the developed simulation framework, the influence of the new features on network reliability and latency is evaluated. Furthermore, an optimal hybrid link adaptation strategy based on all three features is proposed. To achieve this, we formulate an optimization problem that has an objective function based on latency, and constraint based on the Signal to Noise Ratio (SNR). Then, we propose several algorithms to minimize latency and compare them with respect to accuracy and speed. The best hybrid solution is chosen and implemented in the NS-3 simulator by which the latency formulation is verified. The numerical results show that the proposed optimization algorithm for hybrid link adaptation is eight times faster than the exhaustive search approach and yields similar latency.

cs.NI