Linux kernels are being widely deployed in embedded applications, such as increasingly automated vehicles and robots, due to their robust ecosystem. Security modules have been developed to enhance the integrity of Linux kernels, a critical system component. However, these modules consume substantial computational resources, making them unsuitable for embedded domains. We introduce LightRIM, a lightweight method to measure the Linux kernel’s integrity during runtime, ideal for resource-limited embedded applications. We focus on major attack types and extract objects for monitoring. Our approach includes a two-stage hashing process and an event-triggered measurement algorithm tied to the security value. To mitigate Time-of-Check-to-Time-of-Use (TOCTOU) attacks, we introduce a heuristic algorithm that maximizes the attack detection rate within CPU usage constraint and randomizes the measurement intervals. Experimental results indicate that LightRIM incurs less than 0.7% performance overhead while providing extensive attack coverage.

Chiplets promise customized design for different sets of applications with heterogeneity, where there are various kinds of resources to manage. Examples are GPUs, NPUs, and CPUs for computation of AI and general tasks, memory, communication, as well as logical resources such as I/Os. There can be strong contention in access of resources across chiplets by applications, which sometimes have discrepant requirements. Resolving such contention is critical to fully exploit the resources on heterogeneous chiplets and satisfy the needs of dynamic application workloads. This talk will discuss a set of methods that manage these resources during the design phase as well as at runtime, which should interact with the architecture exploration and contribute to the entire chiplets systems design altogether.

The increasing computational demand promotes the application of parallel tasks with complex execution dependencies in industrial applications. The Directed Acyclic Graph (DAG) task model is widely applied with dedicated scheduling algorithms to understand and manage the execution of such systems. In order to validate the effectiveness of different DAG scheduling algorithms, DAG generators are often applied to produce synthesized DAGs for performance evaluation. However, existing DAG generators either fail to provide sufficient topology coverage or suffer from severe scalability issues, leading to biased and incomplete evaluation results. This paper proposes a novel DAG generator that provides full topology coverage under the given DAG structural parameters while eliminating isomorphic DAGs as well as redundant edges in each DAG. In addition, a verification method is constructed that enables topology coverage, isomorphic DAG identification, and constraint satisfaction of the generated DAGs. The experimental results show that compared to existing generators, the proposed DAG generator achieves full topology coverage and significantly reduces the number of DAGs being produced. The DAG generator proposed in this work provides a complete solution for synthesised DAG generation, enabling fair and comprehensive evaluation of DAG systems.

A class-aware routing scheme is proposed in this paper for OBS networks providing offset-time-based differentiated services (DiffServ). To unravel the structure of the routing problem, mathematical programming formulations are utilized. An optimization model for two-class OBS networks is presented and studied in particular. The objective is to minimize the burst loss probability over the entire network for both traffic classes. The effectiveness of the routing model is evaluated via illustrative examples based on programming techniques. Numerical results show that compared with traditional class-oblivious routing schemes, class-aware routing further reduces the burst loss probability of multiple classes especially when the network load is light or moderate.

This paper investigates backup reprovisioning technique to mitigate the impact of double near-simultaneous link failure scenarios. First, a refined model is introduced for accurate identification of vulnerable connections after the failure of the first link. Then, an improved approach termed Successive Backup Reprovisioning (SBR), is developed for online backup reprovisioning to further reduce the number of affected connections when no extra capacities are added to the network for reprovisioning purpose. Complexity analysis and simulation results show that SBR has advantages in tradeoff between capacity efficiency and execution speed

Traditional optical transport networks are gradually evolving to intelligent optical networks. Intelligent optical networks can support fast bandwidth provision, so they need a faster reconfiguration algorithm. In this paper, we present an algorithm based on simulated annealing for solving the joint logical topology design and routing problem for WDM optical networks. We introduce new mechanism to accelerate the running speed of the simulated annealing algorithm. Computational experiments show that our modified simulated annealing algorithm can obtain a solution very close to that of the classical simulated annealing algorithm, but the running speed of the modified algorithm is much faster.