57 research outputs found
Fault-Tolerant Earliest-Deadline-First Scheduling Algorithm ∗
No full textThe general approach to fault tolerance in uniprocessor systems is to maintain enough time redundancy in the schedule so that any task instance can be re-executed in presence of faults during the execution. In this paper a scheme is presented to add enough and efficient time redundancy to the Earliest-Deadline-First (EDF) scheduling policy for periodic real-time tasks. This scheme can be used to tolerate transient faults during the execution of tasks. We describe a recovery scheme which can be used to re-execute tasks in the event of transient faults and discuss conditions that must be met by any such recovery scheme. For performance evaluation of this idea a tool is developed. Keywords: Time-redundancy, real-time scheduling, fault-tolerance, uniprocessor embedded systems, earliestdeadline-first. 1
A Four-StepTechnique forTackling DDoS Attacks
No full textAbstractThis paper proposes a novel feedback-based control technique that tackles distributed denial of service (DDoS) attacks in four consecutive phases. While protection routers close to the server control inbound traffc rate andkeeps the server alive (phase 1), the server negotiate with upstream routers close to traffc sources to install leaky-buckets for its IP address. The negotiation continues until a defense router on each traffc link accepts the request (phase 2). Next, the server through a feedback-control process adjusts size of leaky-buckets until inbound traffc locates in a desired range (phase 3). Then through a fingerprint test, the server detects which port interfaces of defense routers purely carry good traffc and subsequently asks corresponding defense routers to remove the leaky-bucket limitations for those port interfaces. Additionally, the server amends size of leaky-buckets for the defense routers proportional to amount of good traffc that each one carries (phase 4). Simulation-based results shows that our technique effectively, defenses a victim server against various DDoS attacks such that in most cases more than 90% of good inbound traffc reaches the server while the DDoS attack has been controlled as well
FOSeL: Filtering by helping an Overlay Secure Layer to Mitigate DoS Attacks
No full textDenial of service (DoS) attacks are major threat against availability in the Internet. A large number of countermeasure techniques try to detect attack and then filter out DoS attack packets. Unfortunately these techniques that filter DoS traffic by looking at known attack patterns or statistical anomalies in the traffic patterns can be defeated by changing the attack patterns and masking the anomalies that are sought by the filter. Hence, detecting DoS traffic is one of the main challenges for filtering techniques. Furthermore techniques that drop any malicious packet need to process the packet and processing is time-consuming. This paper addresses how an efficient and good filter can be designed by helping an overlay network layer to mitigate DoS attacks. Fosel (Filtering by helping an Overlay Security Layer) filter is independent from DoS attack types, so we do not worry about the changing attack patterns. Furthermore it reduces processing time noticeably. Through simulation this paper shows by employing Fosel filter, DoS attacks have a negligible chance to saturate the target by malicious packets. Our simulation demonstrates that Fosel architecture reduces the probability of successful attack to minuscule levels. Furthermore Fosel is between 10% and 50% faster than SOS (Secure Overlay Services) [8] architecture to drop malicious packets based on attack rate. © 2008 IEEE.status: Publishe
A dependable architecture to mitigate distributed denial of service attacks on network-based control systems
No full textQ‐scheduler: A temperature and energy‐aware deep Q‐learning technique to schedule tasks in real‐time multiprocessor embedded systems
No full textAbstract Reducing energy consumption under processors' temperature constraints has recently become a pressing issue in real‐time multiprocessor systems on chips (MPSoCs). The high temperature of processors affects the power and reliability of the MPSoC. Low energy consumption is necessary for real‐time embedded systems, as most of them are portable devices. Efficient task mapping on processors has a significant impact on reducing energy consumption and the thermal profile of processors. Several state‐of‐the‐art techniques have recently been proposed for this issue. This paper proposes Q‐scheduler, a novel technique based on the deep Q‐learning technology, to dispatch tasks between processors in a real‐time MPSoC. Thousands of simulated tasks train Q‐scheduler offline to reduce the system's power consumption under temperature constraints of processors. The trained Q‐scheduler dispatches real tasks in a real‐time MPSoC online while also being trained regularly online. Q‐scheduler dispatches multiple tasks in the system simultaneously with a single process; the effectiveness of this ability is significant, especially in a harmonic real‐time system. Experimental results illustrate that Q‐scheduler reduces energy consumption and temperature of processors on average by 15% and 10%, respectively, compared to previous state‐of‐the‐art techniques
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