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Abstract OpenFlow-compliant commodity switches face challenges in efficiently managing flow rules due to the limited capacity of expensive high-speed memories used to store them. The accumulation of inactive flows can disrupt ongoing communication, necessitating an optimized approach to flow rule timeouts. This paper proposes Delayed Dynamic Timeout (DDT), a Reinforcement Learning-based approach to dynamically adjust flow rule timeouts and enhance the utilization of a switch’s flow table(s) for improved efficiency. Despite the dynamic nature of network traffic, our DDT algorithm leverages advancements in Reinforcement Learning algorithms to adapt and achieve flow-specific optimization objectives. The evaluation results demonstrate that DDT outperforms static timeout values in terms of both flow rule match rate and flow rule activity. By continuously adapting to changing network conditions, DDT showcases the potential of Reinforcement Learning algorithms to effectively optimize flow rule management. This research contributes to the advancement of flow rule optimization techniques and highlights the feasibility of applying Reinforcement Learning in the context of SDN. 

The Earth’s environment is full of reactive chemicals that can cause harm to organisms. One of the most common is hydrogen peroxide, which is produced by several bacteria in concentrations high enough to kill small animals, such as the roundworm Caenorhabditis elegans . Forced to live in close proximity to such perils, C. elegans have evolved defenses to ensure their survival, such as producing enzymes that can break down hydrogen peroxide. However, this battle is compounded by other factors. For instance, rising temperatures can increase the rate at which the hydrogen peroxide produced by bacteria reacts with the molecules and proteins of C. elegans . In 2020, a group of researchers found that roundworms sense these temperature changes through special cells called sensory neurons and use this information to control the generation of enzymes that break down hydrogen peroxide. This suggests that C. elegans may pre-emptively prepare their defenses against hydrogen peroxide in response to higher temperatures so they are better equipped to shield themselves from this harmful chemical. To test this theory, Servello et al. – including some of the authors involved in the 2020 study – exposed C. elegans to a species of bacteria that produces hydrogen peroxide. This revealed that the roundworms were better at dealing with the threat of hydrogen peroxide when growing in warmer temperatures. Experiments done in C. elegans lacking a class of sensory cells, the AFD neurons, showed that these neurons increased the roundworms’ resistance to the chemical when temperatures increase. They do this by repressing the activity of INS-39, a hormone that stops C. elegans from switching on their defense mechanism against peroxides. This is the first example of a multicellular organism preparing its defenses to a chemical after sensing something (such as temperature) that enhances its reactivity. It is possible that other animals may also use this ‘enhancer sensing' strategy to anticipate and shield themselves from hydrogen peroxide and potentially other external threats. 

Previous research has shown that modern Eurasians interbred with their Neanderthal and Denisovan predecessors. We show here that hundreds of thousands of years earlier, the ancestors of Neanderthals and Denisovans interbred with their own Eurasian predecessors—members of a “superarchaic” population that separated from other humans about 2 million years ago. The superarchaic population was large, with an effective size between 20 and 50 thousand individuals. We confirm previous findings that (i) Denisovans also interbred with superarchaics, (ii) Neanderthals and Denisovans separated early in the middle Pleistocene, (iii) their ancestors endured a bottleneck of population size, and (iv) the Neanderthal population was large at first but then declined in size. We provide qualified support for the view that (v) Neanderthals interbred with the ancestors of modern humans.