Packet classification by multi-level cutting of the classification space

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs) are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Adaptability in organisms and artifacts: A multi level perspective on adaptive processes

Abstract Adaptability to changing circumstances is a key feature of living creatures. Understanding such adaptive processes is central to developing successful autonomous artifacts. In this paper two perspectives are brought to bear on the issue of adaptability. The first is a short term perspective which looks at adaptability in terms of the interactions between the agent and the environment. The second perspective involves a hierarchical evolutionary model which seeks to identify higher-order forms of adaptability based on the concept of adaptive meta-constructs. Task orientated and agent-centered models of adaptive processes in artifacts are considered from these two perspectives. The former isrepresented by the fitness function approach found in evolutionary learning, and the latter in terms of the concepts of empowerment and homeokinesis found in models derived from the self-organizing systems approach. A meta-construct approach to adaptability based on the identification of higher level meta-metrics is also outlined. 2009 Published by Elsevier B.V.

High density mangrove plantation enhances surface accretion, surface elevation change, and tree survival in coastal areas susceptible to sea-level rise

Survival, growth, above ground biomass accumulation, soil surface elevation dynamics and nitrogen accumulation in accreted sediments were studied in experimental treatments planted with four different densities (6.96, 3.26, 1.93 and 0.95 seedlings m-2) of the mangrove Rhizophora mucronata in Puttalam Lagoon, Sri Lanka. Measurements were taken over a period of 1171 days and were compared with those from unplanted controls. Trees at the lowest density showed significantly reduced survival, whilst measures of individual tree growth did not differ significantly among treatments. Rates of surface sediment accretion (means ± S.E.) were 13.0 (±1.3), 10.5 (±0.9), 8.4 (±0.3), 6.9 (±0.5) and 5.7 (±0.3) mm yr-1 at planting densities of 6.96, 3.26, 1.93, 0.95, and 0 (unplanted control) seedlings m-2, respectively, showing highly significant differences among treatments. Mean (± S.E.) rates of surface elevation change were much lower than rates of accretion at 2.8 (±0.2), 1.6 (±0.1), 1.1 (±0.2), 0.6 (±0.2) and -0.3 (±0.1) mm yr-1 for 6.96, 3.26, 1.93, 0.95, and 0 seedlings m-2, respectively. All planted treatments appeared to accumulate greater nitrogen concentrations in the sediment compared to the unplanted control, and suggests one potential causal mechanism for the facilitatory effects observed; high densities of plants potentially contribute to the accretion of greater amounts of nutrient rich sediment. While this potential process needs further study, this study demonstrated how higher densities of mangroves enhance rates of sediment accretion and surface elevation, processes that may be crucial in mangrove ecosystem adaptation to sea level rise. There was no evidence that increasing plant density evoked a trade-off with growth and survival of the planted trees. Rather facilitatory effects enhanced survival at high densities, suggesting that local land managers may be able to take advantage of plantation densities to help mitigate sea-level rise effects by encouraging positive soil surface elevation increment, and perhaps even greater nutrient retention to promote mangrove growth and ameliorate nearshore eutrophication in tropical island environments.

Confounds in pictorial sets: The role of complexity and familiarity in basic-level picture processing

Complexity is conventionally defined as the level of detail or intricacy contained within a picture. The study of complexity has received relatively little attention-in part, because of the absence of an acceptable metric. Traditionally, normative ratings of complexity have been based on human judgments. However, this study demonstrates that published norms for visual complexity are biased. Familiarity and learning influence the subjective complexity scores for nonsense shapes, with a significant training x familiarity interaction [F(1,52) = 17.53, p <.05]. Several image-processing techniques were explored as alternative measures of picture and image complexity. A perimeter detection measure correlates strongly with human judgments of the complexity of line drawings of real-world objects and nonsense shapes and captures some of the processes important in judgments of subjective complexity, while removing the bias due to familiarity effects.