Using Ternary Content Addressable Memories (TCAMs) to perform high-speed packet classification has become the de facto standard in industry because TCAMs facilitate constant time classification by comparing packet fields against ternary encoded rules in parallel. Despite their high speed, TCAMs have limitations of small capacity, large power consumption, and relatively slow access times.One reason TCAM-based packet classifiers are so large is the multiplicative effect inherent in representing d-dimensional classifiers in TCAMs. To address the multiplicative effect, we propose the TCAM SPliT architecture, where a d-dimensional classifier is split into k ≥ 2 low dimensional classifiers, each of which is stored on its own small TCAM. A d-dimensional lookup is split into k low dimensional, pipelined lookups with one lookup on each chip. Our experimental results with real-life classifiers show that TCAM SPliT reduces classifier size by 84% using only two small TCAM chips; this increases to 93% if we use five small TCAM chips.

Abstract-Regular expression (RE) matching is a core component of deep packet inspection in modern networking and security devices. In this paper, we propose the first hardware-based RE matching approach that uses Ternary Content Addressable Memory (TCAM), which is available as off-the-shelf chips and has been widely deployed in modern networking devices for tasks such as packet classification. We propose three novel techniques to reduce TCAM space and improve RE matching speed: transition sharing, table consolidation, and variable striding. We tested our techniques on 8 real-world RE sets, and our results show that small TCAMs can be used to store large Deterministic Finite Automata (DFAs) and achieve potentially high RE matching throughput. For space, we can store each of the corresponding 8 DFAs with 25,000 states in a 0.59Mb TCAM chip. Using a different TCAM encoding scheme that facilitates processing multiple characters per transition, we can achieve potential RE matching throughput of 10 to 19 Gbps for each of the 8 DFAs using only a single 2.36 Mb TCAM chip.

Abstract-Network intrusion detection and prevention systems commonly use regular expression (RE) signatures to represent individual security threats. While the corresponding DFA for any one RE is typically small, the DFA that corresponds to the entire set of REs is usually too large to be constructed or deployed. To address this issue, a variety of alternative automata implementations that compress the size of the final automaton have been proposed such as XFA and D 2 FA. The resulting final automata are typically much smaller than the corresponding DFA. However, the previously proposed automata construction algorithms do suffer from some drawbacks. First, most employ a "Union then Minimize" framework where the automata for each RE are first joined before minimization occurs. This leads to an expensive NFA to DFA subset construction on a relatively large NFA. Second, most construct the corresponding large DFA as an intermediate step. In some cases, this DFA is so large that the final automaton cannot be constructed even though the final automaton is small enough to be deployed. In this paper, we propose a "Minimize then Union" framework for constructing compact alternative automata focusing on the D 2 FA. We show that we can construct an almost optimal final D 2 FA with small intermediate parsers. The key to our approach is a space and time efficient routine for merging two compact D 2 FA into a compact D 2 FA. In our experiments, our algorithm runs on average 155 times faster and uses 1500 times less memory than previous algorithms. For example, we are able to construct a D 2 FA with over 80,000,000 states using only 1GB of main memory in only 77 minutes.

Objectives: To compare the effects of thiopentone sodium and propofol as an intravenous anaesthetic agent in modified ECT. Methods: 30 patients of ASA I & II grade were randomly assigned in to two groups. Both groups were premedicated in ususal manner. Patients were induced with inj. thiopentone sodium 3-5mg/kg (Group T) and inj. Propofol 1.5-2mg/kg (group P) according to the groups. Then, Inj. Succinyl choline 0.5-1mg/kg was given. Patients were ventilated with 100% oxygen with bain circuit and mask. Shock was given after putting bite block. Patients were again ventilated till spontaneous respiration after seizures. Results: Propofol is better induction agent as compared to thiopentone sodium in terms of faster induction, better haemodynaemic stability, no significant effect on seizure duration, early recovery without any side effects. Conclusion: Propofol in the dosage of 1.5-2 mg/kg body weight intravenously can be safely used for modified ECT in ASA grade I and II pateints. Fast, smooth induction, better hemodynamics, early smooth recovery, antiemetic property and uncompromised therapeutic outcome makes propofol as an agent of choice for day care procedure. Though there is reduced seizure duration with Propofol as compared to thiopentone, there is no effect on outcome of the therapy or effectiveness of ECT.