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The included OPEN DESIRE program for Linux solves up to 40,000 ordinary differential equations and implements exceptionally fast and convenient vector operations A smaller educational 20,000 differential-equations version for Microsoft WindowsTM can be obtained without charge from the author by sending an email to gatmkorn@aolcom The user can run, edit, and modify the example simulations keyed to the figures in this book, plus many other examples Many of our programming principles also apply to simulation programs other than DESIRE 1 introduces our subject with a few programs for small differential-equation models, including a simple guided-missile simulation The remainder of the book presents new material 2 begins with a careful discussion of models that involve sampled-data operations and sampled-data difference equations together with differential equations We model mixed analog digital systems such as simulated digital controllers and systems with limiters and switches At this point, we show that many very useful devices (eg, track-hold circuits, trigger circuits, signal generators, automatic scaling) are neatly and efficiently modeled with simple difference equations Last, but not least, we propose improved techniques for proper numerical integration of switched variables Truly powerful simulation programs need a readable notation for vector and matrix assignments, differential equations, and difference equations 3 introduces a novel vector compiler that produces very fast programs for vector and matrix operations We also demonstrate efficient use of submodels We present examples from control engineering and nuclear-reactor simulation The following chapter then shows how we use vectors to replicate complete models 4 describes practical model replication (vectorization): a single simulation run with a vector model will replace hundreds or thousands of conventional simulation runs We apply the vectorizing compiler introduced in 3 to parameter-influence studies and Monte Carlo simulation of dynamic systems with noise-perturbed parameters and random initial conditions We compare repeated-run and vectorized Monte Carlo studies of a weapon trajectory Our interactive programs produce not just time histories of system variables but also time histories of statistics such as averages, mean squares, and probability estimates We also show explicitly how to estimate probability densities 5 discusses more difficult vectorized Monte Carlo simulations involving time-varying noise, which has to be derived from periodic pseudorandom noise samples Examples include Monte Carlo simulation of a continuous random walk, another trajectory study, and two vectorized control-system simulations An inexpensive 24-GHz personal computer exercised 1000 random-input control-system models in seconds We also describe a new heuristic test for the quality of pseudorandom noise.

Transactions are everywhere and often need to be mapped to software - they can be defined as any workflow that is 'all or nothing', that is, it must all succeed or be returned to its original state (or 'rolled back') There are four very important properties that must be guaranteed by systems that support transactions: atomicity, consistency, isolation, and durability These four properties are generally known better by the 'ACID' acronym: Q Q Atomicity - all the actions that make up a transaction form a logical unit As such they must all complete successfully or the transaction is undone and no actions complete Consistency - the data store used by for the transaction must always be in a consistent state That is, if a transaction fails half way through, the data store must not retain partially modified data Uncommitted changes to the data store must be capable of being rolled back Isolation - the state of the transaction is not available outside itself until it has been successfully completed, so it can execute without interference

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One of the simplifying assumptions we make here is that the data that is required for detecting an attack is not encrypted This is usually the case for routing messages, IP header information, and possibly content of messages If a large portion of the network traf c is encrypted, the IDS s ability to analyze intrusion detection information may be signi cantly limited Note that the traf c can still be collected A potential solution to this problem is to make keys available at IDS nodes that can be used for decrypting the relevant data Distribution of such keys may not always be possible and may potentially introduce additional vulnerabilities into the security scheme Note also as mentioned earlier that, even when traf c is encrypted at a particular layer, the intrusion detection analysis could operate at a different layer We next look at the types of evidence 551 Local Evidence

Q Durability - once the transaction has been completed successfully, the state is stored permanently The EJB specification has declarative support for various modes of transactional management As we mentioned in the previous section, the deployment descriptor tells the container how to manage transactions when methods on a bean are invoked The modes are illustrated in the following table: Transaction Support Mandatory Required NotSupported RequiresNew Supports Never Description The caller must start the transaction before it uses the bean An error occurs if no transaction is available The bean requires a transaction; the container will start one if the caller hasn't already done so The container suspends the caller's transaction before calling the bean The container starts a new transaction for every call, even if there is already a transaction in progress, in which case it will suspend it The container just passes the caller's transaction along If there is no transaction in progress, no new one is created The bean does not participate within a transaction context

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