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Our focus in this book has been on security in ad hoc networks As discussed earlier, security of a system can be addressed in a multipronged fashion, the three prongs being prevention, detection, and response We started out by considering the approach of prevention in ad hoc networks This was in the form of the problem of key management Following that we explained the problem of secure routing in ad hoc networks In both these cases, we explained the reasons for adopting a different approach in ad hoc networks for solving these problems This is as compared with similar problems in xed networks We then focused on the detection and recovery aspects in the chapters on intrusion detection and policy management The important problem of location discovery in a secure manner was also addressed We would like to point out here that we have only addressed the tip of the iceberg in this book by considering the basic problems Several advanced problems such as secure group communication, secure time synchronization, secure MAC protocols, interplay of security and performance, trust establishment, management, privacy and so on have not been addressed in this book There are many open problems still in all these areas In addition, we have also not considered in detail mechanisms based on the use of advanced cryptographic primitives such as secret sharing, threshold cryptography, and identity-based systems The basic security problems in MANETs have also been explained in the context of ad hoc and sensor networks Another important application of MANETs which will impact the commercial world is expected to be in the area of vehicular networks We expect this to be a very important future research area Such networks have been garnering a lot of interest recently and are expected to be the subject of increasing attention in the future These networks that allow communication between vehicles as well as between vehicles and the infrastructure are mainly intended to improve traf c safety It is believed that nearly 50 percent of the nearly 43,000 deaths that occur annually on US highways are caused by roadway departure and intersection incidents Similar numbers are also reported for the number of people killed in Europe (http://europaeuint/comm/transport/care/) The annual costs associated with traf c accidents in the United States, including hospital bills and property damage, have been estimated to total about US$1 trillion [172] The number of automobiles in the world is also increasing very rapidly and is disproportionate, especially in some of the developed countries For example, there are about 240 million cars in the United States for a population of about 300 million22 The numbers for Europe are 230 and 740 million, respectively, while for Japan they are 73.

The body of the message is retrieved into a hash table and a message is displayed The synchronized call returns the control to the main thread

DESIRE uses double-precision (64-bit) floating-point arithmetic and accepts command scripts and model descriptions in a readable mathematical notation such as

As the WebLogic server uses a relational database for persistency, some special tables have to be created to store the messages This has already been done within the script setDB cmd provided and executed in 2 In this script a call is made to the program supplied by WebLogic called utils Schema As the Troops are using Oracle, the command line to use is:

C:\jdkl3\bin\java utilsSchema jdbc:weblogicroracle \ weblogicjdbcociDriver \ -s %DBSERVER% -u %DBUSER% -p %DBPASS% -verbose \c:\weblogic\classes\weblogic\jms\ddl\jms_oracleddl

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Command scripts can include operating-system calls, shell scripts, and calls to other computer programs DESIRE s command-script language is itself a general-purpose mathematical language and handles vectors, matrices, and even complex numbers (eg, for frequency-response and root-locus plots) [9] Programs are entered and edited in editor windows (Fig 1-1) Each program begins with an experiment-protocol script that is interpreted much like an advanced Basic dialect When the experiment-protocol script encounters a drun statement, a built-in runtime compiler automatically compiles a DYNAMIC program segment listing model equations The state-equationsolving simulation run then executes at once and produces solution displays in bright color Very fast compilation (typically under 50 ms) simplifies interactive modeling Experimenters can immediately observe results of programmed or screen-edited models and experiment-protocol changes One can enter and edit different models in multiple editor windows and run these models in turn to compare results (Fig 1-1) Runtime displays show solution time histories and error messages during rather than after each simulation run, so that you can save time by aborting undesirable runs before they complete The experiment-protocol script starting each DESIRE program defines an experiment Subsequent DYNAMIC program segments define models used in the experiment and specify runtime input/output requests An experiment protocol can call multiple DYNAMIC segments with different models, different versions of the same model, and/or different input/output operations

In the weblogic properties file, aJDBC connection pool is defined for JMS use, as well as the queue for the orders:

Security for Wireless Ad Hoc Networks, by Farooq Anjum and Petros Mouchtaris Copyright # 2007 John Wiley & Sons, Inc

HOW A SIMULATION RUN WORKS 1-6 Sampling the DYNAMIC Segment Variables When drun calls a simulation run, the program initializes input/output operations requested by the DYNAMIC program segment The independent variable t (simulation time) and the differential-equation state variables start with initial values assigned by the experiment protocol2 A first pass through the DYNAMIC-segment code [Eq (1-1)] produces initial values of the defined

You can work with JTA when you develop bean-managed persistence entity beans Most of the time, however, you won't need to worry about programming explicit transactions with JTA, as that work is done through the JDBC and EJB APIs, handled by the container, and configured by the application deployment descriptor This way you can focus on the design of the transaction rather than its implementation

Java Naming and Directory Interface (JNDI)

Unspecified initial values of unsubscripted differential-equation state variables conveniently default to 0

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