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The object requests that we introduced in Part II all involve a client and a server In 7, we give up all these assumptions and discuss how non-synchronous requests, anonymous requests, and requests between a client and multiple server objects can be achieved In 8, we will discuss how clients can contain the object references of servers, which then enable further communication We will discuss naming and trading services, two principles for locating objects In 9, we will see how the lifecycle of distributed objects can be managed We discuss how the creation of objects on a particular machine can be requested, we see how objects can migrate across the network from one host to another and we review deletion of distributed objects Distributed objects may be deactivated by the middleware when they have been idle for some period.

Since the number of unknowns is greater than the number of equations, Eqs. (2.5.16) cannot be solved exactly. One way is to use the method of unconstrained multivariable optimization to solve the equations. 2.5.6 The Program IPCSGV

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In this chapter, we will introduce three very simple FLOPS programs. The rst, numbers.fps, tests whether one number is less than, equal to, or greater than another. The .fps suf x to the program name, number.fps, tells us that this is a sequential FLOPS program. Next we compare two programs for adding a column of numbers, one written as a sequential and the other as a parallel program. Remember the general sequence of major program sections. First, we have the data declarations. Next, there are the rules. Then there are the commands to create initial data for the program run; last, we have a run command to start the actual program run. In complex FLOPS programs, this sequence may be more complicated; for example, a rule can be written that will automatically create other rules. We will not deal with this ability in this chapter.

HSUPA speci cation work started after the successful nalization of the rst release of the high-speed downlink packet access (HSDPA) speci cations for 3GPP Release 5 in mid-2002. HSDPA had enhanced downlink capabilities but the uplink capabilities did not match the HSDPA downlink. Thus, work on improving uplink performance started in 3GPP. The obvious choices were to investigate the techniques used for HSDPA and, if possible, adopt them for the uplink as well. The concept of HSUPA was born and in the course of 3 years the concept materialized into speci cations. HSUPA is not a standalone feature, but uses most of the basic features of the WCDMA Release 99 in order to work. Cell selection and synchronization, random access, basic mobility procedures, etc., are needed and remain unchanged with HSUPA operation. The only change is a new way of delivering user data from the user equipment (UE) to the Node B, all other parts of the speci cations remain untouched. For example,

If those objects maintain an internal state, that state will have to be saved onto some persistent storage In 10, we review the principles of object persistence and discuss how persistence services assist server object programmers in storing and restoring distributed object states We present in 11 how more than one object request can be clustered into a distributed object transaction, which is either executed completely or not at all Moreover, the requests within a transaction are executed in isolation from any concurrent transaction and once a transaction is completed durability of the transaction results are guaranteed Finally, object security services help application developers and administrators to prevent non-authorized use of objects and the leakage of information included in object requests We discuss the principles underlying security services that provide authentication, access control, auditing and non-repudiation in 12..

feedforward ANN, where the information presented to the ANN travels from the input layer to the output layer following the direction of the arrows (i.e., from left to right). No loop or feedback occurs in the same layer. The recurrent ANNs are different from the feedforward ANNs because they consist of loops or feedbacks. Recurrent (or feedback) networks. The inputs can travel in both directions; loop is allowed. Figure B.3 depicts a simple recurrent ANN that has a loop in the connections. Before using an ANN, it needs to be trained. In the training phase, the weights are adjusted using some gradient-based algorithms or prede ned learning rules. After training the ANN successfully, it can be used for problem solving.

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