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that can be set at convenient places. The middle tier consists of DataMules, which are mobile nodes (whose mobility pattern is not known) that can communicate with sensors and access points. DataMules have large storage capacity and renewable power. As Data Mules move, they collect data from sensors and forward these data to the access points. The bottom tier consists of sensors which are randomly distributed across a region. To save energy, work performed by the sensors is minimal. DataMules are assumed to be capable of short-range wireless communication and can exchange data from a nearby sensor access point they encounter as a result of their motion (the movements of the DataMules are not predictable). Thus DataMules can pick up data from sensors when in close range, buffer it, and drop off the data to wired access points when in proximity. The main advantage of the three-tier approach is the potential of large power savings that sensors can have because communication now takes place over a short range. Simple analytical models are presented to study the scaling of system characteristics as the system parameters, number of sensors, or number of DataMules change. Numerical results provide some relationship between the buffer requirements at the sensors (and at the DataMules) and the number of sensors (and the number of DataMules), respectively. It is observed that the change in the buffer capacity on each sensor should be greater than the number DataMules so that the same success rate can be maintained.

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// swap() does not swap the value of the arguments! void swap( int v1, int v2 ) { int tmp = v2; v2 = v1; v1 = tmp; }

swap() exchanges the local copies of its arguments The variables that represent swap() 's arguments are unchanged This is illustrated in the following program, which calls swap():

#include <iostream> void swap( int, int ); int main() { int i = 10; int j = 20; cout "Before swap():\ti: " i "\tj: " j endl; swap( i, j ); cout "After swap():\ti: " i "\tj: " j endl; return 0; }

file:///F|/WinDDK/resources/CPPPrimer/c++primerhtm (319 / 1065) [2001-3-29 11:32:06]

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8.3.5 Coding-Based Approaches To cope with wireless channel loss, erasure coding and network coding techniques have recently been proposed for wireless ad hoc networks and DTNs. The basic idea of erasure coding is to encode an original message into a large number of coding blocks. Suppose the original message contains k blocks; using erasure coding, the message is encoded into n (n > k) blocks such that if k or more of the n blocks are received, the original message can be successfully decoded. Here, r = n/k is called the replication factor and determines the level of redundancy. Network coding comes from information theory and can be applied in routing to further improve system throughput. More on network coding will be described later. To extend the work in reference 16, Jain et al. [38] assume the probability, Pi , that the transmission over link i is successful (independent of other transmissions) is known. Given that the replication factor is r, they study the following allocation problem: to determine an optimal fraction, xi , of the erasure code blocks that should be sent over path i, such that the probability of successful reception is maximized. The formal de nition of the problem is given below. De nition. Consider a node s sending a message of size m to node d, and let there be n feasible paths from s to d. For each path i, let Vi be the volume of the path, and let Si be a random variable that represents the fraction of data successfully transmitted on path i. Assume that an erasure coding algorithm can be used (with a replication factor r) to generate b = (mr)/l code blocks of size l such that any m/l code blocks can be used to decode the message.

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The name of a template parameter cannot be used as the name for a class member declared within the class template definition:

u t deg(v)

template <class Type> class QueueItem { public: // private: // error: member cannot have the same name as // the template parameter Type typedef double Type; Type item; QueueItem *next; };

The name of a template parameter can be introduced only once within the template parameter list The following, for example, is flagged at compile-time as an error:

// error: illegal reuse of template parameter named Type template <class Type, class Type> class container;

Multicast protocols suffer from the so-called feedback implosion that occurs when multiple receivers ask for retransmission of data to the server Multiple retransmissions are due to the inevitably different loss patterns that affect different receiver nodes Clearly, it is not affordable for sending nodes to manage multiple retransmissions of different data packets toward different receivers If the sender generates a digital fountain instead, receiver nodes only have to receive an amount of data packets that corresponds to the exact number of original data packets Indeed, any set of packets of size equal to the number of original data packets is appropriate Hence, whenever receivers miss some packets, it is suf cient that they wait for the subsequent redundant packets to come No retransmissions are needed toward different receivers, and no feedback channel is strictly necessary.

The name of a template parameter can be reused across class template declarations or definitions:

// ok: reuse of the name `Type' across templates template <class Type> class QueueItem; template <class Type> class Queue;

The names of the template parameters do not need to be the same across forward declarations and the definition of the class template The following three declarations of QueueItem, for example, all refer to the same class template:

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