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the same channel; hence, standard multiplexing techniques such as TDMA, FDMA, CDMA, and OFDM may not be readily employed For many cooperative schemes, it is assumed that a high level of synchronism can be maintained; if this cannot be done (see Section 144), then considerably lower gains result from noncoherent combining Network Channel Coding In the previous set of scenarios, it was assumed that independent traf c streams would interfere, limiting capacity In network channel coding, the capability of combining information streams as information is redundantly spread over the network is exploited [51].

Figure 13.2. Architectural design of RFSN [2].

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There are two ways in which network coding can improve network capacity [52]: (1) When there is one source to be multicast, store and forward may fail to optimize bandwidth, and (2) when there are two or more independent sources to be transmitted in a network, even for a unicast situation, store and forward relaying may fail to optimize bandwidth Considerable progress has been made on practical schemes for the rst situation [53], but less for the second In some examples, network coding makes the difference between network scalability or not [54] However, in other situations [55] it can be shown that classical routing achieves the same performance as network coding Network Source Coding We have previously addressed network source coding for the classic instances in which data are to be collected in a single communication hop, and now we focus on when it is aggregated across a multihop network.

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The direct reputation, (Rij )D , is updated using the direct observations, that is, the output of the watchdog mechanism. Information Sharing. In RFSN, nodes share their ndings with fellow nodes. However, they are allowed to share only positive information. RFSN gives higher weight to second-hand information from nodes with higher reputation, which is reasonable and fairly novel. The weight assigned by node i to second-hand information from a node k is a function of the reputation of node k maintained by node i. Like many other reputation-and-trust-based systems, RFSN also makes use of the popular Beta distribution model. Information Modeling. Assume node i has established some reputation value, Rij , for node j. Let the two nodes have r + s more interactions with r cooperative and s noncooperative interactions, respectively. The reputation value is now updated as follows.

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In data fusion problems, information from multiple sensors, possibly of different types, is combined to produce a decision variable [56, 57] In classic data fusion problems, reduction of the transmission rate between sensors or fusion points is not considered, but clearly this is an important consideration in sensor networks [1, 58] Remarkably, while obviously suboptimal from the point of view of rate reduction, it may be shown that the decision of a sensor to participate or not in contributing to fusion is suf cient to enable network scalability whenever imperfect delity of source reconstruction is permitted [59] That is, while total network communications capacity increases with the number of nodes, under a delity constraint the amount of information to extract from the network eventually saturates We will explore the consequences of this observation more fully in Section 142.

(13.1)

Treasury bills in your margin account Are services such as real-time quotes, research reports, newsletters, and the like free or is there a charge Can you place orders over the phone or online 24 hours a day, seven days a week How is the firm s support staff when you need them Does the firm even have a customer service department to answer questions you may have regarding your account statements These questions illustrate what I mean by finding out what services a brokerage firm has to offer You may be able to add other needs and questions, but these are some things I think you want to know.

Better energy ef ciency can be achieved by jointly considering coding and routing [60] Here there are two basic choices to make, given that the optimization of network resources (eg, communications energy) is NP hard One can perform a relatively simple form of incremental compression (that is, with all data present at the node where fusion occurs), but then face a dif cult routing optimization problem Alternatively, one can perform (dif cult) joint source coding, but can then route data using simple methods such as shortest path tree (SPT) For lossless compression of discrete sources, it has been shown that Slepian Wolf coding followed by SPT is optimal Either approach can work in small neighborhoods, but becomes impractical over larger regions.

(13.2)

While it has been shown that at high resolution Wyner Ziv coding resembles Slepian Wolf coding [61], there are still many open issues in rate-distortion coding in spite of progress on practical coding methods (eg, 62 66) Reference 67 presents.

(13.3)

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java code 128 reader

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