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Wireless typically falls short of wireline performance in one or more of these QoS parameters, sometimes by one or more orders of magnitude. In addition, grade of service (GoS), the probability of connection on the rst attempt, approximates 1.0 very well on wireline networks but falls off sharply on wireless networks when mobile and during periods of high demand. On the other hand, the probability of connecting to a wireline when you are driving your car is zero, while the probability for wireless is much greater than zero, so when viewed from a mobile consumer s perspective, value of connection is much higher than GoS or QoS alone re ects, suggesting a need to model quality of information. 2.2.5.2 Quality of Information (QoI) The <User/> data structure must accurately model the user s speci c and context-sensitive information value system, QoI. Like QoS and GoS, QoI can be de ned. Unlike those metrics, QoI must be de ned in user-centric terms. QoI is the degree to which available information meets the speci c user s speci c needs at a speci c time, place, and situation. A mathematical framework for QoI is QoI = Availability * Quantity * Relevance * Timelines * Validity (2-2) * Accuracy * Detail * Need Item 5 of Figure 2-1, Change data rate, ltering, source, power to optimize type & quality of information (QoI), requires a QoI metric that re ects <User/> goals. QoI is de ned with respect to a speci c <User/> over a nite space time epoch called a <Scene/>, a Subset of Space x Time for a Speci c User: <Scene/> {<User/> {<Space/>} {<Time/>}} (2-3)

March 24 produced 30 pips, March 25 did 131 pips, and March 26 gave 153 On March 30, it had bounced off the line and fallen back 40 pips And going back to that five-minute chart, from April 2, it had hit the support level and then risen back up 20 pips It had never failed to at least bounce enough to give some profit The average move was 120 pips I decided that would be my profit target Figure 164 shows how the Post-it note now read I stuck it on the desk in front of me, intending to keep it there as a reminder for the next day Then I left This was the best I had felt in a long time I was working to support my family And finally, at the very least, I knew that I had discovered the beginnings of a system.

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In a two-dimensional model, the position of A is unambiguously determined as the intersection of three such circles Each circle can be modeled by a quadratic equation, and the intersection point of these circles is theoretically the location of node A The triangulation algorithm discussed in the sequel avoids quadratic equations and uses instead linear equations, which is a problem of lower dif culty that can be solved with linear algebra tools alone This form of triangulation is used by GPS (see references 15 and 16) for their ad hoc positioning system Figure 26 depicts a node u that needs to determine its position The positions of localized neighbors are used The triangulation is an iterative procedure, which starts with an arbitrary estimate ( u , yu ) of the position of node u The estimate is re ned x from one iteration to the next.

Equation 2-3 makes an ontological statement about referents in the real world, not symbols of a logic system. Speci cally, the ontological primitive <User/> refers to the person using the system. Thus, the intersections refer to a subset of physical space and ordinary time along with the person being served. In a programming language, plus in A + B operates on memory locations, not on the literals A and B. So too, <User/> refers to the memory location out there in the real world, everything inside the skin of that person, including his/her thoughts, perceptions, prejudices, and speci cally information needs. Ontological statements in this book express the open set existential potentiality of the real world, not the closed set existentials and universals of symbolic logic. (See Open Sets in the companion CD-ROM for further treatment.) If there is no information connectivity in the <Scene/>, then Availability = 0 = QoI. If the <Self/> connects the <User/> to all (Quantity = 1.0) the required

The iterative procedure is repeated until the change from the previous estimate is below a given threshold Firstly, the following procedure is applied for each localized neighbor v (Figure 26 depicts an example using node.

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