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15.1.1.2 Administered Objects The JMS platform contains some concepts (which we will loosely refer to as objects) that the JMS API represents using Java interfaces and classes. Although the speci cation completely de nes the behavior for some of these concepts, there are also some concepts mentioned in the speci cation that are not completely controlled by it. Some of the details controlling these partially de ned objects are left as implementation-dependent and proprietary details. These objects are called administered objects in the speci cation, because they refer to things that need to be administered (de ned, monitored, and managed) by the JMS Provider. Because the speci cation does not de ne all the speci c details for these administered objects, each JMS Provider vendor can choose how to implement those unde ned portions of the objects without any restrictions. This enables a JMS Provider to be implemented on top of an existing messaging system that does not directly conform to the JMS speci cation. Some implementations provide (proprietary, nonstandard) programmatic interfaces for administering these objects while others use (proprietary, nonstandard)



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14331 Localization Algorithm We considered two approaches to engineer an RF-based localization system, based on measurements of received signal strength and connectivity, respectively The rst approach for RF-based localization is to use the measured signal strength of received beacon signals to estimate distance, as in the RADAR system [19], with an outdoor radio signal-propagation model We discarded this approach for several reasons relating to our short-range (10-m) radios First, signal strength at short ranges is subject to unpredictable variation due to fading, multipaths, and interferences It does not therefore correlate directly with distance Moreover, short range does not allow much gain in density of reference points when considering signal strength We have found an idealized radio model useful for predicting bounds on the quality of connectivity-based localization We chose this model because it was simple and easy to reason about mathematically This subsection presents this idealized model.

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of the sequence X n and ask for the probability that it exceeds a certain threshold. Speci cally, nd (to rst order in the exponent) Qn P (X1 , X2 , . . . , Xn ) 1 log >0 . n Q(X1 , X2 , . . . , Xn )

Figure 9-11

To our surprise, this model compares quite well to outdoor radio propagation in uncluttered environments, as we explore in the next subsection We make two assumptions in our idealized model: 1 Perfect spherical radio propagation 2 Identical transmission range (power) for all radios Multiple nodes in the network with overlapping regions of coverage serve as reference points (labeled R1 to Rn ) They are situated at known positions, containing their respective positions (X1 , Y1 ) to (Xn , Yn ), that form a regular mesh and transmit periodic beacon signals every T seconds We assume that neighboring reference points can be synchronized so that their beacon signal transmissions do not overlap in time Furthermore, in any time interval, each of the reference points would have transmitted exactly one beacon signal.

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High Limited Maximum < 4 mm FWHM, in practice 16 mm 1 2 min Maximum 8 10 Moderate Potential for actual CBF; in practice, relative counts Moderate Low High Advanced

Each mobile node listens for a xed time period t and collects all the beacon signals that it receives from various reference points We characterize the information per reference point Ri by a connectivity metric, de ned as: CMi N recv(i, t) 100 N sent(i, t).

12.4.6.2 Layer 1 Interface, Basic Rate. The S/ T interface of the reference model, Figure 12.15 (or layer 1, physical interface), requires a balanced metallic transmission medium (i.e., copper pair) in each direction of transmission (four-wire) capable of supporting 192 kbps. Again, this is the NT interface of the ISDN reference model. Layer 1 provides the following services to layer 2 for ISDN operation:

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