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The satellite signals travel distances of 20, 000 26, 000km to reach users near the surface of Earth Typical scenarios are illustrated in Figure 85 A satellite P1 is near zenith with respect to the user A second satellite P2 is near the horizon of the user The atmosphere of Earth is the roughly 1000km wide layer of gases surrounding the planet The gure is not to scale in the sense that the distance from the surface of Earth to the outer edge of the atmosphere (ie, the dotted line) should be 5% of the length of the v1 vector The gure illustrates several points that will be important in the discussion of this section First, the length of the path of the signal through the atmosphere is clearly dependent on the satellite elevation angle The minimum exposure to the atmosphere is for a satellite at zenith This issue is addressed by obliquity or slant factors that are functions of the elevation angle Second, the e ect of the ionosphere is dependent on the path through the atmosphere which depends on both the satellite and user locations The gure shows an asterisk at the midpoint of the portion of each path that is through the ionosphere This point is called the ionospheric pierce point The projection of this point onto the Earth surface can be far from the user location, especially for satellites at low elevation When ionospheric models are used, the models are computed at an ionospheric pierce point Along the portion of the GPS signal path above the Earth atmosphere, the signal travels through a vacuum with speed c = 299792458 108 m s Within the Earth atmosphere, the surrounding medium a ects both the speed and path of signal propagation; however, the e ect on the signal path is much less signi cant than the e ect of the decreased speed of travel v The ratio of c to v is the refractive index c = v.

2:

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Figure 85: Simpli ed illustration of GPS signal propagation to Earth The gure is not to scale The speed v and refractive index are not constants; instead, they vary with the properties of the surrounding medium When the refractive index is a function of the frequency f of the signal, then the medium is called dispersive For the modeling of GPS atmospheric delays, it is su cient to divide the atmosphere into two layers, the troposphere and the ionosphere, where the troposphere is non-dispersive and the ionosphere is dispersive Each of these layers is discussed in one of the next two sections, after the derivation of eqns (858-859) Let the path of propagation from the satellite antenna to the user antenna be denoted by (l) where l is the distance along the path The time1 of-travel from the satellite to the user is ts = (l) v(l) dl Representing r as = S + I + T where S is the portion of the path through space, I is the portion of the path through the ionosphere, and T is the portion of the path through the troposphere, the time-of-travel can be expressed as ts = r

S (l)

Up to this point in the discussion of RAC, we have been looking at the architecture of RAC as if the cluster were supporting a single database In fact, RAC is frequently used as a consolidation platform, supporting many databases and instances Once you start supporting multiple databases on a RAC architecture, you may find that you want to allocate the computing resources to appropriately serve the different uses of the database or even modify those allocations, depending on a variety of factors This section will describe some of the RAC-centric ways to accomplish this task

1 dl + v(l)

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You can see the maximum pro t represented in the expiration line between the two strike prices and decreasing pro ts on each side of the market The dashed line, representing halfway between expiration and inception, and the dotted line, representing no time value decay, show clearly that the trade could quickly go against your position and increase in value The strangle strategy has unlimited risk on the call side of the trade, and risk that is limited only by the underlying asset trading to zero on the put side of the equation

To a connecting session, a RAC database appears as a single, monolithic database This key feature is what allows existing applications to take advantage of RAC without modification But the underlying implementation of RAC involves physically separate servers, and each session will be connected to only one of those servers How does RAC decide which instance to assign to an incoming connection request When RAC was introduced with Oracle 9 i, the software determined the connection target by the CPU utilization of the different member instances A new connection was assigned to the instance running on the server with the lowest level of CPU utilization This type of connection assignment did provide more efficient usage of the overall RAC cluster than a random allocation, but the end result was balancing the load for the overall cluster The process assumed that the entire RAC database was being used equally by all instances As larger clusters went into production, and as users started implementing RAC to consolidate multiple databases on a single cluster, this single-minded approach was not flexible enough to allocate computing resources appropriately Enter services

1 dl + v(l)

T (l)

Upgrading existing CPUs Scaling up the platform by working with the hardware vendor to upgrade current system boards or adding/ activating more CPUs where the machine has spare capacity Buying a bigger machine The newer machine is likely to be relatively more expensive than adding CPUs to a current platform These fork-lift upgrades can be expensive, especially as the new machines are normally sized for growth, and hence there can be a lot of initial capacity that is not used

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