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This method is referred to as fixed assignment (FA), as each node has a fixed set of channels available for its assignment (see for example [9, 35, 25, 28]) A type of labeling that gives regular, periodic graph labelings for lattices was defined in [39], and called labeling by arithmetic progression Such a labeling is a linear, modular function of the coordinates of each node Definition 531 A labeling f of a t-dimensional lattice is a labeling by arithmetic progression if there exist nonnegative integers a1, , at and n such that for each node v with coordinates (m1, , mt), f (v) = a1m1 + + at mt mod n The parameter n is called the cyclic span of the labeling Given integers c1, c2, , where c1 c2 , such a labeling satisfies the constraints c1, c2, .

Each Msg instance also has a message topography type that corresponds to one of the communication topography types (Ad Hoc, Broadcast, or Sequential, as we discussed in Section 15312) The primary difference between these topography types is demonstrated when we consider how they handle Msg object instances that specify more than one destination If an Ad Hoc Msg has multiple Destinations, then the framework will create a separate Ad Hoc message for each destination and send each message as a separate operation By contrast, a Broadcast Msg that has multiple Destinations will send one message to each group of Destinations that are capable of seeing the message (we will discuss this further later) We can consider sending Broadcast messages to be similar to sending a single letter to each household in a family.

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if for all pairs of nodes u, v at graph distance i in the lattice, | f (u) f (v)| max{ci, n ci} A labeling by arithmetic progression is considered optimal for a given set of constraints if its cyclic span is as small as possible Given f, a labeling by arithmetic progression, f (m1, m2) denotes the value of the labeling at the node with coordinates (m1, m2) Labelings by arithmetic progression are easy to define and with Algorithm A they can be used to find channel assignment algorithms Moreover, their regularity may be helpful in designing borrowing methods that will give better channel assignments for nonuniform weights 531 Bipartite Graphs For bipartite graphs with constraints c0 and c1, Algorithm A gives optimal channel assignments if c0 2c1 If c0 < 2c1, bipartite graphs can be colored optimally using Algorithm B, given by Gerke [14].

A merchant can easily implement checks to try and verify the consumer s address, but a merchant cannot build anything that can yield the same check to the bank records. Merchants who really want to verify this information further can perform a manual review by calling the issuing bank to verify the data or doing a reverse lookup.

For example, we might send one letter to the house where our Aunt and Uncle live and another copy of the same letter to the house where both our Grandparents live Similarly, we can consider sending Ad Hoc messages to be similar to sending a separate copy of the letter to each family member (even when all the family members live in the same house) In this case, we would send one copy of the letter to our Aunt, another copy of the letter to our Uncle, another copy to our Grandmother, and yet another copy to our Grandfather, even if we know that some of them live in the same house and most of them talk to each other on a regular basis.

Like Algorithm A, this algorithm uses base coloring of the nodes, but if a node has demand greater than any of its neighbors, it initially gets some channels that are 2c1 apart (which allows interspersing the channels of its neighbors), while the later channels are c0 apart Algorithm B (for bipartite graphs when c1 c0 2c1) Let G = (V, E, c0, c1) be a constrained bipartite graph of n nodes, where c1 c0 w an arbitrary weight vector Assume a base coloring f : V {0,1} is given For each node v, define p(v) = max{w(u) | uv E or u = v} 2c1, and.

(See Sections 5.2 and .5.3 for some of its properties.) Real matrix: A matrix is called real if all its elements are real numbers, Real polynomial matrix: A polynomial matrix is callf'd real if all its elements are real polynomials, (See Section 11.3.)

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