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Page 2 Lecture Notes in Computer Science 2865 Edited by G. Goos ...

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100 E.W. Grundke and A.N. Z<strong>in</strong>cir-Heywoodestimate g, we assume that <strong>by</strong> transmitt<strong>in</strong>g one packet a node can broadcast to g-1other nodes. However, the <strong>in</strong>formation will be new to only about half of those nodes.In total we must reach N nodes, so thatorN = g g-12 , (4)g =2NR 2r 12 + 2R r 1. (5)If the range is m<strong>in</strong>imized (that is, R ª 2r 1 ), the rout<strong>in</strong>g overhead is g = (N/4) -1.Clearly this estimate needs to be ref<strong>in</strong>ed to take specific rout<strong>in</strong>g protocols <strong>in</strong>toaccount. The assumption of reach<strong>in</strong>g (g-1)/2 nodes with a s<strong>in</strong>gle packet may be quiteoptimistic, s<strong>in</strong>ce it requires a receiv<strong>in</strong>g node to “know” whether its position justifiesrebroadcast<strong>in</strong>g a given packet (e.g. whether it is at the edge of the previoustransmitter's range <strong>in</strong> the “forward” direction). On the other hand, some protocols[1,2,9,10] effectively comb<strong>in</strong>e multiple events <strong>in</strong>to a s<strong>in</strong>gle packet to improveefficiency.The rout<strong>in</strong>g overhead is Q(N/R 2 ), and is potentially much more serious than theforward<strong>in</strong>g overhead, which is only Q(÷N/R). It is <strong>in</strong>terest<strong>in</strong>g that g is Q(b 2 ).The rout<strong>in</strong>g packet rate gp W cannot exceed the limit b/g established earlier: gp W £b/g, orp W £ b gg = b g-12N g= b2N [1- r 1 2(R+r 1 ) 2 ] ª b2N . (6)Therefore the maximum rate at which a node can generate l<strong>in</strong>k events is Q(1/N). Itis almost <strong>in</strong>dependent of R because, <strong>in</strong> our model, g is Q(N/R 2 ) while the bandwidthreduction factor, 1/g, is Q(R 2 ).The limit<strong>in</strong>g case p W = b/(gg) is obta<strong>in</strong>ed for a high walk/talk ratio, where theuser data traffic is starved to zero <strong>by</strong> frequent l<strong>in</strong>k events. This sets a fundamentallimit on the product Np W , the network l<strong>in</strong>k event rate. Fortunately, the consequencesare not numerically serious for networks of modest size. For example, if N=100nodes have a bandwidth of 1Mbps each, then each node would have to generatealmost 5 Kbps of l<strong>in</strong>k event packets <strong>in</strong> order to saturate the network. Similarly, if p W= 1 event/second and rout<strong>in</strong>g packets conta<strong>in</strong> 500 bits, then saturation occurs at aboutN=1000.6 Total Traffic and PowerThe comb<strong>in</strong>ed effect of user data traffic and rout<strong>in</strong>g traffic is that each node transmitsbp T + gp W packets per unit time, and the bandwidth constra<strong>in</strong>t for the comb<strong>in</strong>ed traffic

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