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SAC (e Determination) 1 Let l L1 St P 2 Compute H E L2 jL1 l 8H 1 l H PrfL2 l H jL1 lg l l 3 Set E E H l Thus, the current traf c level St is normalized and mapped to the index l L1 St , which is then used to calculate the expectation of L2 conditioned on l H ; H The latter l is then nally used to index into a table E H is called the aggressiveness schedule l The intuition behind the aggressiveness schedule E is that if the expected future contention level is low (ie, H close to 1) then it is likely that applying a high level of l aggressiveness will pay off Conversely, if the expected future contention level is high (ie.

, H near 8) then applying a low level of aggressiveness is called for One l schedule that we use is the inverse schedule, E H 1= H : l l Other schedules of interest include the threshold schedule with threshold y P 1; 8 and aggressiveness factor y*, where E y* if H y, and 0 otherwise l Table 181 shows the CondProb table for two runs corresponding to a 1:05 (top) and a 1:95 (bottom) traf c conditions The column containing hl has been omitted and the entries show actual relative frequencies rather than hlH counts for illustrative purposes Clearly, the conditional probability densities are skewed diagonally for a 1:05 traf c, whereas they are roughly invariant for a 1:95 traf c The expected future contention level H E L2 jL1 l and aggressiveness l schedule (inverse) are shown as separate columns.

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CHAPTER SECTIONS: 1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9

For a 1:05 traf c, the expected future contention level E L2 j varies over a wide range, which is a direct consequence of the predictability that is, skewedness present in the correlation structure For a 1:95 traf c, however, E L2 j is fairly `` at,'' indicating that conditioning on the present does not aid signi cantly in predicting the future..

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18.5 18.5.1

In a cracker's world, the next-best thing to breaking in to your computer is locking you out of it After all, if the cracker cannot use your computer, then neither should you! Attacks that prevent someone from using his or her machine are called denial-of-service attacks in the security community Denial of service comes in many guises Attacks may involve consuming all available CPU cycles, allocating every last bit of memory, hogging all possible screen space, or causing a system to hang while it waits for something impossible to happen The one common requirement is that the user being attacked is effectively locked out of his or her machine An effective denial-of-service attack happens so quickly that it's usually impossible to stop it Experiencing such an attack is a sobering event There are many ways to write applets initiating denial-of-service attacks.

We use the LBNL Network Simulator, ns (version 2), as the basis of our simulation environment. ns is an event-driven simulator derived from Keshav's REAL network simulator supporting several avors of TCP and router packet scheduling algorithms. We have modi ed ns in order to model a bottleneck network environment where several concurrent connections are multiplexed over a shared bottleneck link. A UDP-based unreliable transport protocol was added to the existing protocol suite, and our congestion control and predictive control were implemented on top of it. An important feature of the setup is the mechanism whereby self-similar traf c conditions are induced in the network. One possibility is to have a host inject self-

TABLE 18.1 Snapshot of CondProb 10,000 s After Connection Has Been Established (Top, a 1:05; Bottom, a 1:95) L1 1 2 3 4 5 6 7 8 L1 1 2 3 4 5 6 7 8 L2 L2 1 0.667 0.003 0 0 0 0 0 0 1 0.155 0.043 0.023 0.020 0.012 0.017 0.008 0 2 0.333 0.568 0.126 0.035 0.003 0 0 0 2 0.116 0.058 0.049 0.058 0.039 0.058 0.042 0 3 0 0.306 0.468 0.205 0.078 0.012 0.018 0 3 0.155 0.179 0.132 0.135 0.134 0.141 0.126 0.167 4 0 0.093 0.262 0.368 0.296 0.099 0.079 0 4 0.233 0.272 0.306 0.274 0.273 0.243 0.211 0.233 5 0 0.027 0.116 0.305 0.356 0.285 0.245 0.333 5 0.165 0.257 0.273 0.286 0.307 0.325 0.322 0.233 6 0 0.003 0.023 0.077 0.205 0.418 0.443 0 6 0.078 0.128 0.161 0.167 0.183 0.166 0.195 0.300 7 0 0 0.003 0.201 0.060 0.182 0.213 0.500 7 0.087 0.054 0.054 0.055 0.044 0.044 0.088 0.067 8 0 0 0 0 0.002 0.003 0.003 0.167 8 0.097 0.008 0.003 0.004 0.008 0.007 0.008 0 E L2 j 1.3 2.6 3.4 4.2 4.9 5.7 5.8 6.5 E L2 j 3.8 4.3 4.5 4.5 4.6 4.5 4.8 4.8 E 0.769 0.384 0.294 0.238 0.204 0.175 0.172 0.153 E 0.263 0.232 0.222 0.222 0.217 0.222 0.208 0.208

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