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000099987 0247_ $$2doi$$a10.1109/TNET.2006.886311
000099987 02470 $$2ISI$$a000243041200001
000099987 037__ $$aARTICLE 000099987 245__$$aThe Random Trip Model: Stability, Stationary Regime, and Perfect Simulation The Random Trip Model: Stability, Stationary Regime, and Perfect Simulation
000099987 269__ $$a2006 000099987 260__$$c2006
000099987 336__ $$aJournal Articles 000099987 520__$$aWe define "random trip", a generic mobility model for random, independent node motions, which contains as special cases: the random waypoint on convex or nonconvex domains, random walk on torus, billiards, city section, space graph, intercity and other models. We show that, for this model, a necessary and sufficient condition for a time-stationary regime to exist is that the mean trip duration (sampled at trip endpoints) is finite. When this holds, we show that the distribution of node mobility state converges to the time-stationary distribution, starting from the origin of an arbitrary trip. For the special case of random waypoint, we provide for the first time a proof and a sufficient and necessary condition of the existence of a stationary regime, thus closing a long standing issue. We show that random walk on torus and billiards belong to the random trip class of models, and establish that the time-limit distribution of node location for these two models is uniform, for any initial distribution, even in cases where the speed vector does not have circular symmetry. Using Palm calculus, we establish properties of the time-stationary regime, when the condition for its existence holds. We provide an algorithm to sample the simulation state from a time-stationary distribution at time 0 ("perfect simulation"), without computing geometric constants. For random waypoint on the sphere, random walk on torus and billiards, we show that, in the time-stationary regime, the node location is uniform. Our perfect sampling algorithm is implemented to use with ns-2, and is available to download from http://ica1www.epfl.ch/RandomTrip
000099987 6531_ $$aMobility models 000099987 6531_$$arandom waypoint
000099987 6531_ $$asimulation 000099987 700__$$0241098$$g105633$$aLe Boudec, Jean-Yves
000099987 700__ $$aVojnovic, Milan$$g122205$$0244027 000099987 773__$$j14$$tIEEE/ACM Transactions on Networking$$k6$$q1153-1166 000099987 8564_$$uhttps://infoscience.epfl.ch/record/99987/files/TR-2006-26.pdf$$zn/a$$s1249881
000099987 909C0 $$xUS00024$$0252614$$pLCA 000099987 909C0$$pLCA2$$xU10427$$0252453
000099987 909CO $$qGLOBAL_SET$$pIC$$particle$$ooai:infoscience.tind.io:99987
000099987 937__ $$aLCA-ARTICLE-2007-004 000099987 973__$$rREVIEWED$$sPUBLISHED$$aEPFL
000099987 980__ aARTICLE