Random interval graphs
نویسنده
چکیده
We consider models for random interval graphs that are based on stochastic service systems, with vertices corresponding to customers and edges corresponding to pairs of customers that are in the system simultaneously. The number N of vertices in a connected component thus corresponds to the number of customers arriving during a busy period, while the size K of the largest clique (which for interval graphs is equal to the chromatic number) corresponds to the maximum number of customers in the system during a busy period. We obtain the following results for both the M=D=1 and the M=M=1 models, with arrival rate per mean service time. The expected number of vertices is e , and the distribution of the N=e tends to an exponential distribution with mean 1 as tends to innnity. This implies that log N is very strongly concentrated about ? (where is Euler's constant), with variance just 2 =6. The size K of the largest clique is very strongly concentrated about ee. Thus the ratio K= log N is strongly concentrated about e, in contrast with the situation for random graphs generated by unbiased coin ips, where K= log N is very strongly concentrated about 2= log 2.
منابع مشابه
Threshold dominating cliques in random graphs and interval routing
The existence of (shortest-path) interval routing schemes for random graphs that use at most one interval label per edge is an open problem posed in [8]. In this paper, we show that for any random graph G(n, p) with edge probability p > 0.765, there exists an interval routing scheme that uses at most one label per edge and has an additive stretch 1. In doing so, we provide an interesting constr...
متن کاملTenacity and some other Parameters of Interval Graphs can be computed in polynomial time
In general, computation of graph vulnerability parameters is NP-complete. In past, some algorithms were introduced to prove that computation of toughness, scattering number, integrity and weighted integrity parameters of interval graphs are polynomial. In this paper, two different vulnerability parameters of graphs, tenacity and rupture degree are defined. In general, computing the tenacity o...
متن کاملTitle Scale Free Interval Graphs
Scale free graphs have attracted attention by their non-uniform structure that can be used as a model for various social and physical networks. In this paper, we propose a natural and simple random model for generating scale free interval graphs. The model generates a set of intervals randomly under a certain distribution, which defines a random interval graph. The main advantage of the model i...
متن کاملOptimal Parallel Algorithms for Cut Vertices, Bridges, and Hamiltonian Path in Bounded Interval Tolerance Graphs
We present parallel algorithms to nd cut vertices, bridges, and Hamiltonian Path in bounded interval tolerance graphs. For a graph with n vertices, the algorithms require O(logn) time and use O(n) processors to run on Concurrent Read Exclusive Write Parallel RAM (CREW PRAM) model of computation. Our approach transforms the original graph problem to a problem in computational geometry. The total...
متن کاملAn Improved Interval Routing Scheme for Almost All Networks Based on Dominating Cliques
Motivated by the peer-to-peer content sharing systems in large-scale networks, we will study interval routing schemes in ErdösRényi random graphs. C. Gavoille and D. Peleg [13] posed an open question of whether almost all networks support a shortest-path interval routing scheme with 1 interval. In this paper, we answer this question partially by proving that in almost all networks, there is an ...
متن کاملIntersecting random graphs and networks with multiple adjacency constraints: A simple example
When studying networks using random graph models, one is sometimes faced with situations where the notion of adjacency between nodes reflects multiple constraints. Traditional random graph models are insufficient to handle such situations. A simple idea to account for multiple constraints consists in taking the intersection of random graphs. In this paper we initiate the study of random graphs ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Random Struct. Algorithms
دوره 12 شماره
صفحات -
تاریخ انتشار 1998