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On Radio Broadcasting in Random Geometric Graphs

机译:论随机几何图中的广播

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One of the most frequently studied problems in the context of information dissemination in communication networks is the broadcasting problem. In this paper we consider radio broadcasting in random geometric graphs, in which n nodes are placed uniformly at random in [0, n~(1/2)]~2, and there is a (directed) edge from a node u to a node v in the corresponding graph iff the distance between u and v is smaller than the transmission radius assigned to u. Throughout this paper we consider the distributed case, i.e., each node is only aware (apart from n) of its own coordinates and its own transmission radius, and we assume that the transmission radii of the nodes vary according to a power law distribution. First, we consider the model in which any node is assigned a transmission radius r > r_(min) according to a probability density function ρ(r) ~ r~(-α) (more precisely, ρ(r) = (α -1)r_(min)~(α-1)r~(-α)), where α ∈ (1,3) and r_(min) > δ log n~(1/2) with δ being a large constant. For this case, we develop a simple radio broadcasting algorithm which has the running time O(log log n), with high probability, and show that this result is asymptotically optimal. Then, we consider the model in which any node is assigned a transmission radius r > c according to the probability density function ρ(r) = (α - 1)c~(α-1)r~(-α), where α is drawn from the same range as before and c is a constant. Since this graph is usually not strongly connected, we assume that the message which has to be spread to all nodes of the graph is placed initially in one of the nodes of the giant component. We show that there exists a fully distributed randomized algorithm which disseminates the message in O(D(log log n)~2) steps, with high probability, where D denotes the diameter of the giant component of the graph. Our results imply that by setting the transmission radii of the nodes according to a power law distribution, one can design energy efficient radio networks with low average transmission radius, in which broadcasting can be performed exponentially faster than in the (extensively studied) case where all nodes have the same transmission power.
机译:在通信网络中信息传播的背景下,最常研究的问题之一是广播问题。本文考虑随机几何图中的无线电广播,其中n个节点随机均匀地放置在[0,n〜(1/2)]〜2中,并且从节点u到a有一个(定向)边如果u和v之间的距离小于分配给u的传输半径,则对应图中的节点v较小。在整个本文中,我们考虑分布情况,即每个节点仅知道(除n之外)自己的坐标和自己的传输半径,并且我们假设节点的传输半径根据幂律分布而变化。首先,我们考虑一个模型,在该模型中,根据概率密度函数ρ(r)〜r〜(-α)(更准确地说,ρ(r)=(α- 1)r_(min)〜(α-1)r〜(-α)),其中α∈(1,3)和r_(min)>δlog n〜(1/2),其中δ是一个大常数。对于这种情况,我们开发了一种运行时间为O(log log n)的简单无线电广播算法,概率很高,并且证明了该结果是渐近最优的。然后,我们考虑根据概率密度函数ρ(r)=(α-1)c〜(α-1)r〜(-α)为任意节点分配透射半径r> c的模型,其中α从与前面相同的范围绘制,并且c是常数。由于此图通常不是牢固连接的,因此我们假定必须传播到图的所有节点的消息最初放置在巨型组件的一个节点中。我们表明,存在一种完全分布式的随机算法,该算法以O(D(log log n)〜2)个步骤传播消息的可能性很高,其中D表示图的巨型成分的直径。我们的结果表明,通过根据幂律分布设置节点的传输半径,可以设计出具有低平均传输半径的高能效无线电网络,在该网络中,广播的执行速度要比(广泛研究的)情况下以指数方式快节点具有相同的传输功率。

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