{"title":"Analytical bounds on broadcast with hitch-hiking in wireless ad-hoc networks","authors":"G. Călinescu","doi":"10.1109/MAHSS.2005.1542813","DOIUrl":null,"url":null,"abstract":"Recently, there have been papers indicating that the maximal ratio combiner device can result in energy savings in wireless ad hoc networks by using hitch-hiking. We study the min-energy broadcast with hitch-hiking problem, an idealized version of broadcast using hitch-hiking, a problem studied experimentally in the INFOCOM 2004 paper of Agarwal et al. min-energy broadcast with hitch-hiking captures the maximum savings one can achieve in broadcasting using maximal ratio combiners. We show that the optimum of the classical min-energy broadcast problem is at most O(log2 n) times the optimum of min-energy broadcast with hitch-hiking, where n is the number of nodes in the networks. We show that this bound is tight up to a constant. In the special case when the nodes are on a line and the power requirement for node u to reach node v is d(u,v)K where d(u,v) the Euclidean distance between u and v and K is the signal attenuation exponent, which is assumed to be in between 2 and 5, we show that the optimum of the min-energy broadcast problem is at most a constant times optimum of min-energy broadcast with hitch-hiking. We also show that min-energy broadcast with hitch-hiking is NP-Hard, and present approximation algorithms. A formal definition of min-energy broadcast with hitch-hiking is given below. The input consists of a complete directed graph G = (V, E) with power requirement function c: E rarr R +, and a source s isin V. The output consists of a permutation T = < v1, v2,...., vn > of V with v1 = s and power assignment p(v) of every vertex v. For every 1 les i < j les n, define q(viv j) = p(vi)/c(vivj). An output is feasible if for every j > 1 we have Sigman i=1 p(vi)","PeriodicalId":268267,"journal":{"name":"IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MAHSS.2005.1542813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, there have been papers indicating that the maximal ratio combiner device can result in energy savings in wireless ad hoc networks by using hitch-hiking. We study the min-energy broadcast with hitch-hiking problem, an idealized version of broadcast using hitch-hiking, a problem studied experimentally in the INFOCOM 2004 paper of Agarwal et al. min-energy broadcast with hitch-hiking captures the maximum savings one can achieve in broadcasting using maximal ratio combiners. We show that the optimum of the classical min-energy broadcast problem is at most O(log2 n) times the optimum of min-energy broadcast with hitch-hiking, where n is the number of nodes in the networks. We show that this bound is tight up to a constant. In the special case when the nodes are on a line and the power requirement for node u to reach node v is d(u,v)K where d(u,v) the Euclidean distance between u and v and K is the signal attenuation exponent, which is assumed to be in between 2 and 5, we show that the optimum of the min-energy broadcast problem is at most a constant times optimum of min-energy broadcast with hitch-hiking. We also show that min-energy broadcast with hitch-hiking is NP-Hard, and present approximation algorithms. A formal definition of min-energy broadcast with hitch-hiking is given below. The input consists of a complete directed graph G = (V, E) with power requirement function c: E rarr R +, and a source s isin V. The output consists of a permutation T = < v1, v2,...., vn > of V with v1 = s and power assignment p(v) of every vertex v. For every 1 les i < j les n, define q(viv j) = p(vi)/c(vivj). An output is feasible if for every j > 1 we have Sigman i=1 p(vi)