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題名 Maximizing Submodular Set Function with Connectivity Constraint: Theory and Application to Networks
作者 郭桐惟
Kuo, Tung-Wei;Lin, Kate Ching-Ju;Tsai, Ming-Jer
貢獻者 資科系
關鍵詞 Approximation algorithm, network deployment, submodular set function
日期 2015-04
上傳時間 29-Jun-2017 09:44:23 (UTC+8)
摘要 In this paper, we investigate the wireless network deployment problem, which seeks the best deployment of a given limited number of wireless routers. We find that many goals for network deployment, such as maximizing the number of covered users, the size of the coverage area, or the total throughput of the network, can be modeled with a submodular set function. Specifically, given a set of routers, the goal is to find a set of locations S, each of which is equipped with a router, such that S maximizes a predefined submodular set function. However, this deployment problem is more difficult than the traditional maximum submodular set function problem, e.g., the maximum coverage problem, because it requires all the deployed routers to form a connected network. In addition, deploying a router in different locations might consume different costs. To address these challenges, this paper introduces two approximation algorithms, one for homogeneous deployment cost scenarios and the other for heterogeneous deployment cost scenarios. Our simulations, using synthetic data and real traces of census in Taipei, Taiwan, show that the proposed algorithms achieve better performances than other heuristics.
關聯 IEEE/ACM Transactions on Networking, 23(2), 533-546
資料類型 article
DOI http://dx.doi.org/10.1109/TNET.2014.2301816
dc.contributor 資科系
dc.creator (作者) 郭桐惟zh_TW
dc.creator (作者) Kuo, Tung-Wei;Lin, Kate Ching-Ju;Tsai, Ming-Jer
dc.date (日期) 2015-04
dc.date.accessioned 29-Jun-2017 09:44:23 (UTC+8)-
dc.date.available 29-Jun-2017 09:44:23 (UTC+8)-
dc.date.issued (上傳時間) 29-Jun-2017 09:44:23 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/110582-
dc.description.abstract (摘要) In this paper, we investigate the wireless network deployment problem, which seeks the best deployment of a given limited number of wireless routers. We find that many goals for network deployment, such as maximizing the number of covered users, the size of the coverage area, or the total throughput of the network, can be modeled with a submodular set function. Specifically, given a set of routers, the goal is to find a set of locations S, each of which is equipped with a router, such that S maximizes a predefined submodular set function. However, this deployment problem is more difficult than the traditional maximum submodular set function problem, e.g., the maximum coverage problem, because it requires all the deployed routers to form a connected network. In addition, deploying a router in different locations might consume different costs. To address these challenges, this paper introduces two approximation algorithms, one for homogeneous deployment cost scenarios and the other for heterogeneous deployment cost scenarios. Our simulations, using synthetic data and real traces of census in Taipei, Taiwan, show that the proposed algorithms achieve better performances than other heuristics.
dc.format.extent 3531322 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) IEEE/ACM Transactions on Networking, 23(2), 533-546
dc.subject (關鍵詞) Approximation algorithm, network deployment, submodular set function
dc.title (題名) Maximizing Submodular Set Function with Connectivity Constraint: Theory and Application to Networks
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1109/TNET.2014.2301816
dc.doi.uri (DOI) http://dx.doi.org/10.1109/TNET.2014.2301816