{"title":"面向网络资源公平有效分配的每实体分配特征的多jain公平性指标","authors":"M. Köppen, K. Ohnishi, M. Tsuru","doi":"10.1109/INCoS.2013.161","DOIUrl":null,"url":null,"abstract":"Due to its simplicity and its easy comprehension, Jain's fairness index is still among the most popular measures to compare justness of allocations. However, it was already argued in the original paper that while the way of computing the index is well established, it is not immediately clear to which metric to apply the computation. Thereby, metric stands for a specific choice of a system observable. Here we study the extension of Jain's index to multiple metrics at once. We propose a set of per-entity allocation features to represent justness of an allocation, and to derive corresponding vectors of feature-wise taken Jain's fairness indices. The features give a numerical representation of fulfilling common fairness properties like proportionality, envy-freeness and equity of an allocation. Then, maximizing the smallest index gives an efficient procedure for allocation of goods. We study this procedure for the problem of allocating wireless channels in a multi-user setup and compare the influence of the various feature choices on the efficiency of the solution.","PeriodicalId":353706,"journal":{"name":"2013 5th International Conference on Intelligent Networking and Collaborative Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Multi-Jain Fairness Index of Per-Entity Allocation Features for Fair and Efficient Allocation of Network Resources\",\"authors\":\"M. Köppen, K. Ohnishi, M. Tsuru\",\"doi\":\"10.1109/INCoS.2013.161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to its simplicity and its easy comprehension, Jain's fairness index is still among the most popular measures to compare justness of allocations. However, it was already argued in the original paper that while the way of computing the index is well established, it is not immediately clear to which metric to apply the computation. Thereby, metric stands for a specific choice of a system observable. Here we study the extension of Jain's index to multiple metrics at once. We propose a set of per-entity allocation features to represent justness of an allocation, and to derive corresponding vectors of feature-wise taken Jain's fairness indices. The features give a numerical representation of fulfilling common fairness properties like proportionality, envy-freeness and equity of an allocation. Then, maximizing the smallest index gives an efficient procedure for allocation of goods. We study this procedure for the problem of allocating wireless channels in a multi-user setup and compare the influence of the various feature choices on the efficiency of the solution.\",\"PeriodicalId\":353706,\"journal\":{\"name\":\"2013 5th International Conference on Intelligent Networking and Collaborative Systems\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 5th International Conference on Intelligent Networking and Collaborative Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INCoS.2013.161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Intelligent Networking and Collaborative Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INCoS.2013.161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Jain Fairness Index of Per-Entity Allocation Features for Fair and Efficient Allocation of Network Resources
Due to its simplicity and its easy comprehension, Jain's fairness index is still among the most popular measures to compare justness of allocations. However, it was already argued in the original paper that while the way of computing the index is well established, it is not immediately clear to which metric to apply the computation. Thereby, metric stands for a specific choice of a system observable. Here we study the extension of Jain's index to multiple metrics at once. We propose a set of per-entity allocation features to represent justness of an allocation, and to derive corresponding vectors of feature-wise taken Jain's fairness indices. The features give a numerical representation of fulfilling common fairness properties like proportionality, envy-freeness and equity of an allocation. Then, maximizing the smallest index gives an efficient procedure for allocation of goods. We study this procedure for the problem of allocating wireless channels in a multi-user setup and compare the influence of the various feature choices on the efficiency of the solution.