假設系統中有N個節點。每個節點各具有一組屬性。這些屬性可能隨著時間而改變。在這樣的系統中，我們希望能回答哪些節點的屬性落在某一個範圍內、或是哪些節點的屬性和所下的查詢值相近，這種以屬性為基礎的查詢。今天如果在點對點系統(Peer-to-peer System)當中要解決這樣的問題，通常會採取結構化點對點系統(Structured Peer-to-peer System)的方式，在節點間建立一個分散式的雜湊表(Distributed Hash Table，DHT)，將屬性值儲存於雜湊表當中。但很不幸地由於DHT是以Hash為基礎的解法，這使得它難以回答像是Range query和kNN (k-nearest neighbor) query這類的查詢。因此在這篇論文中，我們主張應該更專注在節點的屬性上，利用節點間的連結來呈現屬性上的關係。所以我們提出了以屬性為基礎的疊蓋式網路(Attribute-based Overlay Network，AON)，利用AON來對節點持續改變的屬性作索引的工作。在AON當中，兩個屬性相近的節點在疊蓋式網路結構中會處於鄰近的地方。由於這樣的結構能夠保留相近屬性之間的相鄰關係，因此AON能夠有效地支援像Range query或kNN query這類的查詢。在本篇論文當中，我們著重於AON是否適合處理點對點系統中以屬性為基礎的查詢，並且在不同的屬性改變頻率及節點進出頻率下，將AON和以DHT為基礎的系統在效能以及維護成本上相比較。實驗模擬的結果顯示：AON在大多數的情況下表現得比以DHT為基礎的系統來得更好。

Consider a system in which there are N nodes. Each node is characterized by a set of attributes. The attribute values may change along time. The problem is to answer queries which look for nodes with attributes satisfying criteria such as range of values or similarity. In peer-to-peer (P2P) systems, this problem is often solved by storing the attribute values in a distributed hash table supported by a structured P2P system. Unfortunately, the hash-based solution makes it difficult to answer queries such as range and k-nearest neighbor queries. In this study, we propose to concentrate on the attributes of the peers and use peer interconnection to exploit their relationship. The result is an attribute-based overlay network (AON) among the peers to index the continuously changing peer attributes. With AON, two peers with similar attribute values will be close to each other in the overlay. By preserving the attribute relationship of peers in the interconnection, AON can support range queries and k-nearest neighbor queries efficiently. In this thesis, we focus primarily on the feasibility of using AON to support attribute-based queries in P2P systems, by contrasting it with DHT-based overlay in terms of performance and cost under different levels of churns and attribute-changing rates. The simulation results show that AON outperforms DHT-based systems in most cases.

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