资源和查询感知,基于点对点的多属性资源发现

H. M. N. Dilum Bandara, A. Jayasumana
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引用次数: 3

摘要

分布式、多属性资源发现(RD)是协作式点对点(P2P)、网格和云计算的基本要求。我们提出了一种高效且负载均衡的基于p2p的多属性RD解决方案,该方案由五个启发式算法组成,可以独立地和分布式地执行。第一种启发式算法在环状覆盖层中保持最小节点数,从而降低了解析范围查询的成本。第二种和第三种启发式算法通过将键转移到邻居和在现有邻居不足时添加新邻居来动态平衡键和查询负载。最后两种启发式方法,即碎片化和复制,形成与覆盖环正交的节点团,以动态平衡高度倾斜的键和查询负载,同时降低查询成本。通过按上述顺序应用这些启发式方法,可以开发出更好地响应现实世界资源和查询特征的RD解决方案。使用真实工作负载进行模拟以证明其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resource and query aware, peer-to-peer-based multi-attribute Resource Discovery
Distributed, multi-attribute Resource Discovery (RD) is a fundamental requirement in collaborative Peer-to-Peer (P2P), grid, and cloud computing. We present an efficient and load balanced, P2P-based multi-attribute RD solution that consists of five heuristics, which can be executed independently and distributedly. First heuristic maintains a minimum number of nodes in a ring-like overlay consequently reducing the cost of resolving range queries. Second and third heuristics dynamically balance the key and query load by transferring keys to neighbors and by adding new neighbors when existing ones are insufficient. Last two heuristics, namely fragmentation and replication, form cliques of nodes that are placed orthogonal to the overlay ring to dynamically balance the highly skewed key and query loads while reducing the query cost. By applying these heuristics in the presented order, a RD solution that better responds to real-world resource and query characteristics is developed. Simulations using real workloads are used to demonstrate its efficacy.
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