东南大学学报(自然科学版)
東南大學學報(自然科學版)
동남대학학보(자연과학판)
JOURNAL OF SOUTHEAST UNIVERSITY
2014年
3期
517-521
,共5页
订阅/发布%大数据量内容%数据分发%多节点协同
訂閱/髮佈%大數據量內容%數據分髮%多節點協同
정열/발포%대수거량내용%수거분발%다절점협동
subscribe/publish%bulk content%data distribution%multi-node cooperation
为了提高分布对称体系结构的订阅/发布系统对大数据量内容的分发效率,提出了一种基于订阅节点协同的数据分发方法。首先,利用MD5算法将订阅节点映射到32 bit逻辑地址空间中;然后依据订阅者与发布者间的逻辑距离所处区间,将订阅节点集合划分成独立不相交的桶,为主题数据的转发规划出合理的路径,且该数据分发路径能适应系统的动态变化。基于逻辑距离的桶分割方法确保了数据分发的单向收敛性,限制了分发路径的深度。真实环境中的实验结果表明,基于订阅节点协同的分发方式通过利用订阅节点的资源,降低了对GB级数据量内容进行分发的分发时延,减轻了发布节点的负载,与传统的点对点分发方式相比,数据分发效率得到了显著提高。
為瞭提高分佈對稱體繫結構的訂閱/髮佈繫統對大數據量內容的分髮效率,提齣瞭一種基于訂閱節點協同的數據分髮方法。首先,利用MD5算法將訂閱節點映射到32 bit邏輯地阯空間中;然後依據訂閱者與髮佈者間的邏輯距離所處區間,將訂閱節點集閤劃分成獨立不相交的桶,為主題數據的轉髮規劃齣閤理的路徑,且該數據分髮路徑能適應繫統的動態變化。基于邏輯距離的桶分割方法確保瞭數據分髮的單嚮收斂性,限製瞭分髮路徑的深度。真實環境中的實驗結果錶明,基于訂閱節點協同的分髮方式通過利用訂閱節點的資源,降低瞭對GB級數據量內容進行分髮的分髮時延,減輕瞭髮佈節點的負載,與傳統的點對點分髮方式相比,數據分髮效率得到瞭顯著提高。
위료제고분포대칭체계결구적정열/발포계통대대수거량내용적분발효솔,제출료일충기우정열절점협동적수거분발방법。수선,이용MD5산법장정열절점영사도32 bit라집지지공간중;연후의거정열자여발포자간적라집거리소처구간,장정열절점집합화분성독립불상교적통,위주제수거적전발규화출합리적로경,차해수거분발로경능괄응계통적동태변화。기우라집거리적통분할방법학보료수거분발적단향수렴성,한제료분발로경적심도。진실배경중적실험결과표명,기우정열절점협동적분발방식통과이용정열절점적자원,강저료대GB급수거량내용진행분발적분발시연,감경료발포절점적부재,여전통적점대점분발방식상비,수거분발효솔득도료현저제고。
To improve the distribution efficiency of bulk content in the subscribe/publish system with symmetrical distributed architecture,a new distribution method based on multi-node cooperation is proposed.First,the subscribers are mapped to a 32 bit logical address space by the message-digest al-gorithm 5 (MD5 algorithm).Then,the sets of the subscribers are divided into independent disjoint buckets according to the intervals of the logical distances between the publisher and the subscribers. A proper route for data forwarding,which can adapt to the dynamic changes in the system,is gener-ated.The unidirectional convergence of data distribution and the limited depth of the route are guar-anteed by the bucket partitioning method based on the logical distance.The prototype experimental evaluation results show that the proposed method reduces subscribers' delay and publisher's load for the distribution of bulk content in GB size by exploiting subscribers'resources.This method outper-forms the traditional point-to-point distribution strategy in distribution efficiency.