Optimizing multiple dimensional queries simultaneously in multidimensional databases

Some significant progress related to multidimensional data analysis has been achieved in the past few years, including the design of fast algorithms for computing datacubes, selecting some precomputed group-bys to materialize, and designing efficient storage structures for multidimensional data. However, little work has been carried out on multidimensional query optimization issues. Particularly the response time (or evaluation cost) for answering several related dimensional queries simultaneously is crucial to the OLAP applications. Recently, Zhao et al. first exploited this problem by presenting three heuristic algorithms. In this paper we first consider in detail two cases of the problem in which all the queries are either hash-based star joins or index-based star joins only. In the case of the hash-based star join, we devise a polynomial approximation algorithm which delivers a plan whose evaluation cost is $ O(n^{\epsilon }$) times the optimal, where n is the number of queries and is a fixed constant with . We also present an exponential algorithm which delivers a plan with the optimal evaluation cost. In the case of the index-based star join, we present a heuristic algorithm which delivers a plan whose evaluation cost is n times the optimal, and an exponential algorithm which delivers a plan with the optimal evaluation cost. We then consider a general case in which both hash-based star-join and index-based star-join queries are included. For this case, we give a possible improvement on the work of Zhao et al., based on an analysis of their solutions. We also develop another heuristic and an exact algorithm for the problem. We finally conduct a performance study by implementing our algorithms. The experimental results demonstrate that the solutions delivered for the restricted cases are always within two times of the optimal, which confirms our theoretical upper bounds. Actually these experiments produce much better results than our theoretical estimates. To the best of our knowledge, this is the only development of polynomial algorithms for the first two cases which are able to deliver plans with deterministic performance guarantees in terms of the qualities of the plans generated. The previous approaches including that of [ZDNS98] may generate a feasible plan for the problem in these two cases, but they do not provide any performance guarantee, i.e., the plans generated by their algorithms can be arbitrarily far from the optimal one. Received: July 21, 1998 / Accepted: August 26, 1999     

网孔处理机阵列上最小生成树算法

已知一加权无向图G(V,E),|V|=n.本文基于网孔处理机阵列,运用分而治之策略和数据归约技术给出了一种新的最小生成树算法.此算法需O(n~2/p)时间,使用了O(p)个处理机(1≤p≤n).当p=n时,此算法仅需O(n)时间和O(n)处理机.而目前基于同一计算模型上此问题的最好算法需O(n)时间和O(n~2)个处理机,因而这里给出的算法在使用处理机数目方面改进了O(n)因子.     

Top-k query evaluation in sensor networks under query response time constraint

Top-k query in a wireless sensor network is to find the k sensor nodes with the highest sensing values. To evaluate the top-k query in such an energy-constrained network poses great challenges, due to the unique characteristics imposed on its sensors. Existing solutions for top-k query in the literature mainly focused on energy efficiency but little attention has been paid to the query response time and its effect on the network lifetime. In this paper we address the query response time and its effect on the network lifetime through the study of the top-k query problem in sensor networks with the response time constraint. We aim at finding an energy-efficient routing tree and evaluating top-k queries on the tree such that the network lifetime is significantly prolonged, provided that the query response time constraint is met too. To do so, we first present a cost model of energy consumption for answering top-k queries and introduce the query response time definition. We then propose a novel joint query optimization framework, which consists of finding a routing tree in the network and devising a filter-based evaluation algorithm for top-k query evaluation on the tree. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithms, in terms of the total energy consumption, the maximum energy consumption among nodes, the query response time, and the network lifetime. The experimental results showed that there is a non-trivial tradeoff between the query response time and the network lifetime, and the joint query optimization framework can prolong the network lifetime significantly under a specified query response time constraint.     

Hypercube多处理器上图的最优算法

已知一个无向图G(V,E),|V|=n.本文在SIMD机器-Hype-rcube上提出了计算图的连通分支和最小生成树的两个最优算法.若Hypercu-be由P个处理器组成,则上述两个算法的时间复杂性都是O(n~2/p),1≤p且PlogP≤n.     

如何保证会针委派制的顺利实施

会计委派制作为会计工作深层改革的新生事物,是将所有会计人员根据隶属区域划归到相应的会计机构,会计机构根据企业状况和会计人员情况与企业签订委派合同并委派会计人员,是针对目前大多数企业因产权结构不完善、监督机制不健全而导致会计人员管理失控、国有和集体财产严重流失以及会计信息失真等而建立的一种会计管理模式.     

成分互补熔体温度处理对高硅铝合金的初生硅相组织的影响

本文研究了成分互补熔体温度处理工艺对于含20%Si的高硅铝合金对组织的影响规律,研究表明,该工艺能够对高硅铝合金的初生Si相产生明显的变质效果,经成分互补熔体温度处理工艺处理后,初生Si的晶粒在100min内尺寸可稳定在36μm左右,这表明对高硅铝合金的变质效果具有长效性,是一种简单实用的高硅铝合金变质处理工艺.     

采煤机牵引部耳子断裂分析

通过化学分析、金相检验、力学性能测试和断口分析等方法对ZG25Mn钢制牵引部耳子断裂进行了检验分析,结果表明,含铝量过高是导致牵引部耳子断裂的主要原因.     

Network lifetime maximization for time‐sensitive data gathering in wireless sensor networks with a mobile sink

With the advances of more and more mobile sink deployments (e.g., robots and unmanned aerial vehicles), mobile sinks have been demonstrated to play an important role in the prolongation of network lifetime. In this paper, we consider the network lifetime maximization problem for time‐sensitive data gathering, which requires sensing data to be sent to the sink as soon as possible, subject to several constraints on the mobile sink. Because the mobile sink is powered by petrol or electricity, its maximum travel distance per tour is bounded. The mobile sink's maximum moving distance from its current location to the next must also be bounded to minimize data loss. As building a new routing tree rooted at each new location will incur an overhead on energy consumption, the mobile sink must sojourn at each chosen location at least for a certain amount of time. The problem, thus, is to find an optimal sojourn tour for the mobile sink such that the network lifetime is maximized, which is subject to a set of constraints on the mobile sink: its maximum travel distance, the maximum distance of each movement, and the minimum sojourn time at each sojourn location. In this paper, we first formulate this novel multiple‐constrained optimization problem as the distance‐constrained mobile sink problem for time‐sensitive data gathering. We then devise a novel heuristic for it. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the performance of the proposed algorithm is very promising, and the solution obtained is fractional of the optimal one. Copyright © 2011 John Wiley & Sons, Ltd.     

成分互补熔体温度处理对高硅铝合金组织的影响

研究了成分互补熔体温度处理工艺对Al-20Si合金组织的影响规律。研究表明,该工艺能够对高硅铝合金的初生Si相产生明显的变质效果,经成分互补熔体温度处理工艺处理后,初生Si的晶粒在100min内尺寸可稳定在36μm左右,这表明对高硅铝合金的变质效果具有长效性,是一种简单实用的高硅铝合金变质处理工艺。     

Improved lightpath (wavelength) routing in large WDM networks

We address the problem of efficient circuit switching in wide area networks. The solution provided is based on finding optimal routes for lightpaths and semilightpaths. A lightpath is a fully optical transmission path, while a semilightpath is a transmission path constructed by chaining several lightpaths together, using wavelength conversion at their junctions. The problem thus is to find an optimal lightpath/semilightpath in the network in terms of the cost of wavelength conversion and the cost of using the wavelengths on links. In this paper, we first present an efficient algorithm for the problem which runs in time O(k²n+km+kn log(kn)), where n and m are the number of nodes and links in the network, and k is the number of wavelengths. We then analyze that the proposed algorithm requires O(d ²nk₀²+mk₀ log n) time for a restricted version of the problem in which the number of available wavelengths for each link is bounded by k₀ and k₀=o(n), where d is the maximum in-degree or out-degree of the network. It is surprising to have found that the time complexity for this case is independent of k. It must be mentioned that our algorithm can be implemented efficiently in the distributed computing environment. The distributed version requires O(kn) time and O(km) messages. Compared with a previous O(k²n+kn²) time algorithm, our algorithm has the following advantages. (1) We take into account the physical topology of the network which makes our algorithm outperform the previous algorithm. In particular, when k is small [e.g., k=O(log n)] and m=O(n), our algorithm runs in time O(n log² n), while the previous algorithm runs in time O(n log n). (2) Since our algorithm has high locality, it can be implemented on the network distributively