To solve the adverse effects brought by resource node transfering the using right to local task and the difficult problem of resource load balancing, a two-phase pricing strategy based on QoS constraints is proposed i...
详细信息
ISBN:
(纸本)9781509015856
To solve the adverse effects brought by resource node transfering the using right to local task and the difficult problem of resource load balancing, a two-phase pricing strategy based on QoS constraints is proposed in this paper. On the premise of guaranteeing the benefits of the resource provider in the cost price, this strategy balances the load of the resource provider by the profit price. The theoretical analysis proves the effectiveness of the pricing strategy, and the algorithm of the pricing strategy is designed in this paper. Resources node information in the real distributed systems is used as the performance parameters of experimental node in the simulation experiments, and the performance of the pricing strategy is tested in a large-scale grid mission. Experimental results show that, compared with the traditional pricing strategies, the two-phase pricing strategy based on QoS constraints has vastly superior performance on the benefits of the resource provider and the balance of resource utilization.
Intermittency of wind energy pose a great challenge for power system operation and control. Wind curtailment might be necessary at certain operating condition to keep the line flow within limit. Remedial Action Scheme...
详细信息
ISBN:
(纸本)9781479983971
Intermittency of wind energy pose a great challenge for power system operation and control. Wind curtailment might be necessary at certain operating condition to keep the line flow within limit. Remedial Action Scheme (RAS) offers quick control action mechanism to keep reliability and security of the power system operation with high wind energy integration. In this paper, a new RAS is developed to maximize the wind energy integration without compromising the security and reliability of the power system based on a specific utility requirements. A new distributed Linear State Estimation (DLSE) is also developed to provide the fast and accurate input data for the proposed RAS. A distributed computational architecture is designed to guarantee the robustness of cyber system to support RAS and DLSE implementation. The proposed RAS and DLSE is validated using modified IEEE-118 Bus system. Simulation results demonstrate the satisfactory performance of the DLSE and effectiveness of RAS.
This work describes modern methods of parallelizing time consuming problems. Commonly used parallelization methods, such as OpenMP, MPI and GPUs, aimed to accelerate the solution of electromagnetic forward problems ar...
详细信息
ISBN:
(纸本)9781509040698
This work describes modern methods of parallelizing time consuming problems. Commonly used parallelization methods, such as OpenMP, MPI and GPUs, aimed to accelerate the solution of electromagnetic forward problems are revisited. Comparison of these technologies, their constraints and benefits for complex three-dimensional geoelectromagnetic field modeling are provided. An approach to configure the distributed computing system to solve most resource-intensive geoelectromagnetic problems is proposed. The problem of load balancing between computational nodes of the distributed computing system, advantages and disadvantages of different task orchestration approaches are considered. Different approaches on building fault tolerant systems to create a reliable one that will be capable of carrying out complex three-dimensional time consuming problems are discussed. The efficiency of the proposed method of distributed computing is shown on the example of solving 3D inverse problems for geoelectromagnetic survey with geoelectrical imaging of a medium with a complex structure. The structure and conductivity of the three layers located at different depths with varying lateral depth, thickness and conductivity was restored. Results of computational experiments show high computational efficiency of the proposed system and fault tolerance to both equipment failures and errors of computing software.
distributed computing infrastructures (DCI) play an important role in modern research by enabling the use of multiple computing resources for solving complex problems. Despite the expansion of large-scale DCIs, the ra...
详细信息
distributed computing infrastructures (DCI) play an important role in modern research by enabling the use of multiple computing resources for solving complex problems. Despite the expansion of large-scale DCIs, the rapid integration of resources into ad-hoc infrastructures for small research projects or personal use still remains a challenge. The paper describes the integration and combined use of resources with Everest, a web-based distributed computing platform. In contrast to existing solutions, Everest follows the PaaS model and can be used remotely by multiple users to seamlessly run computations on arbitrary combinations of external resources attached by users. The integration of Everest with standalone resources and EGI grid is described. The presented approach is demonstrated by running real-world applications on ad-hoc infrastructures consisting of resources of different types.
In this paper we compare different technologies that support distributed computing as a means to address complex tasks. We address the task of n-gram text extraction which is a big computational given a large amount o...
详细信息
ISBN:
(纸本)9789897581939
In this paper we compare different technologies that support distributed computing as a means to address complex tasks. We address the task of n-gram text extraction which is a big computational given a large amount of textual data to process. In order to deal with such complexity we have to adopt and implement parallelization patterns. Nowadays there are several patterns, platforms and even languages that can be used for the parallelization task. We implemented this task on three platforms: (1) MPJ Express, (2) Apache Hadoop, and (3) Apache Spark. The experiments were implemented using two kinds of datasets composed by: (A) a large number of small files, and (B) a small number of large files. Each experiment uses both datasets and the experiment repeats for a set of different file sizes. We compared performance and efficiency among MPJ Express, Apache Hadoop and Apache Spark. As a final result we are able to provide guidelines for choosing the platform that is best suited for each kind of data set regarding its overall size and granularity of the input data.
This paper investigates the problem of allocating parallel application tasks to processors in heterogeneous distributed computing systems. The authors are proposing a simple, fast and effective algorithm to find the b...
详细信息
ISBN:
(纸本)9781889335513
This paper investigates the problem of allocating parallel application tasks to processors in heterogeneous distributed computing systems. The authors are proposing a simple, fast and effective algorithm to find the best possible solution with low computation time. The proposed algorithm uses the Correlation Density Rank (CDR) algorithm on the Virtual Allocation Network (VAN) in order to obtain reliability-based influence coefficients. Those coefficients are used to construct a simple linear programing as a new framework. We study the performance of the proposed algorithm over a wide range of parameters including problem size, the ratio of average communication time to average computation time, and task interaction density. The applicability and effectiveness of our algorithm is demonstrated by comparing with recently published related algorithms, which are found in the literature.
Hella et al. (PODC 2012, distributed computing 2015) identified seven different message-passing models of distributed computing one of which is the port-numbering model-and provided a complete classification of their ...
详细信息
ISBN:
(纸本)9781450343916
Hella et al. (PODC 2012, distributed computing 2015) identified seven different message-passing models of distributed computing one of which is the port-numbering model-and provided a complete classification of their computational power relative to each other. However, their method for simulating the ability to count incoming messages causes an additive overhead of 2 Delta - 2 communication rounds, and it was not clear if this is actually optimal. In this paper we give a positive answer, by using bisimulation as our main tool: there is a matching linear-in-Delta lower bound. This closes the final gap in our understanding of the models, with respect to the number of communication rounds. By a previously identified connection to modal logic, our result has implications to the relationship between multimodal logic and graded multimodal logic.
Recent advances in clustering have shown that ensuring a minimum separation between cluster centroids leads to higher quality clusters compared to those found by methods that explicitly set the number of clusters to b...
详细信息
ISBN:
(纸本)9781509048472
Recent advances in clustering have shown that ensuring a minimum separation between cluster centroids leads to higher quality clusters compared to those found by methods that explicitly set the number of clusters to be found, such as k-means. One such algorithm is DP-means, which sets a distance parameter lambda for the minimum separation. However, without knowing either the true number of clusters or the underlying true distribution, setting lambda itself can be difficult, and poor choices in setting lambda will negatively impact cluster quality. As a general solution for finding lambda, in this paper we present lambda-means, a clustering algorithm capable of deriving an optimal value for lambda automatically. We contribute both a theoretically-motivated cluster-based version of lambda-means, as well as a faster conflict-based version of lambda-means. We demonstrate that lambda-means discovers the true underlying value of lambda asymptotically when run on datasets generated by a Dirichlet Process, and achieves competitive performance on a real world test dataset. Further, we demonstrate that when run on both parallel multicore computers and distributed cluster computers in the cloud, cluster-based lambda-means achieves near perfect speedup, and while being a more efficient algorithm, conflict-based lambda-means achieves speedups only a factor of two away from the maximum-possible.
The BES-III experiment at the Institute of High Energy Physics (Beijing, China) is aimed at the precision measurements in e(+)e(-) annihilation in the energy range from 2.0 till 4.6 GeV. The world's largest sample...
详细信息
The BES-III experiment at the Institute of High Energy Physics (Beijing, China) is aimed at the precision measurements in e(+)e(-) annihilation in the energy range from 2.0 till 4.6 GeV. The world's largest samples of J/psi and psi' events and unique samples of XYZ data have been already collected. The expected increase of the data volume in the coming years required a significant evolution of the computing model, namely shift from a centralized data processing to a distributed one. This report summarizes a current design of the BES-III distributed computing system, some of key decisions and experience gained during 2 years of operations.
In this thesis I study the complexity theory of distributed computing in synchronous message passing models. The focus is on highly local problems, that is, problems in which very little communication is required. In ...
详细信息
In this thesis I study the complexity theory of distributed computing in synchronous message passing models. The focus is on highly local problems, that is, problems in which very little communication is required. In this setting the underlying communication network is also the input graph. The distributed system must collectively compute a solution to a problem related to the structure of this network, with each computer producing its own part of the output. We study the LOCAL model, one of the standard models in distributed computing. It abstracts away faults, congestion, computational requirements, memory requirements, and many other challenges in distributed computing. We study this model to understand the locality aspect of distributed computing: How far does information have to propagate in distributed problem solving? How many communication rounds is required? Many interesting problems, such as finding a spanning tree in the communication network, are inherently global. We are interested in the other extreme: problems that can be solved in time that is weakly dependent or completely independent of the size of the communication network. Typical problems include classical symmetry breaking tasks such as colouring or maximal independent set. Typically the time complexity of such problems depends on two parameters: the size and the maximum degree of the input graph. The connection with the first parameter is well understood with tight upper and lower bounds. The connection with the maximum degree is much less well understood, with an exponential gap between the upper and lower bounds. We develop a new lower bound technique to give the first lower bound for a natural graph problem that is linear in the maximum degree. In addition we study the power of unique in several contexts. We show that while usually unique identifiers are unhelpful for constant-time algorithms, there are certain special cases in which they do help. In the context oflocal decision, where the task
暂无评论