Browsing by Subject "Grid computing"

Now showing 1 - 6 of 6

Open Access
Architecture of a grid-enabled Web search engine
(Elsevier Ltd, 2007) Cambazoglu, B. B.; Karaca, E.; Kucukyilmaz T.; Turk, A.; Aykanat, Cevdet
Search Engine for South-East Europe (SE4SEE) is a socio-cultural search engine running on the grid infrastructure. It offers a personalized, on-demand, country-specific, category-based Web search facility. The main goal of SE4SEE is to attack the page freshness problem by performing the search on the original pages residing on the Web, rather than on the previously fetched copies as done in the traditional search engines. SE4SEE also aims to obtain high download rates in Web crawling by making use of the geographically distributed nature of the grid. In this work, we present the architectural design issues and implementation details of this search engine. We conduct various experiments to illustrate performance results obtained on a grid infrastructure and justify the use of the search strategy employed in SE4SEE. © 2006 Elsevier Ltd. All rights reserved.
Open Access
A cryptocurrency incentivized voluntary grid computing platform for DNA read alignment
(2019-09) Özercan, Halil İbrahim
The main computational bottleneck of High Throughput Sequencing (HTS) data analysis is to map the reads to a reference genome, for which clusters are typically used. However, building clusters large enough to handle hundreds of petabytes of data is infeasible. Additionally, the reference genome is also periodically updated to x errors and include newly sequenced insertions, therefore in many large scale genome projects the reads are realigned to the new reference. Therefore, we need to explore volunteer grid computing technologies to help ameliorate the need for large clusters. However, since the computational demands of HTS read mapping is substantial, and the turnaround of analysis should be fast, we also need a method to motivate volunteers to dedicate their computational resources. For this purpose, we propose to merge distributed read mapping techniques with the popular blockchain technology. Cryptocurrencies such as Bitcoin calculate a value (called nonce) to ensure new block (i.e., \money") creations are limited and di cult in the system, however, this calculation serves no other practical purpose. Our solution (Coinami) introduces a new cryptocurrency called Halocoin, which rewards scienti c work with alternative minting. In Coinami, read alignment problems are published and distributed in a decentralized manner while volunteers are rewarded for their work. Authorities have two main tasks in our system: 1) inject new problem sets (i.e., \alignment problems") into the system, and 2) check for the validity of the results to prevent counterfeit.
Open Access
Haber videolarında ilgililik geribeslemesiyle içerik tabanlı erişim
(IEEE, 2006-04) Çavuş, Özge; Aksoy, Selim
Content-based retrieval in news video databases has become an important task with the availability of large quantities of data in both public and proprietary archives. We describe a relevance feedback technique that captures the significance of different features at different spatial locations in an image. Spatial content is modeled by partitioning images into non-overlapping grid cells. Contributions of different features at different locations are modeled using weights defined for each feature in each grid cell. These weights are iteratively updated based on user's feedback in terms of positive and negative labeling of retrieval results. Given this labeling, the weight updating scheme uses the ratios of standard deviations of the distances between relevant and irrelevant images to the standard deviations of the distances between relevant images. The proposed technique is quantitatively and qualitatively evaluated using shots related to several sports from the news video collection of the TRECVID video retrieval evaluation where the weights could capture relative contributions of different features and spatial locations. © 2006 IEEE.
Open Access
Heuristics for scheduling file-sharing tasks on heterogeneous systems with distributed repositories
(Academic Press, 2007) Kaya, K.; Uçar, B.; Aykanat, Cevdet
We consider the problem of scheduling an application on a computing system consisting of heterogeneous processors and data repositories. The application consists of a large number of file-sharing otherwise independent tasks. The files initially reside on the repositories. The processors and the repositories are connected through a heterogeneous interconnection network. Our aim is to assign the tasks to the processors, to schedule the file transfers from the repositories, and to schedule the executions of tasks on each processor in such a way that the turnaround time is minimized. We propose a heuristic composed of three phases: initial task assignment, task assignment refinement, and execution ordering. We experimentally compare the proposed heuristics with three well-known heuristics on a large number of problem instances. The proposed heuristic runs considerably faster than the existing heuristics and obtains 10-14% better turnaround times than the best of the three existing heuristics. © 2006 Elsevier Inc. All rights reserved.
Open Access
Iterative-improvement-based heuristics for adaptive scheduling of tasks sharing files on heterogeneous master-slave environments
(Institute of Electrical and Electronics Engineers, 2006) Kaya, K.; Aykanat, Cevdet
The scheduling of independent but file-sharing tasks on heterogeneous master-slave platforms has recently found important applications in Grid environments. The scheduling heuristics recently proposed for this problem are all constructive in nature and based on a common greedy criterion which depends on the momentary completion time values of the tasks. We show that this greedy decision criterion has shortcomings in exploiting the file-sharing interaction among tasks since completion time values are inadequate to extract the global view of this interaction. We propose a three-phase scheduling approach which involves initial task assignment, refinement, and execution ordering phases. For the refinement phase, we model the target application as a hypergraph and, with an elegant hypergraph-partitioning-like formulation, we propose using iterative-improvement-based heuristics for refining the task assignments according to two novel objective functions. Unlike the turnaround time, which is the actual schedule cost, the smoothness of proposed objective functions enables the use of iterative-improvement-based heuristics successfully since their effectiveness and efficiency depend on the smoothness of the objective function. Experimental results on a wide range of synthetically generated heterogeneous master-slave frameworks show that the proposed three-phase scheduling approach performs much better than the greedy constructive approach. © 2006 IEEE.
Open Access
Joint resource and network scheduling with adaptive offset determination for optical burst switched grids
(Elsevier, 2010-11-24) Koseoglu, M.; Karasan, E.
Optical burst switching (OBS) is a promising technology for optical grids with short-lived and interactive data communication requirements. On the other hand, burst losses are in the nature of the OBS protocol and these losses severely affect the grid job completion times. This paper first proposes a joint grid resource and network provisioning method to avoid congestion in the network in order to minimize grid job completion times. Simulations show that joint provisioning significantly reduces completion times in comparison to other methods that perform network provisioning after grid scheduling. An adaptive extra offset based quality of service (QoS) mechanism is also proposed in order to reduce grid burst losses in case of network congestion. Results show that this adaptive mechanism significantly reduces grid completion times by exploiting the trade-off between decreasing loss probability and increasing delay introduced by the extra offset time.