Browsing by Subject "Total costs"

Now showing 1 - 4 of 4

Open Access
Average Fisher information maximisation in presence of cost-constrained measurements
(The Institution of Engineering and Technology, 2011) Dulek, B.; Gezici, Sinan
An optimal estimation framework is considered in the presence of cost-constrained measurements. The aim is to maximise the average Fisher information under a constraint on the total cost of measurement devices. An optimisation problem is formulated to calculate the optimal costs of measurement devices that maximise the average Fisher information for arbitrary observation and measurement statistics. In addition, a closed-form expression is obtained in the case of Gaussian observations and measurement noise. Numerical examples are presented to explain the results.
Open Access
Cost-aware strategies for query result caching in Web search engines
(Association for Computing Machinery, 2011) Ozcan, R.; Altingovde, I. S.; Ulusoy, O.
Search engines and large-scale IR systems need to cache query results for efficiency and scalability purposes. Static and dynamic caching techniques (as well as their combinations) are employed to effectively cache query results. In this study, we propose cost-aware strategies for static and dynamic caching setups. Our research is motivated by two key observations: (i) query processing costs may significantly vary among different queries, and (ii) the processing cost of a query is not proportional to its popularity (i.e., frequency in the previous logs). The first observation implies that cache misses have different, that is, nonuniform, costs in this context. The latter observation implies that typical caching policies, solely based on query popularity, can not always minimize the total cost. Therefore, we propose to explicitly incorporate the query costs into the caching policies. Simulation results using two large Web crawl datasets and a real query log reveal that the proposed approach improves overall system performance in terms of the average query execution time. © 2011 ACM.
Open Access
New formulations for the hop-constrained minimum spanning tree problem via Sherali and Driscoll's tightened Miller-Tucker-Zemlin constraints
(Elsevier, 2010) Akgün, İbrahim
Given an undirected network with positive edge costs and a natural number p, the hop-constrained minimum spanning tree problem (HMST) is the problem of finding a spanning tree with minimum total cost such that each path starting from a specified root node has no more than p hops (edges). In this paper, the new models based on the Miller-Tucker-Zemlin (MTZ) subtour elimination constraints are developed and computational results together with comparisons against MTZ-based, flow-based, and hop-indexed formulations are reported. The first model is obtained by adapting the MTZ-based Asymmetric Traveling Salesman Problem formulation of Sherali and Driscoll [18] and the other two models are obtained by combining topology-enforcing and MTZ-related constraints offered by Akgün and Tansel (submitted for publication) [20] for HMST with the first model appropriately. Computational studies show that the best LP bounds of the MTZ-based models in the literature are improved by the proposed models. The best solution times of the MTZ-based models are not improved for optimally solved instances. However, the results for the harder, large-size instances imply that the proposed models are likely to produce better solution times. The proposed models do not dominate the flow-based and hop-indexed formulations with respect to LP bounds. However, good feasible solutions can be obtained in a reasonable amount of time for problems for which even the LP relaxations of the flow-based and hop-indexed formulations can be solved in about 2 days. © 2010 Elsevier Ltd. All rights reserved.
Open Access
Representation of optical fields using finite numbers of bits
(Optical Society of America, 2012-06-04) Özçelikkale, A.; Özaktaş, Haldun M.
We consider the problem of representation of a finite-energy optical field, with a finite number of bits. The optical field is represented with a finite number of uniformly spaced finite-accuracy samples (there is a finite number of amplitude levels that can be reliably distinguished for each sample). The total number of bits required to encode all samples constitutes the cost of the representation. We investigate the optimal number and spacing of these samples under a total cost budget. Our framework reveals the trade-off between the number, spacing, and accuracy of the samples. When we vary the cost budget, we obtain trade-off curves between the representation error and the cost budget. We also discuss the effect of degree of coherence of the field.