scholarly journals RESOURCE ALLOCATION STRATEGIES FOR CONSTRUCTIVE IN-NETWORK STREAM PROCESSING

2011 ◽  
Vol 22 (03) ◽  
pp. 621-638 ◽  
Author(s):  
ANNE BENOIT ◽  
VERONIKA REHN-SONIGO ◽  
YVES ROBERT ◽  
HENRI CASANOVA
Keyword(s):  
Steady State ◽  
Relational Databases ◽  
Stream Processing ◽  
Mapping Problem ◽  
Operator Mapping ◽  
Multiple Data ◽  
Np Complete ◽  
Data Objects ◽  
The Cost ◽  
Allocation Strategies

In this paper we consider the operator mapping problem for in-network stream processing applications. In-network stream processing consists in applying a tree of operators in steady-state to multiple data objects that are continually updated at various locations on a network. Examples of in-network stream processing include the processing of data in a sensor network, or of continuous queries on distributed relational databases. We study the operator mapping problem in a "constructive" scenario, i.e., a scenario in which one builds a platform dedicated to the application by purchasing processing servers with various costs and capabilities. The objective is to minimize the cost of the platform while ensuring that the application achieves a minimum steady-state throughput. The first contribution of this paper is the formalization of a set of relevant operator-placement problems, and a proof that even simple versions of the problem are NP-complete. Our second contribution is the design of several polynomial time heuristics, which are evaluated via extensive simulations and compared to theoretical bounds for optimal solutions.

scholarly journals HEURISTIC ALGORITHM FOR FRAGMENTATION AND ALLOCATION IN DISTRIBUTED OBJECT ORIENTED DATABASE

2016 ◽  
Vol 32 (1) ◽  
pp. 47-60
Author(s):  
Nga Thúy Mai
Keyword(s):  
Relational Databases ◽  
Distributed Databases ◽  
Data Communication ◽  
Object Oriented ◽  
Database System ◽  
Distributed Data ◽  
Distributed Object ◽  
Data Objects ◽  
The Cost ◽  
Object Oriented Database

Class fragmentation and allocation is an important technique to improve the performance of a distributed object oriented database system. The class fragmentation is to split a class into smaller pieces in distributed databases aims to reduce the access to unnecessary data, the allocation is to locate fragmented classes into the sites in the connected network properly to reduce the cost of data transmission. Classes in object databases include attributes describing the characteristics of the object, methods describing the behavior, and relationships with objects with other classes, including relations inheritance. With such characteristics, class fragmentation and allocation in the distributed object oriented database system is more complex than fragmentation technique and design of relational databases. Fragmentation techniques applied in the design of distributed object-oriented database today often do not use cost between the sites, fragments are allocated to the site after getting a fragmentation method of data objects. This paper proposes an algorithm of fragmentation and allocation simultaneously, including the cost of data communication between the sites used for fragmentation to reduce communication costs when processing and querying distributed data.

scholarly journals A Cost Analysis of School-Based Lifestyle Interventions

2018 ◽  
Vol 19 (6) ◽  
pp. 716-727 ◽  
Author(s):  
Marije Oosterhoff ◽  
Hans Bosma ◽  
Onno C.P. van Schayck ◽  
Manuela A. Joore
Keyword(s):  
Physical Activity ◽  
Steady State ◽  
Primary School ◽  
Relative Effectiveness ◽  
First Year ◽  
Lifestyle Interventions ◽  
Stakeholder Perspectives ◽  
School Based ◽  
The Cost ◽  
Cost Offsets

Abstract A uniform approach for costing school-based lifestyle interventions is currently lacking. The objective of this study was to develop a template for costing primary school-based lifestyle interventions and apply this to the costing of the “Healthy Primary School of the Future” (HPSF) and the “Physical Activity School” (PAS), which aim to improve physical activity and dietary behaviors. Cost-effectiveness studies were reviewed to identify the cost items. Societal costs were reflected by summing up the education, household and leisure, labor and social security, and health perspectives. Cost inputs for HPSF and PAS were obtained for the first year after implementation. In a scenario analysis, the costs were explored for a hypothetical steady state. From a societal perspective, the per child costs were €2.7/$3.3 (HPSF) and €− 0.3/$− 0.4 (PAS) per day during the first year after implementation, and €1.0/$1.2 and €− 1.3/$− 1.6 in a steady state, respectively (2016 prices). The highest costs were incurred by the education perspective (first year: €8.7/$10.6 (HPSF) and €4.0/$4.9 (PAS); steady state: €6.1/$7.4 (HPSF) and €2.1/$2.6 (PAS)), whereas most of the cost offsets were received by the household and leisure perspective (first year: €− 6.0/$− 7.3 (HPSF) and €− 4.4/$− 5.4 (PAS); steady state: €− 5.0/$− 6.1 (HPSF) and €− 3.4/$− 4.1 (PAS)). The template proved helpful for costing HPSF and PAS from various stakeholder perspectives. The costs for the education sector were fully (PAS) and almost fully (HPSF) compensated by the savings within the household sector. Whether the additional costs of HPSF over PAS represent value for money will depend on their relative effectiveness.

scholarly journals Research on Cooperative Innovation Behavior of Industrial Cluster Based on Subject Adaptability

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaohui Jia ◽  
Minghui Jiang ◽  
Lei Shi
Keyword(s):  
Steady State ◽  
Evolutionary Game ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Government Support ◽  
Correlated Equilibrium ◽  
Game Model ◽  
Cooperative Innovation ◽  
The Cost ◽  
The Impact

From the perspective of the interactive cooperation among subjects, this paper portrays the process of cooperative innovation in industrial cluster, in order to capture the correlated equilibrium relationship among them. Through the utilization of two key tools, evolutionary stable strategy and replicator dynamics equations, this paper considers the cost and gains of cooperative innovation and the amount of government support as well as other factors to build and analyze a classic evolutionary game model. On this basis, the subject’s own adaptability is introduced, which is regarded as the system noise in the stochastic evolutionary game model so as to analyze the impact of adaptability on the game strategy selection. The results show that, in the first place, without considering subjects’ adaptability, their cooperation in industrial clusters depends on the cost and gains of innovative cooperation, the amount of government support, and some conditions that can promote cooperation, namely, game steady state. In the second place after the introduction of subjects’ adaptability, it will affect both game theory selection process and time, which means that the process becomes more complex, presents the nonlinear characteristics, and helps them to make faster decisions in their favor, but the final steady state remains unchanged.

Cost Modeling and Range Estimation for Top-k Retrieval in Relational Databases

2011 ◽  
pp. 295-315
Author(s):  
Anteneh Ayanso ◽  
Paulo B. Goes ◽  
Kumar Mehta
Keyword(s):  
Relational Databases ◽  
Estimation Method ◽  
Synthetic Data ◽  
Cost Modeling ◽  
Data Sets ◽  
Range Estimation ◽  
Mapping Techniques ◽  
The Cost ◽  
Query Estimation ◽  
Query Mapping

Relational databases have increasingly become the basis for a wide range of applications that require efficient methods for exploratory search and retrieval. Top-k retrieval addresses this need and involves finding a limited number of records whose attribute values are the closest to those specified in a query. One of the approaches in the recent literature is query-mapping which deals with converting top-k queries into equivalent range queries that relational database management systems (RDBMSs) normally support. This approach combines the advantages of simplicity as well as practicality by avoiding the need for modifications to the query engine, or specialized data structures and indexing techniques to handle top-k queries separately. This paper reviews existing query-mapping techniques in the literature and presents a range query estimation method based on cost modeling. Experiments on real world and synthetic data sets show that the cost-based range estimation method performs at least as well as prior methods and avoids the need to calibrate workloads on specific database contents.

Analysis of Some Stochastic Inventory System in Supply Chain

2016 ◽  
pp. 124-147
Author(s):  
Bakthavachalam Rengarajan
Keyword(s):  
Steady State ◽  
Lead Time ◽  
Distribution Center ◽  
Setup Cost ◽  
Steady State Probability ◽  
Stochastic Inventory ◽  
Replenishment Policy ◽  
System States ◽  
Policy Supply ◽  
The Cost

In this chapter we consider a three echelon inventory control system which is modeled as a warehouse, single distribute and one retailer system handling a single product. A finished product is supplied from warehouse to distribution center which adopts one-for-one replenishment policy. The replenishment of items in terms of packets from warehouse to distribution center with exponential lead time having parameter µ1. Then the product is supplied from distribution center to retailer who adopts (s, S) policy. Supply to the retailer in packets of Q (= S - s) items is administrated with exponential lead time having parameter µ0. The demand at retailer node follows a Poisson with mean lambda. The steady state probability distribution of system states and the measures of system performance in the steady state are obtained explicitly. The Cost function is computed by using numerical searching algorithms, the optimal reorder points are obtained for various input parameters. Sensitivity analysis are discussed for various cost parameter such as holding cost, setup cost etc.

Accommodating Hierarchies in Relational Databases

2001 ◽  
pp. 194-209
Author(s):  
Ido Millet
Keyword(s):  
Data Structure ◽  
Relational Databases ◽  
Data Retrieval ◽  
Hierarchical Data ◽  
Inconsistent Data ◽  
The Cost

Relational databases and the current SQL standard are poorly suited to retrieval of hierarchical data. After demonstrating the problem, this chapter describes how two approaches to data denormalization can facilitate hierarchical data retrieval. Both approaches solve the problem of data retrieval, but as expected, come at the cost of difficult and potentially inconsistent data updates. This chapter then describes how we can address these update-related shortcomings via back-end (triggers) logic. Using a proper combination of denormalized data structure and back-end logic, we can have the best of both worlds: easy data retrieval and simple, consistent data updates.

COST ANALYSIS OF THE R-UNRELIABLE-UNLOADER QUEUEING SYSTEM

2008 ◽  
Vol 25 (01) ◽  
pp. 57-73
Author(s):  
KUO-HSIUNG WANG ◽  
CHUN-CHIN OH ◽  
JAU-CHUAN KE
Keyword(s):  
Sensitivity Analysis ◽  
Steady State ◽  
Queueing System ◽  
Cost Model ◽  
Analytic Solutions ◽  
Queueing Model ◽  
Exponential Distributions ◽  
System Parameters ◽  
Optimal Values ◽  
The Cost

This paper analyzes the unloader queueing model in which N identical trailers are unloaded by R unreliable unloaders. Steady-state analytic solutions are obtained with the assumptions that trip times, unloading times, finishing times, breakdown times, and repair times have exponential distributions. A cost model is developed to determine the optimal values of the number of unloaders and the finishing rate simultaneously, in order to minimize the expected cost per unit time. Numerical results are provided in which several steady-state characteristics of the system are calculated based on assumed numerical values given to the system parameters and the cost elements. Sensitivity analysis is also studied.

scholarly journals Sparse Adaptive Channel Estimation Based onlp-Norm-Penalized Affine Projection Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yingsong Li ◽  
Wenxing Li ◽  
Wenhua Yu ◽  
Jian Wan ◽  
Zhiwei Li
Keyword(s):  
Steady State ◽  
Channel Estimation ◽  
Convergence Speed ◽  
Projection Algorithm ◽  
Broadband Wireless ◽  
Sparse Channel Estimation ◽  
Affine Projection ◽  
Affine Projection Algorithm ◽  
The Cost ◽  
Steady State Performance

We propose anlp-norm-penalized affine projection algorithm (LP-APA) for broadband multipath adaptive channel estimations. The proposed LP-APA is realized by incorporating anlp-norm into the cost function of the conventional affine projection algorithm (APA) to exploit the sparsity property of the broadband wireless multipath channel, by which the convergence speed and steady-state performance of the APA are significantly improved. The implementation of the LP-APA is equivalent to adding a zero attractor to its iterations. The simulation results, which are obtained from a sparse channel estimation, demonstrate that the proposed LP-APA can efficiently improve channel estimation performance in terms of both the convergence speed and steady-state performance when the channel is exactly sparse.

scholarly journals Complex Correntropy with Variable Center: Definition, Properties, and Application to Adaptive Filtering

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 70
Author(s):  
Fei Dong ◽  
Guobing Qian ◽  
Shiyuan Wang
Keyword(s):  
Steady State ◽  
Adaptive Filtering ◽  
Gradient Descent ◽  
Gaussian Function ◽  
Complex Domain ◽  
Mean Square ◽  
Kernel Width ◽  
Non Gaussian ◽  
The Cost ◽  
Variable Center

The complex correntropy has been successfully applied to complex domain adaptive filtering, and the corresponding maximum complex correntropy criterion (MCCC) algorithm has been proved to be robust to non-Gaussian noises. However, the kernel function of the complex correntropy is usually limited to a Gaussian function whose center is zero. In order to improve the performance of MCCC in a non-zero mean noise environment, we firstly define a complex correntropy with variable center and provide its probability explanation. Then, we propose a maximum complex correntropy criterion with variable center (MCCC-VC), and apply it to the complex domain adaptive filtering. Next, we use the gradient descent approach to search the minimum of the cost function. We also propose a feasible method to optimize the center and the kernel width of MCCC-VC. It is very important that we further provide the bound for the learning rate and derive the theoretical value of the steady-state excess mean square error (EMSE). Finally, we perform some simulations to show the validity of the theoretical steady-state EMSE and the better performance of MCCC-VC.

Sign in / Sign up

Export Citation Format

Share Document