Simple Allocation Method Research Articles

Efficient task allocation approach using genetic algorithm for cloud environment

As the number of cloud applications is rising exponentially, efficient allocation of these tasks among multiple computing machines ensuring the quality of service and better profit to the cloud service providers is a challenge. Effective task allocation approach needs to be developed considering a number of objectives while making allocation decisions, such as less energy consumption and quick response, in order to make the best resource allocation satisfying the cloud user requirements and improving the overall performance of the cloud computing environment. Hence, in this paper, Genetic Algorithm based efficient task allocation approach has been proposed for achieving the reduced task completion time by making wise allocation decisions. This proposed algorithm has been simulated using cloudsim toolkit and the performance is evaluated by comparing with greedy and simple allocation methods on a set of parameters like makespan and throughput for task scheduling. The evaluation results have shown the better throughput with the proposed approach.

Emissions allocation in transportation routes

This article studies the allocation of CO2 emissions to a specific shipment in routing transportation. The authors show that this problem differs from a cost allocation problem specifically because the concavity condition does not hold necessarily in the CO2 allocation problem. This implies that a traditional cost allocation method cannot be straightforwardly translated into a CO2 allocation problem, and thus, new methods need to be developed. This study proposes four allocation mechanisms that are extensions from the literature and the common practice in industries. In doing so, the authors introduce the concept of carbon efficiency to assess if a particular allocation rule drives companies to carbon emissions reduction. They present analytical properties that show that the current practice of allocating CO2 emissions based on the greenhouse gas protocol, fails to be sensitive to drive companies to the sustainable practice of placing consolidated orders. The authors also conduct an experimental analysis using data of a logistics service provider that operates in Europe. Using the results of the experiments, they show that simple allocation methods can lead to a fair and carbon efficient allocation. In addition, the study provides insights by conducting a sensitivity analysis, and it shows that the CO2 allocations are not substantially susceptible to shipment size estimation errors.

Downlink fairness‐aware adaptive resource allocation approach for LTE networks

AbstractThis article addresses downlink resource allocation strategies in LTE release 8, using orthogonal frequency division access (OFDMA). We consider 3GPP long‐term evolution resource allocation strategies for allocating higher‐layer data to the basic resource allocation units (slots) of OFDMA frames. Then, we introduce two simple allocation methods: adaptive slot allocation and reservation‐based slot allocation. Both approaches consider a fair resource allocation among different types of service data flow (SDF) by considering their quality of service (QoS) characteristics and their channel qualities. The ultimate objective of the proposed approaches is to maximize the capacity of the system subject to the QoS constraints for each type of SDF in terms of data rate and bit error rate. Copyright © 2011 John Wiley & Sons, Ltd.

Downlink resource allocation strategies for OFDMA based mobile WiMAX

This article addresses downlink resource allocation strategies in Mobile WiMAX based on IEEE802.16e standard, using Orthogonal Frequency Division Access (OFDMA). We consider Mobile WiMAX resource allocation strategies for allocating higher layer data to the basic resource allocation units (slots) of OFDMA frames. Then, we introduce two simple allocation methods: Adaptive Slot Allocation (ASA) and Reservation-Based Slot Allocation (RSA). Both approaches consider a fair resource allocation among different types of service flows (SFs) by considering their QoS characteristics and their channel qualities. The ultimate objective of the proposed approaches is to maximize the capacity of the system subject to the quality of service (QoS) constraints for each type of (SFs) in terms of data rate and Bit Error Rate (BER).

A multi‐level satellite channel allocation algorithm for real‐time VBR data

AbstractIntegrated services over a shared satellite channel need a MAC protocol that is able to deal with real‐time traffic without substantially affecting the efficiency of the shared medium. Due to its bursty nature, MPEG coded VBR video transmission is one of the most challenging real‐time applications. In this paper, we analyse the statistical performance of a simple allocation method for VBR traffic by using an accurate statistical model of an MPEG‐2 VBR coded movie, whose traffic exhibits a peak to mean ratio of about 4. The results were obtained both analytically and by simulation, and show that our method is suitable for transmitting non‐interactive video and best‐effort traffic on the same satellite link. The efficiency of the proposed method shows no dependency on the statistical properties of the input traffic. Copyright © 2002 John Wiley & Sons, Ltd.

An efficient memory allocation scheme for Huffman coding of multiple sources

In this paper, we propose an efficient memory allocation scheme for memory-constrained Huffman coding of multiple sources, which can be applied to many adaptive variable-length coding systems. The allocation of a given memory is performed in two stages. At the first stage, the iterative bisection algorithm based on the Lagrange optimization method is used to find a Lagrange allocation , which is either optimal or close to the optimal allocation. In the latter case, the Lagrange method does not fully allocate the given memory and a sequential allocation method is introduced as the second stage to allocate the remaining memory, which is performed in a greedy manner. To explain the proposed allocation scheme, we introduce a function, b ̂ (l) , which approximates the relation between the average bitrate b and the Huffman table size l , and discuss its properties. The use of this function considerably reduces the computational burden for memory allocation. We apply the proposed memory allocation scheme to memory-constrained conditional entropy coding of vector quantization indices for image compression. Simulations show that the proposed memory allocation scheme provides almost optimal performance, which is far better than can be achieved with conventional simple allocation methods.

Needed resources for software module test, using the hyper-geometric software reliability growth model

Considerable testing resources are required during software module testing. This paper, based on the 'hyper-geometric distribution software reliability growth model' (HGDM) investigates two optimal resource allocation (OPT/RA) problems in software module testing: (1) minimization of the number of software faults (NSF) still undetected in the system after testing, given a fixed amount of testing resources; and (2) minimization of the total amount of testing resources required, given the NSF still undetected in the system after testing. Based on the concepts of average allocation and proportional allocation, two simple allocation methods are introduced. Experimental results show that the OPT/RA method can improve the quality and reliability of the software system much more than the simple allocation methods. Therefore, the OPT/RA method is very efficient for solving the 'testing resource allocation' problem.

Power Allocations: Determining Sample Sizes for Subnational Areas

Abstract In many surveys, reliable estimates are required both at the national level and for subnational areas. When the subnational areas vary considerably in population size or importance, problems can arise in the use of standard allocations. In this article, a simple allocation method is suggested for achieving reliable national and subnational estimates.