Storage Allocation Scheme Research Articles

Optimal Storage Allocation for Wireless Cloud Caching Systems With a Limited Sum Storage Capacity

In wireless cloud storage systems, the recovery failure probability depends on not only wireless channel conditions but also storage size of each distributed storage node. For an efficient utilization of limited storage capacity and the performance characterization of allocation strategies, we asymptotically analyze the recovery failure probability of a wireless cloud storage system with a sum storage capacity constraint for both high SNR regime and low SNR regime. Then, we find the optimal storage allocation strategy across distributed storage nodes in terms of the asymptotic recovery failure probability. Our analysis reveals that the maximal symmetric allocation is optimal for high SNR regime and the minimal allocation (with $\lfloor T\rfloor$ complete storage nodes and an incomplete storage node) is optimal for low SNR regime, where $T$ is the sum storage capacity. Based on the numerical investigation, we also show that in intermediate SNR regime, a balance allocation between the minimal allocation and the maximal symmetric allocation would not be required if we select one between them according to SNR.

Optimal Coding and Allocation for Perfect Secrecy in Multiple Clouds

For a user to store data in the cloud, using services provided by multiple cloud storage providers (CSPs) is a promising approach to increase the level of data availability and confidentiality, as it is unlikely that different CSPs are out of service at the same time or collude with each other to extract information of a user. This paper investigates the problem of storing data reliably and securely in multiple CSPs constrained by given budgets with minimum cost. Previous works, with variations in problem formulations, typically tackle the problem by decoupling it into sub-problems and solve them separately. While such a decoupling approach is simple, the resultant solution is suboptimal. This paper is the first one which considers the problem as a whole and derives a jointly optimal coding and storage allocation scheme, which achieves perfect secrecy with minimum cost. The analytical result reveals that the optimal coding scheme is the nested maximum-distance-separable code and the optimal amount of data to be stored in the CSPs exhibits a certain structure. The exact parameters of the code and the exact storage amount to each CSP can be determined numerically by simple 2-D search.

Storage allocation scheme for virtual instances of cloud computing

Cloud computing delivers resources and services through virtual machines on a pay-as-you-go basis. The allocation of storage space to users is usually determined by means of open allocation mechanisms that cannot guarantee an efficient allocation. Current allocation mechanisms do not consider user requests when making provisioning decisions. In other words, they assume that the storage spaces are fixed. In this study, we propose an algorithm for allocating storage spaces based on the requests of users. We present a unified storage allocation scheme (USAS) for cloud computing. USAS is a dynamic storage allocation framework for unlimited, limited, and free users. Our proposed approach is based on a storage partitioning policy, and we have compared our proposed scheme with open storage scheme and fixed storage scheme with common partition. We show through simulation study that USAS dynamically allocates space for different user requirements for all traffic loads.

Fresh Food Distribution Center Storage Allocation Strategy Analysis Based on Optimized Entry-Item-Quantity-ABC

For labour-intensive field, appropriate storage location assignment is the best choice to increase order picking efficiency and reduce order cycle time, which satisfy customers and reduce cost at the same time. In this paper, we advance a storage location assignment for fresh food distribution center with a manual picker-to-parts picking system by using an optimized approach. To reflect the customer demand uncertainty, the orders received in a certain time range have been grouped and given the different coefficients according to the reference value of them. On that basis, the storage location can be designed optimally based on the Entry-Item-Quantity (EIQ) analysis, which can be used to resolve some orders picking issues, long-picking time and high inventory costs, caused by seasonal change of fresh food, unstable customer demand and repeat purchases. From the computational results, new storage allocation strategy achieves at most a 16% reduction in travel time.

Swarm intelligence algorithms for Yard Truck Scheduling and Storage Allocation Problems

In this paper we focus on two scheduling problems in container terminal: (i) the Yard Truck Scheduling Problem (YTSP) which assigns a fleet of trucks to transport containers between the QCs and the storage yard to minimize the makespan, (ii) the integrated Yard Truck Scheduling Problem and Storage Allocation Problem (YTS–SAP) which extends the first problem to consider storage allocation strategy for discharging containers. Its object is to minimize the total delay for all jobs. The second model is improved to consider the truck ready time. Due to the computational intractability, two recently developed solution methods, based on swarm intelligence technique, are developed for problem solution, namely, particle swarm optimization (PSO) and bacterial colony optimization (BCO). As these two algorithms are originally designed for continuous optimization problems, we proposed a particular mapping method to implement them for YTSP and YTS–SAP, both of which are discrete optimization problems. Through comparing the PSO algorithms and BCO algorithm with GA by an experiment conducted on different scale instances, we can draw a conclusion that LPSO perform best in YTSP while BCO perform best in YTS–SAP.

Minimizing data redundancy for high reliable cloud storage systems

Cloud storage system provides reliable service to users by widely deploying redundancy schemes in its system – which brings high reliability to the data storage, but inversely introduces significant overhead to the system, consisting of storage cost and energy consumption. The core behind this issue is how to leverage the relationship between data redundancy and data reliability. To optimize both concurrently is apparently difficult. As such, to fix one as a constraint and then to reach another one becomes the consensus. We aim in the paper to pursue a storage allocation scheme that minimizes the data redundancy while achieving a given (high) data reliability. For this purpose, we have provided a novel model based on generating function. With this model, we have proposed a practical and efficient storage allocation scheme, which is proved to be able to minimize the data redundancy. We analytically demonstrate that the suggested solution brings several advantages, in particular the reduction of the search space and the acceleration to the computation. We also assess the improvement on the savings of data redundancy experimentally by adopting availability traces collected from real world – which encouragingly shows that the reduction of data redundancy by our solution can reach up to more than 30% as compared to the heuristic method recently proposed in the research community.

A VCG Mechanism Based Storage Allocation Strategy in Cloud Computing Environment

A VCG Mechanism Based Storage Allocation Strategy in Cloud Computing Environment

梯级水库防洪库容分配策略研究

针对梯级水库防洪任务和边界条件发生的变化，建立了一种确定梯级水库防洪库容分配的数学模型，耦合水库电力调度优化、防洪效益优化等多种目标，把梯级水库预留的防洪库容最小作为约束条件，采用逐次优化算法求解出使梯级水库发电效益最大的非劣解集。以清江干流梯级水库为例，确定水布垭和隔河岩水库防洪库容的最优分配策略。在水布垭预留5亿m3和隔河岩预留不小于1.5亿m3防洪库容的前提下，若发生100年一遇的洪水时，隔河岩水库的最高调洪水位不会超过200 m，可以满足防洪安全。该研究为梯级水库防洪库容分配提供了一种新的探讨思路。 Due to the changes of flood control task and boundary condition of cascade reservoirs, a mathematical model was established to allocate cascade reservoir flood prevention storage. Coupled hydropower generation with flood control operation objections, progressive optimality algorithm was used to obtain Pareto non-inferior solutions of maximum hydropower generation under the minimum flood prevention storage constrains for cascade reservoirs. The Qingjiang basin was selected as case study, the optimal storage allocation strategy for the Shuibuya and Geheyan reservoirs was given. If the Shuibuya reservoir keeps 500 million m3 and Geheyan reservoir remains not less than 150 million m3 flood prevention storages, the maximum regulation water level of the Geheyan reservoir will not over 200mwhen 100-year flood occurs, which can assurance flood control safety. The proposed method might provide a new approach for cascade reservoir storage allocation.

Scalable, statistical storage allocation for extensible inverted file construction

An Inverted file is a commonly used index for both archival databases and free text where no updates are expected. Applications like information filtering and dynamic environments like the Internet require inverted files to be updated efficiently. Recently, extensible inverted files are proposed which can be used for fast online indexing. The effective storage allocation scheme for such inverted files uses the arrival rate to preallocate storage. In this article, this storage allocation scheme is improved by using information about both the arrival rates and their variability to predict the storage needed, as well as scaling the storage allocation by a logarithmic factor. The resultant, final storage utilization rate can be as high as 97–98% after indexing about 1.6 million documents. This compares favorably with the storage utilization rate of the original arrival rate storage allocation scheme. Our evaluation shows that the retrieval time for extensible inverted file on solid state disk is on average similar to the retrieval time for in-memory extensible inverted file. When file seek time is not an issue, our scalable storage allocation enables extensible inverted files to be used as the main index on disk. Our statistical storage allocation may be applicable to novel situations where the arrival of items follows a binomial, Poisson or normal distribution.

Analyzing the feasibility of building a new mass storage system on distributed resources

The average PC now contains a large and increasing amount of storage with an ever greater amount left unused. We believe there is an opportunity for organizations to harness the vast unused storage capacity on their PCs to create a very large, low-cost, shared storage system. What is needed is the proper storage system architecture and software to exploit and manage the unused portions of existing PC storage devices across an organization and make it reliably accessible to users and applications. We call our vision of such a storage system Storage@desk (SD). This paper describes our first step towards the realization of SD—a study of machine and storage characteristics and usage in a model organization. We studied 729 PCs in an academic institution for 91 days, monitoring the configuration, load and usage of the major machine subsystems, i.e. disk, memory, CPU and network. To further analyze the availability characteristics of storage in an SD system, we performed a trace-driven simulation of some basic storage allocation strategies. This paper presents the results of our data collection efforts, our analysis of the data, our simulation results and our conclusion that an SD system is indeed feasible and holds promise as a cost-effective way to create massive storage systems. Copyright © 2007 John Wiley & Sons, Ltd.

Efficient in-memory extensible inverted file

The growing amount of on-line data demands efficient parallel and distributed indexing mechanisms to manage large resource requirements and unpredictable system failures. Parallel and distributed indices built using commodity hardware like personal computers (PCs) can substantially save cost because PCs are produced in bulk, achieving the scale of economy. However, PCs have limited amount of random access memory (RAM) and the effective utilization of RAM for in-memory inversion is crucial. This paper presents an analytical investigation and an empirical evaluation of storage-efficient inmemory extensible inverted files, which are represented by fixed- or variable-sized linked list nodes. The size of these linked list nodes is determined by minimizing the storage wastes or maximizing storage utilization under different conditions, which lead to different storage allocation schemes. Minimizing storage wastes also reduces the number of address indirections (i.e., chaining). We evaluated our storage allocation schemes using a number of reference collections. We found that the arrival rate scheme is the best in terms of both storage utilization and the mean number of chainings per term. The final storage utilization can be over 90% in our evaluation if there is a sufficient number of documents indexed. The mean number of chainings is not large (less than 2.6 for all the reference collections). We have also showed that our best storage allocation scheme can be used for our extensible compressed inverted file. The final storage utilization of the extensible compressed inverted file can be over 90% in our evaluation provided that there is a sufficient number of documents indexed. The proposed storage allocation schemes can also be used by compressed extensible inverted files with word positions

Message analysis for concurrent programs using message passing

We describe an analysis-driven storage allocation scheme for concurrent systems that use message passing with copying semantics. The basic principle is that in such a system, data which is not part of any message does not need to be allocated in a shared data area. This allows for the deallocation of thread-specific data without requiring global synchronization and often without even triggering garbage collection. On the other hand, data that is part of a message should preferably be allocated on a shared area since this allows for fast ( O (1)) interprocess communication that does not require actual copying. In the context of a dynamically typed, higher-order concurrent functional language, we present a static message analysis which guides the allocation. As shown by our performance evaluation, conducted using a production-quality language implementation, the analysis is effective enough to discover most data which is to be used as a message, and to allow the allocation scheme to combine the best performance characteristics of both a process-centric and a communal memory architecture.

Travel time analysis for general item location assignment in a rectangular warehouse

A travel time model with general item location assignment in a rectangular warehouse system is presented. We give the exact probability mass functions that characterise the tour of an order picker and derive the first and second moments associated with the tour. We apply the model to analysing order batching and storage allocation strategies in an order picking system. The order picking system is modelled as a queueing system with customer batching. The results are compared and validated via simulation. The effects of batching and batch size on the delay time are discussed with consideration to the picking and sorting times for each batch of orders.

Order picking systems: Batching and storage assignment strategies

We consider batching and storage allocation strategies in a manual order picking system of small parts which processes high volume of orders. The arrivals of orders are assumed to follow a Poisson process, and the quantity of items in an order is assumed to be independently and identically distributed negative binomial variates. The order picking system is modeled by a two-stage queueing system with batching and picking activities. Bounds and approximate estimates for the mean and variance of the turnover time (total service time) of a batch of orders are derived. The quality of the results is evaluated via simulation. A comparison between uniform and skewed item storage assignment is also presented. The effects of batching and the batch size on the service time are discussed.

Compile Time Memory Allocation for Parallel Processes

This paper discusses the problem of allocating storage for the activation records of procedure calls within a system of parallel processes. A compile time storage allocation scheme is given, which determines the relative address within the memory segment of a process for the activation records of all procedures called by the process. This facilitates the generation of an efficient run-time code. The allocation scheme applies to systems in which data and procedures can be shared among several processes. However, recursive procedure calls are not supported.

An Automatic Nested Dissection Algorithm for Irregular Finite Element Problems

A formal definition of a nested dissection ordering of the graph of a general sparse symmetric matrix A is given. After introducing some preliminary results which provide a direct relationship between the structures of A and its triangular factor L, where $A = LL^T $, some results about fill for nested dissection orderings are provided. Finally, a heuristic algorithm is described for finding a nested dissection ordering for an undirected graph, along with appropriate data structures and a storage allocation scheme for a linear equation solver to use such orderings. The ordering algorithm/linear equation solver combination is applied to the graphs of matrices arising in typical finite element applications, and numerical experiments are provided which indicate that our combination of ordering and solution schemes is superior to standard band or envelope schemes as long as the problems are moderately large.

Analysis of block-organized buffers for Poisson input and periodic block output

Abstract The statistical behaviour of the block-organized buffers is studied under Poisson input and periodic block output. Analytical expressions concerning mean information loss, channel utilization and expected queueing delay in relation to traffic intensity, block size and buffer length are derived. Results are given for a range of parameters and the block-organized buffer is compared to the corresponding word-organized on a cost-performance basis. The study should prove useful to the design of on-line computer systems, computer networks, storage allocation strategies and the like.

An analytic storage allocation model

An analytical model of a simple computer storage allocation scheme is described, and its Markov nature established given certain conditions on its input and operation. Simple Markov theory is used to compute the expected storage utilisation in some example situations with small memory sizes. These are compared with the analytical closed-form results which are possible when storage relocation is allowed. Some current restrictions and possible future developments and uses of the model are outlined.

Computational algorithms for closed queueing networks with exponential servers

Methods are presented for computing the equilibrium distribution of customers in closed queueing networks with exponential servers. Expressions for various marginal distributions are also derived. The computational algorithms are based on two-dimensional iterative techniques which are highly efficient and quite simple to implement. Implementation considerations such as storage allocation strategies and order of evaluation are examined in some detail.

A Compaction Procedure for Variable-Length Storage Elements

When a dynamic storage allocation scheme requires variable-length elements, an element of a given length may be requested when no free element large enough is available. This can happen even though the total free space is more than adequate to fulfil the request. In such a situation the program will fail unless some method is at hand for forming the available space into a single element large enough to satisfy the request. We present a procedure for compacting the store such that all of the free space forms a single element.