Storage Requests Research Articles

Dual command cycle dynamic sequencing method to consider GHG efficiency in unit-load multiple-rack automated storage and retrieval systems

In some AS/RS, the S/R machine executes a storage request and then a retrieval request to form a dual command (DC) cycle. This paper deals with a DC cycle “dynamic sequencing” method in unit-load multiple-rack AS/RS system. To create a kind of greenhouse gas (GHG) efficiency in the model, tax cost, penalty cost and discount of produced GHG emissions, limitations on available time of all facilities and total permitted GHG emissions produced by all equipment are considered in the model. In addition, an ant colony optimization (ACO) is employed to find a near-optimum solution of proposed mathematical model with the objective of minimizing the total cost of the GHG efficiency in AS/RS. Since no benchmark is available in the literature, a genetic algorithm (GA) is developed as well to validate the result obtained. For further validation, warehouse throughput rate in terms of time and cost is calculated for the model. At the end, twenty numerical examples are presented to demonstrate the application of the proposed methodology. Our results verified that GA was able to find better and nearer optimal solutions.

Understanding I/O Performance Behaviors of Cloud Storage from a Client’s Perspective

Cloud storage has gained increasing popularity in the past few years. In cloud storage, data is stored in the service provider’s data centers, and users access data via the network. For such a new storage model, our prior wisdom about conventional storage may not remain valid nor applicable to the emerging cloud storage. In this article, we present a comprehensive study to gain insight into the unique characteristics of cloud storage and optimize user experiences with cloud storage from a client’s perspective. Unlike prior measurement work that mostly aims to characterize cloud storage providers or specific client applications, we focus on analyzing the effects of various client-side factors on the user-experienced performance. Through extensive experiments and quantitative analysis, we have obtained several important findings. For example, we find that (1) a proper combination of parallelism and request size can achieve optimized bandwidths, (2) a client’s capabilities and geographical location play an important role in determining the end-to-end user-perceivable performance, and (3) the interference among mixed cloud storage requests may cause performance degradation. Based on our findings, we showcase a sampling- and inference-based method to determine a proper combination for different optimization goals. We further present a set of case studies on client-side chunking and parallelization for typical cloud-based applications. Our studies show that specific attention should be paid to fully exploiting the capabilities of clients and the great potential of cloud storage services.

A Survey on Determining the Characteristics of Deadlock, Scheduling and Workflow Instances and Providing New Algorithms for the Issues Arising in Hybrid Cloud

scheduling is a key concern for the execution of performance driven cloud applications. We have analyzed the various characteristics of deadlock, its occurrences and the strategies to overcome it. We have also discussed some of the algorithms used for scheduling and workflow in hybrid and grid computing. To overcome this, we can use dynamic- critical path algorithm and Cost based workflow scheduling algorithm. The goal of Grid computing is to aggregate the power of widely distributed resources. Grid is not capable of optimizing multiple scheduling but it is possible in cloud. Cloud computing is an emerging technology that provide the users on demand service. One of the issues is the occurrence of deadlock because many users are requesting for the same resource. To improve the performance of the entire system a high degree of concurrency is obtained by running multiple instances at the same time. On the other hand, since the amount of storage is limited on most systems, deadlock due to numerous storage requests would-be a problem. Keywordstask scheduling, instances, deadlock, dependency.

A Fair-Rank Ant Colony Algorithm in Distributed Mass Storage System

In general, a distributed mass storage system is composed of a large number of computing nodes and storage nodes, allowing users to access resources transparently, without knowing where the resources are physically located. For every storage request, the storage system scheduler chooses several storage nodes from the entire storage system in order to organize a substorage system. This kind of scheduling is an NP-hard problem; to achieve the storage system’s promising potential, this paper proposes a virtual subsystem quality of service scheduling model and a fair-rank ant colony algorithm. The algorithm provides special incentives to the scheduling results that include new nodes, so the new nodes will have more opportunities to participate in the scheduling system. Tests show that this algorithm performs better in the fairness and load balance than the ant colony algorithm.

Maximizing Active Storage Resources with Deadlock Avoidance in Workflow-Based Computations

Workflow-based workloads usually consist of multiple instances of the same workflow, which are jobs with control or data dependencies to carry out a well-defined scientific computation task, with each instance acting on its own input data. To maximize the performance, a high degree of concurrency is always achieved by running multiple instances simultaneously. However, since the amount of storage is limited on most systems, deadlock due to oversubscribed storage requests is a potential problem. To address this problem, we integrate two novel concepts with the traditional problem of deadlock avoidance by proposing two algorithms that can maximize active (not just allocated) resource utilization and minimize makespan. Our approach is based on the well-known banker's algorithm, but our algorithms make the important distinction between active and inactive resources, which is not a part of previous approaches. The central idea is to leverage the data-flow information to dynamically approximate localized maximum claim (i.e., the resource requirements of the remaining jobs of the instance) to improve either interinstance or intrainstance concurrency and still avoid deadlock. Through simulation-based studies, we show how our proposed algorithms are better than the classic banker's algorithm and the more recent Lang's algorithm in terms of makespan and active storage resource utilization.

De-De Dodging Algorithm for Scheduling Multiple Workflows in Hybrid Cloud

Workflow-based applications usually consist of multiple instances depending on a single workflow, which are jobs with control or data dependencies to provide a well-defined scientific computation task, with each instances acting on its own input data. Due to the raise in convention of many applications currently, there is necessitating for high processing and storage capacity along with the consideration of cost and instance use and also without any deadlocks between those instances. To improve the performance of the entire system a high degree of concurrency is obtained by running multiple instances at the same time. On the other hand, since the amount of storage is limited on most systems, deadlock due to numerous storage requests would-be a problem. In this paper we have proposed a new dependency and deadlock avoidance (De-De algorithm) algorithm along with the consideration of both instance and value. The TCHC algorithm that comes to the decision of desiring which resource should be chartered from public providers is now combined with the newly proposed De-De algorithm considering that each instance of both single and multiple workflows should work without any deadlocks. To address this problem, we have combined two new concepts with the traditional problem of deadlock avoidance by proposing a single algorithm that can maximize active (not just allocated) resource utilization and minimize makespan. Our approach is based on the well-known banker’s algorithm, but our algorithms make the important distinction between active and passive resources, which is not a part of previous approaches. Through simulation-based studies, we show how our proposed algorithms are better than the classic banker’s algorithm.

Malaria infection diagnosis: comparison between traditional methods and a new freeze-dried PCR multiplex test

Malaria is the most diffused parasitic disease that affects humans.A rapid and accurate diagnosis is a prerequisite for an effective treatment. The development of a new ready-to-use test for the screening and the typing of malaria solve the temperature storage requests of common molecular tests and PCR reagents. The performances of STAT-NAT Malaria Screening and STAT-NAT Malaria Typing kits were tested on samples obtained from patients suspected to be infected by malaria’s parasites, Immigrants (I) and International Travellers (IT), and were compared with the gold standard method (microscopy). Samples of peripheral blood of 35 patients (25 IT and 10 I) obtained from San Matteo Hospital in Pavia were analysed.The microscopy identified 18 of them as positive samples: 11 samples were positive for Plasmodium falciparum (5 IT, 6 I), 3 for Plasmodium vivax (3 IT), 2 for Plasmodium ovale (1I, 1 IT) and 2 for Plasmodium malariae (2 I). No co-infections were found. STAT-NAT Malaria kits confirmed the results of 18 positive samples as well as of 17 negative samples (100% sensitivity). In a case STAT-NAT Malaria Typing kit identified the presence of Plasmodium ovale in a sample instead of Plasmodium vivax, as previously diagnosed with the microscopic analysis.The epidemiological analysis and a new microscopic diagnosis confirmed the infection as caused by Plasmodium ovale species (100% specificity). We conclude that the association of the freeze-dried STAT-NAT Malaria tests could be determinant for the correct detection and typing of malaria, mainly where the temperature controlled storage could be problematic.

A step-by-step dual cycle sequencing method for unit-load automated storage and retrieval systems

The sequencing of requests in an automated storage and retrieval system was the subject of many studies in literature. However, these studies assumed that the locations of items to be stored and retrieved are known and the sequencing problem consisted in determining a route of minimal travel time between these locations. In reality, for a retrieval request, an item can be in multiple locations of the rack and so there is a set of locations associated with this item and not only one predetermined location in the rack. In this paper, we deal with the sequencing problem where a required product can be in several rack locations and there is a set of empty locations. Consequently, the retrieval and storage locations are not known a priori. We sequence by the minimum travel time of a double cycle (DC). An optimization method working step-by-step is developed to determine for each DC and according to storage and retrieval requests, the location of the item to be stored and the location of the item to be retrieved allowing the minimum DC time. The storage requests are processed in FCFS and retrieval requests retrievals requests are gathered by block according to wave sequencing.

CARMEN: A Neuroscience Portal for Collaboration via Tools and Data sharing

CARMEN: A Neuroscience Portal for Collaboration via Tools and Data sharing

Throughput performance of automated storage/retrieval systems under stochastic demand

In this paper we are concerned with the throughput performance of an Automated Storage/Retrieval (AS/R) system under stochastic demand, i.e., the case where storage and retrieval requests arrive randomly. Although AS/R systems have been the subject of extensive research, their performance under stochastic demand remains relatively unexplored. In fact, with random storage and retrieval requests, the primary tool for AS/R system analysis has been simulation. Assuming a particular dwell point strategy for the storage/retrieval machine, in this paper we derive closed-form analytical results to evaluate the performance of an AS/R system under stochastic demand and determine whether or not it meets throughput. Although the results are derived for a given system, they can also be used in the design or evaluation of new/proposed systems.

Optimal Scheduling Algorithms for Tertiary Storage

The ever growing needs of large multimedia systems cannot be met by magnetic disks due to their high cost and low storage density. Consequently, cheaper and denser tertiary storage systems are being integrated into the storage hierarchies of these applications. Although tertiary storage is cheaper, the access latency is very high due to the need to load and unload media on the drives. This high latency and the bursty nature of I/O traffic result in the accumulation of I/O requests for tertiary storage. We study the problem of scheduling these requests to improve performance. In particular we address the issues of scheduling across multiple tapes or disks as opposed to most other studies which consider only one or two media. We focus on algorithms that minimize the number of switches and show through simulation that these result in near-optimal schedules. For single drive libraries an efficient algorithm that produces optimal schedules is developed. For multiple drives the problem is shown to be NP-Complete. Efficient and effective heuristics are presented for both single and multiple drives. The scheduling policies developed achieve significant performance gains over naive policies. The algorithms are simple to implement and are not restrictive. The study encompasses all types of storage libraries handling removable media, such as tapes and optical disks.

沈砂池における利水の可能性に関する実験的研究

In the Amami and Okinawa area, Japan, there are a great number of settling basins established in order that suspended sediments, which float from cultivated fields to rivers or sea areas, can be sedimented and removed. Currently, there has been an increase in the number of requests for water storage in these settling basins in cultivated fields with no irrigation reservoirs in order to utilize the water for irrigation. Since settling basins are utilized as a water source, water should always be stored in settling basins. Therefore, it is necessary to investigate how this water affects the function of settling turbid water in settling basins. This paper aims at experimentally investigating the feasibility of using a settling basin as a storage basin for irrigation water use. For this, two extremities of initial water storage in a model basin, i. e., empty and full storages, are considered. The turbidity (the concentration of suspended sediments) and the quantity of water leaving the basin from its outlet are measured to evaluate the amount of suspended sediments not trapped in the basin (i. e., escaping from the basin). Different tests with different initial water storages are comparatively conducted to estimate the effect of keeping the storage full for water use on the primary function of the basin. The results show that in both cases of initial water storage the equilibrium levels to which the outflow turbidities reach as time passes are the same. The amount of the escaping suspended sediments for the initially empty storage is slightly less than that for the initially full storage. It is thus concluded that the settling basin could be used as a storage basin for irrigation water use as well.

Optimal routing in an automated storage/retrieval system with dedicated storage

We address the sequencing of requests in an automated storage/retrieval system with dedicated storage. We consider the block sequencing approach, where a set of storage and retrieval requests is given beforehand and no new requests come in during operation. The objective for this static problem is to find a route of minimal total travel time in which all storage and retrieval requests may be performed. The problem of sequencing a list of retrievals is equivalent to the Traveling Salesman Problem (TSP), and thus NP-hard in general. We show that the special case of sequencing under the dedicated storage policy can be solved in polynomial time. The results apply to systems with arbitrary positions of the input and output stations. This generalizes the models in the literature, where only combined input/output stations are considered. Furthermore we identify a single command area in the rack. At the end we evaluate the model against heuristic procedures.

Expected service time model for a rotary parking system

This paper deals with rotary parking system. For retrieval and storage request, an expected service time model is developed based on the continuous Markov process. The validity of the model is illustrated through simulation studies.

Integrated document caching and prefetching in storage hierarchies based on Markov-chain predictions

Large multimedia document archives may hold a major fraction of their data in tertiary storage libraries for cost reasons. This paper develops an integrated approach to the vertical data migration between the tertiary, secondary, and primary storage in that it reconciles speculative prefetching, to mask the high latency of the tertiary storage, with the replacement policy of the document caches at the secondary and primary storage level, and also considers the interaction of these policies with the tertiary and secondary storage request scheduling. The integrated migration policy is based on a continuous-time Markov chain model for predicting the expected number of accesses to a document within a specified time horizon. Prefetching is initiated only if that expectation is higher than those of the documents that need to be dropped from secondary storage to free up the necessary space. In addition, the possible resource contention at the tertiary and secondary storage is taken into account by dynamically assessing the response-time benefit of prefetching a document versus the penalty that it would incur on the response time of the pending document requests. The parameters of the continuous-time Markov chain model, the probabilities of co-accessing certain documents and the interaction times between successive accesses, are dynamically estimated and adjusted to evolving workload patterns by keeping online statistics. The integrated policy for vertical data migration has been implemented in a prototype system. The system makes profitable use of the Markov chain model also for the scheduling of volume exchanges in the tertiary storage library. Detailed simulation experiments with Web-server-like synthetic workloads indicate significant gains in terms of client response time. The experiments also show that the overhead of the statistical bookkeeping and the computations for the access predictions is affordable.

Sequencing methods for automated storage and retrieval systems with dedicated storage

In this paper, we study the effect of sequencing storage and retrieval requests on the performance of automated storage and retrieval systems (AS/RS) where a storage request is assigned a predetermined storage location. By exploiting this unique operating characteristic, we present several optimum and heuristic sequencing methods under static and dynamic approaches. Applications of such sequencing methods include unit-load AS/RS with dedicated storage, miniload AS/RS, and potentially unit-load AS/RS with randomized storage. We find that the sequencing methods can significantly reduce travel time by a storage and retrieval machine, thereby, increasing throughput, and that the dynamic heuristic method is simple and fast, yet considerably outperforms the others.

Relative pre-positioning of storage/retrieval machines in automated storage/retrieval system to minimize expected system response time

This paper is focused on the control problem of determining the dwell point of an idle storage/retrieval (S/R) machine in an automated S/R system to improve the overall system service level as measured by the turnaround time of requests to the system. The emphasis of the paper is on the minimization of the expected response time over all retrieval and storage requests executed by the system. The model presented is developed under the operating condition that each machine serves several dedicated aisles of the system. The aisles are assumed to exist in the same region of the automated storage/retrieval system (AS/RS) and thus form a valid order S/R zone. A solution algorithm for determining the optimal dwell point location is developed. The paper assumes a dynamic environment where orders arrive over time and are to be serviced by the S/R machine. A dwell point or strategic point to pre-position the machine is to be determined whenever the machine becomes idle in anticipation of an incoming service request. A numerical example is provided to demonstrate how the technique can be used in an actual production setting to improve the overall order turnaround time.

Database system having a plurality of nodes communicating with each other via communication network

A database system includes a communication network, and a plurality of nodes. Each node includes a data storage device, a management part managing a status of the data stored in the data storage device, and a data storage request part for generating an alternative data storage device assignment request for requesting at least one of other nodes among the plurality of nodes to store data in the data storage device of the other node via the communication network when a predetermined condition is satisfied. A determining part receives the alternative data storage device assignment request from a request node which generates the alternative data storage device assignment request and assigns a storage area in the data storage device for storing data related to the alternative data storage device assignment request by referring to the status of the data managed by the management part when the data storage device of the other node has an enough storage capacity to store the data related to the alternative data storage device assignment request.

An iterative, numeric procedure to obtain pair functions applied to two-electron systems

A general, non-variational method to obtain atomic pair excitations, which are the dominating correction to a HF wavefunction, is described in the framework of diagrammatic many-body perturbation theory. The angular part of the function is treated using the angular momentum graph technique and the radial part of the pair function is obtained as the solution of an inhomogeneous two-dimensional differential equation. The radial equations are solved using the finite difference method, which has been modified to reduce computer time and storage requests. By solving the equations iteratively, pair correlation can be obtained to all orders and expressions are given for the right-hand side of the equation. The method has been applied to some two-electron systems to demonstrate its capability.

Anomalous behavior of the fifty-percent rule in dynamic memory allocation

This paper reports simulation data showing that, in dynamic memory allocation, the average free-to-allocated-block ratio can differ considerably and in both directions from the predictions of the 50 percent rule. A new derivation is given, and it is shown that previous derivations make an assumption that may be violated frequently. On the basis of the simulation data and the derivation, it is hypothesized that the anomalous behavior results from the combined effects of systematic placement and the statistics of the release process. Additional simulations support this hypothesis. Systematic placement, which refers to the natural convention of always allocating storage requests against the same end of the free block selected by the allocation strategy, tends to order blocks within contiguous groups according to their allocation time. The degree of anomalous behavior depends on the extent to which allocated blocks are released in the order of their allocation. For non-Markovian release processes, the extent of the correlation between allocation order and release order varies approximately inversely with the coefficient of variation of the memory residence time distribution. The simulations show that allocation efficiency depends strongly on the residence time distribution; efficiency decreases as the distribution's coefficient of variation increases. Some practical implications are briefly discussed.