An Enhanced List Based Packet Classifier for Performance Isolation in Internet Protocol Storage Area Networks

Consolidation of storage into IP SANs (Internet protocol storage area network) has led to a combination of multiple workloads of varying demands and importance. To ensure that users get their Service level objective (SLO) a technique for isolating workloads is required. Solutions that exist include cache partitioning and throttling of workloads. However, all these techniques require workloads to be classified in order to be isolated. Previous works on performance isolation overlooked the classification process as a source of overhead in implementing performance isolation. However, it’s known that linear search based classifiers search linearly for rules that match packets in order to classify flows which results in delays among other problems especially when rules are many. This paper looks at the various limitation of list based classifiers. In addition, the paper proposes a technique that includes rule sorting, rule partitioning and building a tree rule firewall to reduce the cost of matching packets to rules during classification. Experiments were used to evaluate the proposed solution against the existing solutions and proved that the linear search based classification process could result in performance degradation if not optimized. The results of the experiments showed that the proposed solution when implemented would considerably reduce the time required for matching packets to their classes during classification as evident in the throughput and latency experienced.

A study of Storage Area Networks and issues in its management

A data center has hundreds of servers and storage devices running on virtual machines that can be deployed and migrated over servers as per the requirement. If each server uses local storage, migration of this storage and restoration is mandatory. An attempt to organize and track storage throughout the data center is quite tedious. Using a dedicated storage system like a storage array, it possible to collectively monitor and manage such a network. A storage area network is essentially a network dedicated to storage devices. A storage area network can interconnect devices in all its layers, therefore improving storage availability. Interconnecting all elements in SAN also reduces the chances of a single point of failure. Using the storage devices collectively improves their utilization. SAN offers to manage and maintain all devices in the network. Although SAN is beneficial, it has drawbacks when configuring, monitoring, and managing components in a large-scale network. This paper consolidates the problems associated with SAN and offers possible solutions to overcome them.

Solving the problem of energy efficiency of remote agricultural farms

The research focuses on the viability of a mathematical model of energy efficiency of agricultural sector for the case of Russia. The article describes the methodology and results of research aimed at improving energy efficiency in the activities of remote farms of the agro-industrial complex. The emphasis is placed on the application of a scientific approach based on mathematical modeling of work on a limited resource. For this purpose, the most common solutions are SAN (Storage Area Network), while the programs that are common for enterprises of the network are located on cloud servers. The results of the research were applied in a joint project with the Catalan Polytechnic University (Polytechnic University of Catalonia).

Performance Evaluation of Storage Area Network(SAN)With internet Small Computer System Interface (iSCSI)For Local System PC

SCSI is a newly emerging protocol with the goal of implementing the Storage Area Network (SAN) technology over TCP/IP,where enables to access to remote data that in attached storage disks storages - Direct Attached Storage(DAS) over IP-networked. Also it's brings economy and convenience whereas it also raises performance and reliability issues. This paper investigates about possibility , using storage technology of the SANs, and iSCSI-SAN protocol,in local system PC, to improve access to attached storage disks storages in local system, with using iSCSI-SANs as virtual storage, is rather than DAS storage in local system of PC. Explicates after experiment procedure is that improving throughput of iSCSI-SANs was better than attached storage disks storages - DAS in local system . This means is that it can use iSCSI-SANs in local system of PC as attache storage disks storages as DAS , without cost , high performance, and easy control.

SANgo: a storage infrastructure simulator with reinforcement learning support

We introduce SANgo (Storage Area Network in the Go language)—a Go-based package for simulating the behavior of modern storage infrastructure. The software is based on the discrete-event modeling paradigm and captures the structure and dynamics of high-level storage system building blocks. The flexible structure of the package allows us to create a model of a real storage system with a configurable number of components. The granularity of the simulated system can be defined depending on the replicated patterns of actual system behavior. Accurate replication enables us to reach the primary goal of our simulator—to explore the stability boundaries of real storage systems. To meet this goal, SANgo offers a variety of interfaces for easy monitoring and tuning of the simulated model. These interfaces allow us to track the number of metrics of such components as storage controllers, network connections, and hard-drives. Other interfaces allow altering the parameter values of the simulated system effectively in real-time, thus providing the possibility for training a realistic digital twin using, for example, the reinforcement learning (RL) approach. One can train an RL model to reduce discrepancies between simulated and real SAN data. The external control algorithm can adjust the simulator parameters to make the difference as small as possible. SANgo supports the standard OpenAI gym interface; thus, the software can serve as a benchmark for comparison of different learning algorithms.

A Performance Evaluation of Storage Area Network (SAN)With internet Small Computer System Interface (iSCSI)For Local System PC

iSCSI is a newly emerging protocol with the goal of implementing the Storage Area Network (SAN) technology over TCP/IP, where enables to access to remote data that in attached storage disks storages - Direct Attached Storage(DAS) over IP-networked. Also it's brings economy and convenience whereas it also raises performance and reliability issues.This paper investigates about possibility , using storage technology of the SANs, and iSCSI-SAN protocol, to improve access to attached storage disks storages in local system, with using iSCSI-SANs as virtual storage, is rather than DAS storage in local system of PC. Explicates after experiment procedure is that improving throughput of iSCSI-SANs was better than attached storage disks storages - DAS in local system . This means is that it can use iSCSI-SANs in local system of PC as attache storage disks storages as DAS , where was become fact not possible, without cost , high performance, and easy control.

Improved storage area network method for backup approach

<span>Storage Area Network (SAN) could be a dedicated storage network which carries the info between servers and storage devices. SAN offers flexibility to implement and share data between servers and remote devices instead of the traditional method that reduced the performance of service. This paper improves SAN backup method to increase the CPU utilization and reduce the load on the link; the result shows that the improved method is better than of traditional in terms of response time in FTP about 36% while the traffic data is about 3%.</span>