Computer System Resources Research Articles

New Algorithms for Secure Outsourcing of Large-Scale Systems of Linear Equations

Cloud computing is the on-request accessibility of computer system resources, specially data storage and computing power, without direct dynamic management by the client. In the simplest terms, cloud computing means storing and accessing data and programs over the Internet instead of your computer’s hard drive. Along the improvement of cloud computing, more and more applications are migrated into the cloud. A significant element of distributed computing is pay-more only as costs arise. Distributed computing gives strong computational capacity to the general public at diminished cost that empowers clients with least computational assets to redistribute their huge calculation outstanding burdens to the cloud, and monetarily appreciate the monstrous computational force, transmission capacity, stockpiling, and even reasonable programming that can be partaken in a compensation for each utilization way Tremendous bit of leeway is the essential objective that forestalls the wide scope of registering model for clients when their secret information are expended during the figuring procedure. Critical thinking is a system to arrive at the pragmatic objective of specific instruments that tackles the issues as well as shield from pernicious practices.. In this paper, we examine secure outsourcing for large-scale systems of linear equations, which are the most popular problems in various engineering disciplines. Linear programming is an operation research technique formulates private data by the customer for LP problem as a set of matrices and vectors, to develop a set of efficient privacy-preserving problem transformation techniques, which allow customers to transform original LP problem into some arbitrary one while protecting sensitive input/output information. Identify that LP problem solving in Cloud component is efficient extra cost on cloud server. In this paper we are utilizing Homomorphic encryption system to increase the performance and time efficiency.

Hyperband Tuned Deep Neural Network With Well Posed Stacked Sparse AutoEncoder for Detection of DDoS Attacks in Cloud

Cloud computing has very attractive features like elastic, on demand and fully managed computer system resources and services. However, due to its distributed and dynamic nature as well as vulnerabilities in virtualization implementation, the cloud environment is prone to various cyber-attacks and security issues related to cloud model. Some of them are inability to access data coming to and from cloud service, theft and misuse of data hosted, no control over sensitive data access, advance threats like malware injection attack, wrapping attacks, virtual machine escape, distributed denial of service attack (DDoS) etc. DDoS is one of the notorious attack. Despite a number of available potential solutions for the detection of DDoS attacks, the increasing frequency and potency of recent attacks and the constantly evolving attack vectors, necessitate the development of improved detection approaches. This article proposes a novel architecture that combines a well posed stacked sparse AutoEncoder (AE) for feature learning with a Deep Neural Network (DNN) for classification of network traffic into benign traffic and DDoS attack traffic. AE and DNN are optimized for detection of DDoS attacks by tuning the parameters using appropriately designed techniques. The improvements suggested in this article lead to low reconstruction error, prevent exploding and vanishing gradients, and lead to smaller network which avoids overfitting. A comparative analysis of the proposed approach with ten state-of-the-art approaches using performance metrics-detection accuracy, precision, recall and F1-Score, has been conducted. Experiments have been performed on CICIDS2017 and NSL-KDD standard datasets for validation. Proposed approach outperforms existing approaches over the NSL-KDD dataset and yields competitive results over the CICIDS2017 dataset.

An Empirical Research For Secured Storage And Protecting Unauthorized Access Of Organ Donor Details

Cloud computing is the on-demand availability of computer system resources, particularly data storage and computing power, without direct active management by the user. Here an online organ donation system is developed with the help of the aforementioned technologies. The main aim of the paper is to make sure that the organs of the people, who have come forward to donate, reach the respective individual in need of the particular organ. Since everything is stored in the cloud, anybody can access it anytime, which in turn puts the data at risk. The secured sharing of donor detail is necessary. Encryption is done at two levels to provide security, one while the data is entered and the other done by a third party providing proxy re-encryption. Now, whenever a brain-dead patient is in the hospital, after thorough verification for any complications, the deciding parameters such as the organs that can be transplanted, blood group, presence of HIV positive and location, is compared with the cloud database using query filtering, which results in the nearest organ donor available meeting the requirements. The performance enhancement of cloud data using encryption schemes is of high potential.

COMPUTATION FACTORIZATION OF NUMBER AT CHIP MULTITHREADING MODE

Context. Ensuring high-speed calculation by computer systems of the classical task of factorization of integer value on simple factorsrequires the development of effective algorithmic methods using the latest information technologies. Fast computation of factorization ofnumbers to provide high cryptocapability of information data, using multidimensional representation of one-dimensional sequences ofinformation data and other applications is sufficiently in demand in many practical tasks.Objective.The purpose of the work is to improve the method of trial divisions to compute the factorization of integer value with usingparallelization of computations and efficient use of computing resources of computer systems, which ensures faster computation of thevalues of prime factors of the decomposition.Method. It is proposed to use the residuals of each digit of the binary representation of the factorization number in order to check fordivisibility in the method performing of trial divisions into prime numbers.Results. The result of the study is to develop of a program of parallel execution of the factorization of integer value in computer systemswith multi-core processors.Conclusions. In the research, a method of checking for divisibility using the residuals of each digit of the binary representation of thefactorization number was applied, which allows for multi-threaded mode to execute the decomposition of the number into the factors. Thebasic idea of applying the corresponding mathematical apparatus is to use the residuals of the integer exponent of the number two from primenumbers. As a result, the accumulation of residuals is performed, which is checked for equality with the corresponding prime number and itsdegrees. The possibility of a multithreaded software organization for computing the number factorization ensures its parallel execution inmulti-core processors of computer systems

The Literature Review of Cloud-based Enterprise Resource Planning

Enterprise Resource Planning also called ERP is a system that is integrated into business processes in a company, some of the benefits of implementing ERP are higher productivity, better insights, accelerated reporting, lower risk, simpler IT and improved agility. However, ERP also has several disadvantages such as high costs, maintenance costs and this became a common problem when using the ERP system. One way to cut high costs is to use cloud computing. Cloud computing is pools of configurable computer system resources and higher-level services that can be rapidly provisioned management effort, often over the internet, cloud computing also can be the solution for companies that want to implement ERP system with low prices. In this paper, we collect several journals about cloud computing and ERP system and combine that into one literature, and this paper discusses methodology, metadata analysis and future journals related to cloud computing and ERP system

Toward High Performance Solutions as Services of Research Digital Platform

The issues of offering services for providing resources of high-performance hybrid computer systems in applied and fundamental research within the framework of a unified digital platform are considered. Approaches for providing parallel execution of various tasks in a distributed computing cluster are proposed. The problems of organization of the computing process in the joint use of computing resources of a distributed hybrid cluster and organization of network interaction using software-defined networks are formulated.

Cluster based Hybrid Approach to Task Scheduling in Cloud Environment

Cloud computing technology enables sharing of computer system resources among users through internet. Many numbers of users may request for sharable resources from a cloud. The sharable resources must be effectively distributed among requested users with in a less amount of time. Task scheduling is one of the ways of handling the user requests effectively in a cloud environment. There were many existing biologically inspired optimization techniques worked with task scheduling problems. The proposed paper is aimed at clubbing clustering techniques with biologically inspired optimization algorithms for deriving better results. A new hybrid methodology KPSOW (K-means with PSO using weights) has been proposed in the paper, which makes use of the strengths of both the K-means and PSO algorithms with the inclusion of weights concept. The results have shown that KPSOW has made considerable changes in reducing the makespan and improves the utilization of computing resources in the cloud.

Спецификация модели управления доступом к разнокатегорийным ресурсам компьютерных систем

Спецификация модели управления доступом к разнокатегорийным ресурсам компьютерных систем

Automated and High Accuracy Out-Of-Hospital Heart Diseases Early Detection System

Background: ECG measurement and analysis being performed in-hospital normally check patients with obvious symptoms. Asymptomatic patients, for example, those with silent ischemia, paroxysmal atrial fibrillation and Brugada syndrome are very difficult to detect using in-hospital ECG system. To make matter worst, conventional ECG analysis techniques only focuses in time domain that limits the sensitivity, specificity and accuracy of the interpretation due to ECG signals non-stationary nature. Most recent researches have proposed linear joint time-frequency analysis to overcome these limitations, however, their linear methods limit their accuracy. Objective: The main objective is to enable automated and high accuracy out-of-hospital ECG analysis for early detection of heart disease. Materials & Methods: MIT-BIH ECG databases are used to test the performance of the proposed system. The data is pre-processed for amplitude normalization and frequency resampling. The pre-processed output is then fed to the non-linear joint time-frequency algorithm for analysis. The outcome of the analysis is further classified by the machine learning algorithm. Before the classification can be performed, the intelligent classifier is trained using control data that contains 52 normal and 148 patients data. After that, it is used for classifying 40 normal and 88 patients with ischaemia. The entire processes is automated inside a computer. The main disadvantage of the proposed non-linear joint time-frequency technique together with the intelligent classification is that it requires huge amount of computing system resources (big data problem). To solve this issue the system can be connected to the cloud to further enhance the performance and the accuracy of the system. Results: The analysis is performed on 421632 normal and 863282 patients ECG beats. The results obtained show that the system gives high performance of accuracy, sensitivity and specificity with values of 99.03%, 99.59% and 99.57%, respectively. Conclusions: The proposed method operates in joint time-frequency in non-linear fashion. Hence it produces more accurate interpretation compared to the conventional time domain and the more recent linear time-frequency techniques. The high accuracy together with the automated capability of the system can help detect heart problems at the early stages even before the patients pay visit to the hospital.

Modified stretched exponential model of computer system resources management limitations—The case of cache memory

In this paper we present some preliminary results in the field of computer systems management with relation to Tsallis thermostatistics and the ubiquitous problem of hardware limited resources. In the case of systems with non-deterministic behaviour, management of their resources is a key point that guarantees theirs acceptable performance and proper working. This is very wide problem that stands for many challenges in financial, transport, water and food, health, etc. areas. We focus on computer systems with attention paid to cache memory and propose to use an analytical model that is able to connect non-extensive entropy formalism, long-range dependencies, management of system resources and queuing theory. Obtained analytical results are related to the practical experiment showing interesting and valuable results.

Distributed Computer System Resources Control Mechanism Based on Network-Centric Approach

Distributed Computer System Resources Control Mechanism Based on Network-Centric Approach

GERT-model of the initial code generation cyber-attack unauthorized access to computer system resources Peer Network

GERT-model of the initial code generation cyber-attack unauthorized access to computer system resources Peer Network

Pemrosesan Paralel pada Low Pass Filtering Menggunakan Transform Cosinus di MPI (Message Passing Interface)

Parallel processing is a process of calculating two or more tasks simultaneously through the optimization of the computer system resource, one treatment models is a desktop system. The model allows to perform parallel processing between computers with specifications different computers. An implementation of a model network of workstations using MPI (Message Passing Interface). In this study, applied to the case of the low-pass filtering (LPF), a process in the image or the image of the shape of the filter that retrieves the data at low frequencies. filtering programs lowpass using the cosine transform MPI implemented by modifying the algorithm in the process on each node (computer). Depending on the test results, so that the processing speed of a parallel system is influenced by the number of nodes / processes and the number of frequency components that are processed. In the treatment of single larger process, the time it takes more and more and the value prop affects only the amount of high frequency data is filtered on the field. While parallel processing of more and more computers involved in the filter calculation process low-pass, plus the time required to perform the calculation.

ReBudget

Efficiently allocating shared resources in computer systems is critical to optimizing execution. Recently, a number of market-based solutions have been proposed to attack this problem. Some of them provide provable theoretical bounds to efficiency and/or fairness losses under market equilibrium. However, they are limited to markets with potentially important constraints, such as enforcing equal budget for all players, or curve-fitting players' utility into a specific function type. Moreover, they do not generally provide an intuitive "knob" to control efficiency vs. fairness. In this paper, we introduce two new metrics, Market Utility Range (MUR) and Market Budget Range (MBR), through which we provide for the first time theoretical bounds on efficiency and fairness of market equilibria under arbitrary budget assignments. We leverage this result and propose ReBudget , an iterative budget re-assignment algorithm that can be used to control efficiency vs. fairness at run-time. We apply our algorithm to a multi-resource allocation problem in multicore chips. Our evaluation using detailed execution-driven simulations shows that our budget re-assignment technique is intuitive, effective, and efficient.

ReBudget

Efficiently allocating shared resources in computer systems is critical to optimizing execution. Recently, a number of market-based solutions have been proposed to attack this problem. Some of them provide provable theoretical bounds to efficiency and/or fairness losses under market equilibrium. However, they are limited to markets with potentially important constraints, such as enforcing equal budget for all players, or curve-fitting players' utility into a specific function type. Moreover, they do not generally provide an intuitive "knob" to control efficiency vs. fairness. In this paper, we introduce two new metrics, Market Utility Range (MUR) and Market Budget Range (MBR), through which we provide for the first time theoretical bounds on efficiency and fairness of market equilibria under arbitrary budget assignments. We leverage this result and propose ReBudget , an iterative budget re-assignment algorithm that can be used to control efficiency vs. fairness at run-time. We apply our algorithm to a multi-resource allocation problem in multicore chips. Our evaluation using detailed execution-driven simulations shows that our budget re-assignment technique is intuitive, effective, and efficient.

Research on Network Architecture of the E-commerce Platform and Optimization of the System Performance

With the rapid development of computer technology, especially the rapid development of network technology and the acceleration of global economic integration, electronic commerce has been used more and more widely. This also puts forward a new standard for the enterprise application computer to business activities. On one hand, we should take into account the advanced nature of the electronic commerce platform, on the other hand, we should make the existing business system of the enterprise more smoothly into the new business platform. Aiming at the problem of resource bot- tleneck in current e-commerce system, the application model of grid based electronic commerce system is put forward to be based on the application background of grid technology. How to make full use of the existing software and hardware resources, to obtain the largest data processing capacity has become an important part of the electronic commerce plat- form application system. With the rapid development of economic globalization and the rapid development of Internet technology, e- commerce which is a new business model has been the world's attention and recognition. It has become the only way for the development of enterprises, which is gradually changing the business model around the world and triggering a far-reaching economic revolution. With the continuous expansion of electronic commerce, traffic system is more and more big, size of the system database is also increasing, and the property problem of the database is getting more and more prominent. Therefore, the optimization is very impor- tant to electronic commerce system database. The basic prin- ciple of system performance optimization is: access to the required data through the least possible disk access. To evaluate the database performance, in the database before and after the adjustment of the evaluation indexes should be compared, including the trade-off between response time and throughput, the availability of a database, the hit rate of the database, and the use efficiency of memory. It can measure the effect of adjustment measures to guide the direction of adjustment. How to use limited computer system resources for more users? How to guarantee the user's response speed and service quality? These problems can improve the service quality of the electronic commerce platform.

Development of Models and Methods for Optimal Allocation of Information Resources in Computer Systems

The article considered carefully the task of distribution of information resources across the nodes of a computer system. Distribution problem solved during the design of information systems, and in the process re-engineering. Such problems include the class of block- symmetric problems of discrete programming. To solve the above problem and developed an effective algorithm for iterative mapping.

МЕТОД ДИНАМИЧЕСКОГО ФОРМИРОВАНИЯ ПУЛОВ В ИНФОРМАЦИОННО-ВЫЧИСЛИТЕЛЬНЫХ СИСТЕМАХ ВОЕННОГО НАЗНАЧЕНИЯ

Purpose: Military computing systems can face situations when the amount of the tasks drastically increases, or when the systems degrades owing to natural failures and/or adversary's impact. In these situations, the computing system resources are usually insufficient and the functional environment is generally non-stochastic. This research is devoted to the problem of resource distribution for tasks in a non-stochastic environment using adaptive control theory methods. Methods: The informational and technical impact is formalized to specify adversary's opportunities in changing the computing system structure. This helps to create a computing system model in real time during the control process. The pool (assembled resources) is created during the solution of a modified bin packing problem. To speed it up, the set of alternatives is narrowed down step by step, and the tasks are distibuted over the system on a phased basis. Results: A method was proposed which adapts the current structure of a distributed heterogeneous computing system with stationary and mobile elements in order to assemble pools appropriate for the tasks. A pool is assembled from processors, links, inputoutput facilities and storage units. Originally, a pool has an entry-point for the task, i.e. the initial element for the task execution. Later the pool is expanded by adjacent elements. The expanding procedure repeats until all the system resources are used up or until a pool with necessary characteristics is assembled. The obtained pool is not optimal but its assembly time is close to real. Convergence and termination of the proposed method were proved. An example was given, and the conditions of using the method were shown. Practical relevance: The results of the research can be used for building an integrated informational environment of various governmental services using military automated systems.

Innovative Bidimensional Absolute Transducer Based on Video Detection for Positioning into Micro Assembly Processes

This paper explains and demonstrates a method to interconnect the video detection data flow with an innovative coded grid in order to precisely associate absolute coordinates to any scanned (micro) objects over a large area, without the aid of external bulky sensors. The concept of measuring micro-objects absolute coordinates is based on a series of coded information markings (micrometric terminal blocks) regularly and precisely printed on the bottom reference surface. In this manner the image processing could extract the values of the coded markings and precisely provide absolute coordinates for the camera image. The correspondence between the object and its absolute coordinates seems therefore straightforward. A very important challenge which must be solved is to read the information in real time, the method solving an optimization problem between the required processing speed and the maximum computing system resources. Finally it was obtained an innovative mechatronic system made of two essential sub-systems: the vision detection for micro-objects absolute reference positioning and characterization and a 3D micro-robotic translator for working space displacement. This system insured automatic scanning of micro-objects over large working spaces, detection process storing all specific information into a unique database file, which the operator can easily use to assign a set of automatic “pick-and-place” tasks for various micro assembly processes, as presented in the application example.

Hardware-software collaboration for secure coexistence with kernel extensions

Our society is dependent upon computer systems that are the target of a never-ending siege against their resources. One powerful avenue for exploitation is the operating system kernel, which has complete control of a computer system's resources. The current methodology for kernel design, which involves loadable extensions from third parties, facilitates compromises. Most of these extensions are benign, but in general they pose a threat to system trustworthiness: they run as part of the kernel and some of them can be vulnerable or malicious. This situation is paradoxical from a security point of view: modern OSes depend, and must co-exist, with untrustworthy but needed extensions. Similarly, the immune system is continuously at war against various types of invaders and, through evolution, has developed highly successful defense mechanisms. Collaboration is one of these mechanisms, where many players throughout the body effectively communicate to share attack intelligence. Another mechanism is foreign body co-existence with its microbiota. Remarkably, these properties are not leveraged in kernel defense approaches. Security approaches at the OS and virtual machine layers do not cooperate with each other or with the hardware. This paper advocates a new paradigm for OS defense based on close collaboration between an OS and the hardware infrastructure, and describes a hardware-software architecture realizing this vision. It also discusses the architecture design at the OS and hardware levels, including experimental results from an emulator-based prototype, and aspects of an ongoing hardware implementation. The emulator-based proof-of-concept prototype, Ianus, uses Linux as the OS and the Bochs x86 emulator as the architecture layer. It successfully minimized kernel extensions interactions with the original kernel. Its security was evaluated with real rootkits and benign extensions. Ianus' performance was analyzed with system and CPU benchmarks and it caused a small overhead to the system (approximately 12%).