Virtual Partitions Research Articles

Scalable and Secure Virtualization of HSM With ScaleTrust

Hardware security modules (HSMs) have been utilized as a trustworthy foundation for cloud services. Unfortunately, existing systems using HSMs fail to meet multi-tenant scalability arising from the emerging trends such as microservices, which utilize frequent cryptographic operations. As an alternative, cloud vendors provide HSMs as a service. However, such cloud-managed HSM usage models raise security concerns due to their untrusted and shared operating environment. We propose ScaleTrust, a scalable and secure system for key management. ScaleTrust allows us to scale the number of virtual HSM partitions, each of which is isolated with respect to each other and is robust against cloud insider attacks, while preserving physical isolation of the root of trust. To enable this, ScaleTrust uses Intel SGX and multiple HSM features, such as restricting key usage by controlling key attributes of in-HSM keys and establishing a secure channel using only HSM commands. Finally, we apply ScaleTrust to four real-world systems: Keyless SSL for TLS private key offloading, JSON Web Token authentication for microservices, key provisioning, and encryption in database systems. Our evaluation shows that ScaleTrust achieves multi-tenancy in a scalable way by providing multiple virtual HSMs with legacy HSM devices that are designed to support a single tenant. ScaleTrust provides security against insider threats while incurring 11.9% and 39.0% of end-to-end throughput and latency overhead for Keyless SSL compared to stand-alone HSMs.

Managing and Creation of Images in Graphical Mode

Abstract: As the number of applications grows, it becomes increasingly difficult to ship and test the software applications. The growth in the creation and testing of software applications caused an issue of dependencies. Virtual machines could eliminate some of the problems, but the number of dependencies continues to increase due to the wide range of requirements for the environments. Virtual machine partitions allow many environments to operate on a single operating system. Containers solved the problem of dependencies. Containers are lightweight, may be utilized to generate a variety of environments, and are used to ship applications from one team to another. The deployment procedure is time-consuming for redesign, especially when adding new features and versions. In this paper, we introduce a web application with features to manage images and containers and introduce the architecture of the web application with Podman. This paper highlights the advantages of using web applications to manage containers and images.

Reducing the Impact of Interjob Interference in Dragonfly Networks Using Virtual Partitions

In High-Performance Computing systems, the interference among applications that share network resources is one of the major causes of performance degradation and increase variability among different executions of the same application. In this paper we propose a Virtual Partitioning scheme for Dragonfly networks that combines a job-allocation policy with a virtual channel assignment. Our experiments confirm that our proposal offers better performance than the established schemes, also reducing variability.

Virtual-Partition Digital PCR for High-Precision Chromosomal Counting Applications.

Digital PCR (dPCR) is the gold-standard analytical platform for rapid high-precision quantification of genomic fragments. However, current dPCR assays are generally limited to monitoring 1-2 analytes per sample, thereby limiting the platform's ability to address some clinical applications that require the simultaneous monitoring of 20-50 analytes per sample. Here, we present virtual-partition dPCR (VPdPCR), a novel analysis methodology enabling the detection of 10 or more target regions per color channel using conventional dPCR hardware and workflow. Furthermore, VPdPCR enables dPCR instruments to overcome upper quantitation limits caused by partitioning error. While traditional dPCR analysis establishes a single threshold to separate negative and positive partitions, VPdPCR establishes multiple thresholds to identify the number of unique targets present in each positive droplet based on fluorescence intensity. Each physical partition is then divided into a series of virtual partitions, and the resulting increase in partition count substantially decreases partitioning error. We present both a theoretical analysis of the advantages of VPdPCR and an experimental demonstration in the form of a 20-plex assay for noninvasive fetal aneuploidy testing. This demonstration assay─tested on 432 samples contrived from sheared cell-line DNA at multiple input concentrations and simulated fractions of euploid or trisomy-21 "fetal" DNA─is analyzed using both traditional dPCR thresholding and VPdPCR. VPdPCR analysis significantly lowers the variance of the chromosomal ratio across replicates and increases the accuracy of trisomy identification when compared to traditional dPCR, yielding > 98% single-well sensitivity and specificity. VPdPCR has substantial promise for increasing the utility of dPCR in applications requiring ultrahigh-precision quantitation.

Partitioning open-plan workspaces via augmented reality

Open-plan workspaces are becoming common because of their compact footprint, economic advantages, and capacity for fostering communication. However, users of open-plan workspaces often report a high level of distraction, undermining their performance especially on individual cognitive tasks. Existing common solutions require recurrent physical changes, which are neither practical for companies and employees nor desired by interior architects. In this paper, we examine the use of augmented reality (AR) midair pervasive displays and visual separators to address the problem of visual distractions in open-plan workspaces. While past applications of AR in workspaces mostly focused on content creation and manipulation, we use AR to superimpose visual barriers—what we refer to as virtual partitions. To evaluate the impact of virtual partitioning on the occupants’ cognitive performance, we conducted two user studies with a total of 48 participants. The design of assessed virtual partitions was informed by interviews that we conducted with 11 professional space designers. The analysis of collected data suggests that virtual partitions can reduce visual distractions and enable users to personalize the visual attributes of their space leading to an improved experience of shared workspaces.

Predictability and Performance Aware Replacement Policy PVISAM for Unified Shared Caches in Real-time Multicores

Missing the deadline of an application task can be catastrophic in real-time systems. Therefore, to ensure timely completion of tasks, offline worst-case execution time and schedulability analysis is often performed for such real-time systems. One of the important inputs to this analysis is a safe upper bound of misses in each processor cache memory used by the system. Cache miss prediction techniques have matured significantly for private caches in single-core processors; however, remained as a challenge for unified, shared caches in multicore processors. According to prior studies, a task’s miss upper bound on a shared cache can be predicted using available private cache prediction techniques only if the shared cache maintains core-based independent static partitions. The problem is, such partitions require the use of infeasible “write-update consistency protocol” and wastes valuable cache space by duplicate caching. In this regard, this paper presents a novel cache replacement policy called “predictable variable isolation in shared antipodal memory (PVISAM).” Its replacement decisions generate virtual core-based partitions that support demand-based runtime size adjustment and line sharing to better utilize space. Moreover, these partitions require no consistency protocol. Trace-driven experimental results for Parsec benchmark applications reveal that performance of a unified shared cache memory improves by $101.68{\boldsymbol \times }$ on average (minimum $1.09{\boldsymbol \times }$ and maximum $1138.50{\boldsymbol \times }$ ) when PVISAM is used instead of either the aforementioned write-update protocol-based predictable partitioning or the widely used write-invalidate consistency protocol-based partitioning. PVISAM can improve cache performance by $0.74{\boldsymbol \times }$ on average (minimum $0.02{\boldsymbol \times }$ and maximum $1.12{\boldsymbol \times }$ ) compared to having no partitions at all. Both predictable partitioning and PVISAM improve unified, shared cache predictability by 63.44% (minimum 26.89% and maximum 99.99%) and 19.36% (minimum 1.58% and maximum 72.51%) on average compared to no partitions and write-invalidate protocol-based partitioning, respectively. Experimental results for synthetic traces show that PVISAM remarkably improves cache performance and predictability when compared to its three competitors even in scenarios that stress the cache.

Hierarchical load balancing as a service for federated cloud networks

The Software Defined Networking (SDN) paradigm, according to the most popular definition, proposes the ambitious vision of making network infrastructure (e.g., routers and switches) fully programmable. This approach introduces suitable levels of abstraction, in order to adaptnetwork infrastructure functions at runtime through powerful and expressive APIs. In this context, the concept of network virtualisation is of particular importance, namely the idea to create virtual partitions of the physical network infrastructure. When virtualization is applied in this domain, it allows several controller instances and their applications to populate and manage the assigned partitions. Even more useful are the aforementioned concepts when dealing with wide-area networks of cloud-hosting datacenters, especially when trying to provide, e.g., cloud-agnostic and transparent QoS, i.e., cloud-bursting. Scientific research is tackling these new trends following two approaches: multi-cloud and federated cloud. In this work we will pursue the latter, because it leaves the end-users (application owners or companies) free to focus their efforts on application-related activities. Load balancing is among the best practices to distribute user workloads fairly and dynamically among all the nodes in a scaling group, either in a data-center or across clouds. This strategy becomes even more relevant in a scenario featuring federated cloud networks. This is the context where this work finds its place, namely the design of a Load Balancing as a Service (LBaaS) approach for SDN in a OpenStack-based brokered cloud federation.

REFACTORING OF THE OPENVZ DRIVER FOR THE OPENNEBULA CLOUD PLATFORM WITHIN THE JINR CLOUD INFRASTRUCTURE PROJECT

This article explores the possibilities of using OpenVZ virtualization technology in the cloud infrastructure of the Joint Institute for Nuclear Research (JINR), built on the OpenNebula platform. OpenNebula is an open and extensible cloud platform allowing an easy automation of data centers operations. Simplicity of deployment and configuration of virtual machines without the help of specialists is the main advantage of the OpenNebula platform. Also, the main advantages of this cloud platform include the ability to dynamically change the size of the physical infrastructure by adding and removing nodes in real time and splitting the cluster into virtual partitions, which allows us to allocate only the necessary amount of resources for the operation of a certain service. OpenNebula provides a centralized interface for managing all elements of the infrastructure, both virtual and physical, and also has a high degree of utilization of available resources. Initially, OpenNebula does not support the OpenVZ virtualization technology, however its modular architecture allows using third-party drivers, in particular for OpenVZ. To deploy the virtualization technology within OpenNebula, a driver was developed by JINR and the Bogolyubov Institute of Theoretical Physics. The main advantage of OpenVZ virtualization technology is the ability to run multiple isolated copies of the operating system on a single physical server. The authors of this article had to refactor the code of the existing OpenVZ driver for the OpenNebula cloud platform. The work was done using the Ruby software environment. The results obtained are currently used in the JINR cloud infrastructure.

Handling Data Skew in MapReduce Cluster by Using Partition Tuning

The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data.

HYBRID MODEL OF RSA, AES AND BLOWFISH TO ENHANCE CLOUD SECURITY

Cloud is a term used as a metaphor for the wide area networks (like internet) or any such large networked environment. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams. It represents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Cloud based systems saves data off multiple organizations on shared hardware systems. Data segregation is done by encrypting data of users, but encryption is not complete solution. We can do segregate data by creating virtual partitions of data for saving and allowing user to access data in his partition only. In our research work we have used the hybrid combination of RSA, AES and Blowfish for data encryption along with data fragmentation using Gateway.

ENHANCED SECURITY MECHANISM IN CLOUD COMPUTING USING HYBRID ENCRYPTION ALGORITHM AND FRAGMENTATION: A REVIEW

Cloud is a term used as a metaphor for the wide area networks (like internet) or any such large networked environment. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams. It represents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Cloud based systems saves data off multiple organizations on shared hardware systems. Data segregation is done by encrypting data of users, but encryption is not complete solution. We can do segregate data by creating virtual partitions of data for saving and allowing user to access data in his partition only. We will be implementing cloud security aspects for data mining by implementing cloud system. After implementing cloud infrastructure for data mining for cloud system we shall be evaluating security measure for data mining in cloud. We will be fixing threats in data mining to Personal/private data in cloud systems. Â

Enhancing Cloud Computing Security by Using Pixel Key Pattern

Cloud is a term used as a metaphor for the wide area networks (like internet) or any such large networked environment. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams. It represents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Cloud based systems saves data off multiple organizations on shared hardware systems. Data segregation is done by encrypting data of users, but encryption is not complete solution. We can do segregate data by creating virtual partitions of data for saving and allowing user to access data in his partition only. We will be implementing cloud security aspects for data mining by implementing cloud system. After implementing cloud infrastructure for data mining for cloud system we shall be evaluating security measure for data mining in cloud. We will be fixing threats in data mining to Personal/private data in cloud systems. Â

ENHANCED SECURITY MECHANISM IN CLOUD COMPUTING: A REVIEW

Cloud is a term used as a metaphor for the wide area networks (like internet) or any such large networked environment. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams. It represents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Cloud based systems saves data off multiple organizations on shared hardware systems. Data segregation is done by encrypting data of users, but encryption is not complete solution. We can do segregate data by creating virtual partitions of data for saving and allowing user to access data in his partition only. We will be implementing cloud security aspects for data mining by implementing cloud system. After implementing cloud infrastructure for data mining for cloud system we shall be evaluating security measure for data mining in cloud. We will be fixing threats in data mining to Personal/private data in cloud systems. Â

A multi-stage method for connecting participatory sensing and noise simulations.

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales.

A Novel Approach of Cluster based Routing in Mobile Ad hoc Networks

The research on the various issues in Mobile ad hoc networks are getting popularity because of its challenging nature and all time connectivity to communicate . MANET is a random deployable network where devices mobile with dynamic topology. In the network topology, each device is termed as a node and the virtual connectivity among each node is termed as the link. Nodes in the network are dynamically organized into virtual partitions called cluster. Network simulators provide the platform to analyze the working of computer networks along with the typical devices, traffic and other entities using ns2. In this paper we analyze and provide ways of how nodes are made for routing after clustering among nodes during simulation. General Terms Clustering Scheme, Mobile adhoc Network.

Differential dose contributions on total dose distribution of 125I brachytherapy source

This work provides an improvement of the approach using Monte Carlo simulation for the Amersham Model 6711 125I brachytherapy seed source, which is well known by many theoretical and experimental studies. The source which has simple geometry was researched with respect to criteria of AAPM Tg-43 Report. The approach offered by this study involves determination of differential dose contributions that come from virtual partitions of a massive radioactive element of the studied source to a total dose at analytical calculation point. Some brachytherapy seeds contain multi-radioactive elements so the dose at any point is a total of separate doses from each element. It is momentous to know well the angular and radial dose distributions around the source that is located in cancerous tissue for clinical treatments. Interior geometry of a source is effective on dose characteristics of a distribution. Dose information of inner geometrical structure of a brachytherapy source cannot be acquired by experimental methods because of limits of physical material and geometry in the healthy tissue, so Monte Carlo simulation is a required approach of the study. EGSnrc Monte Carlo simulation software was used. In the design of a simulation, the radioactive source was divided into 10 rings, partitioned but not separate from each other. All differential sources were simulated for dose calculation, and the shape of dose distribution was determined comparatively distribution of a single-complete source. In this work anisotropy function was examined also mathematically.

Multi-objective evolutionary learning of granularity, membership function parameters and rules of Mamdani fuzzy systems

In this paper, we propose a multi-objective evolutionary algorithm (MOEA) to generate Mamdani fuzzy rule-based systems with different trade-offs between accuracy and complexity by learning concurrently granularities of the input and output partitions, membership function (MF) parameters and rules. To this aim, we introduce the concept of virtual and concrete partitions: the former is defined by uniformly partitioning each linguistic variable with a fixed maximum number of fuzzy sets; the latter takes into account, for each variable, the number of fuzzy sets determined by the evolutionary process. Rule bases and MF parameters are defined on the virtual partitions and, whenever a fitness evaluation is required, mapped to the concrete partitions by employing appropriate mapping strategies. The implementation of the MOEA relies on a chromosome composed of three parts, which codify the partition granularities, the virtual rule base and the membership function parameters, respectively, and on purposely-defined genetic operators. The MOEA has been tested on three real-world regression problems achieving very promising results. In particular, we highlight how starting from randomly generated solutions, the MOEA is able to determine different granularities for different variables achieving good trade-offs between complexity and accuracy.

X,Y, andZwaves: Extended structures in nonlinear lattices

We propose a new type of waveforms in two-dimensional (2D) and three-dimensional (3D) discrete media-multilegged extended nonlinear structures (ENSs), built as arrays of lattice solitons (tiles and stones, in the 2D and 3D cases, respectively). We study the stability of the tiles and stones analytically, and then extend them numerically to complete ENS forms for both 2D and 3D lattices, aiming to single out stable ENSs. The predicted patterns can be realized in Bose-Einstein condensates trapped in deep optical lattices, crystals built of microresonators, and 2D photonic crystals. In the latter case, the patterns provide for a technique for writing reconfigurable virtual partitions in multipurpose photonic devices.