Hybrid Cloud System Research Articles

An IoT-Enabled Intelligent and Secure Manufacturing Model Using Blockchain in Hybrid Cloud Communication System

The smart manufacturing system can become a linked network with the help of the Internet of Things (IoT). Devices connected to the IoT are susceptible to various attacks and assaults. An effective protection plan is needed to ensure that the billions of IoT nodes are protected from these hazards. The security mechanisms on IoT devices are ineffective due to resource limitations. As a result, the academic community has recently paid attention to the cloud-, fog-, and edge-based IoT systems. A robust cloud provider is in the cloud or fog to perform computationally demanding activities, including safety, data analysis, decision-making process, and monitoring. Hash identities and upgraded Rivest–Shamir–Adleman (RSA) have been used to secure the IoT device’s data. A four-prime integer of 512 bits makes up the proposed security algorithm. A hash signature is used to provide device authentication. An effective clustering method for sensing devices based on the node level, separation from the clusters, remaining energy, and fitness has been presented for long network life. The suggested swarm-based method determines the sensor nodes’ fitness. A deep neural network- (DNN-) based resource scheduling algorithm (DNN-RSM) is meant to reduce the delay and communications overhead for IoT components in the hybrid cloud system. For optimum resource allocation, all queries originating from the cluster head are categorised using DNN based on their storage, processing, and bandwidth needs. The suggested structure delivers better outcomes, particularly regarding energy use, delay, and safety level. The results of the simulation provide credence to the concept that the proposed strategy is superior to the current system. The suggested scheme includes stringent security, decreased energy usage, decreased latency, and efficient resource utilization.

Design and implementation of a hybrid cloud system for large-scale human genomic research

In the field of genomic medical research, the amount of large-scale information continues to increase due to advances in measurement technologies, such as high-performance sequencing and spatial omics, as well as the progress made in genomic cohort studies involving more than one million individuals. Therefore, researchers require more computational resources to analyze this information. Here, we introduce a hybrid cloud system consisting of an on-premise supercomputer, science cloud, and public cloud at the Kyoto University Center for Genomic Medicine in Japan as a solution. This system can flexibly handle various heterogeneous computational resource-demanding bioinformatics tools while scaling the computational capacity. In the hybrid cloud system, we demonstrate the way to properly perform joint genotyping of whole-genome sequencing data for a large population of 11,238, which can be a bottleneck in sequencing data analysis. This system can be one of the reference implementations when dealing with large amounts of genomic medical data in research centers and organizations.

A Flexible KP-ABE Suit for Mobile User Realizing Decryption Outsourcing and Attribute Revocation

Attribute based encryption is an effective method which can solve the access control problem of cloud storage. Realizing both efficient attributes revocation and outsourcing decryption would enhance mobile user experience. In this paper, we present a new scheme of Key-Policy Attribute Based Encryption in hybrid cloud system. In our scheme, the most of computation in the decryption process can be outsourced to the cloud and the efficiency of system is improved. In addition, the attributes of malicious users or expired ones can be revoked with unrelated users offline. Moreover system consumes a little resources rather than rebuilds the system or updates all data immediately. We also give a proof of security, a detailed description of execution and efficiency analysis.

Decentralized, Revocable and Verifiable Attribute-Based Encryption in Hybrid Cloud System

Cloud can provide storage space and services for data owners to host their data, where data privacy and confidentiality become critical issues. Ciphertext policy attribute-based encryption (CP-ABE) is one of the most suitable methods to protect data privacy and provide structured access control. In this paper, we propose a multi-authority CP-ABE scheme with a direct attribute revocation mechanism, cause revocation is an inevitable problem in the application process. Under our proposed revocation mechanism, the remaining users need not to update their secret keys when revocation happens. It relies on the matching of public keys’ version and ciphertext’ version. In a cloud storage model, the update of ciphertext is executed by public cloud, which cannot be fully trusted by data owners. In this case, we propose a hybrid CP-ABE cloud storage model aiming at solving the public cloud trust management problem. The data owners can authorize private cloud to verify whether their ciphertexts have been updated to the newest version. In addition, we prove our construction secure in selective-CPA model. Finally, we compare our scheme with similar multi-authority CP-ABE schemes from functionality, communication overhead and computation cost. The simulation results show that our scheme is more efficient than similar works in encryption, decryption and revocation stages.

Deploying Docker Swarm cluster on hybrid clouds using Occopus

The paper introduces a new method of deploying complex infrastructures in hybrid clouds. The new method is based on a new cloud orchestrator, called Occopus that enables cloud independent infrastructure deployment at user level. Occopus applies a plugin based cloud access architecture. As a result, porting infrastructure among different kind of clouds or deploying an infrastructure on top of a hybrid cloud including private and public (commercial) clouds becomes straightforward. Occopus supports all the major cloud technologies and protocols like OpenStack, OpenNebula, OCCI, Amazon EC2 or CloudSigma. The paper also shows how to apply Occopus in order to deploy a Docker Swarm cluster on the top of hybrid clouds. As a concrete example it shows the deployment on a hybrid cloud system containing OpenStack, Amazon and CloudSigma clouds as components. Using hybrid clouds raises security and communication performance issues that are also covered and investigated in the paper. The technology described in the paper is intensively used in the EU H2020 project COLA for more than 20 commercial applications and on MTA Cloud that is the cloud of the Hungarian Academy of Sciences where more than 40 academic projects run.

A Secure Alignment Algorithm for Mapping Short Reads to Human Genome.

The elastic and inexpensive computing resources such as clouds have been recognized as a useful solution to analyzing massive human genomic data (e.g., acquired by using next-generation sequencers) in biomedical researches. However, outsourcing human genome computation to public or commercial clouds was hindered due to privacy concerns: even a small number of human genome sequences contain sufficient information for identifying the donor of the genomic data. This issue cannot be directly addressed by existing security and cryptographic techniques (such as homomorphic encryption), because they are too heavyweight to carry out practical genome computation tasks on massive data. In this article, we present a secure algorithm to accomplish the read mapping, one of the most basic tasks in human genomic data analysis based on a hybrid cloud computing model. Comparing with the existing approaches, our algorithm delegates most computation to the public cloud, while only performing encryption and decryption on the private cloud, and thus makes the maximum use of the computing resource of the public cloud. Furthermore, our algorithm reports similar results as the nonsecure read mapping algorithms, including the alignment between reads and the reference genome, which can be directly used in the downstream analysis such as the inference of genomic variations. We implemented the algorithm in C++ and Python on a hybrid cloud system, in which the public cloud uses an Apache Spark system.

Flexible CP-ABE Based Access Control on Encrypted Data for Mobile Users in Hybrid Cloud System

In hybrid cloud computing, encrypted data access control can provide a fine-grained access method for organizations to enact policies closer to organizational policies. This paper presents an improved CP-ABE (ciphertext-policy attribute-based encryption) scheme to construct an encrypted data access control solution that is suitable for mobile users in hybrid cloud system. In our improvement, we split the original decryption keys into a control key, a secret key and a set of transformation keys. The private cloud managed by the organization administrator takes charge of updating the transformation keys using the control key. It helps to handle the situation of flexible access management and attribute alteration. Meanwhile, the mobile user’s single secret key remains unchanged as well as the ciphertext even if the data user’s attribute has been revoked. In addition, we modify the access control list through adding the attributes with corresponding control key and transformation keys so as to manage user privileges depending upon the system version. Finally, the analysis shows that our scheme is secure, flexible and efficient to be applied in mobile hybrid cloud computing.

Elastic resource provisioning in hybrid mobile cloud for computationally intensive mobile applications

The paper addresses the integration of hybrid cloud with mobile applications. The challenge about hybrid mobile cloud resource provisioning is the trade-offs between energy consumption, performance provided to users and how resources, such as processing power and network, are being utilized. The proposed elastic hybrid mobile cloud resource provisioning model is jointly optimized to improve mobile user experience within the constraints of available resources and user QoS requirement. The paper presents the system utility of hybrid cloud system involving local cloud and public cloud infrastructure. From the perspectives of both mobile applications and cloud providers, the proposed system utility is optimized to improve the performance of mobile applications and the utilization of cloud resources. The proposed elastic hybrid mobile cloud resource provisioning algorithm includes two sub-algorithms. To evaluate and validate performance of the proposed algorithm, a series of experiments are conducted. The comparison results and analyses are discussed. The experimental results show the improvement to previous works.

Architecture and security protection scheme for distributed new energy public service platform with hybrid cloud system

Architecture and security protection scheme for distributed new energy public service platform with hybrid cloud system

Hybrid cloud entropy systems based on Wiener process

Purpose The paper outlines a self-contained scheme for multiple networking agents at a location. It proposes a mathematical model for intelligent cloud entropy management systems. The purpose of this paper is to minimize the cost of system functionality by proposing the substantial use of a cloud-based system. Design/methodology/approach The paper proposes a hybrid cloud system, based on a fractional calculus of hybrid integral systems. Its discrete dynamics are suggested by using the fractional entropy type known as Tsallis entropy. This approach is based on the Wiener process (i.e. diffusion processes). This involves the net movement of information or data from a state of high meditation to a state of low observation. This property is a basic characteristic of hybrid cloud computing systems. Findings The paper offers a number of solutions to minimize the costs of cloud systems. The method is a proficient technique for presenting various types of fractional differential solutions. Research limitations/implications Researchers are encouraged to test and modify the proposed method. Practical implications The paper includes suggestions for the expansion of a powerful method for managing and integrating cloud systems stably. Originality/value This paper addresses an acknowledged need to study how the cost function of cloud systems can be achieved.

하이브리드형 클라우드 시스템에 관한 연구

제안한 논문은 통신 네트워크 및 관련 시스템 기술에 관한 연구로 USB메모리와 클라우드 스토리지 영역을 동시에 동기화하여 네트워크 오류에 따른 클라우드 스토리지 영역 사용부재 또는 USB 메모리를 분실하는 상황이 발생되더라도 데이터를 안전하게 유지관리하기 위한 기술설계이다. 클라우드를 활용하는 사용자들의 안전한 문서관리 정책의 필요성을 기반으로 매체의 분실 및 네트워크의 오류에 따른 대책을 하이브리드형 클라우드 시스템으로 설계구축하고, 사용자의 편리성에 따른 자동 및 수동 동기화 방법을 설계한다. 마지막으로 윈도우즈 환경에 적합한 사용자의 편의보장을 위해 탐색기형 스토리지 UI를 설계함으로써 점차 늘어나는 클라우드 사용자의 안전성과 편리성을 모두 보장해주기 위한 시스템설계이다. The suggested paper studies communications network and system technology, designing data to sync to both USB memories and cloud storages at the same time, which would allow users to safely keep and manage data even in case of network troubles, affecting cloud storages, and/or loss of physical USB memories, resulting in lost data in the physical memory. The need of secure data management policy for cloud storage users form the basis of this study, offering solutions to network failures and loss of physical storage by creating hybrid cloud system. To provide convenience to windows users, the UI design should integrate that of windows explorer to maximize security and convenience.

Turnaround Time Minimization-Based Static Scheduling Model Using Task Duplication for Fine-Grained Parallel Applications onto Hybrid Cloud Environment

ABSTRACTCloud computing is a multifarious computing paradigm incorporating the benefits of service-oriented architecture and utility computing through virtualization. Hybrid cloud, an amalgamation of two or more public and/or private clouds, is gaining high popularity between users due to various reasons involving improved performance, flexible business operations, capacity expansion, optimized costs, and enhanced security. The efficient execution of fine-grained parallel applications onto hybrid cloud system becomes limited due to a number of factors. From the application point of view, it ranges from the dynamicity of the applications to their precedence and communication constraints while for the computational resources, it includes heterogeneity of processors and participating clouds with their interconnection topology. This work proposes a compile time hybrid cloud-based task duplication strategy to execute the fine-grained applications represented as directed acyclic graph (DAG) onto the hybrid cloud environment. The proposed strategy schedules the tasks based on a degree relative to the critical path in the DAG and tries to achieve lower bound of the DAG. Furthermore, it makes an effort to avoid redundant duplication by duplicating only the required parent tasks considering the available idle slots to minimize the execution time of the application. The experimental study reveals that the proposed strategy performs better than its peers in terms of achieving the lower bound more efficiently with lesser degree of duplication for fine-grained jobs. The strategy is highly useful for cloud environment as it results in lower cost of usage of resources with enhanced system utilization.

Efficient Market Strategy Based Optimal Scheduling in Hybrid Cloud Environments

Hybrid cloud is a combination of a private cloud combined with the use of public cloud services where one or several touch points exist between the environments. Depending on utilization, data center cost and the costs of the cloud provider, an efficient scheduling policy has to decide whether or not moving from private cloud to public cloud is profitable. The paper proposes a market based hybrid cloud optimal scheduling optimization in hybrid cloud. The hybrid cloud marketplace is a virtual place where one or more public cloud providers and private cloud users meet to negotiate simultaneously. The scheduling optimization is conducted by hybrid cloud local scheduling and hybrid cloud global scheduling. For the global scheduling, the hybrid cloud system implements the allocation of public cloud resources to the private cloud application groups; the private cloud application group coordinates the deployments of all private cloud applications that consume the allocation of public cloud resources. For the local scheduling, the private cloud local level adjusts the cloud resource usages to optimize the utility of single private cloud application. In the simulations, compared with other related algorithm, our proposed market based hybrid cloud optimal scheduling algorithms achieve the better performance in terms of QoS satisfaction rate and allocation efficiency.

Integrated Care Concept using Smart Items and Cloud Infrastructure

Abstract In this paper, we explain the OpSIT approach of an integrated cloud system targeting health care facilities and their care staff. Main objective is providing a platform that integrates different smart items in order to support care processes. Therefore, knowledge of the business processes and their related tasks is highly necessary and can be properly gained with the use of Business Process Modeling Notation. We present two independent use cases which are integrated with a secure hybrid cloud system using different access levels and mechanisms, smart gateways for pre-processing and smart items for measuring. The considered smart items are smart blister dispenser, smart emergency button and smart watch.

Request Stream Control for the Access to Broadband Multimedia Educational Resources in the Distance Learning System

This article presents a model of queuing system for broadband multimedia educational resources, as well as a model of access to a hybrid cloud system storage. These models are used to enhance the efficiency of computing resources in a distance learning system. An additional OpenStack control module has been developed to achieve the distribution of request streams and balance the load between cloud nodes.

IBC-Based Entity Authentication Protocols for Federated Cloud Systems

Cloud computing changes the service models of information systems and accelerates the pace of technological innovation of consumer electronics. However, it also brings new security issues. As one of the important foundations of various cloud security solutions, entity authentication is attracting increasing interest of many researchers. This article proposes a layered security architecture to provide a trust transmission mechanism among cloud systems maintained by different organizations. Based on the security architecture, four protocols are proposed to implement mutual authentication, data sharing and secure data transmission in federated cloud systems. The protocols not only can ensure the confidentiality of the data transferred, but also resist man-in-the-middle attacks and masquerading attacks. Additionally, the security properties of the four protocols have been proved by S-pi calculus formal verification. Finally, the performance of the protocols is investigated in a lab environment and the feasibility of the security architecture has been verified under a hybrid cloud system.