• Journal of Information Processing Systems
• /
• v.15 no.2
• /
• pp.239-250
• /
• 2019

An individual's health data is very sensitive and private. Such data are usually stored on a private or community owned cloud, where access is not restricted to the owners of that cloud. Anyone within the cloud can access this data. This data may not be read only and multiple parties can make to it. Thus, any unauthorized modification of health-related data will lead to incorrect diagnosis and mistreatment. However, we cannot restrict semipublic access to this data. Existing security mechanisms in e-health systems are competent in dealing with the issues associated with these systems but only up to a certain extent. The indigenous technologies need to be complemented with current and future technologies. We have put forward a method to complement such technologies by incorporating the concept of blockchain to ensure the integrity of data as well as its provenance.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.9
• /
• pp.315-320
• /
• 2015

In cloud computing, server virtualization supports one or more virtual machines loaded on multiple operating systems on a single physical host server. Migration of a VM is moving the VM running on a source host to another physical machine called target host. A VM live migration is essential to support task performance optimization, energy efficiency and energy saving, fault tolerance and load balancing. In this paper, we propose open source based adaptive VM live migration technique. For this, we design VM monitoring module to decide VM live migration and open source based full-virtualization hypervisor.

• Journal of Information Processing Systems
• /
• v.8 no.4
• /
• pp.555-566
• /
• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• Information and Communications Magazine
• /
• v.31 no.3
• /
• pp.103-116
• /
• 2014

This paper proposes the design of Vehicular Cyber-Physical Systems (called VCPS) based on vehicular cloud for smart road networks. Our VCPS realizes mobile cloud computing services where vehicles themselves or mobile devices (e.g., smartphones and tablets of drivers or passengers in vehicles) play a role of both cloud server and cloud client in the vehicular cloud. First, this paper describes the architecture of vehicular networks for VCPS and the delay modeling for the event prediction and data delivery, such as a mobile node's travel delay along its navigation path and the packet delivery delay in vehicular networks. Second, the paper explains two VCPS applications as smart road services for the driving efficiency and safety through the vehicular cloud, such as interactive navigation and pedestrian protection. Last, the paper discusses further research issues for VCPS for smart road networks.

• Journal of Communications and Networks
• /
• v.18 no.2
• /
• pp.135-149
• /
• 2016

Cloud radio access network (C-RAN) refers to the virtualization of base station functionalities by means of cloud computing. This results in a novel cellular architecture in which low-cost wireless access points, known as radio units or remote radio heads, are centrally managed by a reconfigurable centralized "cloud", or central, unit. C-RAN allows operators to reduce the capital and operating expenses needed to deploy and maintain dense heterogeneous networks. This critical advantage, along with spectral efficiency, statistical multiplexing and load balancing gains, make C-RAN well positioned to be one of the key technologies in the development of 5G systems. In this paper, a succinct overview is presented regarding the state of the art on the research on C-RAN with emphasis on fronthaul compression, baseband processing, medium access control, resource allocation, system-level considerations and standardization efforts.

• Journal of Information Processing Systems
• /
• v.13 no.3
• /
• pp.476-490
• /
• 2017

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down, the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service. To maintain threshold, the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.7
• /
• pp.3026-3049
• /
• 2016

Cloud computing promises high performance and cost-efficiency. However, most cloud infrastructures operate at a low utilization, which greatly adheres cost effectiveness. Previous works focus on seeking efficient virtual machine (VM) consolidation strategies to increase the utilization of virtual resources in production environment, but overlook the under-utilization of backup virtual resources. We propose a heuristic time sharing policy of backup VMs derived from the restless multi-armed bandit problem. The proposed policy achieves increasing backup virtual resources utilization and providing high availability. Both the results in simulation and prototype system experiments show that the traditional 1:1 backup provision can be extended to 1:M (M≫1) between the backup VMs and the service VMs, and the utilization of backup VMs can be enhanced significantly.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.197-205
• /
• 2022

The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

• Journal of Information Processing Systems
• /
• v.20 no.4
• /
• pp.432-441
• /
• 2024

To improve the security of gene information and the accuracy of matching, this paper designs a homomorphic encryption algorithm for gene matching based on cloud computing environment. Firstly, the gene sequences of cloud files entered by users are collected, which are converted into binary code by binary function, so that the encrypted text is obviously different from the original text. After that, the binary code of genes in the database is compared with the generated code to complete gene matching. Experimental analysis indicates that when the number of fragments in a 1 GB gene file is 65, the minimum encryption time of the algorithm is 80.13 ms. Aside from that, the gene matching time and energy consumption of this algorithm are the least, which are 85.69 ms and 237.89 J, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5419-5436
• /
• 2016

Enhancing the performance of computing systems has been an important topic since the invention of computers. The leading-edge technologies of multicore and virtualization dramatically influence the development of current IT systems. We study performance attributes of response time (RT), throughput, efficiency, and scalability of a virtualized Web system running on a multicore server. We build virtual machines (VMs) for a Web application, and use distributed stress tests to measure RTs and throughputs under varied combinations of virtual cores (VCs) and VM instances. Their gains, efficiencies and scalabilities are also computed and compared. Our experimental and analytic results indicate: 1) A system can perform and scale much better by adopting multiple single-VC VMs than by single multiple-VC VM. 2) The system capacity gain is proportional to the number of VM instances run, but not proportional to the number of VCs allocated in a VM. 3) A system with more VMs or VCs has higher physical CPU utilization, but lower vCPU utilization. 4) The maximum throughput gain is less than VM or VC gain. 5) Per-core computing efficiency does not correlate to the quality of VCs or VMs employed. The outcomes can provide valuable guidelines for selecting instance types provided by public Cloud providers and load balancing planning for Web systems.