Transforming OCL to PVS: Using Theorem Proving Support for Analysing Model Constraints

The Unified Modelling Language (UML) is a de facto standard language for describing software systems. UML models are often supplemented with Object Constraint Language (OCL) constraints, to capture detailed properties of components and systems. Sophisticated tools exist for analysing UML models, e.g., to check that well-formedness rules have been satisfied. As well, tools are becoming available to analyse and reason about OCL constraints. Previous work has been done on analysing OCL constraints by translating them to formal languages and then analysing the translated constraints with tools such as theorem provers. This project contributes a transformation from OCL to the specification language of the Prototype Verification System (PVS). PVS can be used to analyse and reason about translated OCL constraints. A particular novelty of this project is that it carries out the transformation of OCL to PVS by using model transformation, as exemplified by the OMG's Model-Driven Architecture. The project implements and automates model transformations from OCL to PVS using the Epsilon Transformation Language (ETL) and tests the results using the Epsilon Comparison Language (ECL )

Statistical Comparison of Architecture Driven Modernization with other Cloud Migration Frameworks and Formation of Clusters

Corporations are migrating their legacy software systems towards the cloud environment for amelioration, to avail benefits of the cloud. Long term success of modernizing a legacy software depends on the characteristics of the chosen cloud migration approach. Organizations must think over how strategically imperative is the chosen cloud migration framework to their business? Thus, the Object Management Group (OMG) has defined standards for the modernization process based on Architecture Driven Modernization (ADM) framework. ADM serves as a vehicle for facilitating the arrangement of information technology with business stratagem and its architecture. Until now, it seems that there is no systematic mapping among ADM and other cloud migration frameworks, highlighting the demanding features. This research aims to give an in-depth study of similar cloud migration frameworks. Thus, the researchers introduced the clusters containing cloud migration frameworks having similar features to ADM. This systematic mapping can be seen as a valuable asset for those who are interested in choosing the best migration framework from the pool of cloud modernization frameworks, according to their legacy software requirements. The clustering technique is used to appraise and compare ADM with some of the other cloud migration frameworks for highlighting the similarities and key differences. The quality of clusters is evaluated by the Rand index and Silhouette measurements. The study distills the record and yields a sound and healthy catalog for essential events and concerns that are communal in cloud migration frameworks. This research offers the one-stop-shop convenience that the industry desperately desires.

Optimizing VMs across Multiple Hosts with Transparent and Consistent Tracking of Unused Memory

Recently, Infrastructure-as-a-Service (IaaS) clouds provide virtual machines (VMs) with a large amount of memory. To make the migration of such large-memory VMs flexible, split migration has been proposed. It divides the memory of a VM into smaller pieces and transfers them to multiple destination hosts. After the migration, the VM runs across multiple hosts and its memory data is exchanged between hosts by remote paging. There is often unused memory in a large-memory VM, but data of even unused memory is transferred via the network. This paper proposes FCtrans to achieve efficient split migration and remote paging by considering unused memory. FCtrans avoids transferring data of unused memory to destination hosts on split migration. Similarly, it does not perform remote paging for unused memory and immediately continues the execution of the VM. To enable this, FCtrans keeps track of the memory usage of a VM after starting split migration. In addition, it transparently and consistently reclaims memory released after used by the guest operating system using VM introspection and deals with it as unused. We have implemented FCtrans in KVM and conducted experiments using a VM with 352 GB of memory on the StarBED testbed. It is shown that split migration became up to 29x faster and the memory access performance of a VM across multiple hosts improved by up to 85 %.2021 IEEE 14th International Conference on Cloud Computing (CLOUD), September 5-10, 2021, Chicago, IL, US

SONDEO ARQUEOLÓGICO CIERRE SUR CORTE 0 [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte, 201

Optimized Memory Encryption for VMs Across Multiple Hosts

Recently, virtual machines (VMs) with a large amount of memory are widely used. It is often not easy to migrate such a large-memory VM because VM migration requires one large destination host. To address this issue, split migration divides the memory of a VM into small pieces and transfers them to multiple destination hosts. The migrated VM exchanges its memory data between the hosts using remote paging. To prevent information leakage from the memory data in an untrusted environment, memory encryption can be used. However, encryption overhead largely affects the performance of the hosts and the VM. This paper proposes SEmigrate for optimizing the memory encryption in split migration and remote paging. SEmigrate avoids decrypting memory data at most of the destination hosts to reduce the overhead and completely prevent information leakage. Also, it selectively encrypts only the memory data containing sensitive information by analyzing the memory of the guest operating system in a VM. SEmigrate could reduce the CPU utilization during encrypted split migration by 6–20% point and improve the performance of the migrated VM with encrypted remote paging to 1.9 × .13th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2021), September 1-3, 2021, Asia University, Virtual Conference (Online Presentation

複数ホストにまたがるVMのデータ暗号化の最適化

第33回コンピュータシステム・シンポジウム（ComSys2021）, 2021年12月2日～3日, オンライン開

Chitosan Coating on Quartz Crystal Microbalance Gas Sensor for Isopropyl Alcohol and Acetone Detection

The development of acoustic wave sensors was driven by the presence of modern technology. Quartz crystal microbalance (QCM) has excellent sensing capabilities and has wide range of applications. Selection of sensing layer is crucial to ensure the performance of the QCM sensor for volatile organic compound (VOC) detection.Hence, the objective of this paper is to compare the performance of chitosan coated QCM sensor for different analyte gas: isopropyl alcohol (IPA). Finite element simulation was implemented using COMSOL Multiphysics to study the resonance frequency shift before and after sensing. Simulation results shows IPA detection shows a higher resonance frequency shift of 62.5 Hz compared to acetone due to higher molar mass. Experimental work is conducted to validate the simulation results where IPA analyte gas yields in 84.8 Hz which is higher than acetone analyte gas at 41.8 Hz. The functional groups for both sensing layer and analyte gas also affects the gas detection performance. IPA analyte gas possessed hydroxyl groups that favors to hydrogen bond formation with chitosan sensing layer. Thus, the QCM sensor with chitosan as the sensing layer has the potential for VOC sensing of different molar mass and functional groups

複数ホストにまたがるVMのデータ暗号化の最適化

近年，大容量メモリを持つ仮想マシン（VM）が利用されるようになってきているが，このようなVMのマイグレーション時に十分なメモリを持つ移送先ホストを常に確保できるとは限らない．そこで，VMのメモリを分割して複数の小さなホストに転送する分割マイグレーションが提案されている．分割マイグレーション後には，VMはメモリデータをメインホストとサブホスト間で交換するリモートページングを行いながら動作する．しかし，実行環境によっては分割マイグレーションやリモートページングの際にメモリデータを盗聴される危険性がある．メモリデータを暗号化することで情報漏洩を防ぐことができるが，暗号化のオーバヘッドにより性能が大幅に低下する．本稿では，分割マイグレーションとリモートページングにおいてメモリ暗号化の最適化を行うSEmigrateを提案する．SEmigrateはサブホストにおいてメモリデータを復号しないようにすることで暗号化のオーバヘッドを削減し，サブホストにおける情報漏洩を完全に防ぐ．また，機密情報が含まれるメモリのみを選択的に暗号化することで，さらに暗号化のオーバヘッドを削減する．そのために，SEmigrateはVM内のゲストOSやアプリケーションのメモリを解析して，メモリ属性やアプリケーション固有の情報を利用する．SEmigrateをKVMに実装し，実験を行った結果，メモリ暗号化を行う場合に分割マイグレーションとマイグレーション後のVMの性能をそれぞれ最大82%と91%改善できることが分かった．情報処理学会 第152回 システムソフトウェアとオペレーティング・システム研究会, 2021年5月27日-28日, オンライン開

Advanced vapour sensing materials: existing and latent to acoustic wave sensors for VOCs detection as the potential exhaled breath biomarkers for lung cancer

Lung cancer is the leading cause of death worldwide and has a significant impact on public health across society. Among all types of cancer, lung cancer is typically silent and it is commonly diagnosed at a later stage where treatment is rarely achievable. There is an urgent need for the development of the early diagnosis of lung cancer for an improved survival rate. Preliminary research shows that lung cancer is accompanied by increased oxidative stress which generates volatile organic compounds (VOCs). Hence, breath analysis offers the most promising solution for the early diagnosis of lung cancer as it is non-invasive and radiation free. Potential VOCs biomarkers in exhaled breath associated with oxidative stress and lipid peroxidation have been discussed to provide a quick approach to the diagnosis of lung cancer. Although gas chromatography–mass spectroscopy (GC–MS) able to analyze the VOCs biomarker, it is bulky, high cost, required expertise to handle and consumes a lot of time. Hence, the sensor-based technique provides the solution to overcome the limitation. Recently, acoustic wave sensors such as quartz crystal microbalance (QCM) and surface acoustic wave sensors (SAW) have been used to identify the presence of VOCs in various applications. This is due to its high selectivity, good reproducibility, and fast response sensing materials. The selection of vapour sensing materials plays a crucial role in developing a highly sensitive and selective and fast response acoustic wave sensors. For this purpose, various types of sensing layers from metal oxides, polymers, biopolymers and composites have been studied. We present a critical review of advanced vapour sensing materials that are primarily used in acoustic wave sensors in identifying the presence of various VOCs. Criteria to evaluate the performance of the acoustic wave sensors such as resonance frequency and sensitivity are also discussed