Nagwa L. Badr

Policy-based autonomic control service

Recently, there has been a considerable interest in policy-based, goal-oriented service management and autonomic computing. Much work is still required to investigate designs and policy models and associate meta-reasoning systems for policy-based autonomic systems. In this paper we outline a proposed autonomic middleware control service used to orchestrate self-healing of distributed applications. Policies are used to adjust the systems autonomy and define self-healing strategies to stabilize/correct a given system in the event of failures.

An Event Service Supporting Autonomic Management of Ubiquitous Systems for e-Health

An event system suitable for very simple devices corresponding to a body area network for monitoring patients is presented. Event systems can be used both for self-management of the components as well as indicating alarms relating to patient health state. Traditional event systems emphasise scalability and complex event dissemination for internet based systems, whereas we are considering ubiquitous systems with wireless communication and mobile nodes which may join or leave the system over time intervals of minutes. Issues such as persistent delivery are also important. We describe the design, prototype implementation, and performance characteristics of an event system architecture targeted at this application domain.

A semantic-based Software-as-a-Service (SaaS) discovery and selection system

With the proliferation of Software-as-a-Service in the cloud environment, users find it tiresome and time consuming to search for the right service that satisfies all their requirements. In addition, services may provide the same functionality but differ in their characteristics or the Quality of Service attributes (QoS) they offer. In this paper, we propose a semantic-based system that facilitates the SaaS publication, discovery and selection processes. To achieve these goals, we developed a unified ontology that combines services domain knowledge, SaaS characteristics, QoS metrics and real SaaS offers. A hybrid service matchmaking algorithm is introduced based on the proposed ontology. It integrates semantic-based metadata and ontology-based matching. Prototypical implementation results demonstrate the effectiveness of the proposed system.

An enhanced test case generation technique based on activity diagrams

Test case generation is a core phase in any testing process, therefore automating it plays a tremendous role in reducing the time and effort spent during the testing process. This paper proposes an enhanced XML-based automated approach for generating test cases from activity diagrams. The proposed architecture creates a special table called Activity Dependency Table (ADT) for each XML file. The ADT covers all the functionalities in the activity diagram as well as handling the decisions, loops, fork, join, merge, object and conditional threads. Then it automatically generates a directed graph called Activity Dependency Graph (ADG) that is used in conjunction with the ADT to extract all the possible final test cases. The proposed model validates the generated test paths during the generation process to ensure meeting a hybrid coverage criterion. The generated test cases can be sent to any requirements management tool to be traced against the requirements. The proposed model is prototyped on 30 differently sized activity diagrams in different domains An experimental evaluation of the proposed model is done as well. It saves time and effort besides, increases the quality of generated test cases, therefore optimizes the overall performance of the testing process Moreover, the generated test cases can be executed on the system under test using any automatic test execution tool.

Self-managed cells for ubiquitous systems

Amongst the challenges of ubiquitous computing is the need to provide management support for personal wireless devices and sensors. In this extended abstract we introduce a policy-based architecture that supports management at varying levels based on the concept of a self-managed cell. Cells include policy-driven agents that support context-based and trust-based access control and system adaptation. Cells can also organize themselves through federation and nesting.

Strictness Petroleum Prediction System Based on Fuzzy Model

Petroleum exploration and production is an industry that provides researchers with multi-variant challenging “real world†properties. Recently, some petroleum soft computing techniques have gained a greater interest in prediction within the oil industry. This paper is interested in the analysis, classifying, mining and predictions, based on fuzzy as an intelligent system and an intelligent system called the Strictness Petroleum Prediction System (SPPS), predicted results and statues of crude oil wells and they are compared with other measurement petroleum values. The evaluation study applies test cases, regression models and time series forecasting of vague petroleum datasets to achieve more accurate results. A regression model was made to show the effect of re-testing the prediction processes of petroleum factors. Prediction in time series using a non-parametric functional technique is considered, based on data which was collected from different sources (Daqing oilfield in China and distinct oilfields in Yemen).

Dynamic Distributed Database over Cloud Environment

An efficient way to improve the performance of database systems is the distributed processing. Therefore, the functionality of any distributed database system is highly dependent on its proper design in terms of adopted fragmentation, allocation, and replication methods. As a result, fragmentation, its allocation and replication is considered as a key research area in the distributed environment. The cloud computing is an emerging distributed environment that uses central remote servers and internet to maintain data and applications. In this paper, we present a dynamic distributed database system over cloud environment. The proposed system allows fragmentation, allocation, and replication decisions to be taken dynamically at run time. It also allows users to access the distributed database from anywhere. Moreover, we present an enhanced allocation and replication technique that can be applied at the initial stage of the distributed database design when no information about the query execution is available.

Auditing-as-a-Service for Cloud Storage

Cloud Storage Service (CSS) is a vital service of cloud computing which relieves the burden of storage management, cost and maintenance. However, Cloud storage introduces new security and privacy challenges that make data owners worry about their data. It is essential to have an auditing service to verify the integrity of outsourced data and to prove to data owners that their data is correctly stored in the Cloud. Recently, many researchers have focused on validating the integrity of outsourced data and proposed various schemes to audit the data stored on CSS. However, most of those schemes deal with static and single copy data files and do not consider data dynamic operations on replicated data. Furthermore, they do not have the facility to repair corrupt data. In this paper, we address these challenging issues and propose a public auditing scheme for multiple-copy outsourced data in CSS. Our scheme achieves better reliability, availability, and scalability by supporting replication and data recovery.

An Enhanced Resource Allocation Approach for Optimizing Sub Query on Cloud

Cloud computing is the latest evolution of computing. It provides services to numerous remote users with different requests. Managing the query workload in cloud environment is a challenge to satisfy the cloud users. Improving the overall performance and response time of the query execution can lead to users’ satisfaction. In this paper, we examine the problem of the slow query response time. Sub query merging and query resource allocation approaches are proposed to minimize the query execution time.

Keystroke dynamics-based user authentication service for cloud computing

User authentication is a crucial requirement for cloud service providers to prove that the outsourced data and services are safe from imposters. Keystroke dynamics is a promising behavioral biometrics for strengthening user authentication, however, current keystroke based solutions designed for certain datasets, for example, a fixed length text typed on a traditional personal computer keyboard and their authentication performances were not acceptable for other input devices nor free length text. Moreover, they suffer from a high dimensional feature space that degrades the authentication accuracy and performance.