Siti Hafizah Ab Hamid

A survey on virtual machine migration and server consolidation frameworks for cloud data centers

Modern Cloud Data Centers exploit virtualization for efficient resource management to reduce cloud computational cost and energy budget. Virtualization empowered by virtual machine (VM) migration meets the ever increasing demands of dynamic workload by relocating VMs within Cloud Data Centers. VM migration helps successfully achieve various resource management objectives such as load balancing, power management, fault tolerance, and system maintenance. However, being resource-intensive, the VM migration process rigorously affects application performance unless attended by smart optimization methods. Furthermore, a Cloud Data Centre exploits server consolidation and DVFS methods to optimize energy consumption. This paper reviews state-of-the-art bandwidth optimization schemes, server consolidation frameworks, DVFS-enabled power optimization, and storage optimization methods over WAN links. Through a meticulous literature review of state-of-the-art live VM migration schemes, thematic taxonomies are proposed to categorize the reported literature. The critical aspects of virtual machine migration schemes are investigated through a comprehensive analysis of the existing schemes. The commonalties and differences among existing VM migration schemes are highlighted through a set of parameters derived from the literature. Finally, open research issues and trends in the VM migration domain that necessitate further consideration to develop optimal VM migration schemes are highlighted.

Application optimization in mobile cloud computing

In Mobile Cloud Computing (MCC), migrating an application processing to the cloud data centers enables the execution of resource-intensive applications on the mobile devices. However, the resource-intensive migration approaches and the intrinsic limitations of the wireless medium impede the applications from attaining optimal performance in the cloud. Hence, executing the application with low cost, minimal overhead, and non-obtrusive migration is a challenging research area. This paper presents the state-of-the-art mobile application execution frameworks and provides the readers a discussion on the optimization strategies that facilitate attaining the effective design, efficient deployment, and application migration with optimal performance in MCC. We highlight the significance of optimizing the application performance by providing real-life scenarios requiring the effective design, efficient deployment, and optimal application execution in MCC. The paper also presents cloud-based mobile application-related taxonomies. Moreover, we compare the application execution frameworks on the basis of significant optimization parameters that affect performance of the applications and mobile devices in MCC. We also discuss the future research directions for optimizing the application in MCC. Finally, we conclude the paper by highlighting the key contributions and possible research directions in cloud-based mobile application optimization.

Network-centric Performance Analysis of Runtime Application Migration in Mobile Cloud Computing

Abstract Mobile cloud computing alleviates the limitations of resource-constrained mobile devices by leveraging the cloud resources. Currently, software-level solutions, also known as computational offloading, migrate the cloud-based mobile applications at runtime to the cloud datacenter to optimize the application execution time. However, the application execution frameworks mainly focus on migrating the application without considering the various critical network-centric parameters, such as traffic load and mobility speed, in application migration decision. In this paper, we analyze the effect of network-centric parameters on the application migration process. The performance of the migration process is analyzed by simulating the migration process in OMNeT++. The effects of various parameters, such as number of users in a WLAN, size of a file containing the application and its running states, traffic load on the wireless access point, message length, number of hops to the cloud, and mobility speed, are studied on the application performance metrics such as application migration time and packet drop ratio. Our analysis shows that the application and its running states migration time is affected by the changes in the network conditions. Based on our research findings, we recommend application execution framework designers to incorporate the network-centric parameters along with other parameters in the decision process of the application migration.

Mobile Storage Augmentation in Mobile Cloud Computing: Taxonomy, Approaches, and Open Issues

Worldwide employment of mobile devices in various critical domains, particularly healthcare, disaster recovery, and education has revolutionized data generation rate. However, rapidly rising data volume intensifies data storage and battery limitations of mobile devices. Mobile Cloud Computing (MCC) as the state-of-the-art mobile computing aims to augment mobile storage by leveraging infinite cloud resources to provide unlimited storage capabilities with energy-dissipation prevention. Researchers have already surveyed varied MCC aspects and its challenges, but successful futuristic Mobile Storage Augmentation (MSA) approaches demand deep insight into the current storage augmentation solutions that highlights critical challenges, which are lacking. This paper thoroughly investigates the main MSA issues in three domains of mobile computing, cloud computing, and MCC to present a taxonomy. Also, it examines several credible MSA approaches and mechanisms in MCC, classifies characteristics of cloud-based storage resources, and presents open issues that direct future research.

A Review on mobile application energy profiling

The shift of the information access paradigm to a mobile platform motivates research in mobile application energy profiling to augment device battery lifetime. Energy profiling schemes estimate mobile application power consumption when it is executed on resource-constrained mobile devices. Accurate power estimation?helps identify rogue applications to optimize mobile battery power usage. The lack of a comprehensive survey on mobile application energy profiling schemes that covers?various energy profiling aspects, such as profiling?granularity,?types, measurement resources,?and?model flexibility, has motivated us to review the existing literature comprehensively. Application energy profiling?schemes exploit either hardware-equipment or software-based solutions to track battery-draining behavior during application execution in mobile devices. This study comprehensively reviews state-of-the-art mobile application energy profiling schemes to?investigate the strengths and weaknesses of existing schemes. We?propose a detailed thematic taxonomy based on the extensive literature review on mobile application energy profiling to classify the existing literature. The critical aspects and related features of existing energy profiling schemes are examined through an exhaustive qualitative analysis. The?significant parameters from the reported literature are also extracted to investigate commonalities and differences among existing schemes. Finally, several research issues in mobile application energy profiling are put forward that should be addressed to increase energy profiling strength.

Adapting project management method and ANFIS strategy for variables selection and analyzing wind turbine wake effect

We present a project management methodology designed for the selection of wind turbines wake effect most influential parameters, who need to run wind farm project for large energy conversion. Very frequently, the managers of these projects are not project management professionals, so they need guidance to have autonomy, using minimal time and documentation resources. Therefore, agile method is adapted to assist the project management. Wind energy poses challenges such as the reduction in the wind speed due to the wake effect by other turbines. If a turbine is within the area of turbulence caused by another turbine, or the area behind another turbine, the wind speed suffers a reduction and, therefore, there is a decrease in the production of electricity. In order to increase the efficiency of a wind farm, analyzing the parameters, which have influence on the wake effect, is one of the focal research areas. To maximize the power produced in a wind farm, it is important to determine and analyze the most influential factors on the wake effects or wake wind speeds since the effect has most influence on the produced power. This procedure is typically called variable selection, and it corresponds to finding a subset of the full set of recorded variables that exhibits good predictive abilities. In this study, architecture for modeling complex systems in function approximation and regression was used, based on using adaptive neuro-fuzzy inference system (ANFIS). Variable searching using the ANFIS network was performed to determine how the five parameters affect the wake wind speed. Our article answers the call for renewing the theoretical bases of wind farm project management in order to overcome the problems that stem from the application of methods based on decision-rationality norms, which bracket the complexity of action and interactions in projects.

Federated cloud resource management

Federation of clouds is the future of cloud computing, mobile cloud computing, Internet of things, and big data applications. The utilization of federated resources is envisioned to increase the quality of service, cost benefits, and reliability. Resource management in the federation of multiple clouds is a pressing issue owing to the lack of cross-domain knowledge, security, trust, and administrative policies. This study classifies these resource management functions in the federated cloud environment into resource pricing, resource discovery, resource selection, resource monitoring, resource allocation, and disaster management. Each federated resource management function is discussed, and insights into state-of-the-art research are then provided. These resource management functions are also compared based on the performance metrics that are suitable for an individual function. Finally, we indicate the open challenges for further research with regard to each classified resource management function.

L3OP: Learning Styles Application Using Learning Objects Approach

Learning Objects is not a new approach in electronic learning system. It has been applied since more than seven years ago. It can be clearly seen in CanCore project [9] in Canada and the emerging of several standards of Learning Objects by well-known organizations such as IEEE. L3OP (Learning Objects Technology in Object-Oriented Programming ELearning System) project applies the Learning Objects concept into electronic learning system focusing on digitalizing learning styles (especially among higher education students). The electronic learning systems have been used by these students since past few generations and many of them have been enhanced. However, some students still feel that the electronic learning systems are not as effective as they may seem. The reason is varieties of traditional methods of learning styles used by these students, for example, jotting down and highlighting notes cannot be done in the electronic learning systems. For example, some students prefer to use highlight pen or marker to underline the important notes. However, the electronic learning systems can not digitize the styles. The project is only concentrated on visual type of learners. The Learning Objects approach used in this project not only to ensure the organization of the database but also the reusability of the learning content itself.

Process state synchronization for mobility support in mobile cloud computing

Mobile Cloud Computing (MCC) extends cloud services to the resource-constrained mobile devices. Compute-intensive mobile applications can be augmented using cloud either in client/server model or through cyber foraging. However, long or permanent network disconnections due to user mobility increase the execution time and in certain cases refrain the mobile devices from getting response back for the remotely performed execution. In this paper, we propose use of process state synchronization (PSS) as a mechanism to mitigate the impact of network disconnections on the service continuity of cloud-based interactive mobile applications. To validate the PSS-based execution, we develop a mathematical model that incorporates the disconnection and synchronization intervals, and mobile device capabilities along with that of cloud. The comparison with existing mechanisms shows that PSS reduces the execution time by upto 47% for intermittent network connectivity compared to COMET and by upto 35% for optimized VM-based offloading.

Conceptual Design of Web-Based Appointment Management System using Object WebML

The rapid growth and diffusion of the Web are nurturing a novel generation of applications which grow in size and complexity. The development of such applications is a hybrid between traditional Information System development and Hypermedia authoring [8]. It challenges the existing tools and approaches for software production [8]. Currently the development of a Web application is somewhat chaotic and often ad-hoc process lacking systematic techniques and methodologies [6]. As a result, many companies today are experiencing severe problems in the management and maintenance of the Web application. Ginige et al. use the term Web crisis to describe this situation [4]. In response to that, this project is to apply Web Modeling Language (WebML) which specified for Web application and .Net four-tier architectureto the appointment management handling in the university/college environment. A Web based appointment management system called WBAMS is designed and implemented so that students and lecturers can arrange meetings in an effective and efficient way.