Huah-Yong Chan

Bio: Huah-Yong Chan is an academic researcher from Universiti Sains Malaysia. The author has contributed to research in topics: Computer science & Negotiation. The author has an hindex of 3, co-authored 3 publications receiving 42 citations.

Conflict Resolution in Resource Federation with Intelligent Agent Negotiation

Abstract: Resource federation in grid computing (Foster et al., 1999, 2001) still requires extensively intervention of resource administrator which is time and cost consuming. This limitation leads to the idea of applying the autonomous intelligent agent to ease the process of resource federation (Foster et al., 2004). The participation and contribution of resources are based on a set of rules and regulations, namely local administrative policies. The local administrative policies can be further detailed into accounting policy, access control policy, resource usage policy and more (Foster et al., 2001). In this study, resource usage policy (as shown in Fig. 1) specifies the requirements and limits on particular resources during resource federation between various participants. A consensus among the participants is achieved through a bargaining mechanism, which aims at maximizing the satisfaction level during policy negotiation. The policy negotiation involves the satisfaction of policy criteria.

Generative adversarial networks with data augmentation and multiple penalty areas for image synthesis

Abstract: The quality of generated images is one of the significant criteria for Generative Adversarial Networks (GANs) evaluation in image synthesis research. Previous researches proposed a great many tricks to modify the model structure or loss functions. However, seldom of them consider the effect of combination of data augmentation and multiple penalty areas on image quality improvement. This research introduces a GAN architecture based on data augmentation, in order to make the model fulfill 1-Lipschitz constraints, it proposes to consider these additional data included into the penalty areas which can improve ability of discriminator and generator. With the help of these techniques, compared with previous model Deep Convolutional GAN (DCGAN) and Wasserstein GAN with gradient penalty (WGAN-GP), the model proposed in this research can get lower Frechet Inception Distance score (FID) score 2.973 and 2.941 on celebA and LSUN towers at 64×64 resolution respectively which proves that this model can produce high visual quality results.

Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform

Abstract: Distributed resource allocation is a very important and complex problem in emerging horizontal dynamic cloud federation (HDCF) platforms, where different cloud providers (CPs) collaborate dynamically to gain economies of scale and enlargements of their virtual machine (VM) infrastructure capabilities in order to meet consumer requirements HDCF platforms differ from the existing vertical supply chain federation (VSCF) models in terms of establishing federation and dynamic pricing There is a need to develop algorithms that can capture this complexity and easily solve distributed VM resource allocation problem in a HDCF platform In this paper, we propose a cooperative game-theoretic solution that is mutually beneficial to the CPs It is shown that in non-cooperative environment, the optimal aggregated benefit received by the CPs is not guaranteed We study two utility maximizing cooperative resource allocation games in a HDCF environment We use price-based resource allocation strategy and present both centralized and distributed algorithms to find optimal solutions to these games Various simulations were carried out to verify the proposed algorithms The simulation results demonstrate that the algorithms are effective, showing robust performance for resource allocation and requiring minimal computation time

High availability in clouds: systematic review and research challenges

Abstract: Cloud Computing has been used by different types of clients because it has many advantages, including the minimization of infrastructure resources costs, and its elasticity property, which allows services to be scaled up or down according to the current demand. From the Cloud provider point-of-view, there are many challenges to be overcome in order to deliver Cloud services that meet all requirements defined in Service Level Agreements (SLAs). High availability has been one of the biggest challenges for providers, and many services can be used to improve the availability of a service, such as checkpointing, load balancing, and redundancy. Beyond services, we can also find infrastructure and middleware solutions. This systematic review has as its main goal to present and discuss high available (HA) solutions for Cloud Computing, and to introduce some research challenges in this area. We hope this work can be used as a starting point to understanding and coping with HA problems in Cloud.

Service-oriented replication strategies for improving quality-of-service in cloud computing: a survey

Abstract: The recent years have witnessed significant interest in migrating different applications into the cloud platforms. In this context, one of the main challenges for cloud applications providers is how to ensure high availability of the delivered applications while meeting users’ QoS. In this respect, replication techniques are commonly applied to efficiently handle this issue. From the literature, according to the used granularity for replication there are two major approaches to achieve replication: either through replicating the service or the underlying data. The latter one is also known as Data-oriented Replication (DoR), while the former one is referred to as Service-oriented Replication (SoR). DoR is discussed extensively in the available literature and several surveys are already published. However, SoR is still at its infancy and there is a lack of research studies. Hence, in this paper we present a comprehensive survey of SoR strategies in cloud computing. We propose a classification of existing works based on the research methods they use. Then, we carried out an in-depth study and analysis of these works. In addition, a tabular representation of all relevant features is presented to facilitate the comparison of SoR techniques and the proposal of new enhanced strategies.