Jemal H. Abawajy

Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing

Cloud computing offers utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of electrical energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only minimize operational costs but also reduce the environmental impact. In this paper, we define an architectural framework and principles for energy-efficient Cloud computing. Based on this architecture, we present our vision, open research challenges, and resource provisioning and allocation algorithms for energy-efficient management of Cloud computing environments. The proposed energy-aware allocation heuristics provision data center resources to client applications in a way that improves energy efficiency of the data center, while delivering the negotiated Quality of Service (QoS). In particular, in this paper we conduct a survey of research in energy-efficient computing and propose: (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering QoS expectations and power usage characteristics of the devices; and (c) a number of open research challenges, addressing which can bring substantial benefits to both resource providers and consumers. We have validated our approach by conducting a performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant cost savings and demonstrates high potential for the improvement of energy efficiency under dynamic workload scenarios.

Fault-tolerant scheduling policy for grid computing systems

Summary form only given. With the momentum gaining for the grid computing systems, the issue of deploying support for integrated scheduling and fault-tolerant approaches becomes paramount importance. Unfortunately, fault-tolerance has not been factored into the design of most existing grid scheduling strategies. To this end, we propose a fault-tolerant scheduling policy that loosely couples job scheduling with job replication scheme such that jobs are efficiently and reliably executed. Performance evaluation of the proposed fault-tolerant scheduler against a nonfault-tolerant scheduling policy is presented and shown that the proposed policy performs reasonably in the presence of various types of failures.

A rough set approach for selecting clustering attribute

A few of clustering techniques for categorical data exist to group objects having similar characteristics. Some are able to handle uncertainty in the clustering process while others have stability issues. However, the performance of these techniques is an issue due to low accuracy and high computational complexity. This paper proposes a new technique called maximum dependency attributes (MDA) for selecting clustering attribute. The proposed approach is based on rough set theory by taking into account the dependency of attributes of the database. We analyze and compare the performance of MDA technique with the bi-clustering, total roughness (TR) and min-min roughness (MMR) techniques based on four test cases. The results establish the better performance of the proposed approach.

Determining Service Trustworthiness in Intercloud Computing Environments

Deployment of applications and scientific workflows that require resources from multiple distributed platforms are fuelling the federation of autonomous Clouds to create Cyber infrastructure environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. In this paper, we present a fully distributed framework that enable interested parties determine the trustworthiness of federated cloud computing entities.

A multi-tier phishing detection and filtering approach

Phishing attacks continue to pose serious risks for consumers and businesses as well as threatening global security and the economy. Therefore, developing countermeasures against such attacks is an important step towards defending critical infrastructures such as banking. Although different types of classification algorithms for filtering phishing have been proposed in the literature, the scale and sophistication of phishing attacks have continued to increase steadily. In this paper, we propose a new approach called multi-tier classification model for phishing email filtering. We also propose an innovative method for extracting the features of phishing email based on weighting of message content and message header and select the features according to priority ranking. We will also examine the impact of rescheduling the classifier algorithms in a multi-tier classification process to find out the optimum scheduling. A detailed empirical performance and analysis of the proposed algorithm is present. The results of the experiments show that the proposed algorithm reduces the false positive problems substantially with lower complexity.

A Layered Security Approach for Cloud Computing Infrastructure

This paper introduces a practical security model based on key security considerations by looking at a number of infrastructure aspects of Cloud Computing such as SaaS, Utility, Web, Platform and Managed Services, Service commerce platforms and Internet Integration which was introduced with a concise literature review. The purpose of this paper is to offer a macro level solution for identified common infrastructure security requirements. This model with a number of emerged patterns can be applied to infrastructure aspect of Cloud Computing as a proposed shared security approach in system development life cycle focusing on the plan-built-run scope.

Power graphs: A survey

This article gives a survey of all results on the power graphs of groups and semigroups obtained in the literature. Various conjectures due to other authors, questions and open problems are also included.

Placement of File Replicas in Data Grid Environments

In this paper, we address the problem of file replica placement in Data Grids given a certain traffic pattern. We propose a new file replica placement algorithm and compare its performance with a standard replica placement algorithm using simulation. The results show that file replication improve the performance of the data access but the gains depend on several factors including where the file replicas are located, burstness of the request arrival, packet loses and file sizes.

Establishing Trust in Hybrid Cloud Computing Environments

Establishing trust for resource sharing and collaboration has become an important issue in distributed computing environment. In this paper, we investigate the problem of establishing trust in hybrid cloud computing environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. We present a fully distributed framework that enable trust-based cloud customer and cloud service provider interactions. The framework aids a service consumer in assigning an appropriate weight to the feedback of different raters regarding a prospective service provider. Based on the framework, we developed a mechanism for controlling falsified feedback ratings from iteratively exerting trust level contamination due to falsified feedback ratings. The experimental analysis shows that the proposed framework successfully dilutes the effects of falsified feedback ratings, thereby facilitating accurate and fair assessment of the service reputations.

Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study

Fog computing (FC) and Internet of Everything (IoE) are two emerging technological paradigms that, to date, have been considered standing-alone. However, because of their complementary features, we expect that their integration can foster a number of computing and network-intensive pervasive applications under the incoming realm of the future Internet. Motivated by this consideration, the goal of this position paper is fivefold. First, we review the technological attributes and platforms proposed in the current literature for the standing-alone FC and IoE paradigms. Second, by leveraging some use cases as illustrative examples, we point out that the integration of the FC and IoE paradigms may give rise to opportunities for new applications in the realms of the IoE, Smart City, Industry 4.0, and Big Data Streaming, while introducing new open issues. Third, we propose a novel technological paradigm, the Fog of Everything (FoE) paradigm, that integrates FC and IoE and then we detail the main building blocks and services of the corresponding technological platform and protocol stack. Fourth, as a proof-of-concept, we present the simulated energy-delay performance of a small-scale FoE prototype, namely, the V-FoE prototype. Afterward, we compare the obtained performance with the corresponding one of a benchmark technological platform, e.g., the V-D2D one. It exploits only device-to-device links to establish inter-thing “ad hoc” communication. Last, we point out the position of the proposed FoE paradigm over a spectrum of seemingly related recent research projects.