Peter Norrington

Exploring decentralized dynamic scheduling for grids and clouds using the community-aware scheduling algorithm

Job scheduling strategies have been studied for decades in a variety of scenarios. Due to the new characteristics of the emerging computational systems, such as the grid and cloud, metascheduling turns out to be an important scheduling pattern because it is responsible for orchestrating resources managed by independent local schedulers and bridges the gap between participating nodes. Equally, to overcome issues such as bottleneck, single point failure, and impractical unique administrative management, which are normally led by conventional centralized or hierarchical schemes, the decentralized scheduling scheme is emerging as a promising approach because of its capability with regards to scalability and flexibility.In this work, we introduce a decentralized dynamic scheduling approach entitled the community-aware scheduling algorithm (CASA). The CASA is a two-phase scheduling solution comprised of a set of heuristic sub-algorithms to achieve optimized scheduling performance over the scope of overall grid or cloud, instead of individual participating nodes. The extensive experimental evaluation with a real grid workload trace dataset shows that, when compared to the centralized scheduling scheme with BestFit as the metascheduling policy, the use of CASA can lead to a 30%-61% better average job slowdown, and a 68%-86% shorter average job waiting time in a decentralized scheduling manner without requiring detailed real-time processing information from participating nodes. Highlights? We introduce a decentralized scheduling algorithm without requiring detailed node information. ? Our algorithm is able to adapt to the changes in grids through time by rescheduling. ? Comparisons with the known BestFit algorithm within a centralized scheduling scheme are made. ? Our algorithm leads to a 30%-61% better average job slowdown. ? Our algorithm leads to a 68%-86% shorter average job waiting time.

The Big Picture, from Grids and Clouds to Crowds: A Data Collective Computational Intelligence Case Proposal for Managing Disasters

Much work is underway within the broad next generation technologies community on issues associated with the development of services to foster collaboration via the integration of distributed and heterogeneous data systems and technologies. Various technology-driven paradigms have emerged, including Web Services, Web 2.0, Pervasive, Grids and Cloud Computing. Recently, some new paradigms have emerged, including Situated Computing and Crowd Sourcing. In this exploratory paper, we aim to be visionary, thus, we offer an overview highlighting relationships between these paradigms, the goal is to present how these fit into the broader picture of IT. More specifically, to discuss how these could help coin and prompt future direction of their usage (integration) in various real-world scenarios. A disaster management scenario is presented to illustrate the big picture’s model architecture, as well as briefly discuss the potential impact resulting from the collective computational intelligence approach.

Multi-objective performance optimization of a probabilistic similarity/dissimilarity-based broadcasting scheme for mobile ad hoc networks in disaster response scenarios

Communications among crewmembers in rescue teams and among victims are crucial to relieve the consequences and damages of a disaster situation. A common communication system for establishing real time communications between the elements (victims, crewmembers, people living in the vicinity of the disaster scenario, among others) involved in a disaster scenario is required. Ad hoc networks have been envisioned for years as a possible solution. They allow users to establish decentralized communications quickly and using common devices like mobile phones. Broadcasting is the main mechanism used to disseminate information in all-to-all fashion in ad hoc networks. The objective of this paper is to optimize a broadcasting scheme based on similarity/dissimilarity coefficient designed for disaster response scenarios through a multi-objective optimization problem in which several performance metrics such as reachability, number of retransmissions and delay are optimized simultaneously.

The usability and practicality of biometric authentication in the workplace

This paper discusses usability and practicality issues for authentication systems based on biometrics. The effectiveness of a system incorporating an authentication method depends not only on theoretical and technological issues, but also on user interaction with and practical implementation of the system by an organisation. It is becoming increasingly common that IT and physical security are converging, especially in the workplace. This has significant ramifications for the workforce and operational matters. In this paper we pay particular attention to the potential issues that arise when companies introduce biometrics for IT or physical security and provide recommendations that help ensure a usable and practical implementation of the technology.

Modelling of a self-led critical friend topology in inter-cooperative grid communities

Abstract For decades, much work has been done to increase the effectiveness and efficiency of job sharing amongst available computational resources. Resources can be organized into a variety of topologies, and recent work has shown that a decentralized distributed resource topology is a crucial but complicated scenario. This is because decentralized resources are normally grouped into independent virtual organizations (VOs) and isolated from each other by VO boundaries. To convey jobs across gaps between various virtual organizations, a novel resource topology called the self-led critical friend model (CFM) is proposed in this work. The CFM deals with trust credits between resources according to their historical collaboration records. This trust reveals a feasible, realistic, and transferable correlation to facilitate the resource selection process for job delegation between arbitrarily connected physical resources. Consequently, the CFM is able to overcome the constraints caused by virtual organization boundaries. Besides the theoretical model, a simulation-based implementation is carried out together with a complementary high-level community-aware scheduling protocol. After evaluating a number of compositional scenarios and criteria objectives, the observed results show the benefit of job scheduling across multiple VOs, as well as the capability of the self-led critical friend model as a novel cross-VO resource topology to represent and interconnect resources.

A Next Generation Technology Victim Location and Low Level Assessment Framework for Occupational Disasters Caused by Natural Hazards

Much work is underway within the broad next generation technologies community on issues associated with the development of services to support interdisciplinary domains. Disaster reduction and emergency management are domains in which utilization of advanced information and communication technologies ICT are critical for sustainable development and livelihoods. In this article, the authors aim to use an exemplar occupational disaster scenario in which advanced ICT utilization could present emergency managers with some collective computational intelligence in order to prioritize their decision making. To achieve this, they adapt concepts and practices from various next generation technologies including ad-hoc mobile networks, Web 2.0, wireless sensors, crowd sourcing and situated computing. On the implementation side, the authors developed a data mashup map, which highlights the criticality of victims at a location of interest. With this in mind, the article describes the service architecture in the form of data and process flows, its implementation and some simulation results.

Managing Inconsistencies in Data Grid Environments: A Practical Approach

Much work has been done in the area of data access and integration using various data mapping, matching, and loading techniques. One of the main concerns when integrating data from heterogeneous data sources is data redundancy. The concern is mainly due to the different business contexts and purposes from which the data systems were originally built. A common process for accessing data from integrated databases involves the use of each data sources own catalogue or metadata schema. In this article, the authors take the view that there is a greater chance of data inconsistencies, such as data redundancies when integrating them within a grid environment as compared to traditional distributed paradigms. The importance of improving the data search and matching process is briefly discussed, and a partial service oriented generic strategy is adopted to consolidate distinct catalogue schemas of federated databases to access information seamlessly. To this end, a proposed matching strategy between structure objects and data values across federated databases in a grid environment is presented.

User-Centred Evaluation and Organisational Acceptability of a Distributed Repository to Support Communities of Learners

This chapter presents the combined results and over-arching conclusions of a two-phase project to assess a pilot distributed e-learning repository for computer-based assessment resources. This investigation takes place within the larger concerns of communities of practice, such as learners interacting with computer-based assessments or the tutors delivering courses or developing themselves as professionals. On the one hand, the online repository not only offers easy ac-cess to online quality materials, but communities of learners may overlap and in-teract through a distributed repository, using such collaborative web-technologies for lifelong learning, particularly as their size and content expand into large scale digital libraries. On the other hand, the online repository enables tutors to share knowledge about the courses and could well serve to create a virtual network among tutors for sharing knowledge and views related to the teaching activity. The online repository presented in this chapter has been evaluated in with real us-ers in two phases. The first phase investigated direct users perceptions of the re-pository and its usability and pedagogical effectiveness with a toolkit of six ex-perimental methods for triangulation. The second phase consisted of interviews with senior staff involved in educational management roles to assess the wider or-ganisational perspective on the acceptability of such a repository. The results of this study showed the benefits of using the e-learning distributed repository to support learning processes of a community of learners and the importance of eva-luating the online repository with real learners in order to achieve its organiza tional acceptability.

Email Classification using Behavior and Time Features

The various forms and tremendous number of spam emails have brought great challenges to accurate email classification. In this paper, we present a behavior- and time-feature-based email classification method. Based on email logs, email social networks are built through the extraction of entities and relations from the email records using the MapReduce model. By combining behavior features from social networks and time features from email sending intervals, we adopt a Support Vector Machine based classifier to identify spammers and nonspammers. Compared with the current email classification methods, the advantages of our method are: (1) in addition to the behavior-based features, our method integrates the time feature to facilitate email classification; (2) to efficiently handle the vast number of emails, we employ the MapReduce model to extract the behavior- and time-based features on the email social network. Experiments on real email data of three years show that the proposed method achieves better classification accuracy.

The Applicability of Best Value in the Nigerian Public Sector

We examine the applicability of Best Value practices in the Nigerian public sector and present a Best Value Model for Nigeria. We find the literature does not extend to the Nigerian context. We make contributions towards understanding stakeholder perceptions of public service delivery best practice. We show Best Value as a significant initiative for improving public service delivery. The mixed methods survey reveals Nigerian Best Value initiatives do not exist significantly, but are applicable. Outcomes are exploration of a new area for Best Value application, incorporation of implementation issues into the model and the seven-stage process for its implementation.