Nigel Linge

A speculative approach to spatial-temporal efficiency with multi-objective optimization in a heterogeneous cloud environment

A heterogeneous cloud system, for example, a Hadoop 2.6.0 platform, provides distributed but cohesive services with rich features on large-scale management, reliability, and error tolerance. As big data processing is concerned, newly built cloud clusters meet the challenges of performance optimization focusing on faster task execution and more efficient usage of computing resources. Presently proposed approaches concentrate on temporal improvement, that is, shortening MapReduce time, but seldom focus on storage occupation; however, unbalanced cloud storage strategies could exhaust those nodes with heavy MapReduce cycles and further challenge the security and stability of the entire cluster. In this paper, an adaptive method is presented aiming at spatial-temporal efficiency in a heterogeneous cloud environment. A prediction model based on an optimized Kernel-based Extreme Learning Machine algorithm is proposed for faster forecast of job execution duration and space occupation, which consequently facilitates the process of task scheduling through a multi-objective algorithm called time and space optimized NSGA-II TS-NSGA-II. Experiment results have shown that compared with the original load-balancing scheme, our approach can save approximate 47-55i¾źs averagely on each task execution. Simultaneously, 1.254i¾ź of differences on hard disk occupation were made among all scheduled reducers, which achieves 26.6% improvement over the original scheme. Copyright

Problem-based learning as an effective tool for teaching computer network design

This paper addresses the challenge of developing techniques for the effective teaching of computer network design. It reports on the experience of using the technique of problem-based learning as a key pedagogical method for teaching practical network design within the context of a Masters program module in data telecommunications and networks at the University of Salford, Salford, Greater Manchester, U.K. A two-threaded approach was adopted that comprised a problem-based learning thread and a conventional lecture thread. The problem-based learning thread within the module comprised sessions designed to place the students in the position of network design consultants who are introduced to scenarios that have a high degree of realism in which a client has specific business requirements that can be met through the adoption of a network solution. In this way, the problem-based learning thread allows the students to develop their design skills, while the lecture thread uses traditional teaching methods to allow students to develop their understanding of key network components and architectures. A formal evaluation of this approach has been carried out and demonstrated a very effective and realistic learning experience for the students. Therefore, the authors propose that problem-based learning is an ideal pedagogical tool for the teaching of computer network design.

Smart cloud search services: verifiable keyword-based semantic search over encrypted cloud data

With the increasing popularity of the pay-as-you- consume cloud computing paradigm, a large number of cloud services are pushed to consumers. One hand, it brings great convenience to consumers who use intelligent terminals; on the other hand, consumers are also facing serious difficulties that how to search the most suitable services or products from cloud. So how to enable a smart cloud search scheme is a critical problem in the consumer-centric cloud computing paradigm. For protecting data privacy, sensitive data are always encrypted before being outsourced. Although the existing searchable encryption schemes enable users to search over encrypted data, these schemes support only exact keyword search, which greatly affects data usability. Moreover, these schemes do not support verifiability of search result. In order to save computation cost or download bandwidth, cloud server only conducts a fraction of search operation or return a part of result, which is viewed as selfish and semi-honest-but-curious. So, how to enhance flexibility of encrypted cloud data while supporting verifiability of search result is a big challenge. To tackle the challenge, a smart semantic search scheme is proposed in this paper, which returns not only the result of keyword-based exact match, but also the result of keyword-based semantic match. At the same time, the proposed scheme supports the verifiability of search result. The rigorous security analysis and performance analysis show that the proposed scheme is secure under the proposed model and effectively achieves the goal of keyword-based semantic search.

DEHEMS: A user-driven domestic energy monitoring system

Persuasive energy monitoring technology has the potential to inspire sustainable energy lifestyles within the home. However, to effect positive ecological behaviour change, a more user-driven approach is needed for the development of the technology, where the design needs to be accompanied by study on user behaviours and motivations, and the prototype deployed and tested on large sample sizes to understand user preferences. We present DEHEMS, a wide-scale energy monitoring system that undergoes three cycles of design, development and usability assessment so that it can help facilitate energy literacy and environmental awareness based on user preferences. Through real-world deployment, survey and focus group studies carried out in the UK, we present motivations and constraints for saving energy, user assessment of the DEHEMS pilot system and identify some critical user expectations and concerns. We describe how the usability analysis is then incorporated into the design of the next generation DEHEMS system and demonstrate that the resulting system achieves 8% reduction in energy consumption within the first week of feedback.

Improving co-operative working in the utility industry through mobile context aware geographic information systems

This paper presents the development of a mobile context aware geographic information system (G.I.S.) based upon IEEE 802.11 compliant standards and equipment, distributed database systems, and modular software components. Delivered across a high bandwidth wireless intranet, and developed from standard “off the shelf” products, the system presents a unique integration of existing technologies that when applied, could be beneficial to a number of industries that rely on remote access to distributed geo-spatial data. Results from extensive field trials of the system in Manchester (UK) are then presented, in terms of the potential impact of the system on both the co-operative and the isolated working practices of field engineers in the Utility Industry.

Active router approach to defeating denial-of-service attacks in networks

Denial-of-service attacks represent a major threat to modern organisations who are increasingly dependent on the integrity of their computer networks. A new approach to combating such threats introduces active routers into the network architecture. These active routers offer the combined benefits of intrusion detection, firewall functionality and data encryption and work collaboratively to provide a distributed defence mechanism. The paper provides a detailed description of the design and operation of the algorithms used by the active routers and demonstrates how this approach is able to defeat a SYN and SMURF attack. Other approaches to network design, such as the introduction of a firewall and intrusion detection systems, can be used to protect networks, however, weaknesses remain. It is proposed that the adoption of an active router approach to protecting networks overcomes many of these weaknesses and therefore offers enhanced protection.

A WSN-based prediction model of microclimate in a greenhouse using extreme learning approaches

Monitoring and controlling microclimate in a greenhouse becomes one of the research hotspots in the field of agrometeorology, where the application of Wireless Sensor Networks (WSN) recently attracts more attentions due to its features of self-adaption, resilience and cost-effectiveness. Present microclimate monitoring and control systems achieve their prediction by manipulating captured environmental factors and traditional neural network algorithms; however, these systems suffer the challenges of quick prediction (e.g. hourly and even minutely) when a WSN network is deployed. In this paper, a novel prediction method based on an Extreme Learning Machine (ELM) algorithm and KELM (Kernel based ELM) is proposed to predict the temperature and humidity in a practical greenhouse environment in Nanjing, China. Indoor temperature and humidity are measured as data samples via WSN nodes. According to the results, our approach (0.0222s) has shown significant improvement on the training speed than Back Propagation (Bp) (0.7469s), Elman (11.3307s) and Support Vector Machine (SVM) (19.2232s) models, the accuracy rate of our model is higher than those models. In the future, research on faster learning speed of the ELM and KELM based neural network model will be conducted.

Local area network bridges

Abstract In this paper the authors describe local area network bridges and how they may be used to link networks. The functionality and the relative advantages and disadvantages of LAN bridges, compared to other network interconnection methods, are discussed. An alternative source routing bridge for token ring networks is also outlined.

A protocol-less scheme for bridging between IEEE 802 local area networks

Abstract This paper describes an algorithm for a MAC-level bridge to interconnect any IEEE 802 local area networks, which does not rely on communications between the bridges. It will resolve the route over any arbitrary network topology between any pair of communicating end-stations to be the shortest possible. Such a technique will make the best possible use of network resources as the routes are always selected dependent on load.

Determining the propagation range of IEEE 802.11 radio LANs for outdoor applications

This paper details the initial development of a unique microcellular wireless network based on IEEE 802.11 compliant equipment. Cellular design considered a free space propagation model supplemented with results from field tested equipment. This model was then used to determine the signal strength that may be achieved in a variety of different environments by applying a classical propagation loss model. This work is funded by the EPSRC in the UK in association with NORWEB Communications, and is aimed at investigating the use of high bandwidth mobile communications, in support of field engineers in the utility industry.