- Department of Computing
The Manchester Metropolitan University
John Dalton Building
Chester Street
Manchester
M1 5GD - +44 (0)161 2472845
- Cognitive Radio Networks, Wireless Relay Networks, Ad Hoc Networks, Sensor networks, Cellular Networks, Cooperative Communication, and 20 moreMulti-User MIMO Communication, Wireless Communications, Computer Forensics, Digital Forensics, Digital Evidence, Digital Forensic Model, Digital Forensic History, Wireless Sensor Networks, Routing protocols, Wsn Routing Protocol Survey, Computer Networks, Computer Science, Computer Engineering, Software Engineering, Cloud Computing, Network Security, Education, Engineering, Information Technology, and Artificial Intelligenceedit
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This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the... more
This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynami...
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The availability and quality of information extracted from Wireless Sensor Networks (WSNs) revolutionised a wide range of application areas. The success of any WSN application is, nonetheless, determined by the ability to retrieve... more
The availability and quality of information extracted from Wireless Sensor Networks (WSNs) revolutionised a wide range of application areas. The success of any WSN application is, nonetheless, determined by the ability to retrieve information with the required level of accuracy, within specified time constraints, and with minimum resource utilisation. This paper presents a new approach to localised information extraction that utilises the Watershed segmentation algorithm to dynamically group nodes into segments, which can be used as programming abstractions upon which different query operations can be performed. Watershed results in a set of well delimited areas, such that the number of necessary operations (communication and computation) to answer a query are minimised. This paper presents a fully asynchronous Watershed implementation, where nodes can compute their local data in parallel and independently from one another. The preliminary experimental results demonstrate that the proposed approach is able to significantly reduce the query processing cost and time without involving any loss of efficiency.
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Wireless sensor networks (WSN) have been useful in a variety of domains. These types of networks have an intimate interaction, via sensors, with the physical environment they operate within. The part of the world with which an application... more
Wireless sensor networks (WSN) have been useful in a variety of domains. These types of networks have an intimate interaction, via sensors, with the physical environment they operate within. The part of the world with which an application is concerned is defined as that application's domain. This paper advocates that the application domain can serve as a supplement to sense data analysis, interpretation, and visualisation methods and tools. To achieve this, we propose a multi-dimensional application domain-driven (M-DAD) information extraction and visualisation framework that uses the application domain to accurately visualise multimodal sense data. M-DAD harnesses the inherent redundancies and relationships among the collected sense data as information about a specific event of interest in a WSN is usually captured in multiple sensed modalities. The proposed mapping framework utilises these correlations, defined in the application domain, to visualise a sense modality, e.g. soil nitrate levels, using other related but independent sense modalities, e.g. temperature and pH, which results in higher accuracy visualisations than visualising from a single sense modality. The primary experimental results demonstrate that the proposed framework performs as well or better than methods without its extended capabilities.
Research Interests: Data Mining, Data Analysis, Computer Networks, Routing, Wireless Sensor Networks, and 11 moreInformation Extraction, Data Visualization, Data Visualisation, Redundancy, Interpolation, Network Topology, Physical Environment, Multi Dimensional, Wireless Sensor Network, Intelligent Sensors, and Inductive Sensors
Research Interests: Cartography, Information Retrieval, Data Mining, Production, Computer Networks, and 12 moreWireless Sensor Networks, Information Extraction, Space Technology, Information Visualisation, Data Visualization, Data Visualisation, Visualisation, Data Structures, Interpolation, Wireless Sensor, Network Services, and Wireless Sensor Network
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Abstract Wireless sensor networks (WSNs) have an intimate interaction, via sensors, with the physical environment they operate within. Application domains have a significant effect on applications performance because WSNs are usually... more
Abstract Wireless sensor networks (WSNs) have an intimate interaction, via sensors, with the physical environment they operate within. Application domains have a significant effect on applications performance because WSNs are usually deployed to perform application specific tasks. The part of the world with which an application is concerned is defined as that application's domain. The application domain may help scientists to leverage computational power to simulate, visualise, manipulate, predict and gain intuition about monitored ...
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Abstract With the size and complexity of modern Wireless Sensor Networks (WSNs) systems, a system's ability to recover from faults is becoming more important. A self-healing system is one that has the... more
Abstract With the size and complexity of modern Wireless Sensor Networks (WSNs) systems, a system's ability to recover from faults is becoming more important. A self-healing system is one that has the capability to recover from faults without human intervention during execution. Since WSNs are inherently fault-prone and since their on-site maintenance is infeasible, scalable self-healing is crucial for enabling the deployment of large-scale sensor network applications. Previous work has typically dealt with single faults in isolation, has ...