engineering at aberdeen communications and imaging research group 7 academic staff 15 research staff...
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Engineering at Aberdeen
Communications and Imaging Research Group
7 academic staff15 research staff and students
•Electronic Engineering•Communications Engineering•Optical Engineering•Parallel and Image Processing
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Communications and Imaging Research Group: WARMER personnel
Directly involved:Dr Alastair AllenProf Tim SpracklenDr Oliver FaustMr Bernhard SputhMr Golam Murshed+ other research students
Other staff related to Wireless Sensor Networks:Prof Anne Glover (Medical Sciences)Dr A Manivannan (Biomedical Physics)Dr Norval Strachan (Physics)+ research staff/students
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Experience & expertise
Embedded systems
Communications
Wireless Sensor Networks
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Embedded systems
Development of optimized algorithms and high performance computer architectures for embedding imaging and other computational intelligence into small devices
Processing of•Signals•Images•Sensor data
Using•Multiprocessor systems•Digital Signal Processors•Microcontrollers•Field Programmable Gate Arrays•Artificial Neural Network hardware
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Embedded systems
• Concurrency– Parallel compiler technology– Formal methods/tools for secure and provable
systems: CSP/FDR– Java and concurrency
• Operating Systems and Device Drivers
• Artificial Neural Network
hardware
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Field Programmable Gate Arrays
Reconfigurable systems•Algorithmic optimisation•Multi-core (eg. MicroBlaze)
Software Defined Radio•Partial reconfigurability•Formal methods for
hardware / firmware / software interfacing
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Communications
Professor Spracklen has been the UK representative on the UN Comprehensive Nuclear Test Ban Treaty Organisation (CTBTO) since 1998, where he has been responsible for– Satellite Network QoS– Network SLA (service level agreement)– NMS (Network Management System)– Independent Subnetworks …
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8
GCI Concept - Basic Topology
IDC
HubHub
HubHubIMS NDC
Atlantic Ocean Region
Pacific Ocean Region
Indian Ocean RegionNDC Data DistributionData CollectionData Distribution
Hub
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Communications
• A comprehensive simulation of the CTBTO Satellite network was undertaken
• This included aspects such as QoS, SLA issues, NMS coverage
• UN member states’ private networks (the so-called Independent subnetworks)
were examined.
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Engineering Research at AberdeenEngineering Research at Aberdeen CommunicationsCommunications
• Adaptive link layer communications protocols incorporated in the first robust reconfigurable satellite modem
• Satellite communications for Road Traffic Management
• Piloting the use of digital satellite TV for high speed direct-to-home Internet services
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Wireless Sensor Networks
Modelling of WSN
Wireless sensor networks offer a great deal of flexibility. Sensor nodes might be added, dislocated or removed. That means the network topology is subject to constant change.
•Use of CSP in the development of reliable communications protocols in a changing network topology
•Power minimisation techniques in processing and communication
•Modelling of network connectivity
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Percolation theory for modelling network connectivity in WSN
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Percolation theory for modelling network connectivity in WSN
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Percolation theory for modelling network connectivity in WSN
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Wireless Sensor Networks
Working prototypes - Physiological monitoring using:– RFID– ZigBee
RFID Reader Tag
Data
Clock
Energy
RFID Reader Tag
Data
Clock
Energy
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University of Aberdeen role in WARMER
WP2: Development of modular algorithms and firmware for data processing and instrument control
Assistance with selection of the best software/hardware platform for implementation of the developed algorithms, taking into account flexibility, possibility of integration with other parts of the system and market-related concerns.
WP3: Technology of remote data collection
Assistance with networking, data fusion, image processing.
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UNIABDN role
WP4: Networking data of water risk management
The overall objective of this work package is to achieve a robust, flexible computational and data networking architecture to support water risk management.
WP 4.1: Development and verification of networking protocols for distributed data processing systems.
WP 4.2: Review and integration in the processing platform of the networking technology.
WP 4.3: Design of a system capable of communicating via different standards at different times.
WP 4.4: Integration of in situ data with satellite-derived data.
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UNIABDN role
WP5: Hardware preparation and industrialisation of the in-situ monitoring system
Assistance with integration of computation and communication algorithms developed in WP2 and WP4 inside the new in-situ monitoring system.
WP7: Field experiments and satellite remote sensing
Assistance with field demonstration
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University of Aberdeen role in WARMER
WP2: Development of modular algorithms and firmware for data processing and instrument control
Assistance with selection of the best software/hardware platform for implementation of the developed algorithms, taking into account flexibility, possibility of integration with other parts of the system and market-related concerns.
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Designing the next generation in-situ monitoring system (IMS)
Processing Platform considerations
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Questionnaire Results
• Many different electrical interfaces (RS-232, RS-422, RS-485, SDI-12, USB, Analogue)
• Different communication standards (GSM, UMTS, Bluetooth)
• Long service intervals (min 3, max 12 months)• Many different processor architectures (x86, XScale,
ARM, 8051 derivatives, MSP430, CPLD, FPGA)• Many different programming languages in use
(Assembler, C, C++, Java, Fortran, VHDL)
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Current Design of In-Situ Monitoring Systems
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Resulting Constraints for the Processing Platform
• Energy Efficiency
• Flexible Electrical Interfaces
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Increasing energy efficiency
The ideal energy efficient solution are Systems on Chip (SoCs). These are very energy efficient, because:
• Components are connected directly• Less components• Avoidance of unnecessary abstraction layers
However, SoCs are inflexible, therefore not applicable to the Processing Platform.
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Refined Design Constraints
SoCs are power efficient, because they avoid unnecessary abstraction layers!
Therefore, our refined design constraints are:
• Removal of unnecessary abstraction layers
• Flexible Electrical Interfaces
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Overview of proposed IMS setup
Sensors FPGA
CPU
CommunicationModule
Storage
ProcessingPlatform
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Within the Processing Platform
CPUCore
SensorController
1
SensorController
2Comms
Controller
StorageController
HardwareAccelerator
Fast Duplex Link
ComponentSpecific Interface
SensorController
N
.
.
.
Sensor1
Sensor2
SensorN
CommsModule
Storage Module
Processing Platform
.
.
.
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Inside the CPU
IMSControl
Processs
SensorProcess 1
SensorProcess 2 Comms
Process
StorageProcess
HardwareAccelerator
Process
Fast Duplex Link
libCSP2Duplex Channel
SensorProcess N
.
.
.
SensorController
1
SensorController
2
SensorController
N
CommsController
Storage Controller
CPU
.
.
.
Hardware Accelerator
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Possible Areas of Collaboration
• Protocol Design– IMS to Data Centre– Data Centre to Applications
• In-situ Monitoring System– What is inside your box?
• Energy saving Operating System– What power saving techniques does your OS use?