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

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

Experience & expertise

Embedded systems

Communications

Wireless Sensor Networks

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

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

Field Programmable Gate Arrays

Reconfigurable systems•Algorithmic optimisation•Multi-core (eg. MicroBlaze)

Software Defined Radio•Partial reconfigurability•Formal methods for

hardware / firmware / software interfacing

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 …

8

GCI Concept - Basic Topology

IDC

HubHub

HubHubIMS NDC

Atlantic Ocean Region

Pacific Ocean Region

Indian Ocean RegionNDC Data DistributionData CollectionData Distribution

Hub

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.

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

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

Percolation theory for modelling network connectivity in WSN

Percolation theory for modelling network connectivity in WSN

Percolation theory for modelling network connectivity in WSN

Wireless Sensor Networks

Working prototypes - Physiological monitoring using:– RFID– ZigBee

RFID Reader Tag

Data

Clock

Energy

RFID Reader Tag

Data

Clock

Energy

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.

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.

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

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.

Designing the next generation in-situ monitoring system (IMS)

Processing Platform considerations

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)

Current Design of In-Situ Monitoring Systems

Resulting Constraints for the Processing Platform

• Energy Efficiency

• Flexible Electrical Interfaces

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.

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

Overview of proposed IMS setup

Sensors FPGA

CPU

CommunicationModule

Storage

ProcessingPlatform

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

.

.

.

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

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?