This degree, offered by the Department of Computer Science, is aimed at graduates who already have a background in computer science or engineering and who wish to acquire the depth of knowledge and the skills required to help design, deploy and use the technologies through which systems can operate in networks and in a distributed way. You will be able to tailor your degree according to your interestm with optional modules available in cybersecurity, large-scale data storage and processing, and artificial intelligence.
Skills that you will acquire include the ability to:
- analyse complex distributed systems in terms of their performance, reliability, and correctness
- design and implement middleware services for reliable communication in unreliable networks
- design and implement reliable data communication and storage solutions for wireless, sensor, and ad-hoc networks
- work with open source and cloud tools for scalable data storage (DynamoDB) and coordination (Zookeeper)
- design custom-built application-driven networking topologies
- work with modern network management technologies (Software-Defined Networking) and standards (OpenFlow)
- work with relational databases (SQL), NoSQL databases (MongoDb), as well as with Hadoop/Pig scripting
- work with low-power wireless and mesh networking standards and technologies, such as IEEE 802.15.4, ZigBee and XBee
- work with state-of-the-art microcontroller devices and kits, such as Arduino and Tessel, and miniature computing technologies, such as RaspberryPi
You will be taught by world-leading academics. We carry out research in all aspects of distributed computing and systems – including design and analysis of algorithms, large-scale and cloud-based systems, fault-tolerance, distributed storage, cloud computing, peer-to-peer, concurrency control, and multi-core computing – and in artificial intelligence, including cognitive and autonomous agents, automated planning, scheduling and domain-independent search control, and applications in surveillance operations, disaster response missions, space operations.
- Study in a highly-regarded departments, ranked 11th in the UK for the quality of research publications (Research Excellence Framework 2014).
- Benefit from strong industry ties, with close proximity to ‘England’s Silicon Valley’.
- Graduate with a Masters degree with excellent graduate employability prospects.
- Tailor your learning with a wide range of engaging optional modules.
- Choose from a one-year programme structure or an optional year in industry.
In this module you will learn about the applications of the Internet of Things (IoT) in society, the components of typical IoT systems and the trends for the future. You will be exposed to IoT design considerations, constraints and interfacing between the physical world and IoT devices. You will develop an understanding of the Arduino platform and how it works in terms of the physical board, the libraries and the IDE (integrated development environment). You will elarn how to program the Arduino via C/C++ code and how to access the pins on the board via the software to control external devices. Finally, you will gain hands-on experience in plugging shields into the main Arduino board to perform other functions such as sensing and actuating.
Wireless Sensor and Actuator Networks
This module combines lectures focussing on the algorithms and the protocols behind wireless sensor and actuator networks (WSANs) with lab classes that focus on how to build wireless sensor and actuator networks for a variety of applications. You will learn about the critical design factors for WSANs, the protocal stack, models and algorithms for WSANs, routing protocols and more advanced open research problems, such as topology control and mobility. The practical classes will cover how to design and build wireless sensor networks and intelligent interactive devices with the ZigBee wireless networking protocol.
Advanced Distributed Systems
The module cover the fundamental principles of building modern distributed systems, for example in the context of the Internet of Things (IoT), focussing in particular two central components of the IoT reference architecture-cloud infrastructure and wireless networking. The module will discuss major challenges found in these environments (such as massive scales, wide distribution, decentralisation, unreliable communication links, component failures and network partitions) and general approaches for dealing with these. Topics covered will include abstract models (such as the synchronous and asynchronous distributed computing models, models for wireless networks); algorithmic techniques (such as distributed coordination, fault-tolerant design of distributed algorithms, synchronization techniques); and practical case studies. You will also have an opportunity to implement various components of a realistic distributed system through a series of formative coursework assignments, lab practicals, and a final project.
The individual project provides you will the opportunity to demonstrate independence and originality, to plan and organise a large project over a long period, and to put into practice some of the techniques you have been taught throughout the programme.
In addition to these mandatory course units there are a number of optional course units available during your degree studies. The following is a selection of optional course units that are likely to be available. Please note that although the College will keep changes to a minimum, new units may be offered or existing units may be withdrawn, for example, in response to a change in staff. Applicants will be informed if any significant changes need to be made.
Advanced Data Communications
Business Intelligence Systems, Infrastructures and Technologies
Computation with Data
Concurrent and Parallel Programming
Decision Theory and Behaviour
Fixed Income Securities and Derivatives
Foundations of Finance
Intelligent Agents and Multi-Agent Systems
Introduction to Cryptography
Investment and Portfolio Management
Large-scale Data Storage and Processing
Methods of Bioinformatics
Methods of Computational Finance
On-line Machine Learning
Programming for Data Analysis
Smart Cards, RFIDs and Embedded Systems Security
Topics in Applied Statistics
Visualisation and Exploratory Analysis
Teaching is organized in terms of 11 weeks each. Examinations are taken in April/May of each academic year, except for Data Analysis for which the exam is in January. The individual project is taken over 12 weeks during the Summer.
A weekly seminar series runs in parallel with the academic programme, which includes talks by professionals in a variety of application areas as well as workshops that will train you to find a placement or a job and lead a successful career.
Assessment is carried out by a variety of methods including coursework, small group projects, and examinations, the proportions of which vary according to the nature of the modules.
This degree can be taken part-time.
UK 2:1 (Honours) or equivalent in Computer Science, Economics, Mathematics, Physics, or other subjects that include a strong element of both mathematics and computing.
Relevant professional qualifications and relevant experience in an associated area.
English language requirements:
6.5 overall. No subscore below 5.5
International and EU entry requirements
Please select your country from the drop-down list below
Students from overseas should visit the International pages for information on the entry requirements from their country and further information on English language requirements. Royal Holloway offers a Pre-Master’s Diploma for International Students and English language pre-sessional courses, allowing students the opportunity to develop their study skills and English language before starting their postgraduate degree.
According to Cisco, the number of 'connected devices' (including vending machines, electricity meters and refrigerators as well as phones and computers) will exceed the number of people on the planet by a factor of two. By 2020 some 27 billion unique objects will be connected wirelessly to the Internet; from then on, the Internet of Things (IoT) will double in size every five years. By 2020, VisionMobile estimates that 4.5 million IoT developers will be needed.
We bring several companies to our campus throughout the year, both for fairs and for delivering advanced topics seminars, which are an excellent opportunity to learn about what they do and discuss possible placements or jobs.
Together with the Royal Holloway Careers and Employability Service, we offer you workshops and one-to-one coaching that train you to find a placement or a job and lead a successful career.
Home and EU students tuition fee per year 2017/18*: £8,300
Overseas students tuition fee per year 2017/18*: £18,500
A scholarship of £2,000 will be automatically provided (and deducted from the fees payable) for overseas students holding the equivalent of a UK first-class undergraduate degree.
The fee for part-time students depends on the number of credits taken during that year.
Other essential costs**: There are no single associated costs greater than £50 per item on this course
Find out more about funding options, including loans, grants, scholarships and bursaries.
*The tuition fees given above apply to students enrolled on a full-time basis. Students studying part-time are charged a pro-rata tuition fee and information is available from the Royal Holloway Student Fees Office on Student-Fees@rhul.ac.uk. All fees are likely to rise annually in line with inflation but no more than 5 per cent per year.
For further information, please see Royal Holloway’s Terms & Conditions.
** These estimated costs relate to studying this particular degree programme at Royal Holloway. Costs, such as accommodation, food, books and other learning materials and printing etc., have not been included.