Distributed and networked computation is now the paradigm that underpins the software-enabled systems that are proliferating in the modern world, with huge impact in the economy and society, from the sensor and actuator networks that are now connecting cities, to cyberphysical systems, to patient-centred healthcare, to disaster-recovery systems.
This new Masters course will educate and train you in the fundamental principles, methods and techniques required for developing such systems. Given the number of elective modules offered, you will be able to acquire further skills in one or more of Cloud Computing, Data Analytics and Information Security.
Facilities include a laboratory where you can experiment with physical devices that can be interconnected in a network, and a cluster facility configured to run the Hadoop MapReduce stack.
A Year in Industry option is also available for this course.
See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/msc-distributed-and-networked-systems.aspx
Why choose this course?
This course will develop a highly analytical approach to problem solving and a strong background in distributed and networked systems, fault-tolerance and data replication techniques, distributed coordination and time-synchronisation techniques (leader-election, consensus, and clock synchronisation), data communication protocols and software stacks for wireless, sensor, and ad hoc networking technologies in virtualisation, and cloud computing technologies.
The course develops an advanced understanding of principles of failure detection and monitoring, principles of scalable storage, and in particular NoSQL technology.
Students will acquire the ability to:
- apply well-founded principles to building reliable and scalable distributed systems
- analyse complex distributed systems in terms of their performance, reliability, and correctness
- design and implement middleware services for reliable communication in unreliable networks
- work with state-of-the-art wireless, sensor, and ad hoc networking technologies
- design and implement reliable data communication and storage solutions for wireless, sensor, and ad hoc networks
- detect sources of vulnerability in networks of connected devices and deploy the appropriate countermeasures to information security threats.
- enforce privacy in “smart” environments
- work with open source and cloud tools for scalable data storage (DynamoDB) and coordination (Zookeeper)
- work with modern network management technologies (Software-Defined Networking) and standards (OpenFlow)
- design custom-built application-driven networking topologies using OpenFlow, and other modern tools
- work with relational databases (SQL), non-relational databases (MongoDb), as well as with Hadoop/Pig scripting and other big data manipulation techniques.
Department research and industry highlights
Royal Holloway is recognised for its research excellence in Machine Learning, Information Security, and Global Ubiquitous Computing.
We work closely with companies such as Centrica (British Gas, Hive), Cognizant, Orange Labs (UK), the UK Cards Association, Transport for London and ITSO.
We host a Smart Card Centre and we are a GCHQ Academic Centre of Excellence in Cyber Security Research (ACE-CSR).
Course content and structure
You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. If you are in the Year-in-Industry pathway, you then take an industrial placement, after which you come back for your project/dissertation (12 weeks).
Core course units are:
Advanced Distributed Systems
Wireless, Sensor and Actuator Networks
Elective course units are:
Computation with Data
Introduction to Information Security
Data Visualisation and Exploratory Analysis
Programming for Data Analysis
Advanced Data Communications
Concurrent and Parallel Programming
Large-Scale Data Storage and Programming
On-line Machine Learning
Smart Cards, RFIDs and Embedded Systems Security
Introduction to Cryptography
Assessment is carried out by a variety of methods including coursework, practical projects and a dissertation.
Employability & career opportunities
Our graduates are highly employable and, in recent years, have entered many different [department]-related areas, including This taught masters course equips postgraduate students with the subject knowledge and expertise required to pursue a successful career, or provides a solid foundation for continued PhD studies.
A minimum of a 2:1 UK honours degree or overseas equivalent in Computer Science, Engineering or other subjects that include a strong element of both mathematics and computing. Relevant professional qualifications and relevant experience in an associated area. IELTS score of 6.5 with 7 in writing for non-native English speaking applicants.