| EPSRC Reference: |
EP/F033591/1 |
| Title: |
Network Coding via Evolutionary Algorithms |
| Principal Investigator: |
Leeson, Dr MS |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Engineering |
| Organisation: |
University of Warwick |
| Scheme: |
Standard Research |
| Starts: |
01 September 2008 |
Ends: |
31 August 2011 |
Value (£): |
338,583
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Networks & Distributed Systems |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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06 Dec 2007
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ICT Prioritisation Panel (Technology)
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Announced
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Summary on Grant Application Form |
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Communication in the Engineering sense refers to the process of transferring information between two or more places in a form that can be processed by communications equipment. Communication systems convey information, which is precisely defined for mathematical analysis but may be taken loosely to mean the symbols that make up the message. At the physical level, the information is often conveyed by a sequence of ones and zeros, forming a binary signal composed of single binary digits (bits). A transmission system is of little use if it cannot transmit information reliably, to help in this process a set of input bits is processing it in some way to produce a different set of output bits, known as coding. Often there are more output bits than input bits because redundant information has been added to help in message recovery. Coding has also been used to compress computer files and for encrypting messages. In 2000, a new use for coding was proposed: to increase the efficiency of message transmission through a computer network. Nodes in a traditional communications network pass on information unaltered if they are not the intended recipient, and all coding takes place at the transmitter and the receiver. In network coding, by allowing the intermediate nodes to modify messages, it has been shown that more information may be sent through a network in a given time in comparison with just forwarding the messages unaltered. Finding the right network codes is not easy, nor is deciding which network nodes should carry out the coding. In fact, some of the problems are of a type that is very difficult to solve in any reasonable time. In recent years the employment of natural processes to inspire solutions to such complex and ill-defined problems has found wide acceptance. This work intends to apply methods derived from nature, known as evolutionary algorithms, to some currently interesting problems in network coding. Two types of evolutionary technique will be employed, genetic algorithms and genetic programming. The former mimic natural processes and work by evolving a population of solutions and improving it in each generation through the means of selection, mating and mutation. The latter generates computer programs from high-level problem descriptions to solve the problems in question. These methods have been very successful in solving many problems for which mathematical expressions for optimisation do not exist or are too complicated to be of use. This project proposes to investigate the employment of evolutionary computing to the search for network codes. The starting point is the selection of nodes for coding via genetic algorithms, which has only recently been considered in the literature. Here, this will first be extended to scenarios outside that in the work to date, which considers one transmitter broadcasting to several receivers in an idealised network. The performance of genetic algorithms will be compared with genetic programming for this problem for the first time. Following this, the implementation of secure network coding in the framework developed will be addressed. This will lead to a secure network coding scheme that takes account of the limited resources available in real networks. In parallel, the dynamic nature of modern communication networks will also be considered. Evolutionary algorithms that function in the presence of changes in network topology will be selected and implemented. Through this phase of the work, network codes will be shown to be practical for future communication networks. Also, valuable insight into the adaptation of evolutionary algorithms for an important area that includes environmental change will be gained.Network coding is an important development in modern communications and combining it with evolutionary algorithms will have a significant impact on the development of new codes for the data-hungry world of today and tomorrow.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.warwick.ac.uk |