Abstract

Despite Moore’s “law”, uniprocessor clock speeds have now stalled. Rather than using single processors running at ever higher clock speeds, it is common to find dual-, quad- or even hexa-core processors, even in consumer laptops and desktops. Future hardware will not be slightly parallel, however, as in today’s multicore systems, but will be massively parallel, with manycore and perhaps even megacore systems becoming mainstream. This means that programmers need to start thinking parallel. To achieve this they must move away from traditional programming models and development processes that offer parallelism as an bolted-on afterthought.

This talk introduces the idea of “paraforming”, a new approach to constructing parallel functional programs using formally-defined refactoring transformations.
We show how parallel programs can be built from a small number of primitive Haskell building blocks, and describe some new refactorings for Parallel Haskell that capture common parallel abstractions, such as divide-and-conquer and data parallelism using these building blocks. Using a paraforming approach, we are able to easily obtain significant and scalable speedups (up to 7.8 on an 8-core machine).

Continue reading

Opportunistic networks provide an ad hoc communication medium without the need for an infrastructure network, by leveraging human encounters and mobile devices. Routing protocols in opportunistic networks frequently rely upon encounter histories to build up meaningful data to use for informed routing decisions. This seminar presents work showing it is possible to use pre-existing social-network information to improve existing opportunistic routing protocols, and that these self-reported social networks have a particular benefit when used to bootstrap an opportunistic routing protocol.

Frequently, opportunistic routing protocols require users to relay messages on behalf of one another: an act that incurs a cost to the relaying node. Nodes may wish to avoid this forwarding cost by not relaying messages. Opportunistic networks need to incentivise participation and discourage the selfish behaviour. This seminar further presents an incentive mechanism that uses self-reported social networks to construct and maintain reputation and trust relationships between participants, and demonstrates its superior performance over existing incentive mechanisms.

Greg Bigwood is a Ph.D. student in the School of Computer Science at the University of St Andrews. He works in the field of opportunistic networks and social networks, researching the use of social-network information to improve opportunistic networks.

He read Computer Science at the University of St Andrews, graduating in 2007.

Abstract: I describe a mathematical systems modelling framework that is motivated by a desire to represent and reason about properties of (large-scale) systems situated in dynamic environments. Motivated by the concepts of distributed systems theory, the framework has at its core mathematical treatments of environment, location, resource, and process, and comes along with a separating modal logic. Extensions to analyze questions in computer security are also considered. The mathematical structures provide a semantics for a modelling tool, called (Core) Gnosis, that, together with some elementary utility theory, has been deployed in a range of commercial projects undertaken with Hewlett-Packard’s information security business and its customers. I conclude by discussing the rôle of economics in the context of modelling questions in information security.

Biography:

Professor David J. Pym, 6th Century Chair in Logic, and SICSA Professor of Computing Science, Head of School of Natural and Computing Sciences, University of Aberdeen. Previously Principal Scientist at HP Labs, Bristol and Professor of Logic & Computation at Bath, Professor of Logic at QMUL. PhD Edinburgh; MA, ScD Cambridge; FIMA, FBCS.

Led the ‘Security Analytics’ project at HP Labs, now deployed commercially by Hewlett-Packard in its information security business. One of the designers of the Core Gnosis tool for systems and security modelling which is used to deliver the modelling part of Security Analytics. See this recent news piece about my colleagues at HP: http://www.hpl.hp.com/news/2011/oct-dec/security_analytics.html


David is currently interested in the following areas:

• Mathematical systems modelling, using algebraic, logical, and stochastic methods, with applications in information security;
  
• Topics related to the economics of information security;
  
• Topics related to the economics of systems thinking;
  
• Topics connecting logic (substructural, modal; process algebra) and utility theory;
  
• Topics in logic related to information flow and trust domains;
  
• Topics related to information security, information stewardship, and cloud computing;
  
• Topics in logic related to the theory of search spaces.
  

Pervasive systems must offer an open, extensible, and evolving portfolio of services which integrate sensor data from a diverse range of sources. The core challenge is to provide appropriate and consistent adaptive behaviours for these services in the face of huge volumes of sensor data exhibiting varying degrees of precision, accuracy and dynamism. Situation identification is an enabling technology that resolves noisy sensor data and abstracts it into higher-level concepts that are interesting to applications. 

In this talk, I will provide a comprehensive analysis of the nature and characteristics of situations, discuss the complexities of situation identification, and introduce a novel situation identification technique called “context lattice”. The context lattice is built on a sound mathematical model, aiming to identify situations by systematically exploring the semantics of sensor data, domain knowledge, and situations in a pervasive computing system. I will present and discuss the evaluation results when applying this technique to recognising human activities in smart home environments. This talk will be concluded with challenging questions in the area of situation identification.
Continue reading