A contingent valuation of the 2012 London Olympic games - A regional perspective

Major sporting events such as the Olympics are usually assessed in terms of economic impacts. Recently, policy makers have begun to place greater emphasis on possible intangible effects (such as civic pride, legacy of sporting facilities) associated with such events. To date, little work has been carried out on quantifying these effects in a meaningful way. This study uses contingent valuation methodology to assess the value of the proposed 2012 London Olympic Games. The survey is carried out on the provincial city of Bath, approximately 2 hours west of London. Conducting the survey outside of London is justified on the basis that the organizers of London 2012 have emphasized the value of the event to the United Kingdom as a whole. The results suggest that positive intangible effects are associated with the event and residents outside of London are willing to pay toward funding.

Analysing orchestrations with risk profiles and angel-daemon games

In this paper game theory is used to analyse the effect of a number of service failures during the execution of a grid orchestration. A service failure may be catastrophic in that it causes an entire orchestration to fail. Alternatively, a grid manager may utilise alternative services in the case of failure, allowing an orchestration to recover, A risk profile provides a means of modelling situations in a way that is neither overly optimistic nor overly pessimistic. Risk profiles are analysed using angel and daemon games. A risk profile can be assigned a valuation through an analysis of the structure of its associated Nash equilibria. Some structural properties of valuation functions, that show their validity as a measure for risk, are given. Two main cases are considered, the assessment of Orc expressions and the arrangement of a meeting using reputations.

Query cost estimation through remote system contention states analysis over the Internet

Query processing over the Internet involving autonomous data sources is a major task in data integration. It requires the estimated costs of possible queries in order to select the best one that has the minimum cost. In this context, the cost of a query is affected by three factors: network congestion, server contention state, and complexity of the query. In this paper, we study the effects of both the network congestion and server contention state on the cost of a query. We refer to these two factors together as system contention states. We present a new approach to determining the system contention states by clustering the costs of a sample query. For each system contention state, we construct two cost formulas for unary and join queries respectively using the multiple regression process. When a new query is submitted, its system contention state is estimated first using either the time slides method or the statistical method. The cost of the query is then calculated using the corresponding cost formulas. The estimated cost of the query is further adjusted to improve its accuracy. Our experiments show that our methods can produce quite accurate cost estimates of the submitted queries to remote data sources over the Internet.