Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload.

Towards conflict or cooperation? The Ukraine crisis and EU-Russia relations

The Ukraine crisis and Russia’s contribution to it have raised numerous concerns regarding the possible emergence of a new ‘Cold War’ in Europe. At the same time, Ukraine’s popular choice and enthusiasm for European integration expressed clearly on the streets of Kyiv seem to have caused Russia to adopt a (neo)revisionist attitude. In this context, relations between Russia and the EU (and the West for that matter) have been limited, frozen and directed on path towards conflict. This article analyses how the traditional dichotomy between conflict and cooperation in EU–Russia relations was replaced by conflict in the context of the Ukraine crisis. The article contends that the breakdown of the symbolic and peaceful cohabitation between the EU and Russia has been influenced by the fact that both actors have chosen to ignore key tensions that characterized their post-Cold War interactions. The article identifies three such tensions: the first emphasizes divisions between EU member states and their impact on coagulating a common EU approach towards Russia; the second (geopolitical) tension highlights the almost mutually exclusive way in which the EU and Russia’s security interests have developed in the post-Soviet space; finally, the third contends that a clash of values and worldviews between the EU and Russia makes conflict virtually unavoidable.