Abstract

Network convergence and new applications running on end-hosts result in increasingly variable and unpredictable traffic patterns. By providing origin-destination pairs with several possible paths, load-balancing has proved itself an excellent tool to face this uncertainty. Formally, load-balancing is defined in terms of a convex link cost function of its load, where the objective is to minimize the total cost. Typically, the link queueing delay is used as this cost since it measures its congestion. Over-simplistic models are used to calculate it, which have been observed to result in suboptimal resource usage and total delay. In this paper we investigate the possibility of learning the delay function from measurements, thus converging to the actual minimum. A novel regression method is used to make the estimation, restricting the assumptions to the minimum (e.g. delay should increase with load). The framework is relatively simple to implement, and we discuss some possible variants. Document type: Part of book or chapter of book

Abstract

Transition towards a low-carbon transport sector fundamentally depends on decarbonization of the passenger car fleet. Therefore, it is critically important to understand the driving factors behind decreasing CO2 emissions of new passenger cars. This paper develops a new decomposition method to break down the change in the average CO2 emissions of new passenger cars into components representing changes in available technology, carbon efficiency of consumer choices, vehicle attributes, fuel mix, and the gap between type-approval and on-road CO2 emissions of passenger cars. Our decomposition draws insights from the traditional index decomposition analysis and frontier-based decomposition of productivity growth. It satisfies such desirable properties as factor reversal, time reversal, and zero-value robustness. An empirical application to a unique data set that covers all registered passenger cars in Finland sheds light on why and how the CO2 emissions of new cars decreased from year 2002 to year 2014. Peer reviewed