Network-based cloud computing is rapidly expanding as an alternative to conventional office-based computing. As cloud computing becomes more widespread, the energy consumption of the network and computing resources that underpin the cloud will grow. This is happening at a time when there is increasing attention being paid to the need to manage energy consumption across the entire information and communications technology (ICT) sector. While data center energy use has received much attention recently, there has been less attention paid to the energy consumption of the transmission and switching networks that are key to connecting users to the cloud. In this paper, we present an analysis of energy consumption in cloud computing. The analysis considers both public and private clouds, and includes energy consumption in switching and transmission as well as data processing and data storage. We show that energy consumption in transport and switching can be a significant percentage of total energy consumption in cloud computing. Cloud computing can enable more energy-efficient use of computing power, especially when the computing tasks are of low intensity or infrequent. However, under some circumstances cloud computing can consume more energy than conventional computing where each user performs all computing on their own personal computer (PC).

One promising approach to peak to average power ratio (PAPR) reduction for orthogonal frequency division multiple access (OFDMA) is the use of reserved tones, which are modulated so as to reduce the PAPR. One problem with this approach is the computationally efficient determination of reserved tone signals that best reduce the PAPR. In this paper we describe a new algorithm for selection of the reserved tone signals. The algorithm results from a differentiable approximation of the PAPR optimisation criterion. We derive a new joint minimisation method capable of reducing multiple peaks simultaneously. It is shown how this can be utilized in a low complexity gradient update algorithm. Simulations show superior performance (lower resultant PAPR) compared to other methods, where system parameters have been motivated by the proposed long term evolution of the 3GPP cellular standard.

We consider a telecommunication competition model involving an incumbent and one or more new entrants who only choose to serve the most profitable traffic. The contribution of this paper is a new analysis that studies the effect of traffic shifts, which are common in the Internet era, on the distribution of market share. Introducing and using a new concept of a shifting network process, we analyze an incumbent network provider adapting its network to this shifting network process with a mixed integer linear program (MILP). In addition, a second MILP is developed to determine the maximum market share obtainable by a single competitor, engaging in so-called "cream-skimming". Further, we investigate the situation wherein multiple competitors compete on specific parts of the network. Numerical results are provided to demonstrate the various market share effects that may occur.