In optical burst switching and optical packet switching, contention of bursts (or packets) can be dealt with most effectively through a combination of wavelength conversion and optical buffering. While this is generally accepted in the optical networking community, and validated through simulation, analytic performance results for optical buffers were limited to the single-wavelength case, and the performance gain from wavelength conversion was never traced analytically for general assumptions. Quantifying this gain analytically is the scope of the current contribution. Relying on generating functions, we developed a fiber delay line (FDL) buffer model with wavelength conversion, which assumes the buffer located at the output of an optical switch, having access to multiple wavelengths. This document presents our model, validates its accuracy, and compares its output for different burst sizes (fixed or varying), scheduling policies and buffer sizes. Several numerical examples assess the applicability of our approximation, and show that our approach yields accurate results.

We study the optimal transmission policy of a sensor node in an energy-harvesting wireless sensor network. We consider a hybrid wireless sensor network in which a mobile sink is used to collect data. Taking cues from recent works on the value of information (VoI), we posit that the optimal policy maximises the VoI that can be sent for the node to the sink. We model this system as a discrete-time queueing model with two coupled queues. In particular, the sensor node under study operates energy neutral and harvests energy according to a Bernoulli process. Discretising energy into “energy chunks”, the battery is modelled as a first queue, whereas a second queue is introduced to hold the VoI at the sensor node. From the vantage point of the sensor node, this means that the sensor can only send when the sink is sufficiently close. When this is the case, the sensor decides whether to transmit its data or not depending on the amount of available energy and the value of the information. Focusing on the optimal transmission policy, we formulate the optimal control problem as a Markov Decision Process with a level-dependent block-triangular transition probability matrix. We find the optimal policy which maximises the mean VoI transmitted from the node in the long run and numerically show that it is of threshold type. Further, we assess the value function at optimal policy analytically and provide some properties. Finally, we investigate the structure of the optimal policy and the mean VoI collected from the node for different system parameters by means of some numerical experiments.