Traditionally, IP network planning and design is mostly based on the average delay or loss constraints which can often be easily calculated. Jitter, on the other hand, is much more difficult to evaluate, but it is particularly important to manage the QoS of real-time and interactive services such as VoIP and streaming video. In this paper, we present simple formulas for the jitter of Poisson traffic in a single queue that can be quickly calculated . It takes into account the packets delay correlation and also the correlation of tandem queues that have a significant impact on the end-to-end jitter. We then extend them to the end-to-end jitter of a tagged stream based on a tandem queueing network. The results given by the model are then compared with event-driven simulations. We find that they are very accurate for Poisson traffic over a wide range of traffic loads and more importantly that they yield conservative values for the jitter so that they can be used in network design procedures. We also find some very counter-intuitive results. We show that jitter actually decreases with increasing load and the total jitter on a path depends on the position of congested links on that path. We finally point out some consequences of these results for network design procedures.

Having neither precise definition nor a commonly accepted scope, the term “MicroGrid” tends to be used differently across researchers and practitioners alike. The management of energy usage within a microgrid is one of the topics that was handled from numerous perspectives. This study presents systematic literature review (SLR) of research on architectures and energy management techniques for microgrids, providing an aggregated up-to-date catalogue of solutions suggested by the scientific community. The SLR incorporated 45 papers selected according to inclusion/exclusion criteria and defined a priori. The selection process was based on an automated search and covered three known digital libraries. The extraction process covers three main questions. (i) The architectures of microgrids including their components, their bus configuration, and the adopted utility grid policy. (ii) The employed methods to ensure an optimal usage of energy under uncertainty. (iii) The confronted challenges and constraints of the suggested strategies. The findings of this SLR indicate a great diversity of methods and a rich background. Finally, the SLR suggests that future research should take into account the uncertainty aspect relating to energy management rather than the direct use of historical data as it is commonly done in most research papers. A sensitivity analysis should be provided in the latter case.

This article highlights the development of a platform for monitoring three-phase energy consumption within a university campus. The core of this platform is low-cost IoT energy sensors, which are designed to transmit real-time data to the data center’s server through different IoT communication technologies, enhancing the preexisting electrical measurement network. The newly recommended measurement structure enables the electrical consumption data collection required for analyzing patterns and proposing forecast models to optimize electricity usage. The major contribution of this work is the design and implementation of smart three-phase energy meters based on the selection of various energy sensors and wireless communication technologies, and then the set up of a global IoT architecture that offers real-time data acquisition, storage, download, and visualization, capitalizing on the campus’s diverse energy profiles for detailed characterization. The proposed platform is considered the cornerstone toward the implementation of a collaborative smart microgrid, allowing forecasting and electrical consumption optimization, enabling research into potential opportunities for energy efficiency in our campus, and enhancing the performance of existing electrical infrastructure.