This paper presents a platform for measuring, evaluating and modeling the energy efficiency aspects of an O-RAN 5G wireless network. We describe our open-source based O-RAN testbed which includes both bare-metal and Kubernetes network functions, in addition to physical network components. We focus on measuring power consumption of servers and workloads of cloudified and virtualized network functions. We show that a combination of different power measurements can be used successfully to achieve the accuracy and granularity required for energy efficiency measurement, evaluation and modeling.

Networks undergo continuous changes to introduce new services and improve existing ones. Network change deployment involves carefully deciding when each change activity will be executed and who will be executing the change. This is a complex process because each service group has to plan its activities following a set of operational and technological constraints. Besides, multiple groups may be working on the same or dependent nodes at the same time, and they must coordinate their deployment plans. If they do not co-ordinate, conflicting change execution could result in unexpected impacts. Traditionally, change deployment has been a tedious and time-consuming task. To address this, we propose an innovative solution Zapper that aims for minimal human effort to coordinate the changes, minimal risk to service quality, and efficient plans to rapidly deploy the changes. Zapper maps change scheduling constraints into mathematical equations and then uses optimization algorithms to generate conflict-free change plans that satisfy all constraints across service groups. We have deployed Zapper at a large service provider and it is being used regularly by the network operations teams for more than two years to schedule over 4.5 million change activities.

Cellular networks are constantly evolving due to frequent changes in radio access and end user equipment technologies, dynamic applications and associated trafflc mixes. Network upgrades should be performed with extreme caution since millions of users heavily depend on the cellular networks for a wide range of day to day tasks, including emergency and alert notifications. Before upgrading the entire network, it is important to conduct field evaluation of upgrades. Field evaluations are typically cumbersome and can be time consuming; however if done correctly they can help alleviate a lot of the deployment issues in terms of service quality degradation. The choice and number of field test locations have significant impacts on the time-to-market as well as confidence in how well various network upgrades will work out in the rest of the network. In this paper, we propose a novel approach — Reflection to automatically determine where to conduct the upgrade field tests in order to accurately identify important features that affect the upgrade. We demonstrate the effectiveness of Reflection using extensive evaluation based on real traces collected from a major US cellular network as well as synthetic traces.

Efficient management and control of modern and next-gen networks is of paramount importance as networks have to maintain highly reliable service quality whilst supporting rapid growth in traffic demand and new application services. Rapid mitigation of network service degradations is a key factor in delivering high service quality. Automation is vital to achieving rapid mitigation of issues, particularly at the network edge where the scale and diversity is the greatest. This automation involves the rapid detection, localization and (where possible) repair of service-impacting faults and performance impairments. However, the most significant challenge here is knowing what events to detect, how to correlate events to localize an issue and what mitigation actions should be performed in response to the identified issues. These are defined as policies to systems such as ECOMP.

As smartphone users increasingly rely on cellular networks to access voice, video, and web applications, guaranteeing good performance and high availability is more important than ever. Historically, managing cellular network configuration has been a manual, error-prone process; recently, automated solutions such as SON (Self-Organizing Networks) controllers are being deployed for dynamic tuning of network configuration to improve end-user service performance under dynamic network and traffic conditions. SON automates many aspects of cellular network configuration, but it is nonetheless susceptible to software bugs and expected traffic changes that could result in sub-optimal performance. In this paper, we propose a capability (Veracity) to analyze and quantify the performance effects of SON actions. Assessing the effects of SON control is difficult because of the dynamic nature of SON and the dependency of end-user performance on factors such as radio channel quality, mobility and traffic load. Veracity addresses these using model-driven impact detection and quantification. Our evaluation using data collected from an operational cellular network demonstrates that Veracity is accurate. Veracity is now being used by the service providers' field operation teams for the assessment of SON effectiveness in arenas and stadiums.

Cellular networks are constantly evolving due to frequent changes in radio access and end user equipment technologies, applications, and traffic. Network upgrades should be performed with extreme caution since millions of users heavily depend on the cellular networks. Before upgrading the entire network, it is important to conduct field evaluation of upgrades.The choice and number of field test locations have significant impact on the time-to-market and confidence in how well various network upgrades will work out in the rest of the network. We propose a novel approach -- Reflection to automatically determine where to conduct the upgrade field tests to accurately identify important features that affect the upgrade and predict for the performance of untested locations. We demonstrate its effectiveness using real traces collected from a major US cellular network as well as synthetic traces.

The author has been involved in the planning and implementation of hundreds of microwave links for various AT&T Business Units. Planning a good, stable and reliable microwave network can be quite challenging. At the same time, it poses several interesting optimization problems. The motivation behind this paper is to introduce these problems to the "optimization world" by mathematically formulating them so that these problems could be solved by interested researchers and hence planning of microwave networks could be easier in the times ahead.

A software system developed by AT&T to do an optimal routing of its international circuits over the worldwide cable and satellite network is described. The planning environment is discussed, and the overall architecture is described. The formulation of the models and their capabilities are summarized. Results generated by this system are used in the planning of international circuit loadings and construction of international facilities. The system does optimal routing of circuits for international message telecommunications service between United States and foreign switches; it also routes custom-services circuits between customer premises. The system takes into account the satellite-loading agreement between COMSAT and AT&T.>