Despite opening attractive perspectives, the concept of Software Defined Networking raises doubts about the performance and practical feasibility. To contradict these concerns, we propose a deployment-ready system aimed at proactive and periodic optimization of flow paths. The modular system consists of modules responsible for traffic prediction, static optimization, measurements, flow management, and validation of optimization results. To make the system efficient, we resolved several scientific issues and proposed novel and valuable solutions, for example methods for efficient proactive flow management and periodic re-optimization of routing policies. Simultaneously, to make the system production-ready and create a reliable research environment, we provide solutions to several technical obstacles. We validate the proposed system with three network topologies, each with three load levels, following real-life traffic models. We consider Equal-Cost Multi-Path Routing as a baseline. The results indicate that the system allows network operators to handle more traffic (packet loss reduced by up to 30%), improve quality of service (less congested links resulted in even 2.5 times lower latency), and reduce operational expenses (energy consumption lowered by up to 10%).

This article is devoted to the problems of static and runtime integrity for cloud deployments. Existing remote attestation solutions for cloud infrastructure do not cover static and dynamic attestation as a whole. They evaluate either the static or dynamic part, not considering the rest. We address this gap by proposing a runtime attestation process based on hardware CET technology, as an enhancement to static attestation enabled by SGX. We show how hardware-assisted protection for control-flow-related attacks can enhance virtual deployment security with minimal tradeoff. Our solution does not significantly increase the processing time. Moreover, a processing time can even be reduced when this mechanism is used as a default protection method against control-flow related attacks.

Modern network services are constantly increasing their requirements in terms of bandwidth, latency and cost efficiency. To satisfy these requirements, the concept of network slicing has been introduced in the context of next-generation 5G networks. However, to successfully provision resources to slices, a complex optimization problem must be addressed to allocate resources over a cloud network, i.e., a distributed computing infrastructure interconnected through high-capacity network links. In this study, we propose two new latency and energy-aware optimization models for provisioning 5G slices in cloud networks comprising both distributed computing and network resources. The proposed approaches differ from other existing solutions since we conduct our studies with respect to the end-to-end latency. Relevant models of latency and energy consumption are proposed based on a comprehensive review of the state-of-the-art. To effectively solve those optimization problems, a configurable heuristic is also proposed and investigated over different network topologies. Performance of the proposed heuristic is compared against near-optimal solutions. Moreover, we assess the importance of matching between resource provisioning algorithms and architectural assumptions related to 5G network slices and a proper problem modeling.

In this paper, we introduce elastic optical bypasses to offload traffic bursts in Elastic Optical Networks. Firstly, the principles of the proposed mechanisms are explained. Secondly, the most spectral efficient path with the largest slices first method is proposed as a bypass-path selection policy. Various proportions of resources reserved for optical bypasses and those available for the IP layer are considered in consecutive experiments. Simulation results indicate improvements in terms of bandwidth blocking probability, the average number of hops per accepted demand, and the overall spectrum occupation in comparison to the reference approach. All the proposed mechanisms are fully compatible with the Software-Defined Networking concept.

The paper focuses on dynamic resource provisioning in an all optical wide area Software Defined Network supporting energy-aware interplay between fog and cloud. The main contribution of this paper is a latencyAware policy for handling fog related traffic. The policy is combined with anycast strategies in order to form a complete approach able to handle fog and cloud traffic simultaneously. The proposed approach was compared with reference solutions with respect to latency of fog related requests, CO2emission and impact on network performance. It is shown that both latency and carbon footprint may be reduced without significant deterioration of network performance.

The paper focuses on cooperation between cloud and network operators, as well as on fitting particular routing strategies to various cloud services. Three cooperation models are presented, analyzed and compared in the paper: the proposed model and two widely used reference models. The main difference between the models is the set of information being exchanged between the involved parties. Additionally, we analyze the applicability of four fitting schemas for each considered model. It is shown that the proposed model, alongside with an appropriate fitting schema, is able to reduce the blocking probability of cloud services requests. At the same time, thanks to the use of green anycast strategies, it is able to significantly reduce carbon dioxide emission.

The paper focuses on dynamic resource provisioning which minimizes carbon footprint of data centers interconnected via optical networks. The main contribution of this paper is a schema of fitting energy aware anycast strategies to different types of cloud services in order to reduce greenhouse gases emission. The proposed schema was compared to the cases when all types of cloud services were handled using the same anycast strategy. It is shown that the proposed schema is able to significantly reduce greenhouse gases emission without significant deterioration of network performance.

The paper deals with the problem of optimizing the use of energy in a telecommunication network. We propose the power capping technology to effectively move power hungry tasks from nodes powered from non-renewable energy sources to nodes powered from renewable resources. The presented technology may also be used to optimize OPEX in case the cost of energy varies in different nodes. The presented results show, that the solution is extremely effective in meeting the aforementioned goals.

The paper focuses on dynamic resource provisioning which minimizes carbon footprint in optical networks. The main contribution of this paper consists of three anycast routing strategies aimed at reducing greenhouse gases emission by processing energy-intensive requests in data centers powered from renewable energy sources. The proposed strategies were compared with reference approaches with respect to CO2emission and their impact on network performance. It is shown that they are able to significantly reduce greenhouse gases emission and, simultaneously, improve network performance.