Network Cost Reduction in Cloud and Fog Computing Environments

Dear Colleagues,

Cloud computing has attracted significant attention in recent years, as a result of delivering alternative and more affordable on-demand access to online services. However, current technological trends, such as Internet of Things (IoT), smart cities, and vehicular networks, in addition to emerging applications, like those envisaged by 5G (and beyond) telecommunications or immersive interactive media (e.g., virtual reality communications), may impose stringent networking, energy, capacity, budget or other constraints. As such, service providers benefit from intelligent Fog and its supplementary (Mobile) Edge-based Computing to offload services near the data sources. In parallel, new prediction and optimization models have allowed the integration of nature-inspired algorithms as well as Artificial Intelligence (AI) and Machine Learning (ML)-based mechanisms, as critical components for network performance enhancement and real-time big data analysis. Still, regardless of the selected approach, new challenges manifest. These networks need to balance an increasing service workload, efficiently manage a large number of users, guarantee their QoS/QoE, and optimize the network utilization. Thus, improving accessibility to the provided (and often limited) resources has become an exceedingly urgent problem. Although environment-specific economic policies can be enforced to modulate the service provisioning, the pervasiveness of resources, heterogeneity of application requirements, and mobility of users generate crucial interconnection performance issues that require, on the one hand, intensive tuning on complex architectures and location-allocation algorithms and, on the other, novel methods which allow the network to dynamically adapt its behavior in a scalable fashion. In any case, the common goal, recognized by all service providers, refers to network cost reduction. This Special Issue solicits original research papers and comprehensive reviews on all areas related to network cost reduction and resource optimization for the cloud/fog (or edge) ecosystem. We welcome papers that propose and examine new ideas on both the theoretical (e.g., algorithms, protocols, and/or mathematical and analytical models) and practical (e.g., experimental results, simulation tools, and/or implementation designs) fronts. Relevant topics include, but are not limited to, the following:

• Joint optimization of computing and communication resources in the cloud, fog (or edge);
• AI and ML-based for configuring or managing cloud, fog (or edge) systems;
• Tradeoffs between application performance, resource utilization, energy consumption, and other performance metrics;
• Business pricing and cost models for cloud, fog (or edge) service provisioning;
• Policies and recommendations for intelligent cloud, fog (or edge) architectures;
• Network load balancing and data traffic management methods;
• Service placement and facility location-allocation networking issues and solutions;
• Softwarization-virtualization network approaches and slicing, SDN, NFV;
• Green, cognitive, and serverless communications and networks;
• Dynamic and scalable resource allocation and monitoring;
• Cross-layer design and optimization;
• Content-aware and semantic network cost reduction models;
• Performance modeling and prediction;
• Architectures, analytical models, simulation tools, testbeds and prototypes;
• QoS/QoE-oriented network adaptation;
• Competition cost strategies and game-theoretic models.

Dr. Konstantinos Oikonomou
Dr. Georgios Tsoumanis
Dr. Athanasios Tsipis
Guest Editors

Manuscript Submission Information

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• cloud/fog/edge computing
• network cost
• performance optimization
• QoS/QoE
• service placement
• resource location-allocation
• analytics
• load balancing
• energy efficiency
• operations research