The Green-Game: Accounting for Device Criticality in Resource Consolidation for Backbone IP Networks

Abstract

The reduction of energy expenditure of communication networks represents a key issue for the research community. A promising technique acting in this direction is known as ''resource consolidation''. It consists in concentrating the workload of an infrastructure on a reduced set of devices, while switching off the others. Deciding on the set of devices that can be safely switched off requires an accurate evaluation of their criticality in the network. We define here a measure of criticality that takes into account not only the network topology, but also the traffic, and different possible network configurations. We model the scenario as a coalitional game. Shapley value ranking is efficiently used to drive the resource consolidation procedure. Numerical results, on real network scenarios, confirm the robustness and relevance of the proposed index in measuring criticality, yielding a good tradeoff between energy efficiency and network robustness, and outperforming other classical indexes.

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

“…Finally, Bianzino et al [81] study the trade-off between bandwidth and energy consumption when an end device has access to multiple networking interfaces and can switch between them. They aim for energy efficiency but use an abstract model of power usage based on the amount of data being shuffled.…”

“…This can extend to the edge domain (clustering edge servers) or remain at end devices. The latter is investigated by Skarlat et al in so-called fog colonies [50], by Arkian et al within vehicular clusters [51], or by Bianzino et al [81] for uploading data streams in presence of mobility.…”

“…However, creating and maintaining a group of devices which can share their resources has a cost, for example shown by Athwani et al [80] who concluded that maintaining the cluster consumes extra energy, especially if the devices are very mobile. This is why it is beneficial to do the resource sharing in two phases, where the first phase is deciding whether the device gains more by working alone or joining a coalition, and the second one is deciding if the device will consume others' resources [81], [87]. Yu et al [87] show that their cooperative solution improves user QoS (defined by how much computing and bandwidth resources are allocated to a user) by 75%.…”

ICT-based Strategies for Environmental Conflicts

“…Now, the picture that emerges from the papers collected in this volume point out that the problem of computational complexity related to games can be to some extent overcome by the use of approximation techniques aimed to make good estimation both of the structure of the game and of the solution concepts associated with it (see, for example, Bianzino et al [3] and Moretti [12]). On the other hand, looking at the different applications of game theoretic models in the literature, it seems that the environmental applications of game theoretic models on real data are still in an embryonic stage, despite the great interest shown for these applications by the scientific community (Bahn et al [2], Parrachino et al [14]).…”

“…In order to reduce their carbon footprint, emerging ICT technologies are embedded with energy-aware protocols and energy saving techniques (Bolla et al [5]). The role of interactions among agents is taken into account in Bianzino et al [3] in this collection, re-introducing and discussing some energy-aware routing approaches in backbone networks, which take into account the criticality of devices in the considered network scenario, the relevance for network connectivity of the devices and the amount of traffic that they are routing.…”