Assessing the efficiency of resource allocations in bandwidth-sharing networks

Resource allocation in bandwidth-sharing networks is inherently complex: The distributed nature of resource allocation management prohibits global coordination for efficiency, i.e., aiming at full resource usage at all times. In addition, it is well recognized that resource efficiency may be conflicting with other critical performance measures such as flow delay. Without a notion of optimal (or “near-optimal”) behavior, the performance of resource allocation schemes can not be assessed properly. In previous work, we showed that optimal workload-based (or queue-length based) strategies have certain structural properties (they are characterized by so-called switching curves), but are too complex in general to be determined exactly. In addition, numerically determining the optimal strategy often requires excessive computational effort. This raises the need for simpler strategies with “near-optimal” behavior that can serve as a sensible bench-mark to test resource allocation strategies. We focus on flows traversing the network, sharing the resources on their common path with (independently generated) cross-traffic. Assuming exponentially distributed flow sizes, we show that in many scenarios optimizing the "drain time" under a fluid scaling gives a simple linear switching strategy that accurately approximates the optimal strategy. When two nodes on the flow path are equally congested, however, the fluid scaling is not appropriate, and the corresponding strategy may not even ensure stability. In such cases we show that the appropriate scaling for efficient workload-based allocations follows a square-root law. Armed with these, we then assess the potential gain that any sophisticated strategy can achieve over standard alpha-fair strategies, which are representations of common distributed allocation schemes, and confirm that alpha-fair strategies perform excellently among non-anticipating policies. In particular, we can approximate the optimal policy with a weighted alpha-fair strategy

Auction-based Bandwidth Allocation Mechanisms for Wireless Future Internet

An important aspect of the Future Internet is the efficient utilization of (wireless) network resources. In order for the - demanding in terms of QoS - Future Internet services to be provided, the current trend is evolving towards an "integrated" wireless network access model that enables users to enjoy mobility, seamless access and high quality of service in an all-IP network on an "Anytime, Anywhere" basis. The term "integrated" is used to denote that the Future Internet wireless "last mile" is expected to comprise multiple heterogeneous geographically coexisting wireless networks, each having different capacity and coverage radius. The efficient management of the wireless access network resources is crucial due to their scarcity that renders wireless access a potential bottleneck for the provision of high quality services. In this paper we propose an auction mechanism for allocating the bandwidth of such a network so that efficiency is attained, i.e. social welfare is maximized. In particular, we propose an incentive-compatible, efficient auction-based mechanism of low computational complexity. We define a repeated game to address user utilities and incentives issues. Subsequently, we extend this mechanism so that it can also accommodate multicast sessions. We also analyze the computational complexity and message overhead of the proposed mechanism. We then show how user bids can be replaced from weights generated by the network and transform the auction to a cooperative mechanism capable of prioritizing certain classes of services and emulating DiffServ and time-of-day pricing schemes. The theoretical analysis is complemented by simulations that assess the proposed mechanisms properties and performance. We finally provide some concluding remarks and directions for future research

When Network Coding and Dirty Paper Coding meet in a Cooperative Ad Hoc Network

We develop and analyze new cooperative strategies for ad hoc networks that are more spectrally efficient than classical DF cooperative protocols. Using analog network coding, our strategies preserve the practical half-duplex assumption but relax the orthogonality constraint. The introduction of interference due to non-orthogonality is mitigated thanks to precoding, in particular Dirty Paper coding. Combined with smart power allocation, our cooperation strategies allow to save time and lead to more efficient use of bandwidth and to improved network throughput with respect to classical RDF/PDF.Comment: 7 pages, 7 figure

End-to-end elasticity control of cloud-network slices

The design of efficient elasticity control mechanisms for dynamic resource allocation is crucial to increase the efficiency of future cloud-network slice-defined systems. Current elasticity control mechanisms proposed for cloud- or network-slicing, only consider cloud- or network-type resources respectively. In this paper, we introduce the elaSticity in cLOud-neTwork Slices (SLOTS) which aims to extend the horizontal elasticity control to multi-providers scenarios in an end-to-end fashion, as well as to provide a novel vertical elasticity mechanism to deal with critical insufficiency of resources by harvesting underused resources on other slices. Finally, we present a preliminary assessment of the SLOTS prototype in a real testbed, revealing outcomes that suggest the viability of the proposal.Peer ReviewedPostprint (published version