Stylianos Georgoulas

Heterogeneous real-time traffic admission control in differentiated services domains

In differentiated services (DiffServ) domains, where services are provisioned on a per-class basis, admission control is an essential control factor in order to ensure that congestion is avoided and that the quality of service (QoS) requirements of individual flows are met. We consider traffic-engineered and provisioned IP differentiated services domains able to support real-time traffic. We present a new measurement-based admission control (MBAC) scheme that uses measurements of aggregate bandwidth only, without keeping the state of any per-flow information. In our scheme there is no assumption made on the nature of the traffic characteristics of the real-time sources, which can be of any heterogeneous nature. Through simulations we show that the admission control scheme is robust with respect to traffic heterogeneity and measurement errors. We also show that our approach compares favorably against other admission control schemes found in the literature.

Neighbor Discovery for Opportunistic Networking in Internet of Things Scenarios: A Survey

Neighbor discovery was initially conceived as a means to deal with energy issues at deployment, where the main objective was to acquire information about network topology for subsequent communication. Nevertheless, over recent years, it has been facing new challenges due to the introduction of mobility of nodes over static networks mainly caused by the opportunistic presence of nodes in such a scenario. The focus of discovery has, therefore, shifted toward more challenging environments, where connectivity opportunities need to be exploited for achieving communication. In fact, discovery has traditionally been focused on tradeoffs between energy and latency in order to reach an overlapping of communication times between neighboring nodes. With the introduction of opportunistic networking, neighbor discovery has instead aimed toward the more challenging problem of acquiring knowledge about the patterns of encounters between nodes. Many Internet of Things applications (e.g., smart cities) can, in fact, benefit from such discovery, since end-to-end paths may not directly exist between sources and sinks of data, thus requiring the discovery and exploitation of rare and short connectivity opportunities to relay data. While many of the older discovery approaches are still valid, they are not entirely designed to exploit the properties of these new challenging scenarios. A recent direction in research is, therefore, to learn and exploit knowledge about mobility patterns to improve the efficiency in the discovery process. In this paper, a new classification and taxonomy is presented with an emphasis on recent protocols and advances in this area, summarizing issues and ways for potential improvements. As we will show, knowledge integration in the process of neighbor discovery leads to a more efficient scheduling of the resources when contacts are expected, thus allowing for faster discovery, while, at the same time allowing for energy savings when such contacts are not expected.

Joint measurement- and traffic descriptor-based admission control at real-time traffic aggregation points

The primary role of admission control is to decide on the amount of traffic accepted into the network so that users conforming to their established traffic contracts achieve predefined performance objectives, e.g. bounded packet loss probability, end-to-end delay. We consider Diffserv networks able to support real-time traffic and we propose a novel framework for admission control that involves both traffic descriptor and measurement-based techniques and we compare its performance with existing approaches. Our simulation results show that the performance of our approach is rather insensitive to variations of the traffic sources. Even when the provided traffic descriptors are as simple as a single value denoting the required peak rate, the proposed scheme achieves satisfactory performance.

Leveraging MPLS Backup Paths for Distributed Energy-Aware Traffic Engineering

Backup paths are usually pre-installed by network operators to protect against single link failures in backbone networks that use multi-protocol label switching. This paper introduces a new scheme called Green Backup Paths (GBP) that intelligently exploits these existing backup paths to perform energy-aware traffic engineering without adversely impacting the primary role of these backup paths of preventing traffic loss upon single link failures. This is in sharp contrast to most existing schemes that tackle energy efficiency and link failure protection separately, resulting in substantially high operational costs. GBP works in an online and distributed fashion, where each router periodically monitors its local traffic conditions and cooperatively determines how to reroute traffic so that the highest number of physical links can go to sleep for energy saving. Furthermore, our approach maintains quality-of-service by restricting the use of long backup paths for failure protection only, and therefore, GBP avoids substantially increased packet delays. GBP was evaluated on the point-of-presence representation of two publicly available network topologies, namely, GÉANT and Abilene, and their real traffic matrices. GBP was able to achieve significant energy saving gains, which are always within 15% of the theoretical upper bound.

Optimization for time-driven link sleeping reconfigurations in ISP backbone networks

Backbone network energy efficiency has recently become a primary concern for Internet Service Providers and regulators. The common solutions for energy conservation in such an environment include sleep mode reconfigurations and rate adaptation at network devices when the traffic volume is low. It has been observed that many ISP networks exhibit regular traffic dynamicity patterns which can be exploited for practical time-driven link sleeping configurations. In this work, we propose a joint optimization algorithm to compute the reduced network topology and its actual configuration duration during daily operations. The main idea is first to intelligently remove network links using a greedy heuristic, without causing network congestion during off-peak time. Following that, a robust algorithm is applied to determine the window size of the configuration duration of the reduced topology, making sure that a unified configuration with optimized energy efficiency performance can be enforced exactly at the same time period on a daily basis. Our algorithm was evaluated using on a Point-of-Presence representation of the GÉANT network and its real traffic matrices. According to our simulation results, the reduced network topology obtained is able to achieve 18.6% energy reduction during that period without causing significant network performance deterioration. The contribution from this work is a practical but efficient approach for energy savings in ISP networks, which can be directly deployed on legacy routing platforms without requiring any protocol extension.

Optimizing Link Sleeping Reconfigurations in ISP Networks with Off-Peak Time Failure Protection

Energy consumption in ISP backbone networks has been rapidly increasing with the advent of increasingly bandwidth-hungry applications. Network resource optimization through sleeping reconfiguration and rate adaptation has been proposed for reducing energy consumption when the traffic demands are at their low levels. It has been observed that many operational backbone networks exhibit regular diurnal traffic patterns, which offers the opportunity to apply simple time-driven link sleeping reconfigurations for energy-saving purposes. In this work, an efficient optimization scheme called Time-driven Link Sleeping (TLS) is proposed for practical energy management which produces an optimized combination of the reduced network topology and its unified off-peak configuration duration in daily operations. Such a scheme significantly eases the operational complexity at the ISP side for energy saving, but without resorting to complicated online network adaptations. The GÉANT network and its real traffic matrices were used to evaluate the proposed TLS scheme. Simulation results show that up to 28.3% energy savings can be achieved during off-peak operation without network performance deterioration. In addition, considering the potential risk of traffic congestion caused by unexpected network failures based on the reduced topology during off-peak time, we further propose a robust TLS scheme with Single Link Failure Protection (TLS-SLFP) which aims to achieve an optimized trade-off between network robustness and energy efficiency performance.

Inter-autonomous system provisioning for end-to-end bandwidth guarantees

This paper addresses the issue of provisioning end-to-end bandwidth guarantees across multiple Autonomous Systems (ASes). We first review a cascaded model for negotiating and establishing service level agreements for end-to-end bandwidth guarantees between ASes. We then present a network dimensioning system that uses traffic engineering mechanisms for the provisioning of end-to-end bandwidth guarantees. The network dimensioning system solves two problems: (1) the economic problem of how to determine the optimum amount of bandwidth that needs to be purchased from adjacent downstream ASes at a minimum total cost; (2) given the available bandwidth resources within and beyond the AS as a result of (1), the engineering problem of how to assign bandwidth guaranteed routes to the predicted traffic while optimizing the network resource utilization. We formulate both as integer-programming problems and prove them to be NP-hard. An efficient genetic algorithm and an efficient greedy-penalty heuristic are, respectively, used to solve the two problems and we show that these perform significantly better than simple heuristic and random approaches.

Link sleeping and wake-up optimization for energy aware ISP networks

Reducing energy consumption in the Telecom industry has become a major research challenge to the Internet community. Towards this end, numerous research works have been carried out to mitigate the growth of energy consumption through intelligent network control mechanisms. This paper proposes a novel approach to achieving energy efficiency in ISP backbone networks according to dynamic traffic conditions. The main objective is to enforce as many links as possible to go to sleep during the off-peak time, while in event of traffic volume increase, the minimum number of sleeping links should be required to wake up to handle this dynamicity and in a way that this creates minimal or no traffic disruption. Based on our simulations with the GEANT and Abilene network topologies and their traffic traces respectively, up to 47% and 44% energy gains can be achieved without any obstruction to the network performance. Secondly, we show that the activation of a small number of sleeping links is still sufficient to cope with any traffic surge instead of reverting to the full topology or sacrificing energy savings as seen in some research proposals.

A survey of autonomic networking architectures: towards a Unified Management Framework

SUMMARY Academic and industrial research initiatives have sought to make fully autonomic networks a reality. Some of these initiatives pursued a holistic approach, while others focused on setting up functionalities for specific networking domains. These efforts did not succeed in being extensively deployed, because the goals of network operators were not satisfactorily met. These goals include unification of management operations, enablement of end-to-end management and enhancement of the overall system performance in a trusted way, while reducing management cost. In this paper, we analyse a set of existing autonomic management architectures and frameworks with respect to a selected set of criteria. We then identify missing parts and challenges and propose a framework to unify the most promising attributes towards a novel approach of realization of autonomic networking management. We call this proposal Unified Management Framework (UMF). Copyright

Admission control placement in differentiated services networks

The primary role of admission control in quality of service enabled networks is to control the amount of traffic injected into the network so that congestion is avoided and certain performance requirements are met. We consider engineered and provisioned IP differentiated services networks able to support realtime traffic and we address the placement of admission control at the traffic aggregation points of the network, and the granularity of the admission control logic. Regarding the first issue, we show that sophisticated admission control schemes that take into account statistical multiplexing gains need only be employed at the first traffic aggregation points. Further downstream, peak rate admission control will suffice. With respect to the second issue, we propose a framework for admission control, which involves a combined approach of traffic descriptor and measurement-based techniques.