Cicek Cavdar

5GrEEn: Towards Green 5G mobile networks

In 2020, mobile access networks will experience significant challenges as compared to the situation of today. Traffic volumes are expected to increase 1000 times, and the number of connected devices will be 10-100 times higher than today in a networked society with unconstrained access to information and sharing of data available anywhere and anytime to anyone and anything. One of the big challenges is to provide this 1000-fold capacity increase to billions of devices in an affordable and sustainable way. Low energy consumption is the key to achieve this. This paper takes as starting point the situation of today, and tries to pinpoint important focus areas and potential solutions when designing an energy efficient 5G mobile network architecture. These include system architecture, where a logical separation of data and control planes is seen as a promising solution; network deployment, where (heterogeneous) ultra dense layouts will have a positive effect; radio transmission, where the introduction of massive antenna configurations is identified as an important enabler; and, finally, backhauling solutions that need to be more energy efficient than today.

Dynamic provisioning strategies for energy efficient WDM networks with dedicated path protection

Energy consumption in optical backbone networks is increasing due to two main reasons: (i) the exponential growth of bandwidth demands, and (ii) the increase in availability requirements in order to guarantee protection of the ultra high capacity optical channels provided by wavelength division multiplexing (WDM) networks. Although state of the art reliability mechanisms are very efficient in guaranteeing high availability, they do not consider the impact of the protection resources on the networks energy consumption. Dedicated (1:1) path protection (DPP) is a well-known mechanism that provides one extra link-disjoint path for the protection of a connection request. This secondary path is reserved and maintained in an active mode even though it is not utilized most of the time. This means that in-line optical amplifiers and switching nodes/ports are always consuming power even when they are not used to reroute any primary traffic. Moreover secondary paths are on average longer than their respective primary paths. These observations motivated us to investigate the energy savings, when all unused protection resources can be switched into a low-power, stand-by state (or sleep mode) during normal network operation and can be activated upon a failure. It is shown that significant reduction of power consumption (up to 25%) can be achieved by putting protection resources into sleep mode. Moreover, in order to enhance this energy saving figure, this paper proposes and evaluates different energy-efficient algorithms, specifically tailored around the sleep mode option, to dynamically provision 1:1 dedicated path protected connection. The trade-off between energy saving and blocking probability is discussed and an efficient mechanism to overcome this drawback is devised. Our results reveal that a 34% reduction of energy consumption can be obtained with a negligible impact on the networks blocking performance.

Energy-Efficient Design of Survivable WDM Networks with Shared Backup

In recent years, energy-efficient design of optical WDM networks has become increasingly important as efforts to reduce the operational expenditure (Opex) and the carbon footprint of the internet are prioritized. In this paper we focus on energy- efficient survivable network design where backup resources are shared for efficient capacity consumption. However there is a trade-off between energy-efficiency and survivability. Survivable network design strategies lead to lightly loaded links in order to minimize the risk in case of a failure and to increase the shareability of backup resources. On the contrary, energy-efficient network design strategies tend to increase the load in a set of links as a consequence of concentrating the traffic in order to be able to switch off as much network resources as possible. In this study, we present a novel method to simultaneously minimize Capex and Opex while providing an energy-efficient, shared backup protected network, under the assumption of backup capacity in sleep mode. For the first time we propose an ILP formulation for the energy-efficient shared backup protection problem. By exploiting the sleep mode for the backup resources, we observe that the ILP solution of our mathematical model brings up to 40% gain in energy efficiency in comparison to energy-unaware shared backup protection approach.

Spectrum allocation policy modeling for elastic optical networks

Today, optical transmission technologies are able to support 400Gbps over a single optical channel. However, this capacity cannot tit in the current fixed frequency grid optical spectrum. On the other hand, high rate optical channels have to co-exist with different ranges of line rates in order to serve heterogeneous bandwidth requests from variety of internet applications. Todays fixed rate and rigid frequency grid optical transmission systems cause over provisioning, where usually more spectral resources are provided than necessary. Recently, the concept of elastic optical networks has been proposed in order to reduce this waste of resources. In networks with such feature enabled, modulation parameters and central frequencies are not fixed and the resources can be allocated with a fine granularity, in contrast to the traditional WDM networks. This flexibility makes it possible to adapt to the granularity of the requested bandwidth without over provisioning. However, this heterogeneous bandwidth allocation may on the other hand result in fragmentation of spectral resources under dynamic traffic. In this study we quantify the fragmentation in elastic optical networks and calculate the blocking probability (BP) together with fragmentation on an elastic optical channel. In this regard, an analytical model based on a Markov Chain is developed under dynamic and flexible bandwidth traffic scenario. By using this analytical model different spectrum allocation policies are compared. A novel spectrum allocation policy is proposed which has lower BP and fragmentation ratio compared to the existing strategies.

Energy-efficient lightpath provisioning in a static WDM network with dedicated path protection

The interest in the energy consumption of communication networks has risen in the recent years. In an effort to tackle this problem, several approaches have been presented to reduce the power consumed by the entire network infrastructure, including optical transport. Most of the solutions studied and proposed in the literature, however, pay little or no attention to the power consumed to ensure the resiliency of the overall network.

Shared-Path Protection With Delay Tolerance (SDT) in Optical WDM Mesh Networks

Optical wavelength-division-multiplexing (WDM) networks have emerged as an ideal backbone for the dynamic transport of bandwidth-intensive applications. Most emerging applications require end-to-end survivable connections to be set up for specific time durations that have sliding or fixed setup times (such as IPTV, grid computing backup storage). It is critical for the development of future network infrastructure that user-centric, dynamic, and end-to-end management and control mechanisms are devised to bridge the gap between the transport capacity and the needs of new applications at the customer edges. In this paper, we study the problem of dynamic provisioning of user-controlled connection requests that have specified holding times and delay tolerances. Delay tolerance is a measure of customer patience, and it is defined as the duration a connection request can be held until it is set up. A connection that cannot be established at the instant of its request could potentially be set up in the remaining duration of its delay tolerance. In this study, different dynamic scheduling algorithms are developed and compared by giving priority to connections according to their arrival rates, delay tolerances, and holding times. Using a mathematical model for impatient requests and simulation experiments, we show that delay tolerance flexibility in the traffic model provides a reduction of up to 50% on blocking probability, without the use of extra backup capacity.

Energy-efficient connection provisioning in WDM optical networks

A novel energy-efficient dynamic provisioning scheme is proposed by using an intelligent load control mechanism and an auxiliary graph model. Significant reduction in total energy consumption is achieved without a noticeable increase in the blocking probability.

Improving energy efficiency in optical cloud networks by exploiting anycast routing

Exploiting anycast routing significantly reduces optical network and server energy usage. In this work we present a case study showing that intelligently selecting destinations and routes thereto, while switching off unused (network) elements, cuts power consumption by around 20% and saves network resources by 29%.

Design of green optical networks with signal quality guarantee

Energy consumption of communication networks is growing very fast due to the rapidly increasing traffic demand. Consequently, design of green communication networks gained a lot of attention. In this paper we focus on optical Wavelength Division Multiplexing (WDM) networks, able to support this growing traffic demand. Several energy-aware routing and wavelength assignment (EA-RWA) techniques have been proposed for WDM networks in order to minimize their operational cost. These techniques aim at minimizing the number of active links by packing the traffic as much as possible, thus avoiding the use of lightly loaded links. As a result, EA-RWA techniques may lead to longer routes and to a high utilization on some specific links. This has a detrimental effect on the signal quality of the optical connections, i.e., lightpaths. In this study we quantify the impact of power consumption minimization on the optical signal quality. and address this problem by proposing a combined impairment and energy-aware RWA (IEA-RWA) approach. Towards this goal we developed a complete mathematical model that incorporates both linear and non-linear physical impairments together with an energy efficiency objective. The IEA-RWA problem is formulized as a Mixed Integer Linear Programming (MILP) model where both energy efficiency and signal quality considerations are jointly optimized. By comparing the proposed IEA-RWA approach with existing RWA (IA-RWA and EA-RWA) schemes, we demonstrate that our solution allows for a reduction of energy consumption close to the one obtained by EA-RWA approaches, while still guaranteeing a sufficient level of the optical signal quality.

Dynamic Scheduling of Survivable Connections with Delay Tolerance in WDM Networks

In optical wavelength-division multiplexing (WDM) networks, recent technological progress is enabling dynamic optical transport in which leasable circuits (connections) can be set up and released for a specific duration of time, providing large capacity to bandwidth-hungry applications. Set-up times can be flexible or fixed, depending on the type of the application. Since the interruption of a high-speed optical connection could lead to huge loss of data, such connections need to be protected against failures. We study the problem of dynamic provisioning of user-controlled connection requests that have specified holding times and particular delay tolerances with shared path protection. The metric of delay tolerance is a measure of customer patience, and it is defined as the time a connection request can be held until it is set up. A connection that cannot be established at the instant of its request could potentially be set up in the remaining duration of its delay tolerance. We show that a reduction of up to 50 percent can be achieved on blocking probability by exploiting delay tolerance in networks without using extra backup capacity. In this study we explore different queuing policies for impatient customers. Different dynamic scheduling algorithms are applied and compared by giving priority to connections according to their arrival rates, delay tolerances and holding times alternatively.