Energy-aware Traffic Engineering Research Articles

Energy-aware traffic engineering in IP networks using non-dominated sorting genetic II algorithm

Wide spreading of computer networks along with increasing traffic demand throughout the Internet caused a dramatic increase in energy consumption by networking devices and Internet infrastructure. Energy-aware traffic engineering is a promising approach towards green networking to achieve a trade-off between energy saving and network utilisation in backbone networks. In this paper, we propose to use non-dominated sorting genetic algorithm (NSGA-II) for energy-aware intra-domain traffic engineering. This algorithm tries to make a trade-off between maximum link utilisation (MLU) and energy reservation. For each pair of network topology and traffic matrix, NSGA-II computes the optimal set of links to put to sleep so that the resulting topology would be able to carry the traffic demand. We developed a simulator to evaluate the performance of our mechanism. The results of comprehensive evaluations show that our energy-aware TE approach increases the network performance in terms of energy conservation by 50% at the cost of slight increase in maximum link utilisation.

Minimizing energy and link utilization in ISP backbone networks with multi-path routing: a bi-level approach

In recent years, green networking has attracted a lot of attention from device manufacturers and Internet Service Providers (ISP) to reduce energy consumption. In the literature, energy-aware traffic engineering problem is proposed to minimize the total energy consumption by switching off unused network devices (routers and links) while guaranteeing full network connectivity. In this work, we are interested in the problem of energy-aware Traffic Engineering while using multi-path routing (ETE-MPR) to minimize link capacity utilization in ISP backbone networks. To this end, we propose a bi-level optimization model where the upper level represents the energy management function, and the lower level refers to the deployed multi-path routing protocol. Then, we reformulate it as a one-level MILP replacing the second level problem by different sets of optimality conditions. We further use these formulations to solve the problem with classical branch-and-bound, cutting plane, and branch-and-cut algorithms. The computational experiments are performed on real instances to compare the proposed algorithms and to evaluate the efficiency of our model against the existing single-path and multi-objective approaches.

An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers.

There is a lot of effort to limit the impact of CO2 emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major power consumer and considerable gains are expected by regulating the operation network devices. In this context, we developed a mixed integer programming (MIP) algorithm to optimize the power consumption of network devices via energy aware traffic engineering. We verified our approach by simulating DC network topologies and demonstrated that clear benefits can be achieved for various network sizes and traffic volumes. Our algorithm can be easily implemented as an application in the software-defined networking (SDN) paradigm, making quite feasible its deployment in a production environment.

A parallel optimization for energy and robustness of file distribution services

This paper focuses on the energy consumption of content distribution and sharing services that have a significant percentage of traffic on the Internet today. Taking the “energy saving” and “network robustness in traditional traffic engineering” as the dual optimization objects, a weighted green factor is introduced and an optimization model called ETE-FD (Energy-Aware Traffic Engineering File Distribution) is established. The model takes into account the overlay layer and the network layer, end systems and routing nodes. A multi-machine parallel algorithm based on dual decomposition and subgradient projection is proposed. Even with more than 1000 nodes, the solution process is still fast. However, when the number of nodes exceeds 3000, the time complexity is not ideal. On this basis, we continue to improve the computational efficiency of the subgradient projection method: using the deflection subgradient to reduce the number of iterations, and introducing the GPU (Graphics Processing Unit) to speed up the calculation, thereby greatly reducing the calculation time. The effectiveness of the model was verified by simulation experiments. Experimental results show that the adjustable range of the ETE-FD model is significant. From the performance-oriented to the energy-oriented adjustment process, the energy consumption of the whole system was reduced by 47.09%, but the reliability of the network was also reduced by 58.18%, and the average download time increased by 90%. The EOCFD (Energy-optimal Collaborative File Distribution) model of the same kind of research also proposes a file distribution scheduling mechanism to save energy by reducing the total time that the hosts receive files. Compared with the EOCFD scheme, the ETE-FD’s power consumption is reduced by about 10.8% compared to the pure energy-saving optimization. If set to only the reliability optimization goal measured by MLU (Maximum Link Utilization), it is about 43.9% higher than EOCFD.

Energy-aware traffic engineering in IP networks using non-dominated sorting genetic II algorithm

Wide spreading of computer networks along with increasing traffic demand throughout the Internet caused a dramatic increase in energy consumption by networking devices and Internet infrastructure. Energy-aware traffic engineering is a promising approach towards green networking to achieve a trade-off between energy saving and network utilisation in backbone networks. In this paper, we propose to use non-dominated sorting genetic algorithm (NSGA-II) for energy-aware intra-domain traffic engineering. This algorithm tries to make a trade-off between maximum link utilisation (MLU) and energy reservation. For each pair of network topology and traffic matrix, NSGA-II computes the optimal set of links to put to sleep so that the resulting topology would be able to carry the traffic demand. We developed a simulator to evaluate the performance of our mechanism. The results of comprehensive evaluations show that our energy-aware TE approach increases the network performance in terms of energy conservation by 50% at the cost of slight increase in maximum link utilisation.

Green Link Weights for Disruption-Free Energy-Aware Traffic Engineering

Energy-aware traffic engineering (ETE) has been gaining increasing research attentions due to the cost reduction benefits that it can offer to network operators and for environmental reasons. While numerous approaches exist which attempt to provide energy reduction benefits by intelligently manipulating network devices and their configurations, most of them suffer from one fundamental shortcoming: however, minor adaptations to a given IP network topology configuration all lead to temporal service disruptions incurred by routing reconvergence, which makes these schemes less appealing to network operators. The more frequently the IP topology reconfigurations take place in order to optimize the network performance against dynamic traffic demands, the more frequently service disruptions will occur to end users. Motivated by the essential requirement for network operators to enable seamless service assurance, we put forward a framework for disruption-free ETE, which leverages on selective link sleeping and wake-up operations in a disruption-free manner. The framework allows for maximizing the opportunities for disruption-free reconfigurations based on intelligent IGP link weight settings, assisted by a dynamic scheme that optimizes the reconfigurations in response to changing traffic conditions. As our simulation-based evaluation show, the framework is capable of achieving significant energy saving gains while at the same time ensuring robustness in terms of disruption avoidance and resilience to congestion.

Designing and building SDN testbeds for energy-aware traffic engineering services

As experimenting with energy-aware techniques on large-scale production infrastructure is prohibitive , a large number of proposed traffic-engineering strategies have been evaluated only using discrete-event simulations. The present work discusses (i) challenges towards building testbeds that allow researchers and practitioners to validate and evaluate the performance and quality of energy-aware traffic-engineering strategies , (ii) requirements to fulfill when porting simulations to testbeds, and (iii) two proof-of-concept testbeds. One testbed uses and provides Software-Defined Network (SDN) services created on the Open Network Operating System (ONOS) while the other is a composition of virtual Open vSwitches (OVS) controlled by the Ryu SDN framework. The aim of the testbeds is to validate previously proposed energy-aware traffic engineering strategies in different environments. We detail the platforms and illustrate how they have been used for performance evaluation. Additionally, the paper compares results obtained in the testbeds with evaluations performed using discrete-event simulations and presents challenges faced while implementing energy-aware traffic engineering mechanisms as SDN services in testbed environments.

Control system for reducing energy consumption in backbone computer network

SUMMARY Network optimization concerned with operational traffic management in existing data networks is typically oriented towards either maximizing throughput in congested networks while providing for adequate transmission quality, or towards balancing the traffic so as to maintain possibly large free capacity for carrying additional (new) traffic. Nowadays, the reduction of power consumption is a new key aspect in the development of modern wired networks. Power management capabilities allow modulating the energy consumption of devices that form a network by putting them into standby state, or by decreasing their performance in case of low incoming traffic volume. This paper presents a framework for backbone network management, which leads to the minimization of the energy used by this network. The policy for dynamic power management of the whole network through energy-aware routing, traffic engineering, and network equipment activity control is introduced and discussed. The concept of the system is to achieve the desired trade-off between total power consumption and the network performance according to the current load, incoming traffic, and user requirements. The effectiveness of our framework is illustrated by means of a numerical study. Copyright © 2012 John Wiley & Sons, Ltd.

Energy-aware traffic engineering in hybrid SDN/IP backbone networks

Software Defined Networking (SDN) can effectively improve the performance of traffic engineering and has promising application foreground in backbone networks. Therefore, new energy saving schemes must take SDN into account, which is extremely important considering the rapidly increasing energy consumption from Telecom and ISP networks. At the same time, the introduction of SDN in a current network must be incremental in most cases, for both technical and economic reasons. During this period, operators have to manage hybrid networks, where SDN and traditional protocols coexist. In this paper, we study the energy efficient traffic engineering problem in hybrid SDN/IP networks. We first formulate the mathematic optimization model considering SDN/IP hybrid routing mode. As the problem is NP-hard, we propose the fast heuristic algorithm named HEATE (Hybrid Energy-Aware Traffic Engineering). In our proposed HEATE algorithm, the IP routers perform the shortest path routing using the distribute OSPF link weight optimization. The SDNs perform the multi-path routing with traffic flow splitting by the global SDN controller. The HEATE algorithm finds the optimal setting of OSPF link weight and splitting ratio of SDNs. Thus traffic flow is aggregated onto partial links and the underutilized links can be turned off to save energy. By computer simulation results, we show that our algorithm has a significant improvement in energy efficiency in hybrid SDN/IP networks.

Simultaneous routing and flow rate optimization in energy–aware computer networks

Abstract The issue of energy-aware traffic engineering has become prominent in telecommunications industry in the last years. This paper presents a two-criteria network optimization problem, in which routing and bandwidth allocation are determined jointly, so as to minimize the amount of energy consumed by a telecommunication infrastructure and to satisfy given demands represented by a traffic matrix. A scalarization of the criteria is proposed and the choice of model parameters is discussed in detail. The model of power dissipation as a function of carried traffic in a typical software router is introduced. Then the problem is expressed in a form suitable for the mixed integer quadratic programming (MIQP) solver. The paper is concluded with a set of small, illustrative computational examples. Computed solutions are implemented in a testbed to validate the accuracy of energy consumption models and the correctness of the proposed traffic engineering algorithm.

An openflow architecture for energy-aware traffic engineering in mobile networks

To cope with the growing traffic demand, future mobile networks will be denser and integrate heterogeneous technologies. However, if not properly engineered, such networks may incur huge energy waste when there is little traffic, and may suffer from an unbearable management burden caused by the variety of technologies integrated. In this article, we propose and implement a novel management architecture for mobile networks based on OpenFlow, which supports resource-ondemand provisioning in a centralized control plane, and hides the technology specifics from the controller through the use of abstractions. The feasibility of the approach is demonstrated by a real-life prototype based on commercial off-the-shelf devices.

Energy-aware traffic engineering with reliability constraint

Current network infrastructures are over-provisioned to increase their resilience against resource failures. Such strategies exhibit poor energy efficiency during off-peak periods. In this respect, energy aware Traffic Engineering (TE) solutions aim to maximally switch off redundant network resources when traffic load is low. However, these green TE solutions do not consider their effects on network fault-tolerance. In this paper, we first aim to quantify the effects of five recently proposed green routing approaches, namely FGH, GreenTE, MSPF, SSPF, and TLDP, on the following two reliability measures: (i) terminal reliability (TR), and (ii) route reliability (RR). Experiments using three topologies with real and synthetic traffic demands show that green approaches that switch off redundant links affect TR and RR significantly. Specifically, routing traffic through multiple paths impacts reliability less while reducing energy, especially when the paths are link disjoint. Interestingly, TLDP and MSPF have better route reliability than using shortest path (SP) routing. We then formulate a problem, called reliable energy-aware-routing (R-EAR), which aims to maximally switch-off network cables subject to link utilization as well as TR/RR requirement. We also propose an effective algorithm, called reliable Green-Routing (R-GR), to solve R-EAR. Evaluation on three real topologies shows that R-GR can save energy while satisfying both reliability and link utilization requirements. Specifically, for the GEANT network, R-GR saves up to 25.65% in energy usage without reducing RR, and saves up to 48.65% whilst reducing its average RR only by 9.1%. For the same network, our solution achieved an energy saving of 28.38% while reducing its average TR by only 8.5%.

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, GEANT 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.

On IGP link weight optimization for joint energy efficiency and load balancing improvement

The energy consumption of backbone networks has risen exponentially during the past decade with the advent of various bandwidth-hungry applications. To address this serious issue, network operators are keen to identify new energy-saving techniques to green their networks. Up to this point, the optimization of IGP link weights has only been used for load-balancing operations in IP-based networks. In this paper, we introduce a novel link weight setting algorithm, the Green Load-balancing Algorithm (GLA), which is able to jointly optimize both energy efficiency and load-balancing in backbone networks without any modification to the underlying network protocols. The distinct advantage of GLA is that it can be directly applied on top of existing link-sleeping based Energy-aware Traffic Engineering (ETE) schemes in order to achieve substantially improved energy saving gains, while at the same time maintain traditional traffic engineering objectives. In order to evaluate the performance of GLA without losing generality, we applied the scheme to a number of recently proposed but diverse ETE schemes based on link sleeping operations. Evaluation results based on the European academic network topology GÉANT and its real traffic matrices show that GLA is able to achieve significantly improved energy efficiency compared to the original standalone algorithms, while also achieving near-optimal load-balancing performance. In addition, we further consider end-to-end traffic delay requirements since the optimization of link weights for load-balancing and energy savings may introduce substantially increased traffic delay after link sleeping. In order to solve this issue, we modified the existing ETE schemes to improve their end-to-end traffic delay performance. The evaluation of the modified ETE schemes together with GLA shows that it is still possible to save a significant amount of energy while achieving substantial load-balancing within a given traffic delay constraint.

Energy-aware traffic engineering: A routing-based distributed solution for connection-oriented IP networks

The present paper deals with energy saving in IP networks and proposes a distributed energy-aware traffic engineering solution, named DAISIES, for switching off network links according to traffic variations. DAISIES works in a connection-oriented network, e.g. an IP/MPLS network, and follows a routing-based approach, i.e. it acts on the routing algorithm whilst link switch-off/on are consequence of routing decisions. The basic idea is to re-compute the path of each traffic demand when its requested capacity changes. A specific cost function is used to compute link weights into the shortest path routing algorithm with the goal of keeping unused as many links as possible. The main advantages of DAISIES can be summarized as follows: (i) no changes are required to current routing and signaling protocols, (ii) packet loss is completely avoided, (iii) both traffic decreasing and increasing and changing network conditions are automatically managed, and (iv) link switch-off/on take place transparently to the routing protocol and to other nodes. The performance of the proposed solution is evaluated in terms of energy saving relative to a static network optimized to support the peak traffic. Results show that DAISIES is able to save about 30% of energy in several traffic conditions. Moreover, it is shown that it is possible keeping the additional complexity low and still reaching high energy efficiency.

Multi-Objective Traffic Engineering for Future Networks

An important goal towards the design of Future Networks is to achieve the best ratio of performance to energy consumption and at the same time assure manageability. This paper presents a general problem formulation for Energy-Aware Traffic Engineering and proposes a distributed, heuristic Energy-Aware Traffic Engineering scheme (ETE) that provides load balancing and energy-awareness in accordance with the operator's needs. Simulation results of ETE compared to the optimal network performance confirm the capability of ETE to meeting the needs of Future Networks.