Taisir E. H. El-Gorashi

IP Over WDM Networks Employing Renewable Energy Sources

With network expansion, the energy consumption and CO2 emissions associated with networks are increasing rapidly. In this paper we propose an approach for energy minimization in IP over WDM networks and furthermore propose the use of renewable energy to further reduce the CO2 emissions at a given energy consumption level. We develop a Linear Programming (LP) model for energy minimization in the network when renewable energy is used and propose a novel heuristic for improving renewable energy utilization. Compared with routing in the electronic layer, routing in the optical layer coupled with renewable energy nodes significantly reduces the CO2 emission of the IP over WDM network considered by 47% to 52%, and the new heuristic introduced hardly affects the QoS. In order to identify the impact of the number and the location of nodes that employ renewable energy on the non-renewable energy consumption of whole network, we also constructed another LP model. The results show that the nodes at the center of the network have more impact than other nodes if they use renewable energy sources. We have also investigated the additional energy savings that can be gained through Adaptive Link Rate (ALR) techniques where different load dependent energy consumption profiles are considered. Our optimized REO-hop routing algorithm with renewable energy and ALR results in a maximum energy saving of 85% (average of 65%) compared to a current network design where all nodes are statically dimensioned for the maximum traffic in terms of IP ports and optical layer and hence consume power accordingly. Furthermore, when all the nodes have access to typical levels of renewable power we show that the associated reduction in non-renewable energy consumption reduces the networks CO2 emissions by 97% peak, 78% average.

On the Energy Efficiency of Physical Topology Design for IP Over WDM Networks

The energy consumption of information and communications technology networks is increasing rapidly as a result of the Internet expansion in reach and capacity. In this paper, we investigate energy-efficient physical topologies for backbone IP over wavelength-division multiplexing (WDM) networks. We develop a mixed integer linear programming model to optimize the physical topology of IP over WDM networks with the objective of minimizing the network total power consumption. We consider the National Science Foundation network topology and compare its energy consumption with the energy consumption of optimized physical topologies under different IP over WDM approaches and nodal degree constraints. We study the physical topology optimization under a symmetric full-mesh connectivity traffic matrix and an asymmetric traffic demand, where data centers create a hot node scenario in the network. We also investigate the power savings obtained by deploying topologies that eliminate the need for IP routers, including a full-mesh topology and a star topology. Simulation results show that the full-mesh and star topologies result in significant power savings of 95% and 92%, respectively. Furthermore, the optimization of the physical topology is investigated considering the presence of renewable energy sources in the network. The results show that optimizing the physical topology increases the utilization of the renewable energy sources.

Energy Efficient Virtual Network Embedding for Cloud Networks

Network virtualization is widely considered to be one of the main paradigms for the future Internet architecture as it provides a number of advantages including scalability, on demand allocation of network resources, and the promise of efficient use of network resources. In this paper, we propose an energy efficient virtual network embedding (EEVNE) approach for cloud computing networks, where power savings are introduced by consolidating resources in the network and data centers. We model our approach in an IP over WDM network using mixed integer linear programming (MILP). The performance of the EEVNE approach is compared with two approaches from the literature: the bandwidth cost approach (CostVNE) and the energy aware approach (VNE-EA). The CostVNE approach optimizes the use of available bandwidth, while the VNE-EA approach minimizes the power consumption by reducing the number of activated nodes and links without taking into account the granular power consumption of the data centers and the different network devices. The results show that the EEVNE model achieves a maximum power saving of 60% (average 20%) compared to the CostVNE model under an energy inefficient data center power profile. We develop a heuristic, real-time energy optimized VNE (REOViNE), with power savings approaching those of the EEVNE model. We also compare the different approaches adopting an energy efficient data center power profile. Furthermore, we study the impact of delay and node location constraints on the energy efficiency of virtual network embedding. We also show how VNE can impact the design of optimally located data centers for minimal power consumption in cloud networks. Finally, we examine the power savings and spectral efficiency benefits that VNE offers in optical orthogonal division multiplexing networks.

Distributed Energy Efficient Clouds Over Core Networks

In this paper, we introduce a framework for designing energy efficient cloud computing services over non-bypass IP/WDM core networks. We investigate network related factors including the centralization versus distribution of clouds and the impact of demand, content popularity and access frequency on the clouds placement, and cloud capability factors including the number of servers, switches and routers and amount of storage required in each cloud. We study the optimization of three cloud services: cloud content delivery, storage as a service (StaaS), and virtual machines (VMS) placement for processing applications. First, we develop a mixed integer linear programming (MILP) model to optimize cloud content delivery services. Our results indicate that replicating content into multiple clouds based on content popularity yields 43% total saving in power consumption compared to power un-aware centralized content delivery. Based on the model insights, we develop an energy efficient cloud content delivery heuristic, DEER-CD, with comparable power efficiency to the MILP results. Second, we extend the content delivery model to optimize StaaS applications. The results show that migrating content according to its access frequency yields up to 48% network power savings compared to serving content from a single central location. Third, we optimize the placement of VMs to minimize the total power consumption. Our results show that slicing the VMs into smaller VMs and placing them in proximity to their users saves 25% of the total power compared to a single virtualized cloud scenario. We also develop a heuristic for real time VM placement (DEER-VM) that achieves comparable power savings.

BitTorrent Content Distribution in Optical Networks

In this paper, we extend our previous study on BitTorrent, the most popular peer-to-peer (P2P) protocol, to investigate different aspects related to its energy efficiency in IP over WDM (IP/WDM) networks, validating the power savings previously obtained by modeling and simulation through experimental results. Our contributions can be summarized as follows: First, we compare the energy consumption of our previously proposed energy efficient BitTorrent protocol to that of the original BitTorrent protocol and the client-server (C-S) schemes over bypass IP/WDM networks considering a range of network topologies with different number of nodes and average hop counts. Our results show that for a certain swarm size, the energy efficient BitTorrent protocol achieves higher power savings in networks with lower number of nodes as the opportunity to localize traffic increases. Second, we extend our previously developed energy efficient BitTorrent heuristic enhancing its performance by allowing peers to progressively traverse more hops in the network if the number of peers in the local node is not sufficient. Third, we extend our previously developed mixed integer linear programming model to optimize the location as well as the upload rates of operator controlled seeders (OCS) to mitigate the performance degradation caused by leechers leaving after finishing the downloading operation. Fourth, we compare the power consumption of video on demand (VoD) services delivered using content distribution networks (CDN), P2P, and a promising hybrid CDN-P2P architecture over bypass IP/WDM core networks. A MILP model is developed to carry out the comparison. We investigate two scenarios for the hybrid CDN-P2P architecture: the H-MinNPC model where the model minimizes the IP/WDM network power consumption and the H-MinTPC model where the model minimizes the total power consumption including the network and the CDN datacenters power consumption. Finally, we carry out an experimental evaluation of the original and energy efficient BitTorrent heuristics.

Energy-Efficient Future High-Definition TV

The rapidly growing IPTV market has resulted in increased traffic volumes raising concerns over Internet energy consumption. In this paper, we explore the dynamics of TV viewing behavior and program popularity in order to devise a strategy to minimize energy usage. We evaluate the impact of our strategy by calculating the power consumption of IPTV delivered over an IP-over-WDM network, considering both standard definition and high definition TV. Caches are used to reduce energy consumption by storing the most popular programs at nodes closer to the end user. We then use our knowledge of viewing behaviors to generate a time-driven content replacement strategy to maximize cache hit ratios and minimize energy use. We develop a mixed integer linear programming (MILP) model to evaluate the power consumption of the network while performing time-driven content replacements on caches and validate the results by simulation. Finally, we extend our model to perform content replacements on caches with sleep-mode capabilities which can save power by reducing their size. Our results show that time-based content replacements with such variable caches increase cache hit ratios and so reduces the overall power consumption by up to 86% compared to no caching. Our findings also show that more power savings are achieved for high definition TV compared to standard definition TV, so this strategy will be beneficial in the long term.

Energy-efficient core networks

In this paper, we optimize core networks to minimize the embodied energy and the operational energy and introduce two measures for energy minimization in core content distribution networks: data compression in optical networks and locality in P2P networks. We investigate the impact of taking the embodied energy of network devices into account in the physical topology optimization and compare it to optimizing the physical topology considering operational energy only. The results show significant embodied energy savings up to 59%, resulting in a total energy saving of 47%. We also investigate energy-efficient data compression for optical networks and how to achieve a trade-off between the power consumption of computational resources and memory required to compress and decompress data and the network power savings. The results show that optimizing the data compression ratios in IP over WDM networks considering the non-bypass approach has saved up to 55% of the networks power consumption. Furthermore, we evaluate the power consumption of BitTorrent, the most popular P2P content distribution protocol, over IP over WDM networks and compare it to client/server (C/S) systems. The results reveal that the power-minimized BitTorrent converges to locality in order to achieve lower power consumption, resulting in 36% power savings compared to the C/S model.

Reduction of energy consumption of Video-on-Demand services using cache size optimization

Due to its high traffic demand, Video-on-Demand (VoD) is an energy consuming service. Traffic can be reduced by the deployment of caches where the most popular content is stored closer to clients. In this paper, we evaluate the energy consumption of a cache-based VoD service over an IP over WDM network. We develop a Mixed Integer Linear Programming (MILP) model to optimize the cache size for each node in the network at different times of the day. We consider two traffic scenarios with different downlink and uplink ratios. Our results reveal that, using the optimal cache size can reduce the energy consumption by up to 42%.

Energy efficiency of optical OFDM-based networks

Orthogonal Frequency Division Multiplexing (OFDM) has been proposed as an enabling technique for elastic optical networks to support heterogeneous traffic demands. In this paper, we investigate the energy efficiency of rate and modulation adaptive optical OFDM-based networks. A mixed integer linear programming (MILP) model is developed to minimize the total power consumption of optical OFDM networks. We differentiate between two optimization schemes: power-minimized and spectrum-minimized optical OFDM-based networks. The results show that while similar power consumption savings of up to 31% are achieved by the two schemes compared to conventional IP over WDM networks, the spectrum-minimized optical OFDM is 51% more efficient in utilizing the spectrum compared to the power-minimized optical OFDM.

Caching in green IP over WDM networks

Increasing popularity of media-rich Internet content and the associated growth in power consumption have highlighted the need for energy efficient content distribution schemes. This paper investigates the power savings introduced by caching content in IP over WDM networks. To carry out the study, we develop a MILP model to minimize the power consumption of cache-based services over an IP over WDM network by optimizing the cache sizes of the network nodes at different times of the day. A Constraint-Based Genetic Algorithm CBGA is developed to validate the optimum cache sizes obtained from the MILP model and a simulation based on lightpath bypass validates the power consumption of routing traffic demands. We consider different popularity distributions including the Zipf, Pareto and Bimodal content popularity distributions to exemplify different types of IPTV services. Our results reveal that deploying the optimum variable cache sizes at the nodes reduces the overall network power consumption by up to 42%, 68% and 72% using Zipf, Pareto and Bimodal distributions for content popularity, respectively. We further study the impact of regular cache updates on power efficiency. The results show that removing the 10 most popular objects from caches increases the network power consumption by up to 20%.