Energy-Efficient Softwarized Networks: A Survey

With the dynamic demands and stringent requirements of various applications, networks need to be high-performance, scalable, and adaptive to changes. Researchers and industries view network softwarization as the best enabler for the evolution of networking to tackle current and prospective challenges. Network softwarization must provide programmability and flexibility to network infrastructures and allow agile management, along with higher control for operators. While satisfying the demands and requirements of network services, energy cannot be overlooked, considering the effects on the sustainability of the environment and business. This paper discusses energy efficiency in modern and future networks with three network softwarization technologies: SDN, NFV, and NS, introduced in an energy-oriented context. With that framework in mind, we review the literature based on network scenarios, control/MANO layers, and energy-efficiency strategies. Following that, we compare the references regarding approach, evaluation method, criterion, and metric attributes to demonstrate the state-of-the-art. Last, we analyze the classified literature, summarize lessons learned, and present ten essential concerns to open discussions about future research opportunities on energy-efficient softwarized networks.Comment: Accepted draft for publication in TNSM with minor updates and editin

Online Multicast Traffic Engineering for Software-Defined Networks

Previous research on SDN traffic engineering mostly focuses on static traffic, whereas dynamic traffic, though more practical, has drawn much less attention. Especially, online SDN multicast that supports IETF dynamic group membership (i.e., any user can join or leave at any time) has not been explored. Different from traditional shortest-path trees (SPT) and graph theoretical Steiner trees (ST), which concentrate on routing one tree at any instant, online SDN multicast traffic engineering is more challenging because it needs to support dynamic group membership and optimize a sequence of correlated trees without the knowledge of future join and leave, whereas the scalability of SDN due to limited TCAM is also crucial. In this paper, therefore, we formulate a new optimization problem, named Online Branch-aware Steiner Tree (OBST), to jointly consider the bandwidth consumption, SDN multicast scalability, and rerouting overhead. We prove that OBST is NP-hard and does not have a $|D_{max}|^{1-\epsilon}$-competitive algorithm for any $\epsilon >0$, where $|D_{max}|$ is the largest group size at any time. We design a $|D_{max}|$-competitive algorithm equipped with the notion of the budget, the deposit, and Reference Tree to achieve the tightest bound. The simulations and implementation on real SDNs with YouTube traffic manifest that the total cost can be reduced by at least 25% compared with SPT and ST, and the computation time is small for massive SDN.Comment: Full version (accepted by INFOCOM 2018

An Information-Aware QoE-Centric Mobile Video Cache

Recent years have seen a tremendous growth in the volume of video traffic in mobile settings. In this paper, we present the design of a mobile video-centric proxy cache, named iProxy, that offers improved performance in terms of both hit rates and streaming quality. Our thesis in designing iProxy is that we need to elevate the traditional view of caching from “data ” to “information ” in order to optimally meet the stringent requirements of video streaming in mobile settings. iProxy relies on recent advances on informationbound references (IBRs) to collapse multiple related cache entries into a single one, improving hitrate while lowering storage costs. iProxy incorporates a novel dynamic linear rate adaptation scheme to ensure high stream quality in face of channel diversity and device heterogeneity. Our evaluation of iProxy using realistic traffic traces shows that it can improve hitrate, but we need to use novel information-aware replacement policies for optimal performance. We show that our linear encoder can adapt well to changes in bandwidth, and yield better bit rates, lower buffering and lower start up delays than state-of-the-art schemes

Refactoring content overhearing to improve wireless performance

Many systems have leveraged the broadcast nature of wireless radios to improve wireless capacity and performance. While conventional approaches have focused on overhearing entire packets, recentdesignshavearguedthatfocusingonoverheardcontentmay be more effective. Unfortunately, key design choices in these approaches limitthem from fullyleveraging the benefits of overhearingcontent. Weproposeacleanerrefactoringoffunctionalitywherein overhearing is realized at the sub-packet payload level through the use of IP-layer redundancy elimination. We show that this dramaticallyimprovestheeffectivenessofprioroverhearingbasedapproaches and enables new designs, e.g., enhanced network coding, where content overhearing can be more effectively integrated to improve performance. Realizing the benefits of IP-layer content overhearing requires us to overcome challenges arising from the probabilistic nature of wireless reception (which could lead to inconsistent state) and the limitedresources on wireless devices. We overcome thesechallenges throughcarefuldatastructureandwirelessredundancy eliminationdesigns. Weevaluate the effectiveness ofoursystemusingexperimentationonrealtraces. Wefindthatour design is highly effective: e.g., it can improve goodput by nearly 25 % and airtime utilizationby nearly20%. Categories andSubject Descriptor

A Low-overhead Network Monitoring for SDN-Based Edge Computing

International audienceUsing Software-Defined Networking (SDN) in edge computing environments allows for more flexible flow monitoring than traditional networking methods. In SDN, the controller collects statistics from all switches and can communicate with switches to dynamically manage the entire network. However, monitoring per-flow or per-switch mechanisms to obtain the flow statistics from all of the switches may significantly increase bandwidth costs between switches and the control plane. In this paper, we propose a Bandwidth Cost First (BCF) algorithm to reduce the number of monitored switches and therefore lower the monitoring cost. The experiment results show that our algorithm outperforms the existing technique by reducing the number of monitored switches by 56%, leading to a reduction in bandwidth overhead of 41% and switch processing delay by 25%

A Low-overhead Network Monitoring for SDN-Based Edge Computing

International audienceUsing Software-Defined Networking (SDN) in edge computing environments allows for more flexible flow monitoring than traditional networking methods. In SDN, the controller collects statistics from all switches and can communicate with switches to dynamically manage the entire network. However, monitoring per-flow or per-switch mechanisms to obtain the flow statistics from all of the switches may significantly increase bandwidth costs between switches and the control plane. In this paper, we propose a Bandwidth Cost First (BCF) algorithm to reduce the number of monitored switches and therefore lower the monitoring cost. The experiment results show that our algorithm outperforms the existing technique by reducing the number of monitored switches by 56%, leading to a reduction in bandwidth overhead of 41% and switch processing delay by 25%

A Low-overhead Network Monitoring for SDN-Based Edge Computing

International audienceUsing Software-Defined Networking (SDN) in edge computing environments allows for more flexible flow monitoring than traditional networking methods. In SDN, the controller collects statistics from all switches and can communicate with switches to dynamically manage the entire network. However, monitoring per-flow or per-switch mechanisms to obtain the flow statistics from all of the switches may significantly increase bandwidth costs between switches and the control plane. In this paper, we propose a Bandwidth Cost First (BCF) algorithm to reduce the number of monitored switches and therefore lower the monitoring cost. The experiment results show that our algorithm outperforms the existing technique by reducing the number of monitored switches by 56%, leading to a reduction in bandwidth overhead of 41% and switch processing delay by 25%