Communication networks need to be both adaptive and scalable. The last few years have seen an explosive growth of software-defined networking (SDN) and network function virtualization (NFV) to address this need. Both technologies help enable networking software to be decoupled from the hardware so that software functionality is no longer constrained by the underlying hardware and can evolve independently. Both SDN and NFV aim to advance a software-based approach to networking, where networking functionality is implemented in software modules and executed on a suitable cloud computing platform. Achieving this goal requires the virtualization paradigm used in these services that play an important role in the transition to software-based networks. Consequently, the corresponding computing platforms accompanying the virtualization technologies need to provide the required agility, robustness, and scalability for the services executed. Serverless computing has recently emerged as a new paradigm in virtualization and has already significantly changed the economics of offloading computations to the cloud. It is considered as a low-latency, resource-efficient, and rapidly deployable alternative to traditional virtualization approaches, such as those based on virtual machines and containers. Serverless computing provides scalability and cost reduction, without requiring any additional configuration overhead on the part of the developer. In this paper, we explore and survey how serverless computing technology can help building adaptive and scalable networks and show the potential pitfalls of doing so.

A common practice to increase the reliability of a cloud application is to deploy redundant instances. Unfortunately such redundancy efforts can be undermined if the application's instances share common dependencies. This paper presents ReCloud, a novel system that can efficiently find a reliable deployment plan for cloud applications. ReCloud considers and avoids common dependencies shared across application instances that may lead to correlated failures, and works with applications that even have complex internal structures. ReCloud utilizes various pieces of available dependency information (e.g., hardware, software and/or network dependencies) about the cloud infrastructure to quantitatively assess the reliability of the application's deployment plan with rigorous error bounds. This assessment further enables ReCloud to find a deployment plan that balances between reliability and other criteria such as application performance and resource utilization. We implemented a fully functional system. The experimental results show that, even in a large cloud environment with more than 27K hosts, ReCloud needs only 30 seconds to find a deployment plan that is one order of magnitude more reliable than the common practice.

Network functions virtualization (NFV) environments can provide increased elasticity and flexibility for operators, as network-related services can be scaled and moved as needed. Such operations require a seamless transfer of state to provide a service without interruption or performance degradation. In this paper, we propose and analyze a novel approach for efficient and seamless NFV state transfers. Our approach is based on the concept of statelets, which are compact representations of information in incoming packets that change the state of a virtualized network function. We present and describe slim migration (SliM), a system for efficient NFV state transfers using a statelet interface that we have implemented as an add-on to the data plane development kit, a high-performance packet I/O library. We have evaluated SliM in a testbed and present results that show its benefits in terms of lower delays and lower packet-loss rates. Moreover, our analysis and evaluation results show that SliM offers three times as much shared link capacity to the dataplane as previous approaches, while reducing the duration of a state transfer to one-third of their time.

Online video presents new challenges to traditional caching with over a thousand-fold increase in number of assets, rapidly changing popularity of assets and much higher throughput requirements. We propose a new hierarchical filtering algorithm for caching online video HiFi. Our algorithm is designed to optimize hit rate, replacement rate and cache throughput. It has an associated implementation complexity comparable to that of LRU. Our results show that, under typical operator conditions, HiFi can increase edge cache byte hit rate by 5%--24% over an LRU policy, but more importantly can increase the RAM or memory byte hit rate by 80% to 200% and reduce the replacement rate by more than 100 times! These two factors combined can dramatically increase throughput for most caches. If SSDs are used for storage, the much lower replacement rate may also allow substitution of lower-cost MLC-based SSDs instead of SLC-based SSDs. We extend previous multi-tier analytical models for LRU caches to caches with filtering. We analytically show how HiFi can approach the performance of an optimal caching policy and how to tune HiFi to reach as close to optimal performance as the traffic conditions allow. We develop a realistic simulation environment for online video using statistics from operator traces. We show that HiFi performs within a few percentage points from the optimal solution which was simulated by Belady's MIN algorithm under typical operator conditions

Instance migration and scale-in/out operations in network functions virtualization (NFV) require state transfer mechanisms, which are known to cause service degradation through increased jitter and packet loss. Techniques such as packet duplication for state synchronization mitigate this problem, however, they incur significant additional costs. In this paper, we provide a novel interface to the VNF to announce “statelets” for incoming packets, which comprise only the information in the packet which is required for a VNF's internal state change. Based on this interface, we design and implement SliM, a statelet-based framework for seamless VNF migration. First evaluation results show that SliM operates seamlessly at very high dataplane utilization of physical links, up to 3 times the utilization level at which existing approaches are failing due to insufficient bandwidth for state synchronization.

Online video presents new challenges to traditional caching with over a thousand fold increase in number of assets, rapidly changing popularity of assets and much higher throughput requirements.

Swarm-based peer-to-peer streaming (SPS) mechanisms tend to generate a significant amount of costly inter-ISP traffic. Localization of overlay connectivity reduces inter-ISP traffic. However, it can adversely affect the delivered quality. In this paper, we systematically examine the performance of SPS for live video over localized overlays. We identify and discuss the fundamental bottlenecks limiting the stream quality and present OLIVES, an ISP-friendly P2P streaming mechanism for live video. OLIVES maintains a fully localized overlay to reduce the volume of inter-ISP traffic and incorporates a two-tier inter-ISP and intra-ISP scheduling scheme to maximize the delivered quality to individual peers. One important design choice is to perform basic scheduling at a substream level and to use implicit coordination among peers. This allows OLIVES to efficiently detect missing blocks and pull them into the ISP in a timely manner with a minimum in coordination overhead. Furthermore, OLIVES incorporates a shortcutting technique that limits the buffer requirements for each participating peer and effectively reduced the playout latency. Through analysis and extensive simulations, we demonstrate the ability of OLIVES to deliver high-quality streams over localized overlays in various realistic scenarios.

The proliferation of pictures and videos in the Internet is imposing heavy demands on mobile data networks. Though emerging wireless technologies will provide more bandwidth, the increase in demand will easily consume the additional capacity. To alleviate this problem, we explore the possibility of serving user requests from other mobile devices located geographically close to the user. For instance, when Alice reaches areas with high device density - Data Spots - the cellular operator learns Alice's content request, and guides her device to nearby devices that have the requested content. Importantly, communication between the nearby devices can be mediated by servers, avoiding many of the known problems of pure ad hoc communication. This paper argues this viability through systematic prototyping, measurements, and measurement-driven analysis.

There is growing evidence that mutually beneficial outcomes can be achieved when content distribution overlays and their underlying ISPs collaborate through open interfaces. We further contribute to this body of work by considering consolidated topology construction strategies that integrate the information provided by multiple ISPs. We focus on situations with potentially conflicting, asymmetric preference costs, since these situations are expected to benefit more from the tradeoffs provided by consolidation to produce an overlay topology with desirable global properties. In this paper we develop a generic model for the multi-domain consolidation of ISP preferences expressed as costs for pairwise peer connections, where peers are grouped into clusters based on topology criteria. Using this model, we propose two consolidated topology construction strategies: Shared Cost, designed to provide a tradeoff for preference cost asymmetries, and Low Cost, designed to reduce the overall preference cost that the overlay imposes on all its underlying ISPs. We evaluate these two models through extensive simulations over a wide range of ISP and peer cluster sizes, and we show that preference consolidation can provide ISPs with outcomes more aligned with their preferences than those provided by non-consolidated operation.

HTTP adaptive streaming (HAS) is quickly becoming a popular mechanism for delivering on-demand video content over the Internet. The chunked transmission and application-layer adaptation create a very different traffic pattern than traditional progressive video downloads where the entire video is downloaded with a single request.

Content-centric networks have been proposed as a new network paradigm that is centered around the distribution of content. A key idea of content-centric networks is to address content by name and to enable nodes in the network to respond to content requests. Most proposals for content-centric networks require a "clean slate" approach and a replacement of today's TCP/IP protocol stack, which raises questions about a feasible deployment path. In this paper, we ask the question to which extent the ideas of content-centric networks can be realized on top of today's IP protocol suite. We explore an approach for name-based addressing that extends today's TCP/IP protocols in a fully standard compliant way. We implement our new method in order to demonstrate its feasibility and evaluate the performance of the system using both latency and processing overhead as measures. The obtained results demonstrate that name-based addressing on IP is feasible. We also acknowledge that content-centric networks designed from the ground up go beyond what can be achieved on top of IP.

The consumer interest in mobile multimedia content is on the rise, driven by the higher bandwidth of 3G networks and by the availability of low-cost high-resolution mobile devices. However, providing a good user experience remains a challenge due to bandwidth bottlenecks at peak time, channel quality variations and high battery drain incurred by long data transmission times at lower bandwidths. Consequently high jitter, buffering delays and frequent network outages are ever so common for mobile multimedia services. The emerging mobile broadcast networks (e.g. BCMCS, MediaFLO, DVB-H) are well suited for efficient delivery of highly popular content but lack the on-demand, interactive and retransmission (for reliability) capabilities by virtue of being one-way. In addition, due to business reasons (e.g. MediaFLO) or technical reasons (e.g. BCMCS) service providers prefer to deliver only a limited number of popular channels over these networks. In this paper we propose a mobile content delivery architecture that takes wireless specifics into account to enhance the user experience with multimedia services. Our solution makes efficient use of the available bandwidth, does network and channel quality- aware content delivery on the unicast 3G network while at the same time efficiently and reliably schedules content delivery over the mobile broadcast network. In our solution the delivered content is pre-cached on the storage available on the mobile device. This provides a better user experience, reduces the peak load on the network, and reduces the battery drain on the mobile device. Motivated by the proposed architecture we study the problem of scheduling content over a hybrid unicast and broadcast mobile network and design efficient algorithms and heuristics for the problem.

The availability of Internet services brings many benefits to developing regions, yet Internet deployment levels in these regions remain staggeringly low. In this work we investigate how existing cellular deployments, which have enjoyed more rapid and wider deployment than client Internet infrastructure, could be used to provide very low cost Internet services in underdeveloped rural areas. We propose a new service model in which traffic is delivered over multihop client-to-client connections that are coordinated by end-to-end control traffic exchanged over cellular infrastructure. To enable this scheme in low client density rural settings, we propose a novel data forwarding mechanism for opportunistic space-time paths. To explore multiple opportunistic paths, but without the high forwarding cost of replicating data on these paths, we use network coding and send only a fraction of the data on each path. Through extensive OPNET simulations we show that globally coordinated opportunistic forwarding enables service acceptable to most applications at only a fraction of cellular infrastructure load. We argue that the reduced load on the cellular infrastructure allows additional users to share services and cost of the network and has the potential to lower the per user price of data services in developing regions.

One of the key questions in dimensioning a hybrid P2P content distribution system is that of the required infrastructure support in terms of server bandwidth. In this paper, we develop and propose simple mathematical models for analyzing and dimensioning hybrid peer-to-peer content distribution networks. We first use a deterministic fluid model to capture the essential peer and server dynamics within a single swarm, and subsequently derive a stochastic fluid model to capture the dynamics in the case of multiple swarms, i.e., concurrent swarms of a number of content objects. Based on the models, we derive solutions for estimating the server capacity required to support a single swarm as well as a number of concurrent file swarms at a given level of service quality. Numerical results demonstrate how a hybrid P2P approach can yield substantial performance gains and capacity savings compared to a pure client/server system, with churn rate and upload bandwidth being critical factors. Compared to a pure peer-to-peer scenario, the hybrid approach can dramatically boost the performance and improve reliability.

Multi-rate multicast has been proposed as a scalable solution to transmitting video over the Internet to receivers with heterogeneous and dynamic rate requirements. The applicability of an equation-based mechanism to congestion control for a protocol which bases its join and leave actions on the calculation of the TCP response function is investigated. We focus on the rate calculation algorithm proposed in TFRC (TCP-friendly rate control), as it is currently a very promising and mature approach to calculating a TCP-compatible rate. By means of a network simulator and an adjusted TFRC protocol implementation, we show that the TCP-compatible rate calculated with the algorithm as originally proposed tends to be biased when applied in environments with a low degree of statistical multiplexing. To improve the performance of the basic algorithm, we propose a simple heuristic approach.