Peeking Behind the NAT: An Empirical Study of Home Networks

2015 IEEE 40th Conference on Local Computer Networks (LCN), 2015

Mobile users' Quality-of-Experience (QoE) is degrading as network usage increases while Internet Service Providers (ISP) face increased inter-domain traffic. This paper presents a network traffic management mechanism, named RB-HORST, addressing these inefficiencies. RB-HORST exploits home routers by using them as caches and forming an overlay network between them to transfer content. To shift traffic from peak hours, RB-HORST employs predictions based on social network properties and based on similarity in the overlay network. To further improve user QoE, home routers allow trusted mobile devices to offload their mobile connection to the local WiFi. Simulation results show that an overlay is imperative for the success of the proposed caching mechanism. Especially ISPs with a large number of customers can benefit if only every thousandth user shares its router, reducing inter-domain traffic by half and superseding an ISP operated cache. The presented implementation proves that the concept is technically feasible and can be deployed and run on constrained devices.

2012 Fourth International Conference on Communication Systems and Networks (COMSNETS 2012), 2012

Wireless home networks are increasingly deployed in people's homes worldwide. Unfortunately, home networks have evolved using protocols designed for backbone and enterprise networks, which are quite different in scale and character to home networks. We believe this evolution is at the heart of widely observed problems experienced by users managing and using their home networks. In this paper we investigate redesign of the home router to exploit the distinct social and physical characteristics of the home.

Proc. PAM, 2011

"Many Internet customers use network address translation (NAT) when connecting to the Internet. To understand the extend of NAT usage and its implications, we explore NAT usage in residential broadband networks based on observations from more than 20,000 DSL lines. We present a unique approach for detecting the presence of NAT and for estimating the number of hosts connected behind a NAT gateway using IP TTLs and HTTP user-agent strings. Furthermore, we study when each of the multiple hosts behind a single NAT gateway is active. This enables us to detect simultaneous use. In addition, we evaluate the accuracy of NAT analysis techniques when fewer information is available. We find that more than 90 % of DSL lines use NAT gateways to connect to the Internet and that 10 % of DSL lines have multiple hosts that are active at the same time. Overall, up to 52 % of lines have multiple hosts. Our findings point out that using IPs as host identifiers may introduce substantial errors and therefore should be used with caution."

Proceedings of the 2015 ACM SIGCOMM Workshop on Crowdsourcing and Crowdsharing of Big (Internet) Data, 2015

Despite the very well known smartphone issues such as on-off behaviour and battery/bandwidth limitations, in this paper we show that smartphones can be successfully employed in a crowdsourcing system to perform Internet AS-level topology discovery. We propose and illustrate a measurement methodology that takes these issues into account. We implemented such methodology in Portolan, our smartphone-based crowdsourcing system, and ran six months of measurements. We show that smartphones mobility allows to obtain measurements from 706 different ASes with just 200 active devices. Moreover, we show that our methodology manages to bring novelty with relatively few measurements. On average 27.75% of the AS links found by Portolan are not found by BGP measurements.

Proceedings of the 2010 ACM SIGCOMM workshop on Home networks - HomeNets '10, 2010

Internet traffic to homes is surging, driven by the demand for rich content and the proliferation of home networks. This creates a huge problem for ISPs since residential customers expect the certainty of a fixed bill while ISPs do not want to upgrade backhaul equipment frequently in the absence of extra revenue streams. We consider simple variants on existing flat-rate schemes that will enable homes to self-select a portion of their peak hours traffic and move it to nonpeak hours to benefit from offered incentives. We present a well-defined formulation of the problem and characterize its computational complexity. We show that a simple fractional algorithm achieves the optimal traffic reallocation and is realizable with small modifications to existing infrastructure. The fractional model also captures the reality that homes may be willing to move a fraction of their delay-tolerant traffic in response to appropriate incentives. Using trace-driven simulations based on well-accepted utility models and actual backbone traffic from a large ISP, we demonstrate that our incentive scheme can substantially lower peak congestion while still satisfying the increased demand of home networks.

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication, 2015

Meraki is a cloud-based network management system which provides centralized configuration, monitoring, and network troubleshooting tools across hundreds of thousands of sites worldwide. As part of its architecture, the Meraki system has built a database of time-series measurements of wireless link, client, and application behavior for monitoring and debugging purposes. This paper studies an anonymized subset of measurements, containing data from approximately ten thousand radio access points, tens of thousands of links, and 5.6 million clients from one-week periods in January 2014 and January 2015 to provide a deeper understanding of realworld network behavior. This paper observes the following phenomena: wireless network usage continues to grow quickly, driven most by growth in the number of devices connecting to each network. Intermediate link delivery rates are common indoors across a wide range of deployment environments. Typical access points share spectrum with dozens of nearby networks, but the presence of a network on a channel does not predict channel utilization. Most access points see 2.4 GHz channel utilization of 20% or more, with the top decile seeing greater than 50%, and the majority of the channel use contains decodable 802.11 headers.

Network measurement practitioners increasingly focus their interest on understanding and debugging home networks. The Universal Plug and Play (UPnP) technology holds promise as a highly efficient way to collect and leverage measurement data and configuration settings available from UPnP-enabled devices found in home networks. Unfortunately, UPnP proves less available and reliable than one would hope. In this paper, we explore the usability of UPnP as a means to measure and characterize home networks. We use data from 120,000 homes, collected with the HomeNet Profiler and Netalyzr troubleshooting suites. Our results show that in the majority of homes we could not collect any UPnP data at all, and when we could, the results were frequently inaccurate or simply wrong. Whenever UPnP-supplied data proved accurate, however, we demonstrate that UPnP provides an array of useful measurement techniques for inferring home network traffic and losses, for identifying home gateway models with configuration or implementation issues, and for obtaining ground truth on access link capacity.

Wireless Networks, 2013

This paper presents the characterization of a commercial nationwide Wi-Fi hotspot network. We examine a 5 month long log of user activity and traffic volume collected by a wireless network service provider operating hotspots in restaurants, serviced apartments, hotels and airports all over Australia. We categorize users based on their account time limits to analyze the impact of account stratification on the overall user behavior. A similarity index is developed to compare two datasets of unknown distributions which we then use to quantitatively compare how similar or different various types of accounts are. The user population of the network is found to be highly fluctuating, hence user specific, population independent metrics are proposed to account for this transience. We also introduce metrics to measure account time and data utilization. Key user and traffic statistics are presented for reference.

Proceedings of the 2nd ACM SIGCOMM workshop on Home networks, 2011

Despite the popularity of home networks, they face a number of systemic problems: (i) Broadband networks are expensive to deploy; and it is not clear how the cost can be shared by several service providers; (ii) Home networks are getting harder to manage as we connect more devices, use new applications, and rely on them for entertainment, communication and work-it is common for home networks to be poorly managed, insecure or just plain broken; and (iii) It is not clear how home networks will steadily improve, after they have been deployed, to provide steadily better service to home users. In this paper we propose slicing home networks as a way to overcome these problems. As a mechanism, slicing allows multiple service providers to share a common infrastructure; and supports many policies and business models for cost sharing. We propose four requirements for slicing home networks: bandwidth and traffic isolation between slices, independent control of each slice, and the ability to modify and improve the behavior of a slice. We explore how these requirements allow cost-sharing, out-sourced management of home networks, and the ability to customize a slice to provide higher-quality service. Finally, we describe an initial prototype that we are deploying in homes.

As the Internet continues to grow; it becomes more and more obvious that the communication network and its nodes play an increasingly important role. The traditional network management tools just monitor basic activity of network devices, but there is a common need for more complex solution including a mobile interface providing users with a convenient remote monitoring. Since the Internet of Things concept relays on the smart home gateway as a key component interacting with all sensors and appliances deployed within a building the network monitoring is not interesting only for network operators or companies. Also common end users want to have their intelligent households under a continuous control and be informed about specific events. Considering that and aiming at the monitoring and management of network components, we proposed a solution which is running on Raspberry Pi device with the support of openHAB platform and is able to monitor system resources and network activity of di...