Live video streaming is widespread and a heavy consumer of Internet bandwidth. As such, it is important to evaluate the quality of that streaming, particularly over links that may pose challenges to near-real-time content delivery. In this paper, we study the performance of Twitch, one of the leading live streaming platforms, over Geosynchronous Earth Orbit (GEO) satellite networks; GEO networks are a key technology for connecting users in challenging environments, yet they suffer from high latency. To do so, we conduct controlled experiments that compare Twitch live stream performance on a high-latency GEO network to that on a low-latency campus network. We analyze core quality of experience metrics – resolution, frames per second, rebuffering, and playback delay – to pinpoint how satellite-induced delays disrupt streaming quality. Our findings reveal a critical flaw in Twitch’s client scheduling: chunk request intervals are not calibrated to accommodate GEO network latency. As a result, playback buffers deplete before the next video chunk arrives, triggering frequent rebuffering, increased latency, and a notable deterioration in quality of experience. By highlighting this gap, our work underscores the urgency of latency-aware streaming strategies and adaptive scheduling algorithms. These insights offer actionable guidance for platform developers, satellite ISPs, and researchers, ultimately paving the way for more robust, inclusive live stream experiences as the medium’s popularity and influence continue to climb.

Poor broadband access undermines civic and economic life, a challenge exacerbated by the fact that millions of Americans still lack access to reliable high-speed broadband connectivity. Federal broadband funding initiatives such as the Connect America Fund (CAF), the Rural Digital Opportunity Fund (RDOF), and the Broadband Equity, Access, and Deployment (BEAD) seek to address these gaps, but their success relies on the accuracy of broadband availability and affordability data. This data is often based on self-reported ISP information that overstates coverage and speeds. Such inaccuracies risk misallocating funds, leaving unserved and underserved communities without high-speed Internet. In this work, we present BQT+, an ML-based data collection platform that queries ISP web interfaces by inputting residential street addresses and extracting the returned data on service availability, quality, and pricing. BQT+ has been applied in policy evaluation studies, including an independent assessment of the state of broadband availability, quality (available speed tiers), and affordability in areas expected to benefit from the $42.45 billion BEAD program.

Residential fixed broadband internet access in the US remains inequitable, despite significant taxpayer investment. This paper evaluates the efficacy of the Connect America Fund (CAF), which subsidizes new broadband monopolies in underserved areas to provide internet access comparable to that in urban regions. CAF's oversight relies heavily on self-reported data from internet service providers (ISPs). Unfortunately, the reliability of this self-reported data has always been open to question. We use the broadband-plan querying tool (BQT) to create a novel dataset that complements ISP-reported information with ISP-advertised broadband plan details from publicly accessible websites for 537k residential addresses across 15 states. Our analysis reveals significant discrepancies, with a serviceability rate of only 55.45%, indicating that a significant fraction of addresses certified as served are still unserved. Furthermore, we observe a compliance rate of only 33.03%, indicating that a significant fraction of served addresses receive download speeds that are non-compliant with the FCC's 10 Mbps threshold for CAF-served addresses. Although we observe that CAF-served addresses occasionally receive higher download speeds than their monopoly-served neighbors, overall, the CAF program has largely failed to achieve its intended goal, leaving many targeted rural communities with inadequate or no broadband connectivity.

In 2011, the United Nations declared Internet access to be a basic human right. Achieving universal Internet access has been a longstanding goal of governments around the world. In the United States (US), provision depends primarily on decisions made by Internet Service Providers (ISPs) driven essentially by commercial market concerns. To encourage deployment in underserved regions, the US federal government has recently allocated unprecedented funding, with distributions guided by the information in broadband maps, spatial representations of current Internet access and quality published by the Federal Communication Commission. Yet, these maps are known to be inaccurate, especially for populations that are marginalized, such as tribal and rural residents. We are interested in the collaborative and contentious efforts to repair the data contained in broadband maps, and particularly by the efforts of citizen groups and local government to counter claims made by ISPs. In this paper, we study these efforts via interviews of 14 individuals involved in various local and regional roles, in policy, IT, advocacy, and research. We draw upon frameworks of repair and of data activism to ask who does this work and why; what tangible and intangible tools are brought to bear; and how the structural context simultaneously empowers and burdens repair workers. In doing so, we make three contributions: (i) we critique the process and system for broadband map repair for the burdens it places on historically marginalized groups to demonstrate how they have been left out of expansion and how their experiences are otherwise silent in official records; (ii) we bring together analytical concepts from repair and data arenas to examine repair work that is substantially shaped by socio, political, and economic context; and (iii) we illustrate how viewing broadband data workers as activists reveals the inadequacy of current tools and the opportunity for better support for their long-term, contextualized, and mediated efforts.

Geosynchronous satellite (GEO) networks are a crucial option for users beyond terrestrial connectivity. However, unlike terrestrial networks, GEO networks exhibit high latency and deploy TCP proxies and traffic shapers. The deployment of proxies mitigates the impact of high network latency, while traffic shapers help realize customer-controlled data-saver options that optimize data usage. It is unclear how the interplay between GEO networks' high latency, TCP proxies, and traffic-shaping policies affects the quality of experience (QoE) for commonly used video applications. In our study, we examine this relationship through a series of video streaming experiments at a shaped rate of 900kbps. Our preliminary analysis reveals that 28% of TCP sessions (with TCP proxies) and 18% of gQUIC sessions (without TCP proxies) experience rebuffering events, while the median average resolution is only 380p for TCP and 299p for gQUIC. Additionally, we identify two key factors contributing to sub-optimal performance: (i) unlike TCP, gQUIC only utilizes 63% of network capacity; and (ii) YouTube's chunk request pipelining is imperfect. To avoid potential degradation in video quality, the satellite provider subsequently discontinued providing data saver options that shape video traffic to US residential customers.

Digital equity in Internet access is often measured along three axes: availability, affordability, and adoption. Most prior work focuses on availability; the other two aspects have received less attention. In this paper, we study broadband affordability in the US by focusing on the nature of broadband plans offered by major ISPs. To this end, we develop a broadband plan querying tool (BQT) that obtains broadband plans (upload/download speed and price) offered by seven major wireline US ISPs for any street address in the US. We then use this tool to curate a dataset, querying broadband plans for over 837 k street addresses in thirty cities for these ISPs. We use a plan's carriage value, defined as the Mbps of a user's traffic that an ISP carries for one dollar, to compare plans. Our analysis provides us with the following new insights: (1) ISP plans vary inter-city. Specifically, up to 60% of the census block groups in a city can receive low carriage value plans from an ISP; (2) ISP plans intra-city are spatially clustered, and the carriage value can vary as much as 600% within a city; (3) Cable-based ISPs offer up to 30% higher carriage value to users when they are competing with fiber-based ISPs in a block group compared to when they are operating alone or in conjunction with a DSL-based ISP; and (4) Fiber deployments, which have better carriage values, are associated with higher average income block groups. While we hope our tool, dataset, and analysis in their current form are helpful for policymakers at different levels (city, county, state), they are only a small step toward quantifying digital inequity. We conclude with recommendations to further advance our understanding of broadband affordability.

The Federal Communications Commission (FCC) has recently released official technical requirements for its Broadband Data Collection (BDC) processes, with the purpose of improving the accuracy of broadband coverage data in the United States. A key process in the BDC establishes the opportunity for communities to crowdsource Internet measurements that may dispute coverage data maintained by Internet service providers. This process outlines complex requirements that may provide a substantial barrier to community participation. In this poster we share the design of a network measurement tool suite and the requirements for a community coordination tool to support community-led efforts to challenge official reports. Our design is based on “counter-data action” principles, which call unethical and authoritative uses of data into question.

It is well documented that, in the United States (U.S.), the availability of Internet access is related to several demographic attributes. Data collected through end user network diagnostic tools, such as the one provided by the Measurement Lab (M-Lab) Speed Test, allows the extension of prior work by exploring the relationship between the quality, as opposed to only the availability, of Internet access and demographic attributes of users of the platform. In this study, we use network measurements collected from the users of Speed Test by M-Lab and demographic data to characterize the relationship between the quality-of-service (QoS) metric download speed, and various critical demographic attributes, such as income, education level, and poverty. For brevity, we limit our focus to the state of California. For users of the M-Lab Speed Test, our study has the following key takeaways: (1) geographic type (urban/rural) and income level in an area have the most significant relationship to download speed; (2) average download speed in rural areas is 2.5 times lower than urban areas; (3) the COVID-19 pandemic had a varied impact on download speeds for different demographic attributes; and (4) the U.S. Federal Communication Commission’s (FCC’s) broadband speed data significantly over-represents the download speed for rural and low-income communities compared to what is recorded through Speed Test.

Globally, 43% of households lack Internet access, primarily in regions where deployment and/or service costs are prohibitive, including in the least developed countries, rural locations, and regions with high concentrations of ethnic minorities and low-income populations. Unfortunately, this lack of Internet access increasingly equates to a lack of access to essential services, such as healthcare, education, and economic opportunities. In an environment of marginal economics, creative and varied approaches to obtaining access have flourished, including Internet kiosks long popular in the Global South, libraries as public access in the Global North, parking lot use of open WiFi access points, and spectrum-based solutions such as TV whitespace links and citizen band radio. In the near future, local 5G and the deployment of satellite constellations promise yet additional options in the price/performance space for access. In this context we are interested in the following research question: How can the presence of multiple networks, with different price, performance, and geographic reach profiles, be best used in concert to improve access to critical services? We propose that a robust answer to this question bears a holistic, cross-layer examination of new communication paradigms, network architecture innovation, and application design. We make this concrete by running to ground a specific case study of two networks, one high performance yet limited in geographic scope and the other low performance yet pervasive. Specifically our LoRaX (LoRa eXtends the Internet) system combines high bandwidth but non-pervasive Internet access with a low data rate, low power, yet ubiquitious network made possible by IoT developments. By focusing on two networks with extreme differences, we explore a design space that offers users new opportunities for participating in Internet-based services–even when high speed Internet connectivity is intermittent. We also reflect on the generality of the environment and our solution approach for future multi-network settings.

Crowdsourced speed test measurements, such as those by Ookla® and Measurement Lab (M-Lab), offer a critical view of network access and performance from the user's perspective. However, we argue that taking these measurements at surface value is problematic. It is essential to contextualize these measurements to understand better what the attained upload and download speeds truly measure. To this end, we develop a novel Broadband Subscription Tier (BST) methodology that associates a speed test data point with a residential broadband subscription plan. Our evaluation of this methodology with the FCC's MBA dataset shows over 96% accuracy. We augment approximately 1.5M Ookla and M-Lab speed test measurements from four major U.S. cities with the BST methodology. We show that many low-speed data points are attributable to lower-tier subscriptions and not necessarily poor access. Then, for a subset of the measurement sample (80k data points), we quantify the impact of access link type (WiFi or wired), WiFi spectrum band and RSSI (if applicable), and device memory on speed test performance. Interestingly, we observe that measurement time of day only marginally affects the reported speeds. Finally, we show that the median throughput reported by Ookla speed tests can be up to two times greater than M-Lab measurements for the same subscription tier, city, and ISP due to M-Lab's employment of different measurement methodologies. Based on our results, we put forward a set of recommendations for both speed test vendors and the FCC to con-textualize speed test data points and correctly interpret measured performance.

Despite widespread LTE deployment, coverage does not necessarily translate to usable service. Even in well-provisioned urban networks, unusually high usage (such as during a public event or after a natural disaster) can lead to congestion that makes the LTE service difficult, if not impossible, to use, even if the user is solidly within the coverage area. A typical approach to detect and quantify congestion on LTE networks is to secure the cooperation of the network provider for access to internal metrics. An alternative approach is to deploy multiple mobile devices with active subscriptions to each network operator. Both approaches are resource and time intensive. In this work, we propose a novel method to estimate congestion from overloaded LTE networks using only passive measurements, and without requiring provider cooperation. We analyze packet-level traces for four commercial LTE service providers, from several locations during both typical levels of usage and during public events that yield large, dense crowds. This study presents the first look at congestion detection through overload estimation by examining unencrypted broadcast messages. We show that an upsurge in broadcast reject and cell barring messages, leading to overload, can accurately detect an increase in network congestion.

Cellular network performance does not cleanly generalize. A variety of factors, such as location, terrain, signal quality and network load, affect the performance of services delivered over LTE networks. As a result, the presence of LTE coverage does not always equate to usable service; coverage can be of poor quality, or it can be congested and difficult to access. Given that reliance on LTE networks for Internet connectivity has exploded, it is critical to understand the quality of experience for applications delivered over these networks in a variety of scenarios. To this end, we develop a robust measurement suite that we use to conduct a unique measurement campaign in tribal, rural, congested urban and uncongested urban regions, representing a variety of under-provisioned, congested, and well-provisioned operational LTE networks run by four major providers. Our analysis confirms that the performance of LTE networks in tribal and rural areas is typically worse than even heavily congested urban networks. More specifically, in the regions that we study, LTE networks in under-provisioned (tribal/rural) areas have $ 9\times$ poorer video streaming quality, $ 10\times$ higher video start-up delay, undergo more than $ 10\times$ the number of resolution switches, and lead to more than $ 2\times$ slower Web browsing experience as compared to urban deployments. We show that throughput and latency are $ 11\times$ and $ 3\times$ worse in tribal and rural locations, despite identical LTE carrier subscription plans.

Researching and designing Internet infrastructure solutions in rural and tribal contexts requires reciprocal relationships between researchers and community partners. Methodologies must be meaningful amid local social textures of life. Achieving transdisciplinarity while relating research impacts to partner communities takes care work, particularly where technical capacity is scarce. The Full Circle Framework is an action research full stack development methodology that foregrounds reciprocity among researchers, communities, and sovereign Native nations as the axis for research purpose and progress. Applying the framework to deploy television white space infrastructure in sovereign Native nations in northern New Mexico reveals challenges for rural computing, including the need to design projects according to the pace of rural and tribal government workflows, cultivate care as a resource for overworked researchers and community partners, and co-create a demand for accurate government data around Internet infrastructures in Indian Country and through rural counties.

Andrew Gaut, Tony Sun, Shirlyn Tang, Yuxin Huang, Jing Qian, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020.

This work uses experimental measurements to study the impact of network configuration and flight planning on Unmanned Aircraft System (UAS) assisted data collection in a 2.4GHz IEEE 802.15.4 outdoor aerial testbed. Our paper builds on previous work in UAS data collection from 802.15.4 outdoor sensor networks by conducting a novel investigation of the impact of antenna orientation on transceivers with external straight wire antennae. We study the effects of toroidal radiation and antenna polarization on signal strength, and we compare external antenna configurations to the commonly used embedded coiled antenna modules. We model our data using a Zero Inflated Negative Binomial (ZINB) model. For each hardware configuration and orientation, we identify the optimal altitude to fly a UAS. Our results show that choosing antenna configuration (including type and orientation) for an IoT network depends on the intended UAS collection flight plan.

Natural disasters are increasing worldwide at an alarming rate. To aid relief operations during and post disaster, humanitarian organizations rely on various types of situational information such as missing, trapped or injured people and damaged infrastructure in an area. Crucial and timely identification of infrastructure and utility damage is critical to properly plan and execute search and rescue operations. However, in the wake of natural disasters, real-time identification of this information becomes challenging. In this research, we investigate the use of tweets posted on the Twitter social media platform to detect power and communication outages during natural disasters. We first curate a data set of 18,097 tweets based on domain-specific keywords obtained using Latent Dirichlet Allocation. We annotate the gathered data set to separate the tweets into different types of outage-related events: power outage, communication outage and both power-communication outage. We analyze the tweets to identify information such as popular words, length of words and hashtags as well as sentiments that are associated with tweets in these outage-related categories. Furthermore, we apply machine learning algorithms to classify these tweets into their respective categories. Our results show that simple classifiers such as the boosting algorithm are able to classify outage related tweets from unrelated tweets with close to 100% f1-score. Additionally, we observe that the transfer learning model, BERT, is able to classify different categories of outage-related tweets with close to 90% accuracy in less than 90 seconds of training and testing time, demonstrating that tweets can be mined in real-time to assist first responders during natural disasters.

Recent studies show that 85% of women have changed their traveled routes to avoid harassment and assault. Despite this, current mapping tools do not empower users with information to take charge of their personal safety. We propose SafeRoute, a novel solution to the problem of navigating cities and avoiding street harassment and crime. Unlike other street navigation applications, SafeRoute introduces a new type of path generation via deep reinforcement learning. This enables us to successfully optimize for multi-criteria path-finding and incorporate representation learning within our framework. Our agent learns to pick favorable streets to create a safe and short path with a reward function that incorporates safety and efficiency. Given access to recent crime reports in many urban cities, we train our model for experiments in Boston, New York, and San Francisco. We test our model on areas of these cities, specifically the populated downtown regions with high foot traffic. We evaluate SafeRoute and successfully improve over state-of-the-art methods by up to 17% in local average distance from crimes while decreasing path length by up to 7%.

Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019.

Jing Qian, Anna Bethke, Yinyin Liu, Elizabeth Belding, William Yang Wang. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Today's smartphones are equipped with both Wi-Fi and cellular interfaces, creating usage opportunities for protocols such as Multi-path TCP (MPTCP), which enable devices to use more than one interface concurrently. One of the biggest hurdles in implementing MPTCP is the heterogeneity in performance characteristics that exists across multiple interfaces. This makes the selection of primary interface of paramount importance, as this interface is also used for DNS resolution. In this work, we explore performance and IP reachability over real world networks. Our findings indicate that widespread MPTCP deployment faces significant obstacles. In particular, we perform controlled and real world experiments over multiple paths with differing loss rates and round trip latencies to assess the effect of primary path selection, and the range of issues that arise from selecting the under-performing path. Using results from our experiments, we show how heterogeneous paths can adversely affect MPTCP performance, especially when one path is lossy.

We investigate Internet traffic logs on rural Native American reservations in California served by a tribally-owned Internet provider. The anonymous user browsing traffic and device preferences create unique failure patterns that reveal where connectivity is not well-served by standard networking technology. Geographical and cultural marginalization has lead to distinctive Internet usage when connectivity is available. For instance, residents commonly visit websites that are not as popular in the wider United States; and mobile devices dominate web request traffic, often with content-heavy video and media downloads, despite sustaining a higher rate of failure than desktop devices. This statistical analysis of passive measurements avoids institutional and cultural biases and ensures continuing research will contribute to a decolonizing narrative of Native American informational practices and values. Based on our analysis, we propose follow-up research angles to better understand the technological and social drivers behind these findings in order to improve user experience in this, and similar, networks.

Over 87% of US mobile wireless subscriptions are currently held by LTE-capable devices [34]. However, prior work has demonstrated that connectivity may not equate to usable service. Even in well-provisioned urban networks, unusually high usage (such as during a public event or after a natural disaster) can lead to overload that makes the LTE service difficult, if not impossible to use, even if the user is solidly within the coverage area. A typical approach to detect and quantify overload on LTE networks is to secure the cooperation of the network provider for access to internal metrics. An alternative approach is to deploy multiple mobile devices with active subscriptions to each mobile network operator (MNO). Both approaches are resource and time intensive. In this work, we propose a novel method to estimate overload in LTE networks using only passive measurements, and without requiring provider cooperation. We use this method to analyze packet-level traces for three commercial LTE service providers, T-Mobile, Verizon and AT&T, from several locations during both typical levels of usage and during public events that yield large, dense crowds. This study presents the first look at overload estimation through the analysis of unencrypted broadcast messages. We show that an upsurge in broadcast reject and cell barring messages can accurately detect an increase in network overload.

Despite widespread LTE adoption and dependence, rural areas lag behind in coverage availability and quality. In the United States, while the Federal Communications Commission (FCC), which regulates mobile broadband, reports increases in LTE availability, the most recent FCC Broadband Report was criticized for overstating coverage. Physical assessments of cellular coverage and quality are essential for evaluating actual user experience. However, measurement campaigns can be resource, time, and labor intensive; more scalable measurement strategies are urgently needed. In this work, we first present several measurement solutions to capture LTE signal strength measurements, and we compare their accuracy. Our findings reveal that simple, lightweight spectrum sensing devices have comparable accuracy to expensive solutions and can estimate quality within one gradation of accuracy when compared to user equipment. We then show that these devices can be mounted on Unmanned Aircraft Systems (UAS) to more rapidly and easily measure coverage across wider geographic regions. Our results show that the low-cost aerial measurement techniques have 72% accuracy relative to the ground readings of user equipment, and fall within one quality gradation 98% of the time.

Unmanned Aircraft Systems (UAS) are a promising technology for data collection from outdoor sensor networks. Environmental and agricultural networks may not have existing internet backhauls for data delivery due to low population densities in rural areas, making UASs a potential data delivery alternative. UASs can be deployed as aerial network relay nodes [1, 2, 3, 4] or as data mules [5, 6]. In addition to mending network fragmentation, UAS applications include post-disaster data collection involving inoperative communication infrastructure [7, 8, 9], supplementing existing communication in- frastructure for vehicular networks [10], and rural applications in environmental monitoring [11, 12] and precision agriculture [13, 14].

While cellular networks connect over 3.7 billion people worldwide, their availability and quality is not uniform across regions. Under-provisioned and overloaded networks, as are common in rural or post-disaster areas, lead to poor network performance and a poor-quality user experience. To address this problem, we propose HybridCell: a system that leverages locally-owned small-scale cellular networks to augment the operation of overloaded commercial networks. HybridCell is the first system to allow a user with their existing SIM card and mobile phone to seamlessly switch between commercial and local networks in order to maintain continuous connectivity. HybridCell accomplishes this by identifying poorly-performing networks and taking action to provide seamless cellular connectivity to end users. Using traces from commercial cellular networks collected during our visit to the Za'atari refugee camp in Jordan, we demonstrate HybridCell's capability to detect and act upon commercial network overload, offering an alternate communication channel during times of congestion. We show that even in scenarios where provider networks deny calls due to overload, HybridCell is able to accommodate users and facilitate local calling.

Existing work on automated hate speech detection typically focuses on binary classification or on differentiating among a small set of categories.In this paper, we propose a novel method on a fine-grained hate speech classification task, which focuses on differentiating among 40 hate groups of 13 different hate group categories.We first explore the Conditional Variational Autoencoder (CVAE) (Larsen et al., 2016;Sohn et al., 2015) as a discriminative model and then extend it to a hierarchical architecture to utilize the additional hate category information for more accurate prediction.Experimentally, we show that incorporating the hate category information for training can significantly improve the classification performance and our proposed model outperforms commonly-used discriminative models.

With fewer than 66% of eligible voters registered and voter turnout rates 5-14 percentage points lower than any other ethnic group, Native Americans comprise the least participatory ethnic group in U.S. political elections [42, 57, 49, 25]. While discourse surrounding Native American issues and interests has increasingly moved to social media [55, 56], there is a lack of data about Native American political discourse on these platforms. Given the heterogeneity of Native American peoples in the U.S., one way to begin approaching a holistic understanding of Native American political discourse on social media is to characterize how Native American advocates utilize social media platforms for connective action. Using a post-structural, interdisciplinary, mixed methods approach, we use theories of connective action [5] and media richness [14] to analyze a Twitter data set culled from influential Native American advocates and their followers during the 2016 primary presidential election season. Our study sheds light on how Native American advocates use social media to propagate political information and identifies which issues are central to the political discourse of Native American advocates. Furthermore, we demonstrate how the bandwidth characteristics of content impact its propagation and we discuss this in the context of pernicious digital divide effects present in Indian Country.

While online social networks (OSNs) play a critical role in developing social capital [18], many communities are unable to utilize the benefits of OSNs due to lack of Internet accessibility. In this paper, we investigate the feasibility of the Radio Broadcast Data System (RBDS) associated with FM radio stations as a means to deliver social network content to OSN users who do not have access to Internet services. Using Instagram as a case study, we analyze data from 254 public Instagram users associated with the Tribal Digital Village (TDV) network in Southern California. Our analysis of over 1.2 million unique Instagram posts reveals that Instagram users in the TDV network interact with locally generated content 46.6× more often than content generated by users from outside the network. We use our observations of OSN usage to compare five OSN content scheduling approaches. Our evaluation reveals that up to 81% of users received at least half of their content requests and 35.5% of the 1.1 million requested Instagram photos were transmitted to users.

Ubiquitous cellular coverage is often taken for granted, yet numerous people live outside, or at the fringes, of commercial cellular coverage. Further, natural disasters and human rights violations cause the displacement of millions of people annually worldwide, with many of these people relocating to shelters and camps in areas at or just beyond the margins of existing cellular infrastructure. In this work we design PhoneHome, a system prototype that extends existing cellular coverage to areas with no or damaged cellular infrastructure, or infrastructure that is otherwise poorly performing. We explore the feasibility of PhoneHome and address current limitations and future directions for independently operated, user-extensible cellular infrastructure.

Despite the appearance of uniform availability of mobile services, in many locales granular network analyses reveal the persistence of physical access divides. It stands to reason these divides, similar to those at larger scales, are also reflections of community-level social and economic divides.

While cellular networks connect over 3.7 billion people worldwide, their availability and quality is not uniform across regions. Under-provisioned and overloaded networks lead to poor network performance and an aggravated user experience. To address this problem we propose HybridCell: a system that leverages locally-owned small-scale cellular networks to augment the operation of overloaded commercial networks. HybridCell is the first system to allow a user with their existing SIM card and mobile phone to seamlessly switch between commercial and local networks in order to maintain continuous connectivity. Hybrid-Cell accomplishes this by identifying poorly-performing networks and taking action to provide seamless cellular connectivity to end users. Using traces collected from observing the cellular infrastructure during our visit to the Za'atari refugee camp in Jordan, we demonstrate HybridCell's capability to detect and act upon commercial network overload, offering an alternate communication channel during times of congestion. We show that even in scenarios where provider networks deny calls due to overload, HybridCell is able to accommodate users and facilitate local calling.

No abstract available.

With broadband penetration rates of less than 10% per capita, Tribal areas in the U.S. represent some of the most underserved communities in terms of Internet access. Although numerous sources have identified this digital divide, there have been no empirical measurements of the performance and usage of services that do exist in these areas. In this paper, we present the characterization of the Tribal Digital Village (TDV) network, a multi-hop wireless network currently connecting 13 reservations in San Diego county. This work represents the first traffic analysis of broadband usage in Tribal lands. After identifying some of the unique purposes of broadband connectivity in indigenous communities, such as language revitalization and cultural development, we focus on the performance of popular applications that enable such activities, including Youtube and Instagram. Though only a fraction of the bandwidth capacity is actually used, 30% of Youtube uploads and 24% of Instagram uploads fail due to packet loss on the relay and access links that connect the reservations to the TDV backbone. Although failure rates are prohibitive to the contribution of locally generated media (particularly videos), our analysis of Instagram media interactions and engagement in the TDV network reveals a high locality of interest. Residents engage with locally created media 8.2 times more than media created by outside sources. Furthermore, locally created media circulates through the network two days longer than non-local media. The results of our analysis point to new directions for increasing content availability on reservations.

Due to frequent non-line-of-sight (NLOS) signal reception, geopositioning using Global Navigation Satellite Systems (GNSS), such as GPS, is unreliable in urban environments, with errors on the order of tens of meters. This poses a major problem for mobile services that benefit from accurate urban localization, such as navigation, geofencing, and hyperlocal advertising applications. Mobile network operators also seek improvements in localization, as government regulators increase handset location accuracy requirements of enhanced 991 service (e911). In our demonstration, we will present the most recent prototype of our urban location improvement technology, called ShadowMaps, which will be shown to accurately track a mobile device in an urban environment, with up to an order of magnitude reduction in GNSS positioning error.

The IEEE 802.11n standard defines channel bonding that allows wireless devices to operate on 40 MHz channels by doubling their bandwidth from standard 20 MHz channels. Increasing channel width increases capacity, but it comes at the cost of decreased transmission range and greater susceptibility to interference. However, with the incorporation of Multiple-Input Multiple-Output (MIMO) technology in 802.11n, devices can now exploit the increased transmission rates from wider channels with minimal sacrifice to signal quality and range. The goal of our work is to identify the network factors that influence the performance of channel bonding in 802.11n networks and make intelligent channel bonding decisions. We discover that channel width selection should consider not only a link's signal quality, but also the strength of neighboring links, their physical rates, and interferer load. We use our findings to design and implement a network detector that successfully identifies interference conditions that affect channel bonding decisions in 100% of our test cases. Our detector can form the foundation for more robust and accurate algorithms that can adapt bandwidth to variations in channel conditions. Our findings allows us to predict the impact of network conditions on performance and make channel bonding decisions that maximize throughput.

The increased demand for wireless connectivity emphasizes the necessity of efficient wireless communication as resources such as the available spectrum and energy reserves become limiting factors for network proliferation. Recent advancements in software-defined radio enable high flexibility of the physical layer allowing fine grained transmission adjustments. Although communication efficiency can greatly benefit from physical layer flexibility, modern wireless protocols can neither handle these new opportunities nor allocate resources according to the overlying application needs. In this work we develop WhiteRate, a method for physical layer parameter adaptation that efficiently utilizes available energy and spectrum resources, while maintaining the desired quality of communication. Our solution adjusts the modulation and coding scheme, and channel width to achieve a communication profile that matches application requirements. We implement WhiteRate in GNUradio and evaluate it in both indoor and outdoor environments. We demonstrate improvements on two important fronts: spectrum utilization and energy efficiency. Moreover, we show that by using WhiteRate, both benefits can be achieved simultaneously.

Cellular networks are often the first telecommunications infrastructure in developing regions. By studying cellular net- work traffic, researchers gain insight into how technologies can be used to access services critical to further development. In this work, we approach a cellular traffic dataset provided by Orange in Cote d'Ivoire with the goal of identifying distinctions between urban and rural use of cellular infrastructure. We report on a number of interesting differences between urban and rural usage of cellular infrastructure. For instance, 70% of calls that originate in rural areas occur within the vicinity of the same antenna, whereas the same is true for only 23% of calls with urban origin. We are compelled to conclude that development efforts for rural areas might be implemented differently from development efforts in urban areas based on divergent use of current cellular infrastructure.

Studies of user behavior in cellular networks have served as a knowledge base for development of critical applications and services catered to specific user needs. In this paper we examine community persistence in egocentric social graphs extracted from cellular network traces in the Cote d'Ivoire provided by Orange. The goal of our study is to inform mechanisms for improved dissemination of information by identifying subscribers or groups that can serve as information relays. We find that communities that persist in an egocentric network are independent of one another. Thus, multiple information relays can be selected from each independent community, to increase the probability that information will flow to the ego.

Cellular networks have revolutionized the way people communicate in rural areas. At the same time, deployment of commercial-grade cellular networks in areas with low population density, such as in rural sub-Saharan Africa, is prohibitively expensive relative to the return of investment. As a result, 48% of the rural population in Africa remains disconnected. To address this problem, we design a local cellular network architecture, Kwiizya, that provides basic voice and text messaging services in rural areas. We deployed an instance of Kwiizya in the rural village of Macha in Zambia. In this video we present interviews with people from the Macha community talking about their use of cellphones. We also present footage from the installation of Kwiizya in Macha.

Cellular networks have revolutionized the way people communicate in rural areas. At the same time, deployment of commercial-grade cellular networks in areas with low population density, such as in rural sub-Saharan Africa, is prohibitively expensive relative to the return of investment. As a result, 48\% of the rural population in Africa remains disconnected. To address this problem, we design a local cellular network architecture, Kwiizya, that provides basic voice and text messaging services in rural areas. Our system features an interface for development of text message based applications that can be leveraged for improved health care, education and support of local businesses. We deployed an instance of Kwiizya in the rural village of Macha in Zambia. Our deployment utilizes the existing long distance Wi-Fi network in the village for inter-base station communication to provide high quality services with minimal infrastructure requirements. In this paper we evaluate Kwiizya in-situ in Macha and show that the network maintains low delay and jitter (20ms and 3ms, respectively) for voice call traffic, while providing high call Mean Opinion Score of 3.46, which is the theoretical maximum supported by our system.

The emergence of MIMO antennas and channel bonding in 802.11n wireless networks has resulted in a huge leap in capacity compared with legacy 802.11 systems. This leap, however, adds complexity to selecting the right transmission rate. Not only does the appropriate data rate need to be selected, but also the MIMO transmission technique (e.g., Spatial Diversity or Spatial Multiplexing), the number of streams, and the channel width. Incorporating these features into a rate adaptation (RA) solution requires a new set of rules to accurately evaluate channel conditions and select the appropriate transmission setting with minimal overhead. To address these challenges, we propose ARAMIS (Agile Rate Adaptation for MIMO Systems), a standard-compliant, closed-loop RA solution that jointly adapts rate and bandwidth. ARAMIS adapts transmission rates on a per-packet basis; we believe it is the first 802.11n RA algorithm that simultaneously adapts rate and channel width. We have implemented ARAMIS on Atheros-based devices and deployed it on our 15-node testbed. Our experiments show that ARAMIS accurately adapts to a wide variety of channel conditions with negligible overhead. Furthermore, ARAMIS outperforms existing RA algorithms in 802.11n environments with up to a 10 fold increase in throughput.

Mobile telephony brings clear economic and social benefits to its users. As handsets have become more affordable, ownership has reached staggering numbers, even in the most remote areas of the world. However, network coverage is often lacking in low population densities and low income rural areas of the developing world, where big telecoms often defer from deploying expensive infrastructure. To solve this coverage gap, we propose VillageCell, a low-cost alternative to high-end cell phone networks. VillageCell relies on software defined radios and open-source solutions to provide free local and cheap long-distance communication for remote regions. Our architecture is simple and easy to deploy, yet robust and requires no modification to GSM handsets. Through measuring the call quality metrics and the system capacity under a realistic rural-area network load, we show that VillageCell is indeed an attractive solution for rural area voice connectivity.

The Internet is evolving from a system of connections between humans and machines to a new paradigm of social connection. However, it is still dominated by a hub and spoke architecture with inter-connectivity between users typically requiring connections to a common server on the Internet. This creates a large amount of traffic that must traverse an Internet gateway, even when users communicate with each other in a local network. Nowhere is this inefficiency more pronounced than in rural areas with low-bandwidth connectivity to the Internet. Our previous work in a rural village in Macha, Zambia showed that web traffic, and social networking in particular, are dominant services. In this paper we use a recent network trace, from this same village, to explore the degree of local user-to-user interaction in the village. Extraction of a social graph, using instant message interactions on Facebook, reveals that 54% of the messages are between local users. Traffic analysis highlights that the potential spare capacity of the local network is not utilized for direct local communication between users even though indirect communication between local users is routed through services on the Internet. These findings build a strong motivation for a new rural network architecture that places services that enable user-to-user interaction and file sharing in the village.

A fundamental question in multihop wireless network protocol design is how to partition the network's transport capacity among contending flows. A classically "fair” allocation leads to poor throughput performance for all flows because connections that traverse a large number of hops (i.e., long connections) consume a disproportionate share of resources. However, naïvely biasing against longer connections can lead to poor network utilization, because a significantly high fraction of total connections are long in large networks with spatially uniform traffic. While proportional fair allocation provides a significant improvement, we show here that there is a much richer space of resource allocation strategies for introducing a controlled bias against resource-intensive long connections in order to significantly improve the performance of shorter connections. Specifically, mixing strongly biased allocations with fairer allocations leads to efficient network utilization as well as a superior trade-off between flow throughput and fairness. We present an analytical model that offers insight into the impact of a particular resource allocation strategy on network performance, taking into account finite network size and spatial traffic patterns. We point to protocol design options to implement our resource allocation strategies by invoking the connection with the well-studied network utility maximization framework. Our simulation evaluation serves to verify the analytical design prescriptions.

The IEEE 802.11n standard allows wireless devices to operate on 40MHz-width channels by doubling their channel width from standard 20MHz channels, a concept called channel bonding. Increasing channel width should increase bandwidth, but it comes at the cost of decreased transmission range and greater susceptibility to interference. However, with the incorporation of MIMO (Multiple-Input Multiple-Output) technology in 802.11n, devices can now exploit the increased transmission rates from wider channels at a reduced sacrifice to signal quality and range. The goal of our work is to understand the characteristics of channel bonding in 802.11n networks and the factors that influence that behavior to ultimately be able to predict behavior so that network performance is maximized. We discuss the impact of channel bonding choices as well as the effects of both co-channel and adjacent channel interference on network performance. We discover that intelligent channel bonding decisions rely not only on a link's signal quality, but also on the strength of neighboring links and their physical rates.

Recent advancements in wireless transmission have enabled networks with a high level of physical layer flexibility. Unfortunately, these new opportunities are not harnessed by modern wireless systems. Due to inefficient resource allocation, systems typically encounter problems such as spectrum scarcity, energy depletion or low quality of service. In this paper we consider the problem of physical layer parameter adaptation in a flexible wireless system. We observe that for many practical purposes the acceptable quality of communication depends on the interplay among the packet loss ratio, energy savings and spectrum utilization. We harness this fact and propose a context-aware physical layer parameter adaptation solution, WhiteRate. Our solution adjusts the modulation level, coding scheme and channel width to achieve the communication profile that matches application requirements. We implement WhiteRate in GNUradio and evaluate it in both indoor and outdoor environments. We demonstrate improvements on two important fronts: spectrum utilization and energy efficiency. Moreover, we show that by using WhiteRate, both benefits can be achieved simultaneously.

Abstract Monitoring and troubleshooting a large wireless mesh network (WMN) presents several challenges. Diagnosis of problems related to wireless access in these networks requires a comprehensive set of metrics and network monitoring data. Collection and offloading of a large amount of data are infeasible in a bandwidth constrained mesh network. Additionally, the processing required to analyze data from the entire network restricts the scalability of the system and impacts the ability to perform real‐time fault diagnosis. To this end, we propose MeshMon, a network monitoring framework that includes a multi‐tiered method of data collection. MeshMon, dynamically controls the granularity of data collection based on observed events in the network, thereby achieving significant bandwidth savings and enabling real‐time automated management. Our evaluation of MeshMon on a real testbed shows that we can diagnose a majority (87%) of network faults with a 66% savings in bandwidth required for network monitoring. Copyright © 2010 John Wiley & Sons, Ltd.

Wireless mesh networks (WMNs) provide an attractive method to provide Internet connectivity in developing regions. Traditional mesh routing protocols are designed to find high quality/throughput multihop routes in the network. However, these solutions do not consider constraints imposed by the capacity at the gateway, often the bottleneck in such rural area networks. In this paper, we demonstrate the importance of intelligent choice of gateways in WMNs. We present the design of a new gateway-aware routing metric that picks high throughput routes in the presence of heterogeneous gateways. Our evaluation in simulations as well as on a testbed show significant increase in network throughput.

Rate adaptation is a critical component that impacts the performance of IEEE 802.11 wireless networks. In congested networks, traditional rate adaptation algorithms have been shown to choose lower data-rates for packet transmissions, leading to reduced total network throughput and capacity. A primary reason for this behavior is the lack of real-time congestion measurement techniques that can assist in the identification of congestion-related packet losses in a wireless network. In this work, we first propose two real-time congestion measurement techniques, namely an active probe-based method called Channel Access Delay, and a passive method called Channel Busy Time. We evaluate the two techniques in a testbed network and a large WLAN connected to the Internet. We then present the design and evaluation of Wireless cOngestion Optimized Fallback (WOOF), a rate adaptation scheme that uses congestion measurement to identify congestion-related packet losses. Through simulation and testbed implementation we show that, compared to other well-known rate adaptation algorithms, WOOF achieves up to 300 percent throughput improvement in congested networks.

Wireless networks have evolved into an important technology for connecting users to the Internet. As the utility of wireless technology grows, wireless networks are being deployed in more widely varying conditions. The monitoring of wireless networks continues to reveal key implementation deficiencies that need to be corrected in order to improve protocol operation and end-to-end network performance. In wireless networks, where the medium is shared, unwanted traffic can pose significant overhead and lead to suboptimal network performance. Much of the previous analyses of unwanted traffic in wireless networks focus on malicious traffic. However, another major contributor of unwanted traffic is incorrect link layer behavior. Using data we collected from the 67th Internet Engineering Task Force (IETF) meeting held in November 2006, we show that a significant portion of link layer traffic stems from mechanisms that initiate, maintain, and change client-AP associations. We further show that under conditions of high medium utilization and packet loss rate, handoffs are initiated incorrectly. We analyze the traffic to understand when handoffs occur and whether the handoffs were beneficial or should have been avoided.

We consider the problem of providing ubiquitous yet affordable Internet connectivity to devices at home, at work, and on the move. In this context, we take advantage of two significant technology trends: the commoditization of WiFi WLAN technology and the rapid growth of cellular data services. We propose an architecture called Cool-Tether that harnesses the cellular radio links of one or more mobile smartphones in the vicinity, builds a WiFi hotspot on-the-fly, and provides energy-efficient, affordable connectivity.

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.

The Internet has revolutionized communication, education, commerce and information access for its users worldwide. Unfortunately, the lack of copper/fiber infrastructure in the rural areas of the developing world has prevented a large majority of the human population from reaping the benefits of the Internet. While the number of mobile subscribers in the developing world has more than quadrupled in the last five years, the adoption of the Internet has shown a slow growth pattern. Recently, there has been a growing interest in providing Internet access to rural areas by means of inexpensive long distance WiFi mesh networks. However, the expensive Internet uplink and the difficulty in troubleshooting of WiFi mesh networks has hindered their large scale deployment. In this paper, we propose Cell-Share an architecture that leverages the explosive growth in cellular network penetration in the developing world to provide rural WiFi mesh networks with an on-demand scalable Internet uplink and troubleshooting back-channel using a collaborative mobile phone framework. We implement Cell-Share on Windows Mobile and Android platforms to demonstrate the feasibility of using the infrastructure of cellular data networks to provide a back-channel for network troubleshooting as well as capacity enhancement for rural mesh networks.

We present a cross-layer modeling and design approach for multiGigabit indoor wireless personal area networks (WPANs) utilizing the unlicensed millimeter (mm) wave spectrum in the 60 GHz band. Our approach accounts for the following two characteristics that sharply distinguish mm wave networking from that at lower carrier frequencies. First, mm wave links are inherently directional: directivity is required to overcome the higher path loss at smaller wavelengths, and it is feasible with compact, low-cost circuit board antenna arrays. Second, indoor mm wave links are highly susceptible to blockage because of the limited ability to diffract around obstacles such as the human body and furniture. We develop a diffraction-based model to determine network link connectivity as a function of the locations of stationary and moving obstacles. For a centralized WPAN controlled by an access point, it is shown that multihop communication, with the introduction of a small number of relay nodes, is effective in maintaining network connectivity in scenarios where single-hop communication would suffer unacceptable outages. The proposed multihop MAC protocol accounts for the fact that every link in the WPAN is highly directional, and is shown, using packet level simulations, to maintain high network utilization with low overhead.

Throughput performance of multihop wireless networks is governed by how the network's transport capacity (in bit-meters per second) is partitioned among different network flows. Max-min fair allocation leads to poor throughput performance for all flows because connections traversing a large number of hops consume a disproportionate share of resources. While proportional fair allocation provides a significant improvement, we point out here that there is a much richer space of resource allocation strategies for introducing a controlled bias against resource-intensive long connections in order to significantly improve the performance of shorter connections. We present an analytical model that gives insight into the impact of a particular resource allocation strategy on network performance, in a manner that captures the effect of finite network size and spatial traffic patterns. Our simulation results demonstrate that it is possible to provide significantly better performance to shorter connections than max-min fair or proportional fair resource allocations, with minimal impact on the performance of long connections, using mixed bias strategies blending "fair" allocations with a strong bias against long connections.

Traditional rate adaptation solutions for IEEE 802.11 wireless networks perform poorly in congested networks. Measurement studies show that congestion in a wireless network leads to the use of lower transmission data rates and thus reduces overall network throughput and capacity. The lack of techniques to reliably identify and characterize congestion in wireless networks has prevented development of rate adaptation solutions that incorporate congestion information in their decision framework. To this end, our main contributions in this paper are two-fold. First, we present a technique that identifies and measures congestion in an 802.11 network in real time. Second, we design Wireless congestion Optimized Fallback (WOOF), a measurement-driven rate adaptation scheme for 802.11 devices that uses the congestion measurement to identify congestion related packet losses. Through experimental evaluation, we show that WOOF achieves up to 300% higher throughput in congested networks, compared to other well-known adaptation algorithms.

When new wireless technologies are deployed and subjected to real usage patterns, unforeseen performance problems inevitably seem to arise, to be fixed only in later generations. Why do these performance issues fail to appear in experimental settings before the technology is deployed? We believe that one of the major reasons behind the discrepancies found between experimental performance evaluations and real-world experience lies in the unrealistic workload patterns typically used in experiments. One of the significant contributions of this work is to rigorously demonstrate that common synthetic traffic models for wireless local-area networks induce drastically distorted performance metrics at every layer of the protocol stack. In order to show this, we present a testable definition of “sufficient realism” for traffic models, and develop the theoretical methodology necessary to interpret experimental results using this definition. Finally, we show by example that this distortion can completely invert the relative performance of protocols. The greater overall contribution of this paper, however, is the complete collection of ideas, techniques and analytical tools that will allow the development of more realistic synthetic traffic models in the future.

The rapid growth in the popularity of cellular networks has led to aggressive deployment and a rapid expansion of mobile services. Services based on the integration of cellular networks into the Internet have only recently become available, but are expected to become very popular. One current limitation to the deployment of many of these services is poor or unknown network performance, particularly in the cellular portion of the network. Our goal in this paper is to motivate and present the Mobile Internet Services Test (MIST) platform, a new distributed architecture to measure and characterize cellular network performance as experienced by mobile devices. We have used MIST to conduct preliminary measurements; evaluate MIST’s effectiveness; and motivate further measurement research.

As the utility of wireless technology grows, wireless networks are being deployed in more widely varying conditions. The monitoring of these networks continues to reveal key implementation deficiencies that need to be corrected in order to improve protocol operation and end-to-end performance. Using data we collected from the 67th Internet Engineering Task Force (IETF) meeting held in November 2006, we show that under conditions of high medium utilization and packet loss, handoffs can be incorrectly initiated. Using the notion of persistence and prevalence for the association of a client to an Access Point (AP), we show that although the clients were predominantly static, the handoff rate is surprisingly high. Through the analysis of the data set, we show that unnecessary handoff events not only increase the amount of management traffic in the network, but also severely impact client performance.

The 7 GHz of unlicensed spectrum in the 60 GHz band offers the potential for multiGigabit indoor wireless personal area networking (WPAN). With recent advances in the speed of silicon (CMOS and SiGe) processes, low-cost transceiver realizations in this "millimeter (mm) wave" band are within reach. However, mm wave communication links are more fragile than those at lower frequencies (e.g., 2.4 or 5 GHz) because of larger propagation losses and reduced diffraction around obstacles. On the other hand, directional antennas that provide directivity gains and reduction in delay spread are far easier to implement at mm-scale wavelengths. In this paper, we present a cross-layer modeling methodology and a novel multihop medium access control (MAC) architecture for efficient utilization of 60 GHz spectrum, taking into account the preceding physical characteristics. We propose an in-room WPAN architecture in which every link is constrained to be directional, for improved power efficiency (due to directivity gains) and simplicity of implementation (due to reduced delay spread). We develop an elementary diffraction-based model to determine network link connectivity, and define a multihop MAC protocol that accounts for directional transmission/reception, procedures for topology discovery and recovery from link blockages.

Research has shown that multi-radio multi-channel mesh networks provide significant capacity gains over single-radio mesh networks. Traditional single path routing can lead to poor utilization of the available channels in these networks. Opportunistic multipath routing can better exploit the available channel diversity in a multi-radio network. The goal of this paper is to select multiple paths that, when used concurrently, provide high end-to-end throughput. To this end, we present a metric for multipath selection in multi-radio networks. We evaluate the metric through simulations in Qualnet and show that intelligent multipath routing significantly outperforms single path routing in multi-radio mesh networks.

The capacity problem in wireless mesh networks can be alleviated by equipping the mesh routers with multiple radios tuned to non-overlapping channels. However, channel assignment presents a challenge because co-located wireless networks are likely to be tuned to the same channels. The resulting increase in interference can adversely affect performance. This paper presents an interference-aware channel assignment algorithm and protocol for multi-radio wireless mesh networks that address this interference problem. The proposed solution intelligently assigns channels to radios to minimize interference within the mesh network and between the mesh network and co-located wireless networks. It utilizes a novel interference estimation technique implemented at each mesh router. An extension to the conflict graph model, the multi-radio conflict graph, is used to model the interference between the routers. We demonstrate our solution’s practicality through the evaluation of a prototype implementation in a IEEE 802.11 testbed. We also report on an extensive evaluation via simulations. In a sample multi-radio scenario, our solution yields performance gains in excess of 40% compared to a static assignment of channels.

Multimedia transmission over wireless local area networks is challenging due to the varying nature of the wireless channel as well as the inherent difference between multimedia and data traffic. In the MAC layer, a single bit error in the packet can lead to the entire packet being discarded. This results in a higher packet error rate for larger payload sizes. Retransmission due to packet errors causes the contention window to double, and this leads to a decrease in throughput if the wireless channel does not improve for the retransmitted packets. Hence, throughput is a function of packet payload length as well as the maximum number of allowable retransmissions. In this paper, we investigate the effect of payload length adaptation and retransmissions on the throughput and capacity of multimedia users. Numerical results and simulations reveal that careful payload adaptation significantly improves the throughput performance at low signal to noise ratios (SNRs). It is also observed that excessive retransmissions reduce the effective throughput, thereby decreasing the capacity of multimedia users in the presence of data users. Since multimedia traffic is more latency constrained and less error constrained, by carefully selecting the payload length and maximum number of allowable retransmissions based on the channel conditions, a greater number of multimedia users can be supported.

Flash crowds and high concentrations of users in wireless LANs (WLANs) cause significant interference problems and unsustainable load at access points. This leads to poor connectivity for users, severe performance degradation, and possible WLAN collapse. To validate this claim, we present two case studies of large, heavily loaded operational WLANs. These studies provide significant insight into the degraded performance and collapse of a WLAN during heavy use. To address these problems, we propose IQU, a practical queue-based user association management system for heavily loaded WLANs. IQU grants users fair opportunities to access the WLAN while maintaining high overall throughput, even when the WLAN is heavily loaded. The basic premise of IQU is to control user associations with the WLAN through request queues and work period allocations. We implement a prototype of IQU and evaluate it on a wireless testbed. Our evaluation demonstrates that IQU significantly improves network throughput under heavy load; the tradeoff is that users have to wait for network access. We explore the impact of IQU parameters on system performance, and validate the robustness of IQU under heavy load conditions. Through IQU, WLANs can be utilized efficiently and network collapse prevented.

As wireless networks become more prevalent, users will demand the same applications that are currently available in wired networks. Further, they will expect to receive a quality of service similar to that obtained in a wired network. Included in these applications are real-time applications such as voice over IP and multimedia streams. To enable the support of applications that require real-time communication in ad hoc networks, congestion must be prevented so that the needed quality of service can be provided. An admission control mechanism is an essential component of the quality of service solution. Unfortunately, current admission control solutions encounter problems during mobility, often resulting in unacceptable disruptions in communication. To solve this problem, we apply multi-path routing mechanisms that maintain alternate paths to the destination and propose a new admission control protocol. We show through simulation that our solution is able to prevent communication disruptions and meet the QoS needs of applications better than previous solutions.

Simulation environments are an important tool for the evaluation of new concepts in networking. The study of mobile ad hoc networks depends on understanding protocols from simulations, before these protocols are implemented in a real-world setting. To produce a real-world environment within which an ad hoc network can be formed among a set of nodes, there is a need for the development of realistic, generic and comprehensive mobility, and signal propagation models. In this paper, we propose the design of a mobility and signal propagation model that can be used in simulations to produce realistic network scenarios. Our model allows the placement of obstacles that restrict movement and signal propagation. Movement paths are constructed as Voronoi tessellations with the corner points of these obstacles as Voronoi sites. Our mobility model also introduces a signal propagation model that emulates properties of fading in the presence of obstacles. As a result, we have developed a complete environment in which network protocols can be studied on the basis of numerous performance metrics. Through simulation, we show that the proposed mobility model has a significant impact on network performance, especially when compared with other mobility models. In addition, we also observe that the performance of ad hoc network protocols is effected when different mobility scenarios are utilized.

Initial work in ad hoc routing has considered only the problem of providing efficient mechanisms for finding paths in very dynamic networks, without considering security. Because of this, there are a number of attacks that can be used to manipulate the routing in an ad hoc network. In this paper, we describe these threats, specifically showing their effects on ad hoc on-demand distance vector and dynamic source routing. Our protocol, named authenticated routing for ad hoc networks (ARAN), uses public-key cryptographic mechanisms to defeat all identified attacks. We detail how ARAN can secure routing in environments where nodes are authorized to participate but untrusted to cooperate, as well as environments where participants do not need to be authorized to participate. Through both simulation and experimentation with our publicly available implementation, we characterize and evaluate ARAN and show that it is able to effectively and efficiently discover secure routes within an ad hoc network.

Mobile ad hoc network routing protocols are highly susceptible to subversion. Previous research in securing these protocols has typically used techniques based on encryption and redundant transmission. These techniques prevent a range of attacks against routing protocols but are expensive to deploy on energy-constrained wireless devices. Experience in securing wired networks has demonstrated that, in addition to intrusion prevention techniques, it is useful to deploy intrusion detection techniques as a second line of defense. In this paper, we discuss some of the threats to wireless ad hoc networks, and, specifically, some attacks against the AODV routing protocol. We also present a tool aimed at real-time detection of these attacks. The tool monitors network packets to detect local and distributed attacks within its radio range. Experiments show that the tool provides effective intrusion detection functionality while using only a limited amount of resources.

Admission control of flows is essential for providing quality of service in multihop wireless networks. In order to make an admission decision for a new flow, the expected bandwidth consumption of the flow must be correctly determined. Due to the shared nature of the wireless medium, nodes along a multihop path contend among themselves for access to the medium. This leads to intra-flow contention; contention between packets of the same flow being forwarded at different hops along a multihop path causing the actual bandwidth consumption of the flow to become a multiple of its single hop bandwidth requirement. Determining the amount of intra-flow contention is non-trivial since interfering nodes may not be able to communicate directly if they are outside each other's transmission range. In this paper, we propose two methods to determine the extent of intra-flow contention along multihop paths. The highlight of the proposed solutions is that carrier-sensing data is used to deduce information about carrier-sensing neighbors, and no high power transmissions are necessary. Analytical and simulation results show that our methods estimate intra-flow contention with low error, while significantly reducing overhead, energy consumption and latency as compared to previous approaches.

Current mobile ad hoc network (MANET) routing protocols operate with networks as flat address spaces, treating all nodes in the network as independent peers. However, these nodes are not always independent; they can form groups due to physical or environmental restraints. By taking advantage of these natural groupings, there is an opportunity to optimize the performance of MANET routing in these settings. This paper examines address aggregation in MANETs, focusing primarily on its ability to reduce routing overhead. We specifically describe the work necessary to implement address aggregation in the ad hoc on-demand distance vector routing protocol (AODV). We found the benefits of aggregation to be quite significant, reducing overhead and delay by 42% to 82% and 30% to 62%, respectively.

Summary form only given. Simulation is an important tool in the development of mobile ad hoc networks. It has a number of important benefits in providing an environment to experiment and verify routing protocol correctness. However, there is no guarantee that the protocol works in practice because simulators contain assumptions and simplified models that may not reflect real network operation. For instance, while most widely used mobility models create a dynamic environment that can be used to stress a protocol in a mobile network, they do not generate realistic movement patterns. It has been shown that mobility model selection directly influences the performance of the routing protocol. Hence, the use of an unrealistic model results in predictions that do not reflect achievable performance in the real world. Other sources of predication inaccuracy stem from the omission of relevant, up-to-date protocol models. As a result of these simplifications, inaccuracies and omissions, mobile network performance can be incorrectly predicted. In particular, the performance of field networks can be orders of magnitude worse than the simulated performance of the same network. This poses a serious problem for mobile networking researchers, who have invested heavily in simulation as a tool for network development and evaluation. The talk describes some of the disparities between predicted and measured performance, and discuss mechanisms for bridging this gap.

Ad hoc networks have been proposed for a variety of applications where support for real time, multimedia services may be necessary. This requires that the network is able to offer quality of service (QoS) appropriate for the latency and throughput bounds needed to meet the real time constraint. An important component for QoS provisioning is resource estimation and quality prediction. The paper describes a model-based resource prediction (MBRP) mechanism to support real time communication in multi-hop wireless networks. Specifically, we develop an analytical model for differentiated MAC scheduling protocols. The model can predict per-flow and system-wide throughput and delivery latency, thereby enabling admission control of the flows and providing an efficient network management utility. After describing the basic model, we propose enhanced MBRP (EMBRP) for realistic network environments. Our proposed quality prediction method is beneficial in the deployment of a real ad hoc network where knowledge of resource allocation and consumption is needed to meet the service requirements. Analytical and simulation results show that EMBRP provides accurate flow quality prediction. The results also demonstrate the effectiveness of EMBRP as an admission control solution in multi-hop ad hoc networks.

Existing solutions for QoS-aware routing in mobile multihop networks attempt to discover a QoS-satisfactory route for the user at the user's current location. If a suitable route is not available at the current location, the user is denied access. This approach does not take advantage of the special characteristics of mobile multihop networks. That is, users in these networks are mobile and their connectivity is dependent on their location and the locations of other users. By changing their location, users can alter their connectivity characteristics and potentially obtain better service from the network. In this paper, we propose enhancing QoS-aware routing protocols to take advantage of this characteristic. With our solution, if a satisfactory route is not available at the user's current location, the protocol discovers a nearby location where a better route is available. The user can then choose to move to the suggested location to improve the received quality of service. We demonstrate our idea by appropriately extending a QoS-sensitive version of the AODV routing protocol, and presenting a simulation-based evaluation. Simulation results show the effectiveness and efficiency of our idea.

In wireless ad hoc networks, heterogeneity is inherent and each node has different characteristics, resources, and policies. Most current ad hoc routing protocols do not consider node heterogeneity when making routing decisions. Although existing ad hoc routing protocols can be extended to consider heterogeneity, these methods require changes to the routing protocol packets and packet processing. We propose a simple, transparent modification during the route discovery phase of an on-demand routing protocol to select the best route considering heterogeneity. In our solution, nodes can influence their likelihood of participating in routing packets for the other nodes, and there is no noticeable change to the routing protocol. To evaluate our solution, we modify an ad hoc on-demand distance vector (AODV) routing protocol implementation. Our solution's ability to influence path selection is studied in both a testbed and a network simulator. We show that using the method described in this paper, nodes that want to avoid routing packets for others are avoided when other routes exist.

Traditional approaches to guarantee quality of service (QoS) work well only with predictable channel and network access. In wireless mobile networks, where conditions dynamically change as nodes move about the network, a stateless approach is required. As wireless networks become more widely used, there is a growing need to support advanced services, such as multimedia streaming and voice over IP. Since shared wireless resources are easily over-utilized, the load in the network must be controlled so that an acceptable QoS for real-time applications can be maintained. If minimum real-time requirements are not met, these data packets waste bandwidth and hinder other traffic, compounding the problem. To address this issue, we propose the perceptive admission control (PAC) protocol. PAC monitors the wireless channel and dynamically adapts admission control decisions to enable high network utilization while preventing congestion. Through discussion and simulations, we show that PAC achieves this goal and ensures low loss and delay for all admitted flows.

With the advent of small form-factor devices, protocol standardization, and robust protocol implementations, multi-hop mobile networks are witnessing widespread deployment. The monitoring of such networks is crucial for their robust operation. To this end, this paper presents DAMON, a distributed system for monitoring multi-hop mobile networks. DAMON uses agents within the network to monitor network behavior and send collected measurements to data repositories. DAMON's generic architecture supports the monitoring of a wide range of protocol, device, and network parameters. Other key features of DAMON include seamless support for multiple repositories, auto-discovery of sinks by the agents, and resiliency of agents to repository failures. We have implemented DAMON agents that collect statistics on data traffic and the ad hoc on-demand distance vector (AODV) routing protocol. We have used our implementation to monitor an ad hoc network at the 58th Internet Engineering Task Force (IETF) meeting held November 2003 in Minneapolis, MN. In this paper, we describe the architecture of DAMON and report on the performance of the IETF network using monitoring information collected by DAMON. Our network monitoring system is available online for use by other researchers.

Mobile ad hoc networks (MANET) have more severe operating conditions than traditional wireless networks. The MAC protocol of IEEE 802.11 mitigates collisions and ensures error-free packet transmissions at the cost of limiting capacity and increasing latency. For voice transmission over MANETs this cost should be minimized. We propose and examine selective error checking (SEC) at the MAC layer of 802.11 that takes advantage of the fact that many of the speech bits can tolerate errors while other bits must be protected for effective reconstruction of the speech. Simulation results demonstrate that the network performance and the speech quality are substantially improved by modifying the MAC layer with SEC to suit a particular GSM speech compression standard, the narrow-band adaptive multirate (NB-AMR) coder operating at a rate of 7.95 kbps.

Abstract Dynamic address assignment enables nodes in mobile ad hoc networks to obtain a routable address without the need for any explicit configuration. It provides a means for nodes to communicate without any centralized infrastructure and provides a mechanism for dynamic network membership. Recently, a considerable number of dynamic addressing protocols have been proposed. While these approaches bear some similarities to each other, they also differ in some important characteristics. To understand the benefits of these different approaches, it is necessary to test the protocols in a wide range of network conditions so that their performance and suitability can be predicted. This paper studies existing solutions by categorizing and qualitatively analyzing the scalability and other performance properties of the approaches. We also introduce a new addressing approach that provides both quick and efficient unique address assignment. We then compare selected protocols through quantitative analysis based on extensive simulations. Based on the simulation results, we point out the applicability of the protocols and offer suggestions to improve protocol performance. Copyright © 2004 John Wiley & Sons, Ltd.

Ad hoc networks meet the demands of spontaneous network set-up. They are characterized by the use of wireless links, dynamically changing topology, multi-hop connectivity and decentralized routing mechanisms and decision-making. AODV and DSR are the two most widely studied on-demand ad hoc routing protocols. Previous studies have shown limitations of these protocols in certain network scenarios. To improve the performance of AODV, we modify AODV to include the source route accumulation feature of DSR. We call this AODV with path accumulation. This protocol optimizes AODV to perform effectively in terms of routing overhead and delay during high load. The performance of the protocol is evaluated by a simulation model under a variety of network conditions. We also compare its performance with that of unmodified AODV and DSR. We demonstrate how a small change to the AODV protocol can lead to significantly improved performance results.

Hybrid wireless networks are a viable networking solution to combat the limitations of infrastructured wireless networks and provide Internet connectivity to ad hoc networks. This paper first analyzes the requirements for deployment of hybrid networks in different application scenarios. Then two routing schemes designed for different traffic patterns in hybrid networks are proposed to achieve optimal performance. Simulation results show that with a large percentage of short web-based traffic sessions, using a gateway as a default router results in better performance with lower latency, fewer routing table entries, and manageable control overhead. When traffic locality is high and Internet traffic is only an occasional occurrence, the reactive routing scheme results in better performance, yielding low control overhead and higher throughput.

Mobile ad hoc networks are autonomous self-organized networks in which each node relies on the other nodes in the network to perform routing on its behalf. Proper functioning of the network is dependent on participation and cooperation of the nodes in routing and packet forwarding. Unfortunately, providing these services may not be in the best interest of a mobile node, since it results in the depletion of the node's resources. Selfish behavior by a node may result in degraded network performance due to denial of service, decrease in network throughput and partitioning of the network. Because it is in a node's interest to not forward traffic, nodes should be given some form of incentive for the services they provide. In this paper, we address the problem of selfishness in mobile ad hoc networks by proposing a protocol called AD-MIX that encourages participation. AD-MIX discourages selfishness by concealing the true destination of packets from intermediate nodes along the path, forcing a node to participate or risk dropping packets destined for itself. Simulation results show that employing AD-MIX encourages participation without a significant increase in overhead. In addition to encouraging participation, AD-MIX also facilitates anonymization and secure communication between nodes.

One of the most important methods for evaluating the characteristics of ad hoc networking protocols is through the use of simulation. Simulation provides researchers with a number of significant benefits, including repeatable scenarios, isolation of parameters, and exploration of a variety of metrics. The topology and movement of the nodes in the simulation are key factors in the performance of the network protocol under study. Once the nodes have been initially distributed, the mobility model dictates the movement of the nodes within the network. Because the mobility of the nodes directly impacts the performance of the protocols, simulation results obtained with unrealistic movement models may not correctly reflect the true performance of the protocols. The majority of existing mobility models for ad hoc networks do not provide realistic movement scenarios; they are limited to random walk models without any obstacles. In this paper, we propose to create more realistic movement models through the incorporation of obstacles. These obstacles are utilized to both restrict node movement as well as wireless transmissions. In addition to the inclusion of obstacles, we construct movement paths using the Voronoi diagram of obstacle vertices. Nodes can then be randomly distributed across the paths, and can use shortest path route computations to destinations at randomly chosen obstacles. Simulation results show that the use of obstacles and pathways has a significant impact on the performance of ad hoc network protocols.

Most recent ad hoc network research has focused on providing routing services without considering security. We detail security threats against ad hoc routing protocols, specifically examining AODV and DSR. In light of these threats, we identify three different environments with distinct security requirements. We propose a solution to one, the managed-open scenario where no network infrastructure is pre-deployed, but a small amount of prior security coordination is expected. Our protocol, authenticated routing for ad hoc networks (ARAN), is based on certificates and successfully defeats all identified attacks.

Abstract Clustering is a method by which nodes are hierarchically organized on the basis of their relative proximity to one another. Routes can be recorded hierarchically, across clusters, to increase routing flexibility. Hierarchical routing greatly increases the scalability of routing in ad hoc networks by increasing the robustness of routes. This paper presents the Adaptive Routing using Clusters (ARC) protocol, a protocol that creates a cluster hierarchy composed of cluster leaders and gateway nodes to interconnect clusters. ARC introduces a new algorithm for cluster leader revocation that eliminates the ripple effect caused by leadership changes. Further, ARC utilizes a limited broadcast algorithm for reducing the impact of network floods. The performance of ARC is evaluated by comparing it both with other clustering schemes and with an on‐demand ad hoc routing protocol. It is shown that the cluster topology created by ARC is more stable than that created by other clustering algorithms and that the use of ARC can result in throughput increases of over 100%. Copyright © 2002 John Wiley & Sons, Ltd.

An ad hoc mobile network is a collection of nodes, each of which communicates over wireless channels and is capable of movement. Wireless nodes have the unique capability of transmission at different power levels. As the transmission power is varied, a tradeoff exists between the number of hops from source to destination and the overall bandwidth available to individual nodes. Because both battery life and channel bandwidth are limited resources in mobile networks, it is important to ascertain the effects different transmission powers have on the overall performance of the network. This paper explores the nature of this transmission power tradeoff in mobile networks to determine the optimum node density for delivering the maximum number of data packets. It is shown that there does not exist a global optimum density, but rather that, to achieve this maximum, the node density should increase as the rate of node movement increases.

Ad hoc networks are characterized by multi-hop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of two prominent on-demand routing protocols for mobile ad hoc networks - dynamic source routing (DSR) and ad hoc on-demand distance vector routing (AODV). A detailed simulation model with MAC and physical layer models is used to study inter-layer interactions and their performance implications. We demonstrate that even though DSR and AODV share a similar on-demand behavior the differences in the protocol mechanics can lead to significant performance differentials. The performance differentials are analyzed using varying network load, mobility and network size. Based on the observations, we make recommendations about how the performance of either protocol can be improved.

As mobile computing gains popularity, the need for ad hoc routing protocols will continue to grow. There have been numerous simulations comparing the performance of these protocols under varying conditions and constraints. One question that arises is whether the choice of MAC protocol affects the relative performance of the routing protocols being studied. This paper investigates the answer to that question by simulating the performance of three ad hoc routing protocols when run over different MAC protocols. It is determined that the choice of MAC layer protocol does, in fact, affect the relative performance of the routing protocols.

The Ad hoc On-Demand Distance Vector (AODV) routing protocol is designed for use in ad hoc mobile networks. Because of the difficulty of testing an ad hoc routing protocol in a real-world environment, a simulation was first created so that the protocol design could be tested in a variety of scenarios. Once simulation of the protocol was nearly complete, the simulation was used as the basis for an implementation in the Linux operating system. In the course of converting the simulation into an implementation, certain modifications were needed in AODV and the Linux kernel due to both simplifications made in the simulation of AODV and to incompatibilities of the Linux kernel and the IP-layer to routing in a mobile environment. This paper details many of the changes that were necessary during the development of the implementation.

An ad-hoc network is the cooperative engagement of a collection of (typically wireless) mobile nodes without the required intervention of any centralized access point or existing infrastructure.To provide optimal communication ability, a routing protocol for such a dynamic self-starting network must be capable of unicast, broadcast, and multicast.In this paper we extend Ad-hoc On-Demand Distance Vector Routing (AODV), an algorithm for the operation of such ad-hoc networks, to offer novel multicast capabilities which follow naturally from the way AODV establishes unicast routes.AODV builds multicast trees as needed (i.e., on-demand) to connect multicast group members.Control of the multicast tree is distributed so that there is no single point of failure.AODV provides loop-free routes for both unicast and multicast, even while repairing broken links.We include an evaluation methodology and simulation results to validate the correct and efficient operation of the AODV algorithm.