Network management facilitates a healthy and sustainable network. However, its practice is not well understood outside the network engineering community. In this paper, we present Robotron, a system for managing a massive production network in a top-down fashion. The system's goal is to reduce effort and errors on management tasks by minimizing direct human interaction with network devices. Engineers use Robotron to express high-level design intent, which is translated into low-level device configurations and deployed safely. Robotron also monitors devices' operational state to ensure it does not deviate from the desired state. Since 2008, Robotron has been used to manage tens of thousands of network devices connecting hundreds of thousands of servers globally at Facebook.

The poor performance of TCP in wireless networks is a well-known problem, and a large amount of research effort has been devoted to it. However, our own experiments show that existing solutions including split TCP and recently developed congestion control algorithms still suffer significant performance degradation in lossy environments, leaving considerable room for improvement. Rather than developing a more sophisticated congestion control algorithm, we explore a radically different approach: we instead propose to completely remove congestion control between the Wi-Fi access points and the wireless receivers. We introduce TCP Fixed, a TCP used in split TCP environments that eliminates congestion control for the last lossy hop, allowing TCP to send data as fast as the channel allows. Extensive evaluations in both lab and real-world settings demonstrate that our approach significantly improves TCP performance in the presence of packet losses. In addition, our results indicate that existing 802.11 rate adaptation schemes which strive to minimize frame loss unnecessarily decrease the data rate in the presence of TCP Fixed. These results offer new opportunities for future link-layer rate adaptation designs.

Rate adaptation is a MAC-layer mechanism in IEEE 802.11 networks that ensures efficient utilization of constantly varying wireless channel. For broadcast communication, however, the current practice is to send data at base rates (i.e., 1 or 2 Mbps in 802.11b/b+g and 6Mbps in 802.11a/g), leaving the channel capacity significantly underutilized. In this paper, we present a practical rate adaptation framework designed for broadcasting of streaming data to improve the channel utilization of 802.11 networks. The proposed framework jointly selects the data rate and the error protection level of FEC in a novel manner, and does not require changes to either existent applications or to the 802.11 standards - thus can be deployed in existing 802.11 networks. Using the performance measurement study in various live networking environments, we show that the proposed scheme provides substantial improvement in wireless channel utilization (more than 10x improvement compared to the current broadcast mode) and can adapt to different operational environments.

Rate adaptation is a mechanism unspecified by the IEEE 802.11 standards, yet critical to the system performance by exploiting the multirate capability at the physical layer. In this paper, we conduct a systematic experimental study on rate adaptation over 802.11 wireless networks. Our key contributions are as follows: First, we present a critique on popular design guidelines adopted by many practical algorithms and we uncover their limitations. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incurring significant performance penalty in certain scenarios. Second, we study the short-term channel dynamics and explore how they guide rate adaptation. To this end, we design and implement a new History-Aware Robust Rate Adaptation Algorithm (HA-RRAA). HA-RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, a cost-effective adaptive RTS filter to prevent collision losses from triggering rate decrease and an adaptive time window to limit transmissions at high loss rates. Our extensive experiments show that HA-RRAA outperforms popular algorithms in all tested scenarios, with goodput gains up to 51.9 percent in field trials.

Interoperation in MANETs is an important issue in many operational situations, because of the growing number of heterogeneous MANETs with different standards, technologies and adminstrative management. To enable interoperation, gateways are often deployed for protocol translation, inter-MANET routing, and management policy enforcement among these heterogeneous MANETs. To optimize gateway deployment, we consider the gateway functionalities to be enabled or disabled dynamically in response to the changing network topology. In this paper, we offer mechanisms to select the minimal subset of enabled gateways among the deployed gateways to ensure the interoperation among the MANETs. To this aim, we formulate a novel graph optimization problem, called Minimal Gateway Assignment Problem, and prove that it is NP-hard. Nonetheless, we provide efficient algorithms to solve this problem with varying degrees of complexity and coordination. First, we provide a centralized polynomial-time algorithm that is 2-approximable, and a distributed algorithm. Second, by simulation, we show that our centralized and distributed algorithms can perform close to the optimal. We also report an interesting result that cooperation is the key factor to produce optimal outcomes - a simple algorithm with tight cooperation among MANETs gives much better outcomes than a smart algorithm with loose cooperation.

We study the challenging problem of strategic content placement in a dynamic MANET. Existing content placement techniques cannot cope with such network dynamics since they are designed for fixed networks. Opportunistic caching approaches are insufficient as they do not actively manage contents for certain goals. In this paper, we present a novel content management approach called LACMA, which leverages the location information available to mobile devices via GPS. The main idea of LACMA is to bind data to geographic location (as opposed to network nodes). This location-based strategy decouples the content placement problem from the changing network topology, and allows us to design an optimization framework even in a dynamic MANET environment. We present key components of LACMA used for strategic content placement and content-location binding (through proactive content push). We evaluate LACMA and compare its performance with existing caching schemes and show that LACMA considerably outperforms existing schemes over a wide range of scenarios.

We consider a coalition network where multiple groups are interconnected via wireless links. Gateway nodes are designated by each domain to achieve a network-wide interoperability. Due to the inter-domain communication cost, the optimal gateway selection for one single domain depends on the gateway selections of other domains and vice versa. In this paper, we investigate the interactions of gateway selections by multiple domains from a potential game perspective. The equilibrium inefficiency in terms of price of stability is characterized under various conditions. In addition, we examine the well-established equilibrium selective learning algorithm B-logit and show that B-logit is a special case of a general family of algorithms, denoted by Γ collectively. A novel learning algorithm named MAX-logit is proposed, which retains the favorable equilibrium selection property with the provably fastest convergence speed than any other algorithms in Γ, and can be applied to many other applications of potential games. Simulation results show that MAX-logit can improve the convergence speed of B-logit by up to 33.85%.

The advancements of diverse radio technologies and emerging applications have spawned increasing heterogeneity in mobile ad hoc networks (MANETs). But the collaborative nature of communications and operations often requires that these heterogeneous MANETs to be interoperable. Nonetheless, the existing interconnection protocols designed for the Internet (namely inter-domain routing protocol such as BGP) are not adequate for handling the unique challenges in MANETs. In this paper, we present a novel Inter-MANET Routing protocol called InterMR that can handle the heterogeneity and dynamics of MANETs. Our first contribution is an Inter-MANET address scheme based on a variety of node attributes (e.g., symbolic name, property, etc.); this allows dynamic merging/split of network topologies without a separate Name Server. Our second contribution is to provide a seamless routing mechanism across heterogeneous MANETs without modifying the internal routing mechanisms in each MANET. The proposed scheme can transparently adapt to topological changes due to node mobility in MANETs by dynamically assigning the gateway functionalities. We show, by packet-level simulation, that the performance of InterMR can be improved by up to 112% by adaptive gateway assignment functionalities. We also show that InterMR is scalable with only modest overhead by analysis.

This paper studies MIMO based rate adaptation (RA) in 802.11n wireless networks. Our case study shows that existing RA algorithms offer much lower throughput than even a fixed-rate scheme. The fundamental problem is that, all such algorithms are MIMO oblivious; they do not consider the characteristics of diversity-oriented, single-stream mode and the spatial multiplexing driven, double-stream mode. We propose MiRA, a novel MIMO RA scheme that zigzags between intra- and inter-mode rate options. Our experiments show that MiRA consistently outperforms three representative RA algorithms, SampleRate, RRAA and Atheros MIMO RA, in static, mobility and collision settings.

In this paper, a novel procedural framework for increasing the efficiency of the model composition process for the end-to-end transactional behavior of various classes of business-level computer applications is presented. The objectives of the framework are reducing the composition time and the level of engagement of domain experts in deploying business management solutions. Starting with application footprints (i.e., raw log data of various types) and without the need for a priori understanding of their syntax and semantics, the framework permits the analysis of the footprints based on an agnostic tokenization of log data. The framework then produces candidate states and relationships that form the basis for composing the transactional models via the framework's state and relationship manipulation utilities. The main architectural components of the framework are presented and their underlying principles discussed. A case study highlighting the use of the framework, based on an implementation of it, is given and a discussion regarding additional features of the framework and its relation to other research activities is also provided.

Security and privacy are two major concerns in supporting roaming users across administrative domains. In current practices, a roaming user often uses encrypted tunnels, e.g., Virtual Private Networks (VPNs), to protect the secrecy and privacy of her communications. However, due to its encrypted nature, the traffic flowing through these tunnels cannot be examined and regulated by the foreign network's firewall, which may lead the foreign network widely open to various attacks from the Internet. This threat can be alleviated if the users reveal their traffic to the foreign network or the foreign network reveals its firewall rules to the tunnel endpoints. However, neither approach is desirable in practice due to privacy concerns. In this paper, we propose a Cross-Domain Cooperative Firewall (CDCF) that allows two collaborative networks to enforce each other's firewall rules in an oblivious manner. In CDCF, when a roaming user establishes an encrypted tunnel between his home network and the foreign network, the tunnel endpoint (e.g., a VPN server) can regulate the traffic and enforce the foreign network's firewall rules, without knowing these rules. The key ingredients in CDCF are the distribution of firewall primitives across network domains, and the enabling technique of efficient oblivious membership verification. We have implemented CDCF and integrated it with the OpenVPN software, and evaluated its performance using extensive experiments. Our results show that CDCF can protect the foreign network from encrypted tunnel traffic with minimal overhead.

SMS has been arguably the most popular wireless data service for cellular networks. Due to its ubiquitous availability and universal support by mobile handsets and cellular carriers, it is also being considered for emergency notification and other mission-critical applications. Despite its increased popularity, the reliability of SMS service in real-world operational networks has received little study so far. In this work, we investigate the reliability of SMS by analyzing traces collected from a nationwide cellular network over a period of three weeks. Although the SMS service incorporates a number of reliability mechanisms such as delivery acknowledgement and multiple retries, our study shows that its reliability is not as good as we expected. For example the message delivery failure ratio is as high as 5.1% during normal operation conditions. We also analyze the performance of the service under stressful conditions, and in particular during a "flash-crowd" event that occurred in New Year's Eve of 2005. Two important factors that adversely affect reliability of SMS are also examined: bulk message delivery that may induce network-wide congestion, and the topological structure of the social network formed by SMS users, which may facilitate quick propagation of viruses or other malware.

Smartphones have recently become increasingly popular because they provide "all-in-one" convenience by integrating traditional mobile phones with handheld computing devices. However, the flexibility of running third-party softwares also leaves the smartphones open to malicious viruses. In fact, hundreds of smartphone viruses have emerged in the past two years, which can quickly spread through various means such as SMS/MMS, Bluetooth and traditional IP-based applications. Our own implementations of two proof-of-concept viruses on Windows Mobile have confirmed the vulnerability of this popular smartphone platform.

In modern cellular networks, the channel quality is dynamic among users and also over time. The time-granularity for such dynamics is significantly diverse - either slow or fast compared to packet transmission time. Because of these issues most existing scheduling policies can not work consistently well. In this work, we propose a scheduling policy with performance relatively insensitive to the time-granularity of the dynamics of channel quality. Our policy is self-adaptive to the scale of channel variations by using an ensemble of proposed algorithms. The proposed scheduling policy is proved to have a worst-case performance bound in the existence of both slow and fast time-varying channels. Simulation results confirm that the policy better tolerates channel variations than other popular schemes such as EDF and the Greedy algorithm.

Data dissemination is an indispensible protocol component for the emerging large-scale sensor networks. In this paper, we propose a secure data dissemination protocol that enhances directed diffusion to operate in the presence of compromised sensors. Our proposed solution, secure diffusion, utilizes a novel security primitive called location-binding keys, and exploits the available end-to-end feedback loop in directed diffusion. In secure diffusion, sensor nodes use pairwise neighbor keys to establish secure gradients, and the sink uses location-binding keys to authenticate the received sensing data. By differentiating authentic data from fabricated ones, the sink can selectively reinforce data paths and assist intermediate nodes in local reinforcement decisions to combat compromised nodes. Our security analysis shows that, in the presence of compromised nodes, secure diffusion can ensure both high-quality delivery of authentic data and local containment of malicious traffic.

In recent years, cellular networks have experienced an astronomical increase in the use of Short Message Service (SMS), making it a popular communication means for inter-personal as well as content provider-to-person usage. Yet little is known about the traffic and message user behavior in real SMS systems. In this paper, we present a measurement study of SMS based on traces collected from a nationwide cellular carrier during a three-week period. We characterize message traffic at both the message level and the conversation thread level. We also examine the "store-and-forward" mechanism of SMS and present initial measurements on how messages are actually delivered.

Rate adaptation is a mechanism unspecified by the 802.11 standards, yet critical to the system performance by exploiting the multi-rate capability at the physical layer.I n this paper, we conduct a systematic and experimental study on rate adaptation over 802.11 wireless networks. Our main contributions are two-fold. First, we critique five design guidelines adopted by most existing algorithms. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incur significant performance penalty in certain scenarios. The fundamental challenge is that rate adaptation must accurately estimate the channel condition despite the presence of various dynamics caused by fading, mobility and hidden terminals. Second, we design and implement a new Robust Rate Adaptation Algorithm (RRAA)that addresses the above challenge. RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, and an adaptive RTS filter to prevent collision losses from triggering rate decrease. Our extensive experiments have shown that RRAA outperforms three well-known rate adaptation solutions (ARF, AARF, and SampleRate) in all tested scenarios, with throughput improvement up to 143%.

Several studies have recently been performed on wireless university campus networks, corporate and public networks. Yet little is known about the flow-level characterization in such networks. In this paper, we statistically characterize both static flows and roaming flows in a large campus wireless network using a recently-collected trace. For static flows, we take a two-tier approach to characterizing the flow arrivals, which results a Weibull regression model. We further discover that the static flow arrivals in spatial proximity show strong similarity. As for roaming flows, they can also be well characterized statistically.We explain the results by user behaviors and application demands, and further cross-validate the modeling results by three other traces. Finally, we use two examples to illustrate how to apply our models for performance evaluation in the wireless context.