We present the DeepWiFi protocol, which hardens the baseline WiFi (IEEE 802.11ac) with deep learning and sustains high throughput by mitigating out-of-network interference. DeepWiFi is interoperable with baseline WiFi and builds upon the existing WiFi's PHY transceiver chain without changing the MAC frame format. Users run DeepWiFi for: i) RF front end processing; ii) spectrum sensing and signal classification; iii) signal authentication; iv) channel selection and access; v) power control; vi) modulation and coding scheme (MCS) adaptation; and vii) routing. DeepWiFi mitigates the effects of probabilistic, sensing-based, and adaptive jammers. RF front end processing applies a deep learning-based autoencoder to extract spectrum-representative features. Then a deep neural network is trained to classify waveforms reliably as idle, WiFi, or jammer. Utilizing channel labels, users effectively access idle or jammed channels, while avoiding interference with legitimate WiFi transmissions (authenticated by machine learning-based RF fingerprinting) resulting in higher throughput. Users optimize their transmit power for low probability of intercept/detection and their MCS to maximize link rates used by backpressure algorithm for routing. Supported by embedded platform implementation, DeepWiFi provides major throughput gains compared to baseline WiFi and another jamming-resistant protocol, especially when channels are likely to be jammed and the signal-to-interference-plus-noise-ratio is low.

Though a cooperative broadcast scheme has been proposed for fading environments, it has two defects: First, it only handles a packet flow from a single source node in the network, but does not consider the scenario of multiple packet flows simultaneously broadcasted from different source nodes. Second, it only allows a single relay node to forward a packet in each time slot, though multiple relay nodes forwarding in a time slot can significantly reduce broadcast latency. In this paper, we aim achieve low-latency multi-flow broadcast in wireless multi-hop networks with fading channels. To describe the interference among the transmission in different flows, we incorporate the Rayleigh fading model to the signal to noise ratio (SNR) model. Then, we introduce a cooperative diversity scheme which allows multiple relays forwarding in a time slot to reduce broadcast latency. We then formulate an interesting problem: In a fading environment, what is the optimal relay allocation schedule to minimize the broadcast latency? We propose a warm up heuristic algorithm for single-flow cooperative broadcast, based on which, we further propose a heuristic algorithm for multi-flow cooperative broadcast. Simulation results demonstrate that the two algorithms achieve lower broadcast latency than a previous method.

Underlying link-layer protocols of well-established wireless networks that use the conventional “store-and-forward” design paradigm cannot provide highly sustainable reliability and stability in wireless communication, which introduce significant barriers and setbacks in scalability and deployments of wireless networks. In this paper, we propose a Code Embedded Distributed Adaptive and Reliable (CEDAR) link-layer framework that targets low latency and balancing en/decoding load among nodes. CEDAR is the first comprehensive theoretical framework for analyzing and designing distributed and adaptive error recovery for wireless networks. It employs a theoretically sound framework for embedding channel codes in each packet and performs the error correcting process in selected intermediate nodes in a packet's route. To identify the intermediate nodes for the decoding, we mathematically calculate the average packet delay and formalize the problem as a nonlinear integer programming problem. By minimizing the delays, we derive three propositions that: 1) can identify the intermediate nodes that minimize the propagation and transmission delay of a packet; and 2) and 3) can identify the intermediate nodes that simultaneously minimize the queuing delay and maximize the fairness of en/decoding load of all the nodes. Guided by the propositions, we then propose a scalable and distributed scheme in CEDAR to choose the intermediate en/decoding nodes in a route to achieve its objective. The results from real-world testbed “NESTbed” and simulation with MATLAB prove that CEDAR is superior to schemes using hop-by-hop decoding and destination decoding not only in packet delay and throughput but also in energy-consumption and load distribution balance.

Underlying link-layer protocols of wireless networks use the conventional “store and forward” design paradigm cannot provide highly sustainable reliability and stability in wireless communication, which introduce significant barriers and setbacks in scalability and deployments of wireless networks. In this paper, we propose a Code Embedded Distributed Adaptive and Reliable (CEDAR) link-layer framework that targets low latency and high throughput. CEDAR is the first comprehensive theoretical framework for analyzing and designing distributed and adaptive error recovery for wireless networks. It employs a theoretically-sound framework for embedding channel codes in each packet and performs the error correcting process in selected intermediate nodes in packet's route. To identify the intermediate nodes for the en/decoding for minimizing average packet latency, we mathematically analyze the average packet delay, using Finite State Markovian Channel model and priority queuing model, and then formalize the problem as a non-linear integer programming problem. Also, we propose a scalable and distributed scheme to solve this problem. The results from real-world testbed “NESTbed” and simulation with Matlab prove that CEDAR is superior to the schemes using hop-by-hop decoding and destination-decoding not only in packet delay but also in throughput. In addition, the simulation results show that CEDAR can achieve the optimal performance in most cases.

Cooperative broadcast, in which a packet receiver cooperatively combines received weak signal power from different senders to decode the original packet, has gained increasing attention. However, existing approaches are developed based on the assumption that there is a single flow in the network; thus, they are not suitable for multi-flow broadcasting in which broadcasts are initiated by different nodes and consist of more than one packet at any point in time. In this paper, we aim to achieve low-latency multi-flow broadcast in wireless multihop networks with fading channels. We formulate this problem as a Minimum Slotted Delay Cooperative Broadcast (MSDCB) problem, and prove that it is NP-complete and o(logN) inapproximable. We then propose two heuristic algorithms named PCBHS and PCBH-M to solve MSDCB. Our experimental results show that our algorithms outperform previous methods.

This paper presents the design of a new paradigm for a content-aware wireless MAC layer that is optimized for wireless video (first and foremost) while targeting fairness and stability among competing video traffic, and among video and non-video traffic. Hence, we refer to the proposed MAC framework as the FAST (Fair And STable) protocol. FAST employs two parameters for each packet, a quality value and a time-to-live value. Based on these parameters, FAST is designed on a multiclass priority queuing system that classifies the incoming traffic according to the content of each traffic flow and further identifies different priorities within each video content. We develop analytical frameworks to formulate channel allocation based on video/non-video fairness and video stability requirements as a joint bandwidth maximization and scheduling optimization problem. We incorporate these frameworks to design and simulate a content-aware channel access mechanism, which utilizes video traffic content classifications and users demand in conjunction with stability and fairness requirements at the MAC layer to allocate wireless channels to individual wireless users. Our simulation results show that FAST provides significant improvements in packet-loss-ratio, delay, overall fairness, and stability parameters when compared with leading access control mechanisms over 4G/LTE environment.

In this paper, we develop a Reliable Energy Adept Link-layer (REAL) protocol for power-constrained networks to provide reliable data transmissions among battery-operated wireless nodes. REAL dynamically performs error recovery with respect to the overall distortions in the system and the available energy at wireless nodes. REAL employs rate-adaptive low density parity check (LDPC) codes for error recovery. We develop a theoretical model to estimate the distortion imposed by wireless channels and to compute the likelihood of successful decoding at the link-layer. Next, we present a recovery model using Markovian decision process to formulate the optimal decoding policy as a linear optimization problem. We design and implement the REAL protocol which provides system reliability with efficient energy utilization. We demonstrate experimentally that REAL achieves 5%-40% throughput and 3%-18% energy consumption improvements over channel traces with varying bit error rates (BERs) collected on 802.15.4 environment. Further, REAL shows 5-15db PSNR better video quality over various realtime video scenarios.

In this paper, we develop Prioritized Adaptive Code-Enhanced (PACE) link-layer protocol to achieve preferred data recovery order across connections, while maintaining stable and reliable data flow over a wireless network. We classify link-layer traffic arrivals into different priorities based on delay constraint and distortion associated with that traffic. We formulate the link-layer buffer as a multiclass M/G/1 priority queuing system and the decoding process by a nonhomogeneous Geometric density function. This formulation enables the determination of an optimal dynamic decoder scheduling for heterogeneous link-layer traffic. PACE employs rate-adaptive Low Density Parity Check (LDPC) codes for error recovery. We demonstrate experimentally that PACE reduces the throughput-delay cost by 20%-70% in comparison with the IEEE802.11 ARQ and Hybrid ARQ (HARQ) protocols. Further, it achieves 20%-60% throughput and 2-10dB PSNR improvements in channel bandwidth utilization and realtime video playback quality.

Despite major developments in link-layer design to address reliability issues associated with the wireless communication (in a presence of heavy noise), these efforts fall short on many fronts. This includes a clear demonstration regarding the viability of a truly reliable link-layer capable of providing a minimal level of guaranteed sustainable flows for the higher layers. In this paper, we present an analytical and experimental study to design and implement a reliable wireless link-layer that provides sustainable flow control. We develop an experimental platform using Software Radio Defined (SDR) technology with the Universal Software Radio Peripheral (USRP) frontend to capture and measure the behavior of an error process imposed on a wireless channel. Next, we design a Reliable And StablE (RASE) link-layer protocol to provide reliability (by achieving optimal throughput) and stability (by ensuring a sustainable traffic flow) for realtime and non-realtime wireless communications. We then incorporate the RASE protocol into the SDR-USRP platform to investigate the level of throughput and realtime stability achieved in comparison with the IEEE802.11 ARQ and the FEC-based HARQ protocols. We demonstrate experimentally that RASE provides 20%-50% improved reliability. In addition, realtime video communication experiments show a 2-8dB PSNR gain in playback quality.

Real-time video communication over wireless channels is subject to information loss since wireless links are error-prone and susceptible to noise. Popular wireless link-layer protocols, such as retransmission (ARQ) based 802.11 and hybrid ARQ methods provide some level of reliability while largely ignoring the latency issue which is critical for real-time applications. Therefore, they suffer from low throughput (under high-error rates) and large waiting-times leading to serious degradation of video playback quality. In this paper, we develop an analytical framework for video communication which captures the behavior of real-time video traffic at the wireless link-layer while taking into consideration both reliability and latency conditions. Using this framework, we introduce a delay constraint packet embedded error control (DC-PEEC) protocol for wireless link-layer. DC-PEEC ensures reliable and rapid delivery of video packets by employing various channel codes to minimize fluctuations in throughput and provide timely arrival of video. In addition to theoretically analyzing DC-PEEC, the performance of the proposed scheme is analyzed by simulating real-time video communication over ldquorealrdquo channel traces collected on 802.11 b WLANs using H.264/AVC JM14.0 video codec. The experimental results demonstrate performance gains of 5-10 dB for different real-time video scenarios.

Internet blackholes have emerged as very effective tools for monitoring changes in the Internet's traffic behavior. Prior studies have shown that traffic observed at a blackhole contains valuable information about emerging malware. While blackhole traffic has been effectively used for attack forensics, a systematic method of leveraging this traffic for online Internet- scale anomaly detection is not available. In this paper, we propose a novel technique to detect malware outbreaks using deviations in a robust statistical model of a blackhole's traffic. First, we introduce a novel and accurate Piecewise Poisson process Model (PPM) of traffic observed at an Internet Motion Sensor (IMS) blackhole which provides a statistical quantification of the intensity or rate of incoming traffic at a blackhole, which can in turn be used to detect malware outbreaks. After establishing the accuracy of the proposed PPM model, we develop a regression model that can characterize variations in the PPM's traffic rates. Once an accurate model of traffic rates is in place, malware outbreaks can be detected using deviations from the model's likely statistical patterns. After removing simple deterministic patterns, we observe that a blackhole's traffic rate residuals have a skewed and heavy-tailed behavior. Consequently, we employ a stable distribution that models variations in traffic rate residuals with very high accuracy. Finally, we propose an online detection mechanism that utilizes deviations from the rate residual distribution of blackhole traffic data to detect malware outbreaks. Experimental results using the IMS data for approximately one year show that the proposed mechanism accurately detects malware outbreaks in a timely manner.

Research has shown that fluid limits of Markov processes can be used to obtain closed form expressions for the evolution of the ripple-size. In this work we extend the above analysis to generalized LT (GLT) codes, which can be used to represent LT encoding (with priorities) over multiple data segments. In our analysis, we segregate the ripple into multiple colored ripples, where each color corresponds to a segment. We derive closed form expressions for the size of each ripple. We utilize these expressions to design GLT distributions, optimized for a desired intermediate and unequal recovery.

A primary focus of popular wireless link-layer protocols is to achieve some level of reliability using ARQ or Hybrid ARQ mechanisms. However, these and other leading link-layer protocols largely ignore the stability aspect of wireless communication, and rely on higher layers to provide stable traffic flow control. This design strategy has led to a great deal of inefficiency in throughput and to other major issues (such as the well-known TCP over-wireless performance degradation phenomenon and the numerous studies in attempt to fix it). In this paper, we propose a paradigm shift where both reliability and stability are targeted using an Automatic Code Embedding (ACE) wireless link-layer protocol. To the best of our knowledge this is the first effort to develop a theoretical framework for analyzing and designing a wireless link-layer protocol that targets system stability in conjunction with reliable communication. We present two distinct analytical frameworks to determine optimal code embedding rates which ensure system reliability and stability for wide range of traffic demand. An important conclusion of our analysis is that various traffic demand can be met using a packet-by-packet code embedding rate constraint that is independent of traffic type. We demonstrate experimentally that ACE provides both rapid and reliable point-to-point wireless data transmission for realtime and non-realtime traffic over real channel traces collected on 802.11b WLAN. We also have conducted extensive TCP simulations in conjunction with ACE; and we demonstrate the high level of efficiency and stability that can be achieved for TCP over ACE, while not making any changes to TCP. Further, the implementation of ACE for real-time video communication shows performance gains of 5-10dB over IEEE ARQ schemes. More importantly, ACE is layer oblivious and requires no changes to higher or lower PHY layers.

Reliable transmission is a challenging task over wireless LANs since wireless links are known to be susceptible to errors. Although the current IEEE802.11 standard ARQ error control protocol performs relatively well over channels with very low bit error rates (BERs), this performance deteriorates rapidly as the BER increases. This paper investigates the problem of reliable transmission in a contention free wireless LAN and introduces a packet embedded error control (PEEC) protocol, which employs packet-embedded parity symbols instead of ARQ-based retransmission for error recovery. Specifically, depending on receiver feedback, PEEC adaptively estimates channel conditions and administers the transmission of (data and parity) symbols within a packet. This enables successful recovery of both new data and old unrecovered data from prior transmissions. In addition to theoretically analyzing PEEC, the performance of the proposed scheme is extensively analyzed over real channel traces collected on 802.11b WLANs. We compare PEEC performance with the performance of the IEEE802.il standard ARQ protocol as well as contemporary protocols such as enhanced ARQ and the hybrid ARQ/FEC. Our analysis and experimental simulations show that PEEC outperforms all three competing protocols over a wide range of actual 802.11b WLAN collected traces. Finally, the design and implementation of PEEC using an adaptive low-density-parity-check (A-LDPC) decoder is presented.