Different from intermittent ISM signals like Bluetooth and WiFi, LTE signals are continuous in time and more pervasive in space, which makes them suitable carriers for ambient backscatter systems. However, due to the continuous LTE traffic and complex frame structures, existing ambient backscatter systems, such as HitchHike and LScatter, cannot reliably backscatter LTE signals in a standard-compatible way. We observe that the primary cause of their failures is that tags cannot accurately synchronize with LTE excitations. To address this issue, we propose SyncLTE, an LTE backscatter system that achieves high-accuracy synchronization and standard-compatible backscatter communication. The key novelty is a new tag design that uses the periodicity of LTE signals for synchronization and provides a customized single-symbol modulation scheme for LTE carriers. Our design is prototyped using FPGAs, SDR LTE eNBs and UEs. Comprehensive experiments have been done in various scenarios, including LoS, NLoS, indoor and outdoor. Results show that SyncLTE is 22.4x and 7.4x better than LScatter and Multiscatter in terms of the 80th percentiles of synchronization errors. Also, SyncLTE can deliver throughputs of up to 200 bps using BPSK and 400 bps using QPSK while other systems suffer from failures.

The use of controlled excitation makes pervasive backscatter communication difficult to achieve and the redundant modulation severely limits the performance of the system. We present a novel WiFi backscatter system that can take uncontrolled OFDM WiFi signals as excitations and efficiently embed tag data at the single-symbol rate. Specifically, we are the first to discover the fundamental reason why the previous systems have to rely on multi-symbol modulation, which makes it possible to demodulate tag data on the single-symbol level. Further, we design deinterleaving-twins decoding that can reuse any uncontrolled WiFi signals as carriers to backscatter tag data. Moreover, we present how to robustly handle high-order excitations, including different demapping rules for diverse excitations and three different bit-translation methods for decoding. To verify the effectiveness of our proposal, we prototype our solution using various FPGAs and SDRs. Comprehensive evaluations show that our solution’s maximum throughput is 3.92x and 1.97x better than FreeRider and MOXcatter. In addition, with 16QAM excitations, the decoding BERs of majority voting are around 5%, which is 10x better than subsequence matching and jaccard similarity methods. Meanwhile, the throughput of deinterleaving-level demodulation is 2x better than payload-level demodulation with 16QAM ambient traffic.

Backscatter is an emerging ultra-low-power wireless communication technology for Internet-of-Things. However, as the widely used modulation scheme in OFDM systems, the combination of QAM and WiFi backscatter is not very satisfactory. To deploy QAM in the WiFi backscatter system, we propose PilotScatter, the first OFDM backscatter system supporting both 16-QAM modulation and non-redundant coding. These changes significantly improve the throughput of PilotScatter over previous backscatter systems. The key insight of PilotScatter is the use of pilot tones and differential demodulation. By modifying the phase and amplitude of pilot tones of the carrier signal, PilotScatter can modulate tag data on ambient WiFi with a 16-QAM scheme. At the receiver, PilotScatter uses a differential algorithm to demodulate tag data. It makes PilotScatter achieve 16-QAM demodulation without relying on ambient WiFi data and past symbols. We prototype PilotScatter using FPGAs, commodity radios, and USRPs. Comprehensive evaluations demonstrate that PilotScatter achieves up to 932.22 kbps throughput for WiFi 802.11g, and the backscatter communication range (Tag-to-Rx) is up to 19 m in Line-of-Sight (LoS) and 16 m in Non-Line-of-Sight (NLoS). Compared with the symbol-level backscatter research, PilotScatter has 7.49x and 3.78x goodput gains over MOXcatter and RapidRider, respectively.

Over the past decade, backscatter nodes have received booming interest for many emerging mobile applications, such as sports analytics and interactive gaming. However, backscatter networks are not ready to provide a high-throughput and stable communication platform for billions of such mobile nodes due to two main factors in rate adaptation. First, the common mapping paradigm that chooses the optimal rate based on RSSIs is hardly adaptable to hardware diversity. Second, the current probing processes are not optimized for mobile scenarios due to inefficient probing trigger, inaccurate channel estimation, and unique self-interference. To address those issues, we propose MobiRate, a mobility-aware rate adaptation link-layer that fully exploits the mobility hints from PHY information to deliver a high-throughput link-layer for mobile backscatter networks. The key insight is that mobility-hints can greatly benefit link-layer design, including rate selection and channel probing. Specifically, we introduce a novel velocity-based loss-rate estimation module, a mobility-assisted probing trigger, a selective probing module, and a robust self-interference detection module, significantly saving probing time and improving probing accuracy. As MobiRate is fully compatible with the current standard, we prototype it using COTS RFID readers and commercial tags. Our extensive experiments demonstrate that MobiRate can successfully identify self-interference with detection accuracy over 90% for tags of different velocities. Moreover, it achieves up to 3.8x throughput gain over the state-of-the-art methods across a wide range of mobility, channel conditions, and tag types.

We present multiscatter, a novel battery-free backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Moreover, we introduce a low-power listening scheme to improve energy efficiency. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications. We prototype multiscatter using an FPGA and various commodity radios. Extensive experiments show that for mixed 802.11b&n, Bluetooth and ZigBee signals, the average identification accuracy of four protocols is more than 93%. The maximal aggregate throughput of both productive and tag data is 278.4 kbps with a single Bluetooth radio. When the transmitter-to-tag distance is increased from 0.2 to 1.8 m, the maximal communication for BLE drops from 71 m to 29 m. And it can leverage excitation diversity to provide uninterrupted communication and greater throughput gains, whereas the single-protocol tag being idle when carrier signals are unavailable. With indoor office light as harvesting sources, the low-power listening scheme can support backscatter rate at 12 pkts/s.

We present CAB, a content-agnostic backscatter system that can demodulate both tag and ambient data from ambient backscattered WiFi alone. In contrast to prior ambient backscatter systems that use ambient data (content) as tag-data carriers, we focus on zero-subcarriers, which are invariant and independent for any ambient OFDM WiFi. The idea of using zero-subcarriers to convey tag data is simple and elegant. Not only does it for the first time remove the dependency of tag-data demodulation on ambient data, but it also significantly improves the practicality of ambient backscatter.

Due to extremely low power consumption, backscatter is promising to become general-purpose communication for Internet of Things (IoT) networks. The state-of-the-art BLE backscatter system RBLE can work fully with commodity Bluetooth Low Energy (BLE) devices, however, the communication reliability of RBLE is still limited by its modulation scheme based on Binary Frequency Shift Keying (BFSK). To address this issue, we refer to the modulation of active BLE radios to improve the modulation scheme of the backscatter tag. We present PBLE, a practical BLE backscatter communication system that modulates using phase shift. We conduct experiments to verify the feasibility and efficacy. Evaluation results demonstrate the feasibility and performance gains over RBLE in terms of bit error rate (BER). With PBLE, it is possible for us to reliably read the sensor data of tags using daily BLE devices.

This paper presents RapidRider, the first WiFi backscatter system that takes uncontrolled OFDM WiFi signals, e.g., 802.11a/g/n, as excitations and efficiently embeds tag data at the single-symbol rate. Such design brings us closer to the dream of pervasive backscatter communication since uncontrolled WiFi signals are everywhere. Specifically, we show that RapidRider can demodulate tag data for each OFDM symbol while previous systems rely on multi-symbol demodulation. Further, we design deinterleaving-twins decoding that enables RapidRider to use any uncontrolled WiFi signals as carriers. We prototype RapidRider using FPGAs, commodity radios, and USRPs. Comprehensive evaluations show that RapidRider's maximum throughput is 3.92x and 1.97x better than FreeRider and MOXcatter. To accommodate cases where there is only one receiver available, we design RapidRider+ that can take productive data and tag data on the same packet. Results demonstrate that it can achieve an aggregated goodput of productive and tag data around 1 Mbps on average.

Modern acoustic wearables with microphone arrays are promising to offer rich experience (e.g., 360° sound and acoustic imaging) to consumers. Realtime multi-track audio streaming with precise synchronization however poses significant challenges to the existing wireless microphone array designs that depend on complex digital synchronization as well as bulky and power-hungry hardware.

The communication reliability of state-of-the-art Bluetooth Low Energy (BLE) backscatter systems is fundamentally limited by their modulation schemes because the Binary Frequency Shift Keying (BFSK) modulation of the tag does not exactly match commodity BLE receivers designed for Gauss Frequency Shift Keying (GFSK) modulated signals with high bandwidth efficiency. Gaussian pulse shaping is a missing piece in state-of-the-art BLE backscatter systems. Inspired by active BLE and applying calculus, we present IBLE, a BLE backscatter communication system that achieves full compatibility with commodity BLE devices. IBLE leverages the fact that phase shift is the integral of frequency over time to build a reliable physical layer for BLE backscatter. IBLE uses instantaneous phase shift (IPS) modulation, GFSK modulation, and optional FEC coding to improve the reliability of BLE backscatter communication to the commodity level. We prototype IBLE using various commodity BLE devices and a customized tag with FPGA. Empirical results demonstrate that IBLE achieves PERs of 0.04% and 0.68% when the uplink distances are 2 m and 14 m respectively, which are 280x and 70x lower than the PERs of the state-of-the-art system RBLE. On the premise of meeting the BER requirements of the BLE specification, the uplink range of IBLE is 20 m. Since BLE devices are everywhere, IBLE is readily deployable in our everyday IoT applications.

Recently backscatter communication with commodity radios has received significant attention since specialized hardware is no longer needed. The state-of-the-art BLE backscatter system, FreeRider, realizes ultra-low-power BLE backscatter communication entirely using commodity devices. It, however, suffers from several key reliability issues, including unreliable two-step modulation, productive-data dependency, and lack of interference countermeasures. To address these problems, we propose RBLE, a robust BLE backscatter system that works with an excitation BLE device and a single BLE receiver. First, it uses BLE signals with partial single tones as excitations, making single-bit modulation much more robust. Then it designs dynamic channel configuration that enables channel hopping to avoid interfered channels. Moreover, it presents BLE packet regeneration that uses adaptive encoding to further enhance reliability for various channel conditions. The prototype is implemented using TI BLE radios, iPhones, Android phones, and customized tags with FPGAs. Empirical results demonstrate that RBLE achieves more than 17x uplink goodput gains over FreeRider under indoor LoS, NLoS, and outdoor environments. We also show that RBLE can realize uplink ranges of up to 25 m for indoors and 56 m for outdoors.

We present multiscatter, a novel backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications.

Backscatter communication with ambient excitations receives great attention recently as it provides a practical battery-free way to convey various IoT data. However, state-of the-art solutions are of low data rates and thus cannot serve highbandwidth applications, e.g., live streaming. This paper presents Hermit Crab, the first WiFi-backscatter system that achieves high-throughput communication for video streaming. The key contribution is a differential decoding algorithm using pilot phase. By doing so, it supports single symbol encoding, which is much faster than multi-symbol encoding of previous systems. In addition, Hermit Crab can recover the production data and tag data at the same time. Through extensive experiments, we show that it achieves throughputs of up to 960 Kbps with 802.1lg ambient signals, which is 7. 6x better than the state-of-the-art system. We also demonstrate that with such good throughputs, it can stably support live streaming of 480p videos at 30 fps.

Recently backscatter communication with commodity radios has received significant attention since specialized hardware is no longer needed. The state-of-the-art BLE backscatter system, FreeRider, realizes ultra-low-power BLE backscatter communication entirely using commodity devices. It, however, suffers from several key reliability issues, including unreliable two-step modulation, productive-data dependency, and lack of interference countermeasures. To address these problems, we propose RBLE, a reliable BLE backscatter system that works with a single commodity receiver. It first introduces direct frequency shift modulation with the single tone generated by an excitation BLE device, making robust single-bit modulation possible. Then it designs dynamic channel configuration that enables channel hopping to avoid interfered channels. Moreover, it presents BLE packet regeneration that uses adaptive encoding to further enhance reliability for various channel conditions. The prototype is implemented using TI BLE radios and customized tags with FPGAs. Empirical results demonstrate that RBLE achieves more than 17x uplink goodput gains over FreeRider under indoor LoS, NLoS, and outdoor environments. We also show that RBLE can realize uplink ranges of up to 25 m for indoors and 56 m for outdoors.

Virtualized datacenters are often designed from scratch with multiple, redundant paths. Yet the majority of the existing congestion control schemes for virtual machines or containers are variants based on single-path TCP design. Lacking the flexibility of leveraging underlying paths, these schemes cannot further improve the utilization of datacenter networks, or mitigate hotspot links. In this paper, we examine the performance of multipath congestion control design on typical hypervisor and container virtualization platforms. We observe that, the involvement of virtual switch, together with the multi-tenancy nature on these platforms, poses new challenges when handling multipath traffic. Through realworld experiments with production-grade applications, we further reveal that, while multipath congestion control increases per-connection throughput and achieves better traffic balancing, it experiences performance degradation when the number of connections is abruptly increased or there exist path-sharing subflows. These issues are due to the enforced QoS policies and interface mapping schemes applied by virtual switch. To this end, we present vMCC, a practical solution which incorporates explicit congestion notification (ECN) support on virtual switches and ECN-aware multipath congestion control algorithms. We show by comprehensive evaluations that vMC-C improves throughput, round trip time, fairness, and energy efficiency for cloud datacenter traffic, and subsequently benefits typical cloud workloads.

This paper presents a systematic study on adaptive streaming over MPTCP. We start from realworld experiments with Dynamic Adaptive Streaming over HTTP (DASH) and analysis on its performance over MPTCP. We show that DASH can greatly benefit from the improved aggregated throughput by MPTCP; yet the inter-path throughput difference and the intra-path throughput fluctuation have noticeable (negative) impact, too. Without a proper design of path selection and adaptation in MPTCP, they can easily confuse the adaptation logic of DASH, resulting in low bitrates or frequent rebuffering even if high-bandwidth paths are available. We present MPTCP+, an extended multipath TCP solution to offer high quality and smooth playback for adaptive HTTP streaming. MPTCP+ incorporates a path use decision algorithm that smartly disables/enables a path to minimize the inter-path difference, and a novel congestion control algorithm that smooths congestion window evolution with multiple paths. We have implemented MPTCP+ in the MPTCP Linux kernel, with minimum change on the server-side MPTCP module only. It is fully compatible with the existing MPTCP clients and requires no change on the upper-layer protocols, too. Our experiments suggest that MPTCP+ increases the quality of experience (QoE) of DASH by up to 50%.

Backscatter communication, in which data is conveyed through reflecting excitation signals, has been advocated as a promising green technology for Internet of Things (IoT). Existing backscatter solutions however are mostly centralized, relying on a single excitation source, typically within one hop. Though recent works have demonstrated the viability of multi-hop backscatter, the excitation signal remains centralized, which attenuates quickly and fundamentally limits the communication scope. For long-range and high-quality communication, distributed excitations are expected and also naturally available as ambient signals (WiFi, BLE, cellular, FM, light, sound, etc.), albeit not being explored for boosting nearby tags for relaying.

Recently backscatter networks have received booming interest because, they offer a battery-free communication paradigm using propagation radio waves as opposed to active radios in traditional sensor networks while providing comparable sensing functionalities, ranging from light and temperature sensors to recent microphones and cameras. While sensing data on backscatter nodes has been seen on a clear path to increasing in both volume and variety, backscatter communication is not well prepared and optimized for transferring such continuous and high-volume data. To bridge this gap, we propose a high-throughput rate adaptation scheme for backscatter networks by exploring the unique characteristics of backscatter links and the design space of the ISO 18000-6C (C1G2) protocol. Our key insight is that while prior work has left the downlink unattended, we observe that the quality of downlink is affected significantly by multipath fading and thus can degrade the uplink and overall throughput considerably. Therefore, we introduce a novel rate mapping algorithm that chooses the best rate for both the downlink and uplink. Also, we design an efficient channel estimation method fully compatible with the C1G2 protocol and a reliable probing trigger, substantially saving probing overhead. To combat interference, we further design an interference detector using clusters and lightweight countermeasures to make rate adaptation more robust. Our scheme is prototyped using commercial RFID readers and tags. The results show that we can achieve up to 2.6× throughput gain over state-of-the-art approaches across various mobility, channel, network-size, and interference conditions.

Multipath TCP (MPTCP) has recently been suggested as a promising transport protocol to boost the utilization of underlaying datacenter networks, yet it also increases the host CPU power consumption. It remains unclear whether datacenters can indeed benefit from using MPTCP from the perspective of energy efficiency. Through realworld measurement of MPTCP, we show that the energy efficiency of MPTCP is largely related to the flow completion time and the existence of link-sharing subflows. In particular, we find that the link-sharing subflows in MPTCP will significantly elevate the CPUs' power consumption on hosts. To make the matter worse, it will also reduce the transmission efficiency for both throughput-sensitive long flows and latency-sensitive short flows. To address such a problem, we present MPTCP-D, an energy-efficient enhancement of MPTCP in datacenter networks. MPTCP-D incorporates a novel congestion control algorithm that improves energy efficiency by minimizing the flow completion time. It also has a build-in subflow elimination mechanism that precludes link-sharing subflows from increasing the host CPU power consumption. We implement MPTCP-D in the Linux kernel, analyze the parameter selection in the algorithm and study its performance through packet-level simulation and on Amazon EC2. Our results show that, without degrading the performance of the long flow throughput and the short flow completion time, MPTCP-D reduces the long flow energy consumption by up to 72% compared to DCTCP for data transfers, and reduces the short flow power consumption by up to 46% compared to MPTCP with link-sharing subflows.

Backscatter communication offers a cost- and energy-efficient means for IoT sensor data exchange. The IoT vision for ubiquitous interconnection, in practice, demands multi-hop connectivity for robust and scalable sensor networks, as well as compatibility with such prevailing wireless technologies as WiFi. Today's backscatter solutions however typically follow a single-hop paradigm, i.e., tags do not relay for each other. This paper presents X-Tandem, a multi-hop backscatter system that works with commodity WiFi devices. For the first time, we demonstrate that sensing tags can not only work as relays for each other but also modulate their sensing data into a single backscatter packet, which remains a legit WiFi packet that can be decoded with any commercial WiFi NICs. We discuss the design details of X-Tandem and have built a prototype with FPGAs and off-the-shelf WiFi devices. The prototype demonstrates a two-hop implementation, achieving a throughput up to 200 bps with tag-to-tag distances up to 0.4 m and communication ranges up to 8 m. Compared to single-hop solutions, X-Tandem can improve backscatter throughput by more than 10x in challenging indoor environments with obstacles.

Backscatter WiFi offers a novel low-cost and low-energy solution for RFID tags to communicate with existing WiFi devices. State-of-the-art backscatter WiFi solutions have seldom explored advanced features in the latest WiFi standards, in particular, spatial multiplexing, which has been the cornerstone for 802.11n and beyond. In this paper, we present MOXcatter, a WiFi backscatter communication system that works with spatial streams using commodity radios, while keeping the ongoing data communication unaffected. In MOXcatter, a backscatter tag can embed its sensing data on ambient spatial-stream packets, and both the sensing data and the original packets can be decoded by commodity WiFi devices. We have built a MOXcatter prototype with FPGAs and commodity WiFi devices. The experiments show that MOXcatter achieves up to 50 Kbps throughput for a single stream and up to 1 Kbps for double streams with a communication range (tag-to-RX) up to 14 m. We discuss the tradeoffs therein and possible enhancements, and also showcase the applicability of our design through a sensor communication system.

Multipath TCP (MPTCP) enables transmission via multiple routes for an end-to-end connection to improve resource usage of regular TCP. Due to the increasing concern in green computing, there has been significant interest in designing energy-efficient multipath transport. For existing MPTCP congestion control algorithms, the research community still lacks a comprehensive understanding of which components in such an algorithm play the fundamental role in energy efficiency, how various algorithms compare against each other from energy-consuming perspective, or whether there exist potentially better solutions for energy saving. In this paper, we take a first step to answer these questions. Based on the MPTCP Linux kernel experiments, we first summarize that the energy consumption is related to three aspects: average throughput, path delay and different network scenarios. In order to bridge congestion control to the three aspects, we analyze the existing algorithms and capture the essential parameters of multipath congestion control model related to MPTCP's energy-efficiency. Then we design a window increase factor to shift traffic to low-delay energy-efficient paths. We further extend this design by using an energy-aware compensative parameter to fit the general hierarchical Internet topology. We evaluate the performance of existing multipath congestion control algorithms and our proposed algorithm in different network scenarios. The results successfully validate the improved energy efficiency of our design.

Nearly 50% of the energy overhead in today's datacenters comes from host-to-host data transfers, which largely depend on the transport layer performance. Multipath TCP (MPTCP) has recently been suggested as a promising transport protocol to improve datacenter network throughput, yet it also increases the host CPU power consumption. It remains unclear whether datacenters can indeed benefit from using MPTCP from the perspective of energy efficiency. By analyzing the performance of MPTCP, we show that (1) despite consuming higher host CPU power than TCP, MPTCP can largely reduce the long flow completion time and thus save the aggregated energy; (2) link-sharing subflows in MPTCP not only has negative impact on both throughput-sensitive long flows and latency-sensitive short flows, but also noticeably increases the host CPU power, especially for short flows. We present MPTCP-D, an energy-efficient variant of multipath TCP for datacenters. MPTCP-D incorporates a novel congestion control algorithm that can provide energy efficiency by minimizing the flow completion time, and an extra subflow elimination mechanism that can preclude link-sharing subflows from increasing the host CPU power. We implement MPTCP-D in the Linux kernel and study its performance by experiments on Amazon EC2. Our results show that, without degrading the performance of the long flow throughput and short flow completion time, MPTCP-D reduces the long flow energy consumption by up to 72% compared to DCTCP for data transfers, and reduces the short flow power consumption by up to 46% compared to MPTCP with linksharing subflows.

There has been explosive growth in Mobile Personal Livestreaming (MPL) market since 2016. MPL services are booming not only because they introduce the popular live content by spontaneous and personalized broadcasters, but also because they are deliberately designed to be the innovative social networking service (SNS) platforms. The latter is a very important aspect that distinguishes MPL from the traditional livestreaming services. In this paper, we study the social networking of a large scale MPL service “Inke” (with more than 200 million registered users, 15 million daily active users) in China. By analyzing the dataset we crawl and the features of Inke app, we show that the social media stickiness of Inke comes from three aspects: the follower-followee model, the virtual-gift-based incentive mechanism, and the multi-perspective interactivity between broadcasters and viewers. First, Inke introduces the follower-followee model rather than the traditional broadcaster-viewer model, and every user in Inke can be a broadcaster. This makes MPL have some different patterns from both the traditional livestreaming services and SNS platforms. Second, Inke use virtual gift giving and user ranking as its incentive mechanism. Our measurement results show that this mechanism can indeed enhance user stickiness. Furthermore, Inke incorporates a variety of features during broadcasting to strengthen interactivity. The insight we gain in this paper has important implications for both existing and future designs.

Multipath TCP (MP-TCP) algorithms are supposed to be fair to single-path TCP and utilize multiple paths to support high quality end-to-end services. Existing MP-TCP algorithms in literature are confronted with the problems: 1) MP-TCP can be excessively aggressive towards single-path TCP in their coexisting environments; 2) they sometimes fail to balance congestion on multiple paths; 3)their performance is prone to degradation under the circumstances of path heterogeneity, wireless network environments and bandwidth-intensive applications. In this paper, we propose a fluid-based MP-TCP algorithm to address the above problems. Our algorithm has a unique stable equilibrium and serves the design goals of fairness and congestion-balancing. Simulation results show that our algorithm achieves improvement of TCP-friendliness and window fluctuation performance in different scenarios.

Multipath congestion control algorithms are supposed to be friendly to traditional single-path TCP (SP-TCP). Existing multipath Additive Increase Multiplicative Decrease algorithms (MP-AIMD) for multipath TCP (MP-TCP) are confronted with the problems: 1) they are unfair to SP-TCP when the multiple available paths have heterogeneity, e.g. different RTT; 2) they all use packet losses as congestion signals and induce spurious backoffs on a wireless link with high error rate; 3) congestion window fluctuation reduces their potential to support smooth high-quality service such as multimedia applications. This paper proposes a path quality based multipath AIMD (AIMD-PQ) to tackle the above problems. We utilize the round trip time (RTT) on each sub-path to formulate the path quality estimation. AIMD-PQ balances the loads among its sub-paths, moves traffic off the most congested sub-path, and triggers Multiplicative Decrease by both packet loss and path quality signals. Simulation results show that AIMD-PQ improves both the TCP-friendliness and window fluctuation performance of MP-TCP in a heterogeneous wireless network environment.

Extension for the multi-homing feature of Stream Control Transport Protocol (SCTP), Concurrent Multipath Transfer (CMT) can achieve bandwidth aggregation by making use of parallel transmisson over selected paths. However, if CMT-based path selection depended solely upon the information provided by transport layer, it cannot really make the desired bandwidth aggregation. Motivated by the urgent needs of cross-layer bandwidth aggregation and the advances of Ant Colony Optimization (ACO) in network selection, this paper proposes a novel ACO based cross-layer bandwidth aggregation scheme for efficient Concurrent Multipath data Transfer (CMT-ACO) in wireless transmission. CMT-ACO provides an efficient data delivery with two modules, which are ACO-based Efficiency Aware model (ACO-EA) that devotes to sense paths' transmission efficiency(supported by a cross-layer factor) and reduce ``ping-pongquot; path switching (enabled by a stabilization factor), and ACO-based Bandwidth Aggregation scheme (ACO-BA) that contributes to provide a cross-layer optimal bandwidth aggregation scheme. The results gained by a close realistic simulation topology show that how CMT-ACO outperforms existing CMT protocol in terms of performance and quality of service in multi-homed SCTP-based wireless networks.

With feature of flows across multiple interfaces based on the multi-homing feature of Stream Control Transport Protocol (SCTP), Concurrent Multipath Transfer (CMT) has been regarded as a promising protocol for content-rich multimedia data delivery under stringent bandwidth, delay, and loss wireless environment. However, current CMT researches mostly pay attention to improve CMT protocol itself depended solely upon the information provided by transport layer. In this paper, we propose a novel MAC-SCTP based Cross-layer Cognitive CMT (CMT-CC) for efficient multimedia distribution in varying wireless transmission. A Cross-layer Quality Sense Model (CQSM) is designed in the CMT-CC to cognize the paths' quality and select candidate paths for multimedia content delivery. By condition-aware cognitive ability to distinguish the causes of transmission condition change, a further proposed Intelligent Multimedia Content Distributor (IMCD) makes adaptive multimedia delivery behaviors in compliance with real-time wireless condition. Results obtained by a close realistic simulation topology show how the CMT-CC outperforms existing CMT approach in terms of users' of quality of experience for multimedia streaming services.