In this paper we consider transport layer approaches for achieving high rate, low delay communication over edge paths where the bottleneck is a modern WLAN which can aggregate multiple packets into each WLAN frame. We show that regulating send rate so as to maintain a target aggregation level can be used to avoid queue buildup at the WLAN AP. We derive an approximate downlink throughput model for WLANs using aggregation, verify its accuracy using experimental measurements and using this determine a convex low delay rate region. This allows us to derive a low delay proportional fair rate allocation for which we present a prototype transport layer implementation.
In recent years there has been an upsurge in interest in userspace transports due to their flexibility and support for innovation combined with ease of rollout. This has been greatly facilitated by the high efficiency possible in userspace with the support of modern kernels. Notable examples of new transports developed in this way include Google QUIC @cite_14 , UDT @cite_9 and Coded TCP @cite_18 @cite_4 @cite_2 . ETSI has also recently set up a working group to study next generation protocols for 5G @cite_15 . The use of performance enhancing proxies, including in the context of WLANs, is also not new e.g. RFC3135 @cite_0 provides an entry point into this literature. However, none of these exploit the use of aggregation in WLANs to achieve high rate, low delay communication.
@cite_18 @cite_14 @cite_4 @cite_9 @cite_0 @cite_2 @cite_15
2171031315 2891570868 2164675070 2746866883
The most recent FCC ruling proposes relying on a database of incumbents as the primary means of determining white space availability at any white spaces device (WSD). While the ruling provides broad guidelines for the database, the specifics of its design, features, implementation, and use are yet to be determined. Furthermore, architecting a network where all WSDs rely on the database raises several systems and networking challenges that have remained unexplored. Also, the ruling treats the database only as a storehouse for incumbents. We believe that the mandated use of the database has an additional opportunity: a means to dynamically manage the RF spectrum. Motivated by this opportunity, in this paper we present SenseLess, a database driven white spaces network. As suggested by its very name, in SenseLess, WSDs obviate the need to sense the spectrum by relying entirely on a database service to determine white spaces availability. The service, using a combination of an up-to-date database of incumbents, sophisticated signal propagation modeling, and an efficient content dissemination mechanism ensures efficient, scalable, and safe white space network operation. We build, deploy, and evaluate SenseLess and compare our results to ground truth spectrum measurements. We present the unique system design considerations that arise due to operating over the white spaces. We also evaluate its efficiency and scalability. To the best of our knowledge, this is the first paper that identifies and examines the systems and networking challenges that arise from operating a white space network, which is solely dependent on a channel occupancy database. Nowadays, network traffic classification plays an important role in many fields including network management, intrusion detection system, malware detection system, etc. Most of the previous research works concentrate on features extracted in the non-encrypted network traffic. However, these features are not compatible with all kind of traffic characterization. Google's QUIC protocol (Quick UDP Internet Connection protocol) is implemented in many services of Google. Nevertheless, the emergence of this protocol imposes many obstacles for traffic classification due to the reduction of visibility for operators into network traffic, so the port and payload- based traditional methods cannot be applied to identify the QUIC- based services. To address this issue, we proposed a novel technique for traffic classification based on the convolutional neural network which combines the feature extraction and classification phase into one system. The proposed method uses the flow and packet-based features to improve the performance. In comparison with current methods, the proposed method can detect some kind of QUIC-based services such as Google Hangout Chat, Google Hangout Voice Call, YouTube, File transfer and Google play music. Besides, the proposed method can achieve the microaveraging F1-score of 99.24 percent. With the increasing development of IEEE 802.11 based wireless local area network (WLAN) devices, large-scale multi-cell WLANs with a high density of users and access points (APs) have emerged widely in various hotspots. Providing resilient data transmission has been a primary challenge for scaling the WLANs because the high density of users and APs results in too many collisions. In this paper, we analyze and point out the defect of the single association mechanism defined in IEEE 802.11 on transmission reliability from a network perspective. Then, we propose a "multi-AP" architecture with which a MAC layer device called an AP controller (AC) is employed to enable each user to associate and cooperate with multiple APs. In this way, the users can benefit from the diversity effect of multipaths with independent collisions and transmission errors. This paper concentrates on the theoretical analysis of performance comparison between the proposed ldquoMulti-APrdquo architecture and that in IEEE 802.11. Extensive simulation results show that the proposed ldquomulti-APrdquo architecture can obtain much better performance in terms of the throughput per user and the total throughput, and the performance gain is position dependent. Moreover, the unfairness issue in traditional WLANs due to capture effect can be alleviated properly in the ldquomulti-APrdquo framework. Since the inception of IEEE 802.11 wireless local area networks (WLANs) in 1997, wireless networking technologies have tremendously grown in the last few decades. The fundamental IEEE 802.11 physical (PHY) and medium access control (MAC) protocols have continuously been enriched with new technologies to provide the last mile wireless broadband connectivity to end users. Consequently, several new amendments of the basic IEEE 802.11 gradually came up in the forms of IEEE 802.11a, IEEE 802.11b, and IEEE 802.11g. More recently, IEEE 802.11n, IEEE 802.11ac, and IEEE 802.11ad are introduced with enhanced PHY and MAC layers that boost up physical data rates to the order of Gigabit per second. So, these amendments are generally known as high throughput WLANs (HT-WLANs). In HT-WLANs, PHY layer is enhanced with multiple-input multiple-output antenna technologies, channel bonding, short guard intervals, enhanced modulation and coding schemes. The MAC sublayer overhead is reduced by introducing frame aggregation and block acknowledgement technologies. However, several existing studies reveal that, many a time, the aforesaid PHY and MAC enhancements yield negative impact on various upper layer protocols, that is end-to-end transport and application layer protocols. As a consequence, a large number of researchers have focused on improving the coordination among PHY MAC and upper layer protocols. In this survey, we discuss impact of HT-WLAN PHY and MAC layer enhancements on various transport and application layer protocols. This paper also summarizes several research works that use aforesaid enhancements effectively to boost up data rate of end-to-end protocols. We also point out limitations of the existing researches and list down different open challenges that can be meaningfully explored for the development of the next generation HT-WLAN technologies.