Future 5G systems will need to support ultra-reliable low-latency communications scenarios. From a latency-reliability viewpoint, it is inefficient to rely on average utility-based system design. Therefore, we introduce the notion of guaranteeable delay which is the average delay plus three standard deviations of the mean. We investigate the trade-off between guaranteeable delay and throughput for point-to-point wireless erasure links with unreliable and delayed feedback, by bringing together signal flow techniques to the area of coding. We use tiny codes, i.e. sliding window by coding with just 2 packets, and design three variations of selective-repeat ARQ protocols, by building on the baseline scheme, i.e. uncoded ARQ, developed by Ausavapattanakun and Nosratinia: (i) Hybrid ARQ with soft combining at the receiver; (ii) cumulative feedback-based ARQ without rate adaptation; and (iii) Coded ARQ with rate adaptation based on the cumulative feedback. Contrasting the performance of these protocols with uncoded ARQ, we demonstrate that HARQ performs only slightly better, cumulative feedback-based ARQ does not provide significant throughput while it has better average delay, and Coded ARQ can provide gains up to about 40 in terms of throughput. Coded ARQ also provides delay guarantees, and is robust to various challenges such as imperfect and delayed feedback, burst erasures, and round-trip time fluctuations. This feature may be preferable for meeting the strict end-to-end latency and reliability requirements of future use cases of ultra-reliable low-latency communications in 5G, such as mission-critical communications and industrial control for critical control messaging.
Network RTT can be estimated using delay measurements reported from the receiver's acknowledgments @cite_32 . RTT can also be estimated using traffic already flowing between two points without requiring precise time synchronization between each point @cite_33 . However, measuring the time-varying RTT actually experienced by an application is a substantial challenge, particularly when the RTT fluctuates more frequently than one can sample the path. The unpredictability of RTT might have massive effects on upper layer protocols. Therefore, it is required to design robust protocols which are more predictable across statistics, hence are more stable when RTT is unreliable.
@cite_32 @cite_33
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Accurate and frequent round trip time (RTT) measurements are important in testbeds and operational networks. Active measurement techniques inject probe packets that may modify the behaviour of the observed network and may produce misleading RTT estimates if the network handles probe packets differently to regular packets. Previous passive measurement techniques address these issues, but require precise time synchronisation or are limited to certain traffic types. We introduce Synthetic Packet-Pairs (SPP), a novel passive technique for RTT measurement. SPP provides frequently updated RTT measurements using any network traffic already present in the network without the need for time synchronisation. SPP accurately measures the RTT experienced by any application's traffic, even applications that do not exhibit symmetric client-server packet exchanges. We experimentally demonstrate the advantages of SPP. Real-time communication (RTC) applications such as VoIP, video conferencing, and online gaming are flourishing. To adapt and deliver good performance, these applications require accurate estimations of short-term network performance metrics, e.g., loss rate, one-way delay, and throughput. However, the wide variation in mobile cellular network performance makes running RTC applications on these networks problematic. To address this issue, various performance adaptation techniques have been proposed, but one common problem of such techniques is that they only adjust application behavior reactively after performance degradation is visible. Thus, proactive adaptation based on accurate short-term, fine-grained network performance prediction can be a preferred alternative that benefits RTC applications. In this study, we show that forecasting the short-term performance in cellular networks is possible in part due to the channel estimation scheme on the device and the radio resource scheduling algorithm at the base station. We develop a system interface called PROTEUS, which passively collects current network performance, such as throughput, loss, and one-way delay, and then uses regression trees to forecast future network performance. PROTEUS successfully predicts the occurrence of packet loss within a 0.5s time window for 98 of the time windows and the occurrence of long one-way delay for 97 of the time windows. We also demonstrate how PROTEUS can be integrated with RTC applications to significantly improve the perceptual quality. In particular, we increase the peak signal-to-noise ratio of a video conferencing application by up to 15dB and reduce the perceptual delay in a gaming application by up to 4s. High-speed networks with large delays present a unique environment where TCP may have a problem utilizing the full bandwidth. Several congestion control proposals have been suggested to remedy this problem. The existing protocols consider mainly two properties: TCP friendliness and bandwidth scalability. That is, a protocol should not take away too much bandwidth from standard TCP flows while utilizing the full bandwidth of high-speed networks. This work presents another important constraint, namely, RTT (round trip time) unfairness where competing flows with different RTTs may consume vastly unfair bandwidth shares. Existing schemes have a severe RTT unfairness problem because the congestion window increase rate gets larger as the window grows ironically the very reason that makes them more scalable. RTT unfairness for high-speed networks occurs distinctly with drop tail routers for flows with large congestion windows where packet loss can be highly synchronized. After identifying the RTT unfairness problem of existing protocols, This work presents a new congestion control scheme that alleviates RTT unfairness while supporting TCP friendliness and bandwidth scalability. The proposed congestion control algorithm uses two window size control policies called additive increase and binary search increase. When the congestion window is large, additive increase with a large increment ensures square RTT unfairness as well as good scalability. Under small congestion windows, binary search increase supports TCP friendliness. The simulation results confirm these properties of the protocol. Several multihop applications developed for vehicular ad hoc networks use broadcast as a means to either discover nearby neighbors or propagate useful traffic information to other vehicles located within a certain geographical area. However, the conventional broadcast mechanism may lead to the so-called broadcast storm problem, a scenario in which there is a high level of contention and collisions at the link layer due to an excessive number of broadcast packets. While this is a well-known problem in mobile ad hoc wireless networks, only a few studies have addressed this issue in the VANET context, where mobile hosts move along the roads in a certain limited set of directions as opposed to randomly moving in arbitrary directions within a bounded area. Unlike other existing works, we quantify the impact of broadcast storms in VANETs in terms of message delay and packet loss rate in addition to conventional metrics such as message reachability and overhead. Given that VANET applications are currently confined to using the DSRC protocol at the data link layer, we propose three probabilistic and timer-based broadcast suppression techniques: weighted p-persistence, slotted 1-persistence, and slotted p-persistence schemes, to be used at the network layer. Our simulation results show that the proposed schemes can significantly reduce contention at the MAC layer by achieving up to 70 percent reduction in packet loss rate while keeping end-to-end delay at acceptable levels for most VANET applications.