Goodput Improvement Research Articles

Congestion-aware delay-guaranteed scheduling and routing with renewal optimization

The emergence of time-critical applications imposes great challenges on traditional best-effort data networks. Such applications demand delay-guaranteed services with different granularity. In this paper, we propose a novel fully distributed approach that provides delay-guaranteed services at the packet level within an autonomous system. Specifically, we adopt priority queues with fixed buffer sizes to provide differentiated services and per-hop delay upper bound and explore path diversity in the network to achieve multiplex gain. Network congestion is a major cause of long delay. To address this issue, a virtual queue manager is deployed at each node in the network to exchange their local queue information with neighbors periodically. The exchanged queue information reflects the congestion status of the neighborhood so the nodes can avoid congested routes in making routing decisions. Given the rich control space including routing and queuing decisions, we aim at maximizing the overall network utility. Due to the randomness caused by network dynamics, we transform the utility maximization problem into renewal optimization which is solved at each node. A delay laxity-based reward function and a weighted queue time cost are designed to characterize each decision. To solve the renewal optimization problem, an algorithm named DSROpt is proposed using an iterative approach. Extensive experiments are conducted to verify the performance of the proposed solution using NS-3. Simulation results show that the proposed solution can guarantee packet-level delay while achieving significant performance improvements in goodput and network utility over the state-of-the-art.

LMAC: Efficient Carrier-Sense Multiple Access for LoRa

Current LoRa networks including those following the LoRaWAN specification use the primitive ALOHA mechanism for media access control due to LoRa’s lack of carrier sense capability. From our extensive measurements, the channel activity detection feature that was recently introduced to LoRa for energy-efficiently detecting preamble chirps can also detect payload chirps reliably. This sheds light on an efficient carrier-sense multiple access protocol that we refer to as LMAC for LoRa networks. This article presents the designs of three advancing versions of LMAC that respectively implement carrier-sense multiple access, and balance the communication loads among the channels defined by frequencies and spreading factors based on the end nodes’ local information and then additionally the gateway’s global information. Experiments on a 50-node lab testbed and a 16-node university deployment show that, compared with ALOHA, LMAC brings up to 2.2× goodput improvement and 2.4× reduction of radio energy per successfully delivered frame. Thus, should LoRaWAN’s ALOHA be replaced with LMAC, network performance boosts can be realized.

Intelligent Resource Allocation in LoRaWAN Using Machine Learning Techniques

With the ubiquitous growth of Internet-of-things (IoT) devices, current low-power wide-area network (LPWAN) technologies will inevitably face performance degradation due to congestion and interference. The rule-based approaches to assign and adapt the device parameters are insufficient in dynamic massive IoT scenarios. For example, the adaptive data rate (ADR) algorithm in LoRaWAN has been proven inefficient and outdated for large-scale IoT networks. Meanwhile, new solutions involving machine learning (ML) and reinforcement learning (RL) techniques are shown to be very effective in solving resource allocation in dense IoT networks. In this article, we propose a new concept of using two independent learning approaches for allocating spreading factor (SF) and transmission power to the devices using a combination of a decentralized and centralized approach. SF is allocated to the devices using RL for contextual bandit problem, while transmission power is assigned centrally by treating it as a supervised ML problem. We compare our approach with existing state-of-the-art algorithms, showing a significant improvement in both network level goodput and energy consumption, especially for large and highly congested networks.

Coarse-Grained Load Balancing with Traffic-Aware Marking in Data Center Networks

In the data center environment, meeting the dissimilar requirements of transmission performance for long and short data flows is crucial for guaranteeing the data center service quality. It is well known that optimizing the network transmission performance is the key. Abundant research studies have reported that designing an effective load-balancing scheme can boost the network performance by enhancing the path utilization of multirooted data center networks. Unfortunately, the existing data center load-balancing schemes fail to provide satisfying flow-level transmission performance since they choose to ignore the constant changing path status and blindly assign paths to data flows regardless of their different performance requirements. In order to solve these issues, we propose a data center load-balancing scheme called TAM to meet the performance requirements of long and short flows simultaneously. In detail, TAM leverages the traffic-aware ECN marking mechanism to force long flows to proactively maintain the switch queue length at a low level and release bandwidth to short flows when they compete for the bottleneck link. On the contrary, TAM carries out the coarse-grained routing or rerouting for short and long flows, respectively, in real time by perceiving the path status. In this way, the short flows achieve low delay transmission while the long flows obtain high throughput. The simulation results based on NS2 tests show that TAM achieves up to 60% lower FCTs for short flows and a 40% improvement in goodput for long flows.

Multiattribute‐based routing for lifetime maximization in opportunistic mobile social networks

SummaryWith the advancement in wireless technology and portable devices, smart phones have become one of the belongings of human being. People share their data online, but it has limitations due to transmission range and mobility. Yet opportunistic mobile social network enables users to share data online even if there is no connected path between source and destination. The widespread use of mobile phones equipped with WiFi, Bluetooth, and several other components and contact opportunities among humans bridge the gap between internet available and nonavailable area. In this paper, we have proposed a new routing approach which utilizes both spatial and temporal attributes of user such as probability to meet a particular location and remaining intercontact time between two nodes to select better relay nodes. Generally, users visit different locations such as sports stadium and mall, with varying probability. Users with similar interest form group, and each user has different intercontact time with other users according to their point of interest and visiting pattern. By utilizing multiattributes, different forwarding strategies have been devised for both inter and intragroup routing. The proposed work “point of interest (PoI)‐based routing” is implemented in Opportunistic Network Environment simulator, and the performance is analysed in terms of delivery rate, latency, overhead, goodput, and energy consumed. The simulation results show that PoI diminishes 23% of overhead and yields 24% improvement in goodput over the state‐of‐the‐art protocol. Thus, the simulation results reveal that our proposed work provides the balance between routing performance and resource consumption.

Interpath Contention in MultiPath TCP Disjoint Paths

Interpath contention is a phenomenon experienced in a MultiPath TCP (MPTCP) connection when its subflows dispute resources of shared bottlenecks in end-to-end paths. Although solutions have been proposed to improve MPTCP performance in different applications, the impact of interpath contention on the multipath performance is little understood. In this paper, we evaluated such phenomenon experimentally in disjoint paths–an ordinary multipath scenario where subflows dispute bottlenecks of paths physically disjointed in a connection. Under several path conditions determined from emulations of capacity, loss, and delay of bottlenecks, we analyzed the influence of MPTCP mechanisms such as packet scheduling, congestion control, and subflow management. Differently from other studies, we observed that the very first influence was caused by the current subflow manager, full-mesh , with dichotomous impact on the multipath performance when establishing several subflows per disjoint path. Experimental results showed that contention among subflows can lead to positive (goodput improvement) or negative (goodput degradation) impacts according to the bottleneck conditions. In certain conditions, simply establishing subflows in single-mesh , with at most one subflow per disjoint path, could avoid interpath contention while improving goodput significantly, by doubling the performance of full-mesh under different conservative congestion controls.

MegaLight

Screen-camera communication using dynamic barcode streaming has emerged as a convenient and secure method for short-range, impromptu device-to-device communication. Conventional dynamic barcode systems adopt a rule-based approach to recognize the color barcode stream in the receiver, which is empirical, inflexible, and lacks self-adaptiveness. In this paper, we propose a novel solution framework for color barcode stream recognition basing on machine learning techniques. By including a number of training frames into the barcode stream to build a classification model, the proposed framework can achieve high accuracy in color barcode recognition and is adaptive to different ambient lighting conditions (without sudden changes during transmission). A semi-supervised learning approach basing on the Mixture of Experts (MoE) model is further proposed to reduce the start-up time. We implement MegaLight on both black-white and color barcode systems. Extensive experiments demonstrate that MegaLight can significantly reduce the frame demodulation error and reach up to 3x improvement in system goodput comparing to conventional barcode stream recognition approaches.

Energy-Aware Concurrent Multipath Transfer for Real-Time Video Streaming Over Heterogeneous Wireless Networks

The advancements in networking technologies and hand-held devices enable mobile users to concurrently receive real-time multimedia streaming (e.g., high-definition video) with different radio interfaces (e.g., Wi-Fi and LTE networks). Stream control transmission protocol (SCTP) is an important transport-layer solution to implement concurrent multipath transfer (CMT) over heterogeneous wireless networks with multihomed terminals. However, it is challenging to distribute multimedia content to resource-limited mobile devices because of the contradiction between energy consumption and streaming quality. To deliver the energy-efficient and quality-aware multimedia streaming over multiple wireless networks, this paper presents an Energy and goodPut Optimized CMT (EPOC) solution. First, we develop an analytical framework to model the relationship between energy consumption and goodput performance for real-time multimedia transmission to multihomed mobile devices. Second, we propose a joint forward error correction coding and rate allocation scheme to minimize energy consumption while satisfying goodput constraint. EPOC effectively leverages the energy-goodput tradeoff and multipath diversity to optimize mobile multimedia transmission in heterogeneous networking environment. We conduct the performance evaluation through extensive semi-physical emulations in Exata involving H.264 video streaming. Compared with the reference CMT schemes using SCTP, EPOC achieves appreciable improvements in energy conservation, goodput, and video peak signal-to-noise ratio.

Goodput Improvement for MPTCP Based on Controlling the Difference of Delay

Goodput Improvement for MPTCP Based on Controlling the Difference of Delay

Coupled IEEE 802.11ac and TCP Goodput Improvement Using Aggregation and Reverse Direction

This paper suggests a new model for the transmission of Transmission Control Protocol (TCP) traffic over IEEE 802.11 using the new features of IEEE 802.11ac. The paper examines the first step in this direction and as such we first consider a single TCP connection, which is typical in a home environment. We show that when the IEEE 802.11ac MAC is aware of QoS TCP traffic, using Reverse Direction improves the TCP Goodput in tens of percentages compared to the traditional contention based channel access. In an error-free channel this improvement is 20% while in an error-prone channel the improvement reaches 60% also using blind retransmission of frames. In our operation modes we also assume the use in Two-Level aggregation scheme, the Automatic Repeat-Request (ARQ) protocol of the IEEE 802.11ac MAC layer, the data rates and the four Access Categories defined in this standard.

Optimal Configuration of Network Coding in Ad Hoc Networks

In this paper, we analyze the impact of network coding (NC) configuration on the performance of ad hoc networks with the consideration of two significant factors, namely, the throughput loss and the decoding loss, which are jointly treated as the overhead of NC. In particular, physical-layer NC and random linear NC are adopted in static and mobile ad hoc networks (MANETs), respectively. Furthermore, we characterize the goodput and delay/goodput tradeoff in static networks, which are also analyzed in MANETs for different mobility models (i.e., the random independent and identically distributed (i.i.d.) mobility model and the random walk model) and transmission schemes (i.e., the two-hop relay scheme and the flooding scheme). Moreover, the optimal configuration of NC, which consists of the data size, generation size, and NC Galois field, is derived to optimize the delay/goodput tradeoff and goodput. The theoretical results demonstrate that NC does not bring about order gain on delay/goodput tradeoff for each network model and scheme, except for the flooding scheme in a random i.i.d. mobility model. However, the goodput improvement is exhibited for all the proposed schemes in mobile networks. To our best knowledge, this is the first work to investigate the scaling laws of NC performance and configuration with the consideration of coding overhead in ad hoc networks.

Goodput improvement for multipath transport control protocol in cooperative relay‐based wireless networks

Multipath transport control protocol (MPTCP) standardised by Internet Engineering Task Force offers a promising solution to support simultaneous delivery of transport control protocol packets over multiple interfaces of multi-radio mobile devices. Even when there is no multiple access coverage, it is still possible to enable multipath transmission by involving mobile devices in vicinity as cooperative relays. However, the available bandwidth provided by relays can be highly varying because of wireless channel fading or dynamic local traffic load. Although MPTCP can pool the available bandwidths of multiple paths, it is challenging to address the dynamics of the cooperative wireless network and ensure a stable performance. In this study, the authors extend MPTCP for the long-term evolution network with cooperative relays by an integrated solution in three aspects, namely, subset ‘sum-based relay selection’, ‘adaptive congestion control’ and ‘differentiated packet forwarding’. Extensive simulations in NS-3 show that the proposed modules can achieve a stable aggregate throughput by engaging a small number of relays and significantly improve the goodput in various scenarios.

IFrag: interference-aware frame fragmentation scheme for wireless sensor networks

Reliable data transmission is a fundamental challenge in resource-constrained wireless sensor networks. In current implementations, a single bit error requires retransmitting the entire frame. This incurs extra processing overhead and power consumption, especially for large frames. Frame fragmentation into small blocks with individual error detection codes can reduce the unnecessary retransmission of the correctly received blocks. The optimal block size, however, varies based on the wireless channel conditions. In this paper, we propose an interference-aware frame fragmentation scheme called iFrag. iFrag dynamically adjusts the number of blocks inside a frame based on current channel conditions, and effectively addresses all challenges associated with such dynamic partitioning. Through analytical and experimental results, we show that iFrag achieves up to $$3\times$$ improvement in goodput when the channel is noisy, while reducing the delay by 12 % compared to other static fragmentation approaches. On average, it shows a 13 % gain in goodput across all channel conditions used in our experiments. Our testbed results also show that iFrag lowers the energy consumed per useful bit by 60 %, as improved data transmission reliability reduces the number of frame retransmissions which increases the motes energy efficiency.

Design, Implementation and Characterization of Practical Distributed Cognitive Radio Networks

Opportunistic Spectrum Access (OSA) in distributed cognitive radio networks (CRNs) has been well studied in the literature from a theoretical perspective. However, such theoretically-optimized distributed OSA approaches are challenged by several practical implementation issues. In this paper, we design a custom cross-layer framework that enables the: (i) clean-slate implementation of a wide variety of OSA mechanisms; (ii) experimental evaluation of the individual practical OSA components of the Rate-Adaptive Probabilistic (RAP) framework; and (iii) detailed comparison of the performance of such a practical OSA approach against theoretical OSA approaches developed for fully-capable CRNs. Our evaluation reveals the multi-fold goodput improvement and remarkable fairness characteristics of the practical RAP OSA approach compared to the OSA approaches that overlook the OSA and CR practical limitations. However, the superior performance of practical OSA comes at the expense of more outages to the primary licensed networks but within the permissible bounds. Another key finding is that the wide family of existing theoretically-optimized OSA protocols can benefit from the gains available to the individual components of the practical RAP approach, namely, the random spectrum sensing and the probabilistic non-greedy access.

TOAR: transmission-aware opportunistic ad hoc routing protocol

Opportunistic routing (OR) protocols for ad hoc networks basically consist of selecting a few forwarders between the source and destination and prioritizing their transmission. The performance of OR protocols depends on how these two steps are performed. The aim was to reduce the number of transmissions to deliver packets to the destination. In this paper, we first present a mathematical model to compute the total number of packets including duplicate packets generated by OR protocols. We use the model to analyse well-known OR protocols and understand the reason behind their increase in number of transmissions. Next, we propose an OR scheme transmission-aware opportunistic ad hoc routing (TOAR) protocol, which attempts to minimize retransmissions. Our proposed OR protocol uses tree structures to select forwarders and prioritize them. The use of tree structures helps in identifying primary forwarders which carry packets farthest to the destination during each transmission round. TOAR also helps in choosing secondary forwarders which will transmit packets missed out by the forwarder. The optimized selection of forwarders results in significant reduction in retransmissions, a smaller forwarder list set, and improvement in goodput.

Self and static interference mitigation scheme for coexisting wireless networks

High density of coexisting networks in the Industrial, Scientific and Medical (ISM) band leads to static and self interferences among different communication entities. The inevitability of these interferences demands for interference avoidance schemes to ensure reliability of network operations. This paper proposes a novel Diversified Adaptive Frequency Rolling (DAFR) technique for frequency hopping in Bluetooth piconets. DAFR employs intelligent hopping procedures in order to mitigate self interferences, weeds out the static interferer efficiently and ensures sufficient frequency diversity. We compare the performance of our proposed technique with the widely used existing frequency hopping techniques, namely, Adaptive Frequency Hopping (AFH) and Adaptive Frequency Rolling (AFR). Simulation studies validate the significant improvement in goodput and hopping diversity of our scheme compared to other schemes and demonstrate its potential benefit in real world deployment.

Goodput-Based Link Resource Adaptation for Reliable Packet Transmissions in BIC-OFDM Cognitive Radio Networks

Cognitive radio (CR) stands out as a potential cornerstone to break the spectrum gridlock through enabling the coexistence of licensed (primary) and unlicensed (secondary) users in the same bandwidth. This paper deals with a novel link resource adaptation (LRA) strategy to be applied in CR scenarios for reliable packet transmissions based on bit interleaved coded orthogonal frequency division multiplexing (BIC-OFDM). We first formulate the power allocation (PA) problem constrained by both the available power at the secondary transmitter (ST) and the interference tolerable at the primary receivers, aimed at maximizing the offered layer 3 data rate, i.e., the goodput (GP) metric. Then, we derive the optimal PA strategy resorting to the customary Lagrangian dual decomposition (LDD) technique, which, however, like many other conventional numerical methods, exhibits several drawbacks, such as slow convergence and need for parameter tuning. These restrictions are circumvented through the development of a novel iterative yet simple PA algorithm, referred to as successive set reduction (SSR) approach, whose optimality conditions are analytically demonstrated by resorting to the Quasi Variational Inequality (QVI) framework. Based on this PA algorithm, an adaptive modulation and coding (AMC) scheme at the ST is eventually derived. Simulation results over a realistic scenario corroborate the effectiveness of the proposed SSR-based AMC algorithm, highlighting the GP improvements over non-adaptive LRA techniques, besides a remarkable complexity reduction w.r.t. conventional numerical methods.

Robust Network Covert Communications Based on TCP and Enumerative Combinatorics

The problem of communicating covertly over the Internet has recently received considerable attention from both industry and academic communities. However, the previously proposed network covert channels are plagued by their unreliability and very low data rate. In this paper, we show through a new class of timing channels coined as Cloak that it is possible to devise a 100 percent reliable covert channel and yet offer a much higher data rate (up to an order of magnitude) than the existing timing channels. Cloak is novel in several aspects. First, Cloak uses the different combinations of N packets sent over X flows in each round to represent a message. The combinatorial nature of the encoding methods increases the channel capacity largely with (N,X). Second, based on the well-known 12-fold Way, Cloak offers 10 different encoding and decoding methods, each of which has a unique tradeoff among several important considerations, such as channel capacity and camouflage capability. Third, the packet transmissions modulated by Cloak can be carefully crafted to mimic normal TCP flows for evading detection. We have implemented Cloak and evaluated it in the PlanetLab and a controlled testbed. The results show that it is not uncommon for Cloak to have an order of channel goodput improvement over the IP Timing channel and JitterBug. Moreover, Cloak does not suffer from any message loss under various loss and reordering scenarios.

Packet skipping and network coding for delay-sensitive network communication

We provide an analytical study of the impact of packet skipping and opportunistic network coding on the timely communication of messages through a single network element. In a first step, we consider a single-server queueing system with Poisson arrivals, exponential service times, and a single buffer position. Packets arriving at a network node have a fixed deadline before which they should reach the destination. To preserve server capacity, we introduce a thresholding policy, based on remaining time until deadline expiration, to decide whether to serve a packet or skip its service. The obtained goodput improvement of the system is derived, as well as the operating conditions under which thresholding can enhance the performance. Subsequently, we focus our analysis on a system that supports network coding instead of thresholding. We characterize the impact of network coding at a router node on the delivery of packets associated with deadlines. We model the router node as a queueing system in which packets arrive from two independent Poisson flows and undergo opportunistic coding operations. We obtain an exact expression for the goodput of the system and study the achievable gain. Finally, we provide an analytical model that considers both network coding and packet skipping, capturing their joint performance. A comparative analysis between the aforementioned approaches is provided.

Energy-efficient and reliable multicasting for WiMAX multi-hop relay networks

Orthogonal frequency division multiplexing (OFDM)-based wireless transmission technologies such as WiMAX are now widely deployed, and the frame check sequence (FCS) scheme is used to enhance the reliability of OFDM-based systems. As the padding overhead cannot be completely avoided in such systems when variable-length medium access control (MAC) frames are encapsulated, the authors propose a novel cyclic redundancy check (CRC)-based error-correction scheme that utilises the frame padding overhead to carry as much extra segmented FCS information as possible. In a multi-hop relay environment, a mobile station might receive a multicast frame more than once, so the error bit correction scheme could be triggered in the first transmission. In the IEEE's work, the original CRC scheme is optional and only has limited error-detection capability in upper MAC layer. FCS requires a few bits in a frame, but in our work, CRC is compulsory and all sub-FCSs are carried by padding space without using any extra bit. For the best error-correction capability, all transmissions must be padded as many sub-FCSs are possible in cross layer. The proposed approach achieves a significant performance improvement over the legacy FCS scheme in terms of error detection and correction of multicast frames in a transparent mode multi-hop relay network, and it is redundancy-free as well as energy efficient. The authors assess the performance improvement via both mathematical analysis and simulations. The results show that the mobile stations get significant improvement of goodput and utilisation in an error-prone WiMAX multi-hop relay network.