Maximum Achievable Throughput Research Articles

Two-Tier Communication for UAV-Enabled Massive IoT Systems: Performance Analysis and Joint Design of Trajectory and Resource Allocation

In this article, we propose a two-tier communication strategy to facilitate data collection in unmanned aerial vehicle (UAV)-enabled massive Internet of Things (IoT) systems through introducing ground access points (APs) to serve between the UAV and IoT devices. In the first tier of our proposed strategy, all IoT devices transmit their packets to their local APs via a multi-channel ALOHA-based random access scheme, while in the second tier, APs deliver their aggregated data to the UAV through coordinated time division multiple access. Thus, our introduced APs not only liberate the UAV from the potential massive IoT congestion but also facilitate the design of UAV's trajectory based on the location of APs. To examine the performance of our strategy, we propose a tractable framework to analyze the average system throughput. We reveal that the average two-tier throughput of each AP monotonically increases with its maximum achievable throughput in the second tier, while the increasing slope becomes steeper with a higher traffic load mean in the first tier. Then, we formulate the joint design of UAV's trajectory and resource allocation as a non-convex optimization problem to maximize the average system throughput while considering the heterogeneous quality of service requirement of each AP. To solve this problem, a low-complexity iterative algorithm is devised based on successive convex approximation. Numerical results demonstrate the substantial average system throughput gain achieved by our proposed strategy and design in the context of massive access, compared to the baseline schemes in the literature.

Constrained channel bonding based on maximum achievable throughput in WLANs

In Wireless Local Area Networks, channel bonding allows several basic channels to constitute a wide channel. The wide channel can increase potential throughput in a single Basic Service Set (BSS). However, channel contention among BSSs is more serious because the number of non-overlapping channels decreases. Therefore, the appropriate channel bandwidth should be chosen to improve the throughput of the whole network. In this paper, to control channel contention and improve throughput, we propose a channel bonding algorithm in which the channel bandwidth is constrained based on the achievable throughput analysis. At first, the channel contention relationship among BSSs is obtained according to the topology of the network. In each possible channel bonding and channel allocation scheme, the achievable throughput can be calculated according to the contention graph and the maximal clique algorithm. Then, the channel bonding scheme with the maximum achievable throughput can be selected. In the selected channel bonding scheme, each BSS uses a specific channel which consists of several basic channels, and these basic channels are candidate channels of constrained channel bonding in this BSS. Finally, constrained channel bonding will be performed in each BSS, and the combined wide channel can only be constituted by some or all of candidate basic channels. In this manner, channel contention among BSSs can be controlled. Simulation results show that the proposed constrained channel bonding achieves better performance than traditional channel bonding.

An Analytical Approach to Flow-Guided Nanocommunication Networks.

Continuous progress of nanocommunications and nano-networking is opening the door to the development of innovative yet unimaginable services, with a special focus on medical applications. Among several nano-network topologies, flow-guided nanocommunication networks have recently emerged as a promising solution to monitoring, gathering information, and data communication inside the human body. In particular, flow-guided nano-networks display a number of specific characteristics, such as the type of nodes comprising the network or the ability of a nano-node to transmit successfully, which significantly differentiates them from other types of networks, both at the nano and larger scales. This paper presents the first analytical study on the behavior of these networks, with the objective of evaluating their metrics mathematically. To this end, a theoretical framework of the flow-guided nano-networks is developed and an analytical model derived. The main results reveal that, due to frame collisions, there is an optimal number of nano-nodes for any flow-guided network, which, as a consequence, limits the maximum achievable throughput. Finally, the analytical results obtained are validated through simulations and are further discussed.

MPWiFi: Synergizing MPTCP Based Simultaneous Multipath Access and WiFi Network Performance

Multipath TCP (MPTCP) enables a client to exploit multiple wireless paths simultaneously for improved throughput and mobility resilience. However, MPTCP clients in WiFi networks may easily lower the achievable throughput of the network due to excessively created connections over access points (APs), particularly those that own a weak link quality. This is caused by the fact that the maximal achievable throughput of a WiFi AP can be easily affected by the number of connections accessing it and the link qualities of those connections. In this paper, we first verify such effects through extensive experiments and analysis. We then propose a novel scheme, denoted MPWiFi, to solve this issue while keeping the benefits of MPTCP based multipath access in WiFi networks. Our scheme allows a MPTCP client to obtain resources on its best WiFi path freely and suppresses its subflows in additional paths when congestion happens. As a result, the degrading to the WiFi AP's achievable throughput is greatly prevented with acceptable influences on the benefits of MPTCP clients (i.e., their multipath access is intervened only on congested non-best APs). The fairness to MPTCP clients is also guaranteed through their best WiFi connection. The proposed solution is implemented along with the Linux Kernel MPTCP implementation. Extensive real-world deployment based experiments and NS3 simulation show that the proposed scheme can effectively alleviate the adverse impact of MPTCP based multipath access in WiFi networks while keeping its benefits.

Adapting the concept of artificial DNA and hormone system to AUTOSAR environments

Abstract Embedded systems are growing very complex because of the increasing chip integration density, larger number of chips in distributed applications and demanding application fields, e.g. in autonomous cars. Bio-inspired techniques like self-organization are a key feature to handle the increasing complexity of embedded systems. In biology the structure and organization of a system is coded in its DNA, while dynamic control flows are regulated by the hormone system. We adapted these concepts to embedded systems using an artificial DNA (ADNA) and an artificial hormone system (AHS). Based on these concepts, highly reliable, robust and flexible systems can be created. These properties predestine the ADNA and AHS for the use in future automotive applications. However, computational resources and communication bandwidth are often limited in automotive environments. Furthermore, in many critical areas, the AUTOSAR Classic Platform in combination with CAN bus is used as a static operating system. Nevertheless, in this paper we show that the dynamic concept of ADNA and AHS can successfully be applied to a static system like the AUTOSAR Classic Platform and that the available computational resources are more than sufficient for automotive applications. The major bottleneck becomes the CAN bus communication when implemented on top of AUTOSAR’s communication stack as this limits the maximum achievable throughput for a single device in order to provide bandwidth for numerous different participants. Implementing the CAN bus communication directly through AUTOSAR’s CAN driver mostly removed this problem. Furthermore, we lay the foundations of our concept’s adaption to the AUTOSAR Adaptive Platform, thus enabling interesting interoperation scenarios for ADNA-based automotive systems implemented on both AUTOSAR platforms.

Total Throughput Maximization of Cooperative Cognitive Radio Networks With Energy Harvesting

Cognitive radio and energy harvesting techniques have provided significant benefits in terms of spectrum reuse and lifetime prolongation for conventional wireless networks. We are thus motivated to consider the energy harvesting cognitive radio networks (CRNs) consisting of multiple primary users (PUs) and secondary users (SUs). We introduce two cooperation modes: the energy cooperation mode and joint cooperation mode. In the energy cooperation mode, there only exists energy cooperation between PUs and SUs, i.e., the SU transmits its own packets by using the energy harvested from primary signals. In the joint cooperation mode, the SU relays primary packets by using the energy harvested from primary signals. In each cooperation mode of three representational scenarios (the CRN with one pair of PUs and one pair of SUs, the CRN with two pairs of PUs and one pair of SUs, and the CRN with one pair of PUs and two pairs of SUs) and the general scenario, we exploit the optimal time allocation between PUs and SUs, and balance the tradeoff between energy harvesting and packet transmission to obtain the maximum total achievable throughput. To be specific, we first formulate the throughput maximization problems as non-linear optimization problems, and then prove them as convex problems by monotonicity analysis. Moreover, we obtain the closed-form optimal solution in the energy cooperation mode. We prove the existence of the optimal solution in the joint cooperation mode, obtain the upper and lower bounds, and provide numerical analysis for the optimal solution. Finally, we highlight the benefits of information cooperation and the impact of multi-user gain on the maximum of the total achievable throughput.

Evaluating the Suitability of IEEE 802.11ah for Low-Latency Time-Critical Control Loops

A number of industrial wireless technologies have emerged over the last decade, promising to replace the need for wires in a variety of use cases. Except for customized time division multiple access (TDMA)-based wireless technologies that can achieve ultralow latency over a very limited area, wireless communication generally has reliability and latency issues when it comes to industrial applications. Closed loop communication requires high reliability (over 99%), limited jitter and latency, which poses a challenge especially over a wide area measuring in hundreds of meters. Extended coverage is promised with the advent of sub-GHz technologies, one of them being IEEE 802.11ah which is the only one that offers sufficient data rate for frequent bidirectional communication. Thus, we evaluated IEEE 802.11ah for low-latency time-critical control loops. We propose the network setup for adjusting the network dynamics to that of control loops, enabling limited jitter and high reliability. We explore the scalability of IEEE 802.11ah network hosting both control loops and monitoring sensors that periodically transmit measurements. Assigning the control loop end-nodes to dedicated restricted access window (RAW) slot results in over 99.99% successful deliveries. Furthermore, interpacket delay is concentrated around the cycle-time in the following or preceding beacon interval in case the beacon interval is at least half the value of the shortest cycle-time. Adjusting the beacon interval to the fastest control loop in the network ensures latency requirements at the cost of maximum achievable throughput and energy consumption.

Performance of Random Access Markov Modelling for Two-Way Buffer-Aided Relaying Networks with Wireless Assisted Links

In this paper, we consider two-way relaying networks (TWRNs) in which information of two users randomly exchange via buffer-aided relay. We assume that all nodes work on half-duplex decode-and-forward for relaying of data packets. The relay is equipped with two finite-size buffers and both the users know the exact number of data packets. The data packets are scheduling with different channel access probabilities to avoid collision at relay. The protocols are developed on the basis of selective transmission scheme with states of Markov chain at relay for buffer state information (BSI) and Hybrid buffer state information/channel state information (BSI/CSI). On the basis of these protocols, we investigate closed-from expressions of maximum achievable sum throughput and end-to-end throughput for TWRNs. The numerical results are obtained with the help of CVX software package. Our proposed scheme significantly outperforms the existing two-way buffer-aided relaying scheme in literature.

Delay-Sensitive Communications Over IR-HARQ: Modulation, Coding Latency, and Reliability

With the growing popularity of delay-sensitive applications (e.g., real-time conversational video, online gaming, and augmented reality) and future trends toward ultra-reliable low-latency communications such as the tactile Internet, performance analysis of wireless systems under the finite code blocklength constraint becomes extremely important. In this paper, we investigate the maximum achievable throughput of incremental redundancy-hybrid automatic repeat request (IR-HARQ) over the (correlated) Rayleigh fading channel under finite blocklength and delay-violation probability constraints as a function of the modulation scheme. The maximum number of HARQ rounds together with the transport block size specifies the underlying coding latency of the IR-HARQ scheme. A framework, namely the HARQ Markov model (HARQ-MM), is introduced to track the throughput and the probability of error of IR-HARQ over the Rayleigh fading channel as a function of the modulation scheme. The dispersion of parallel additive white Gaussian noise channels with finite input alphabets (e.g., pulse amplitude modulation) is analytically characterized. It is used to identify the state transition probabilities of the underlying HARQ-MM. An algorithm is developed to efficiently compute the steady-state distribution of the HARQ-MM. Extensive performance evaluation is conducted, which shows a good match between the throughput performance characterized by the theoretical framework and that achieved by the practical channel codes.

On the Throughput of Large-but-Finite MIMO Networks Using Schedulers

This paper studies the sum throughput of the {multi-user} multiple-input-single-output (MISO) networks in the cases with large but finite number of transmit antennas and users. Considering continuous and bursty communication scenarios with different users' data request probabilities, we derive quasi-closed-form expressions for the maximum achievable throughput of the networks using optimal schedulers. The results are obtained in various cases with different levels of interference cancellation. Also, we develop an efficient scheduling scheme using genetic algorithms (GAs), and evaluate the effect of different parameters, such as channel/precoding models, number of antennas/users, scheduling costs and power amplifiers' efficiency, on the system performance. Finally, we use the recent results on the achievable rates of finite block-length codes to analyze the system performance in the cases with short packets. As demonstrated, the proposed GA-based scheduler reaches (almost) the same throughput as in the exhaustive search-based optimal scheduler, with substantially less implementation complexity. Moreover, the power amplifiers' inefficiency and the scheduling delay affect the performance of the scheduling-based systems significantly.

Analysis of Pure and Slotted ALOHA With Multi-Packet Reception and Variable Packet Size

Multiple packet reception (MPR) is becoming a viable reality for wireless random access protocols thanks to advances in the physical layer and new coding techniques. In the simplest $K$ -MPR model, a receiver can resolve up to $K\geq 1$ parallel transmissions. We extend the classical analysis of pure and slotted ALOHA to $K$ -MPR devices with arbitrary degree $K$ for fixed and variable packet size. Through a parsimonious modeling approach, we derive relatively simple analytical expressions. In this way, we gain insight and quantitative understanding on the fundamental tradeoffs between pure and slotted ALOHA and on the scaling of maximum achievable throughput with $K$ .

Adaptive Buffer-Aided Wireless Powered Relay Communication With Energy Storage

In this paper, we consider wireless powered relay network, where the energy-constrained decode-and-forward relay is provisioned with both data buffer and energy storage. First, the optimal parameter in time-switching-based relaying scheme is derived to realize the maximal achievable throughput. Second, an adaptive relaying scheme is proposed to dynamically allocate time slots in order to maximize the throughput under the stability constraint of data buffer and the feasibility constraint of energy storage. Third, the relaying scheme is reformulated as a stochastic optimization problem. By employing the Lyapunov optimization framework, an online buffer-energy-aware adaptive transmission scheme is proposed to adjust the transmission according to the dynamic channel state information, the data buffer state information, and the energy state information. Moreover, the tradeoff between the achievable throughput and the transmission delay is presented to show the great potential of the proposed adaptive transmission design to improve the achievable throughput. Finally, simulations are conducted to validate the efficiency of the proposed relaying protocols and confirm the great potentials of buffer-aided relaying in wireless powered relay networks with energy storage.

Multicast Scheduling of Wavelength-Tunable, Multiqueue Optical Data Center Switches

The all-optical switching of multicast flows using star couplers and tunable transceivers is a promising solution for emerging cloud data center applications. However, the limited tuning range of optical components on one hand and the buffer management challenges for multicast traffic delivery on the other pose a significant impact on the performance of optical multicast scheduling algorithms. Using only one queue per input port results in head-of-line (HOL) blocking and limits the throughput, especially for bursty traffic patterns. As the number of possible multicast destinations grows exponentially with the switch size, allocating one queue per destination is not a feasible solution. To resolve HOL blocking, in this paper we consider only a handful of queues per switch input port and devise scalable scheduling algorithms that take into account transceiver tunability constraints. According to our Monte Carlo analysis of a switch with 64 ports and operating under bursty traffic, it is possible to improve the maximum achievable throughput by 44% when the number of queues per port is increased from one to eight. We show that the performance gains due to an increase in the queue count depend on the availability of the spectral resources. With the scarcity of wavelengths, an increase in the number of queues leads to diminishing returns.

On the Achievable Throughput of Energy-Harvesting Nanonetworks in the Terahertz Band

In this paper, the maximum achievable throughput of electromagnetic nanonetworks in the terahertz (THz) band (0.1–10 THz) is comprehensively investigated. On the one hand, the peculiarities of the THz-band channel are taken into account by capturing the impact of the molecular absorption loss on the signal propagation. On the other hand, a two-state medium access control protocol is utilized to reflect the behavior of energy-harvesting nano-devices with constrained harvesting rate and maximum transmission power $P_{0}$ . An ad-hoc nanonetwork is considered with $n$ identical randomly located nano-devices, and each is capable of utilizing $W$ Hz of bandwidth. When the node density of nanonetworks is low, the achievable throughput is $O (W P_{0} ( { (n\log n )^{({\alpha _{spr}-1}/{2})}}/{\exp (({ \alpha _{abs}}/{({n \log n})^{1/2}} ))}) )^{({1}/{2})}$ , where $\alpha _{spr}$ and $\alpha _{abs}$ refer to the spreading loss coefficient and the molecular absorption loss coefficient. When the node density of nanonetworks is very high, the interference among nano-devices governs the network behavior and the achievable throughput becomes $O (({W^{2} P_{0}/ {I(n)}}) ({ (n\log n )^{({\alpha _{spr}-1}/{2})}}/~{\exp (({ \alpha _{abs}}/{({n \log n})^{1/2}}) )} ))^{({1}/{2})}$ . For both the cases, the upper boundaries of the achievable throughput are analytically derived, and the numerical results are provided. Numerical results illustrate that the molecular absorption loss plays the main role when the nanonetwork is sparse, and the interference dominates when the nanonetwork node density is very high.

Vehicle automation and freeway \u2018pipeline\u2019 capacity in the context of legal standards of care

The study evaluates, in the context of freeway segments, the interaction between automated cars’ kinematic capabilities and the standard legal requirement for the operator of an automobile to not strike items that are in its path (known as the ‘Assured Clear Distance Ahead’ criterion). The objective is to characterize the impacts of ACDA-compliant driving behavior on the system-level indicator of roadway-network capacity. We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDA-compliant automated-driving model to analytically estimate freeway ‘pipeline’ capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. We demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive “fundamental diagrams” (relationships between speed and flow). Our results suggest that such automated-driving strategies (under a baseline set of assumptions) would sustain higher flow rates at free-flow speeds than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion would be steeper. ACDA-compliant automated cars also would have a higher level of maximum-achievable throughput, though the impact on maximum throughput at free-flow speed depends on the specific interpretation of ACDA. We also present a novel quantification of the tradeoff between freeway-capacity and various degrees of safety (one failure in 100,000 events, one failure in 1,000,000, etc.) that explicitly accounts for the irreducible uncertainty in emergency braking performance, by drawing on empirical distributions of braking distance testing. Finally, we assess the vulnerability of ACDA-compliant automated cars to lateral ‘cut-ins’ by vehicles making lane changes. The paper concludes with a brief discussion of policy questions and research needs.

Microfluidic networking: Switching multidroplet frames to improve signaling overhead

Microfluidic networking is an emerging research field for the numerous applications it allows in the field of biomedicine. Previous literature has shown that it is indeed possible to develop purely hydrodynamic microfluidic networks by using a droplet logic. However, while the design of switches and medium access control devices is possible, up to date communications have been proposed by exploiting only pairs of droplets – a header and a payload – thus leading to single droplet frames which cause an overhead of 50%; this makes current solutions scarcely applicable to real systems. In this paper we overcome this limitation by designing and validating a microfluidic switch which employs multidroplet frames, thus significantly improving the overhead and making networking applications feasible. Simulation results carried out with the OpenFOAM software assess the effectiveness of the solution and give an overview of the maximum achievable throughput. Moreover we find out upper and lower bounds for the design of the droplets distance in each frame in such a way to define the functioning regions for the switch device.

Optimisation of throughput of two‐way buffer‐aided relaying networks with wireless‐assisted links

The authors propose protocols to optimise throughput of a relay in relaying networks where two users communicate only through buffer-aided relay. Both the users randomly access finite size buffer of the relay. The protocols are developed on the basis of buffer state information (BSI) and channel state information (CSI). In their proposed scheme, half-duplex decode-and-forward (DF) concept is used for improving the spectral efficiency of two-way relaying networks. In this work, the authors derive maximum achievable relay throughput with fixed-rate transmission which is in the form of linear-fractional programming. For simplification, they transform the fractional programme into linear programme which is efficiently computed through the standard convex/linear numerical tool. The numerical results are performed with the assisted software such as CVX tool. They theoretically analyse the events to provide necessary performance endorsement. The BSI/CSI outperforms all the cases studied named as conventional relaying, BSI only, and CSI only.

On the Optimal Set of Channels to Sense in Cognitive Radio Networks

In the channel selection problem, a secondary user (SU) senses a subset of size $M$ out of $N$ existing channels, and then accesses up to $K$ sensed-free channels. Given $M$ , $N$ , $K$ , and some estimates on the rates of channels, and the sensing accuracy, the channel selection problem asks what set of channels SU should sense to maximize its throughput. The intuitive answer is the set of $K$ channels with the highest rewards, where the reward of a channel is defined as the expected number of bits that can be successfully transmitted on that channel. Surprisingly, the above-mentioned intuitive solution is not optimal when $M>K$ . In this letter, we study the case $M>K$ , and propose polynomial-time optimal solutions for special cases where $K=1$ or where $M$ or $N-M$ are small. We also derive an upper bound on the maximum achievable throughput, and propose a generic near-optimal heuristic algorithm.

Hybrid Energy Harvesting-Based Cooperative Spectrum Sensing and Access in Heterogeneous Cognitive Radio Networks

In order to design energy efficient and energy harvesting (EEH) cooperative spectrum sensing (EEH-CSS), four fundamental constraints must be considered: 1) collision constraint to protect primary users from the collision with secondary users (SUs); 2) energy-causality constraint which states that the energy harvested by a time instant must be greater than or equal to the consumed energy until that time instant; 3) energy half-duplex (EHD) constraint which prevents the batteries from charging and discharging at the same time; and 4) correlation constraint which limits the information about the primary channel (PC) state of next time slot can be extracted from the current PC state. In this regard, we consider a hybrid energy harvesting SU (EH-SU) model which can harvest energy from both renewable sources, e.g., solar and ambient radio frequency signals. A heterogeneous EEH-CSS scheme is first proposed to handle EH-SUs with nonidentical harvesting, sensing, and reporting characteristics by permitting them to sense and report at different sensing accuracy. Formulating the energy state evolution of EH-SUs with and without EHD constraint, we analyze the asymptotic activity behavior of a single EH-SU by deriving the theoretical upper bound for the chance of being active to sense and transmit. Thereafter, we develop a convex framework to find maximum achievable total throughput by optimizing the asymptotic active probability, sensing duration, and detection threshold of each SU subject to above constraints. Given a potential set of SUs, determining the optimal subset of cooperating EH-SUs is of the essence to achieve maximum achievable total throughput. Since EH-SU selection is inherently a combinatorial problem, a fast yet high performance solution is proposed based on SUs' energy harvesting, sensing, and reporting attributes. Finally, a myopic access procedure is developed to determine the active set of EH-SUs given the best subset of SUs.

Real-Time Control System for Improved Precision and Throughput in an Ultrafast Carbon Fiber Placement Robot Using a SoC FPGA Extended Processing Platform

We present an architecture for accelerating the processing and execution of control commands in an ultrafast fiber placement robot. The system consists of a robotic arm designed by Coriolis Composites whose purpose is to move along a surface, on which composite fibers are deposed, via an independently controlled head. In first system implementation, the control commands were sent via Profibus by a PLC, limiting the reaction time and thus the precision of the fiber placement and the maximum throughput. Therefore, a custom real-time solution was imperative in order to ameliorate the performance and to meet the stringent requirements of the target industry (avionics, aeronautical systems). The solution presented in this paper is based on the use of a SoC FPGA processing platform running a real-time operating system (FreeRTOS), which has enabled an improved comamnd retrieval mechanism. The system’s placement precision was improved by a factor of 20 (from 1 mm to 0.05 mm), while the maximum achievable throughput was 1 m/s, compared to the average 30 cm/s provided by the original solution, enabling fabricating more complex and larger pieces in a significant fraction of the time.