Small Packet Sizes Research Articles

Assessing the Impact of Media Stream Packet Size Adaptation on Wireless Multimedia Applications

Multimedia applications constitute greater percentage of traffic in wireless networks. Thus, require investigation of factors influencing effective delivering of media contents in the future, which will include not only conventional multimedia broadcast, but also video streaming to users on demand while meeting the expected quality requirements. In this article, analysis of effect of media packet size adaptation on quality performance of multimedia application is presented. Experiments were performed using standard test media sequences. The encoded media streams at different packet sizes were transmitted over wireless channel at different channel conditions. The quality performance of received media streams were measured using Peak to Signal Noise Ratio (PSNR) software tool to assess the impact of media packet adaptation on quality performance of multimedia applications. A comparative quality performance under same poor channel condition, shows that small media packet size of 256 bytes recorded the highest received quality performance of 22.52dB, compared to the quality performance of 21.87dB for 384 bytes, 21.37dB for 512 bytes, 20.68dB bytes for 640 bytes and 19.47dB for 768 byes, respectively. The findings show media packet size and channel conditions have significant impact on the quality performance of wireless multimedia applications.

Hybrid mmWave-Li-Fi 5G Architecture for Reconfigurable Variable Latency and Data Rate Communications

Despite modern vehicles having the necessary advanced driver assistance systems (ADAS) for autonomous operation, current implementations rely solely on sensor information from the surrounding environment or data from smart infrastructure. However, shortcomings in current implementations and standards around cost-effective variable latency and data rate have prevented widespread adoption of the technology to enable autonomous operation. This paper presents a proof-of-concept (PoC) reconfigurable design and performance of a hybrid high-ultra-high bands [i.e., millimetre-Wave (mmWave)-light fidelity (Li-Fi)] fifth generation (5G) architecture for autonomous vehicular communication applications. The hybrid multiple input multiple output (MIMO) system architecture design is mathematically modelled and presented. The reported prelim PoC validation focuses on the Li-Fi experiment and results. The proposed hybrid system’s effectiveness was evaluated using the open-source “Model-based Autonomous Traffic Simulation” (MOBATSim). The simulation results of a potential Li-Fi system and a PoC prototype are presented to demonstrate the role of the Li-Fi system in the proposed hybrid mmWave-Li-Fi 5G architecture. Three models of LED/lamp and two models of photodiode were simulated at three different vehicle speeds to ascertain the potential of the system. Promising results are reported at low speeds with received power values of up to -8.39 dBm and signal to noise ratios of up to 29.39 dB. Practical prototype simulations showed auspicious results including received power of -24.6 dBm to -34.12 dBm at the vehicle speeds of 10 MPH to 30 MPH respectively. The implemented PoC Li-Fi technology component has demonstrated the ability to transmit information with a theoretical output of 333 bits per second at 1.92 m, without the use of any high-power processors, components, and modulation techniques. The proposed system yields high data rates due to reconfigurable high bandwidth channels; many simultaneous multimedia mmWave-Li-Fi connections enabled due to spatial reuse with narrow beams; and easier mmWave-Li-Fi ultra-low latency support occasioned by smaller packet sizes. This holds a great promise for the hybrid 5G/6G mmWave-Li-Fi autonomous vehicular communication use case and/or applications.

Teletraffic analysis of energy-efficient intruder detection using hash function techniques in images for remote monitoring in Wireless Sensor Networks

Many surveilling applications that use Wireless Sensor Networks (WSNs) are based on image transmissions to monitor relevant events like intruder detection. However, the continuous transmission of such images promptly drains the energy supply of nodes due to the large size of packets compared to other WSN-based applications such as temperature, gas leakages, and humidity, where packets are relatively small.In this work, we propose two techniques to reduce the packet size in image transmission data for outdoor surveillance. These techniques are based on obtaining a hash function of the histograms of images in different formats to transmit small-sized packets containing relevant information about the surveilled environment. If an event is detected, the complete images are transmitted to perform an in-depth inspection of the region of interest. Additionally, we propose an ON/OFF scheme to reduce energy consumption further. A teletraffic analysis is provided to evaluate the efficiency of such schemes for different environments. The derived mathematical model allows finely tuning the system variables to achieve both performance goals, which are usually in contraposition to each other, namely, increasing system lifetime and high detection probability.

Takeaways from an experimental evaluation of eXpress Data Path (XDP) and Data Plane Development Kit (DPDK) under a Cloud Computing environment

The popularization of the Linux kernel at data center servers became a significant factor to consider when developing or deploying network applications. New “packet processing frameworks” emerged to ensure fast packet processing inside these servers that rely on the Linux kernel, XDP and DPDK being the two main ones. Alongside this, Cloud Computing environments dominated the data center scenario, bringing virtualization to the center of these servers. This research compares DPDK and XDP packet processors when subject to a cloud computing environment with I/O, CPU, and network load. We first describe an architecture that implements frameworks and emulates a cloud environment. We measure throughput and packet loss while varying the number of competing VMs, CPU usage by the frameworks, and packet size and present our results in the form of takeaways. Furthermore, we conclude that the virtual environment can impact the performance of both frameworks depending on the received packet size and the type of workload the cloud environment performs. A significant case to highlight is when the cloud environment performs network load, and the servers receive small-sized packets, creating both throughput degradation and increasing packet loss. We conclude our experiments by conducting statistical non-parametric hypothesis tests to enhance our conclusions and have a closer look at the results.

Short Frame Transmission at Very Low SNR by Associating CCSK Modulation With NB-Code

In this paper, we present a frame structure that can be viewed as a preamble for the detection and synchronization process (leading to low cost receiver) and as an encoded codeword carrying the transmitted message (leading to reliable transmission). This duality facilitates an ALOHA protocol avoiding preamble overhead. The frame structure, named Quasi-Cyclic Short Packet (QCSP), is based on the association of a Cyclic Code Shift Keying (CCSK) modulation and a non-binary error control code. The detection/correction algorithm of the QCSP system is presented, its performance is theoretically derived and discussed for different parameters. A QCSP frame can be transmitted and received correctly with an error probability of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbf {10^{-4}}$ </tex-math></inline-formula> , distanced by <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1.2</b> dB from Polyanskiy’s bound (an estimated Shannon’s limit for small packet size) at −11 dB of SNR for a payload of 360 bits. Compared to a classical preamble-based frame using a modern binary error control code, the size of a QCSP frame is reduced by 23%. Moreover, detecting a QCSP frame requires a lower complexity than detecting a longer classical preamble.

Design of an adaptive CRSN using OFDM

Cognitive Radio (CR) is a novel concept that enables wireless devices to detect and adapt to their surroundings in order to enhance communication quality. The cognitive radio sensor network (CRSN) has proved to be a cost-effective solution for the spectrum constraints in wireless sensor networks (WSN). Optimizing the optimum packet size is regarded to be an essential energy constrained issue to address the practical implementation of CRSN out of all the difficulties. Small packets generate data traffic in device-to-device communication, while big packets may cause data bit corruption, requiring retransmission at a greater frequency. This will not allow access from the secondary network to the main network, since it may cause further disturbance. To maximise the WSN's energy efficiency, the optimum packet size for CRSN should be maintained while keeping the same degree of interference as the primary licenced users. The purpose of this article is to examine formulations for small, medium, and large packet sizes in order to determine the optimum packet size for adaptive CRSN. To do so, CR requires a flexible physical layer capable of carrying out the necessary tasks. This article examines the performance of CR systems that use the Orthogonal Frequency Division Multiplexing technique, which is a possible transmission technology for CR. Interference and delays are minimised and the channels are ultimately utilised effectively through Scheduling MAC protocol. This article gives the design steps to adjust the network design to get the better performance. For achieving the greatest performance on the Cognitive Radio Sensor Network (CRSN). The Jellyfish Search Optimization algorithm and the hybrid Momentum Search Algorithm are hybridized and results are achieved. This makes it possible to calculate precise packet sizes. The suggested approach decision outperforms existing methods like the Group Sparse Optimization algorithm and the Throughput Maximization Algorithm. The MATLAB/SIMULINK Platform were used to get the results.

Designing Routing Table by Using Static Algorithm of Routing

Transfering information in computer networks is administered through many intermediary routing devices and this task is devided into small size packets. While transfering packets from the local network to the remote networks, Default gateway is the destination address. As a rule, each network to which the router contacts, needs a separate interface. This interface is used both linking local networks (LAN) and global networks (WAN). To a large extent, Lan is an Ethernet network. WAN-s are used when we want to link networks on a large territory. For an instance, connection to WAN can be used when we need Lan to be switched onto ISP network. To administer this process, certain devices called routers are actively used. Their chief functions are to determine the optimal route of package and sending packets to their destination. In order to find the best route for sending a packet, the router uses its own routing table. It checks the packet destination and besides, it takes into account as to by which interface packets should be sent to each well-known network. When the optimal route is discovered, the router incapsulates the packet and secures sending the packet to its destination.The material presented in our study is interesting as the existing route is often replaced by the shorter route during the estimation process for the spesific fragment of the given network, and every further estimetion process should be taken into account to obtain right final result. Yet, in reality we must heed the fact that not only little length of ditance determines the transfer of informatio fast. The example given presents a quite interesting case of solving the task (in terms of determining the short possible route), and it can be successfully applied in learning process in this direction.

Integrating the IEEE 1451 and IEC 61499 Standards with the Industrial Internet Reference Architecture.

Industrial Internet of Things focuses on the manufacturing process and connects with other associated concepts such as Industry 4.0, Cyber-Physical Systems, and Cyber-Physical Production Systems. Because of the complexity of those components, it is necessary to define reference architectures models to manage Industry 4.0 and the Industrial Internet of Things. The reference architecture models aim to solve the interoperability problem enabling the syntactical and semantic levels of interoperability. A reference architecture model provides a bottom/top view of an industrial process, from the physical transducers at the physical layer to the business layer. The physical layer provides access to a twin representation of a physical thing in the digital world, extending the functionalities in the manufacturing process. This paper studies the syntactic interoperability between the IEEE 1451 and IEC 61499 in an industrial environment. The IEEE 1451 family of standards has the essential characteristics to support the information exchange between smart transducers (sensors and actuators), building the digital elements and meeting the Industry 4.0 requirements. The IEC 61499 standard enables industrial control and automation. These two standards combined at the syntactic level solve an interoperability problem. The IEC 61499 also provides data to the framework layer, supplying all the parameters defined for the communication layer specified by a reference architecture model. This paper combines the IEEE 1451 with the IEC 61499, enabling data exchange in a reference architecture model proposed for Industry 4.0. Network performance at the communication level of a reference architecture model in a local network and an external network is evaluated for the proposed application. The IEEE 1451 standard implementation and adoption to acquire data and communicate it inside an industrial process allowed the IEC 61499 standard to control an industrial process. The IEEE 1451 standard is implemented in a MSP430 low power microcontroller. A Raspberry Pi running FORTE and 4diac in the USA and Portugal were used to test a local network in Portugal and an external network in USA. Data related to network performance was obtained with Wireshark and processed with MATLAB. Tests using the Message Queuing Transport Telemetry Transport and Hypertext Transport Protocols verified the performance of these protocols, supported by the IEEE 1451 and IEC 61499 standards, showing that communication inside an Industry 4.0 environment is possible. MQTT protocol is faster, has a small packet size, and consumes less bandwidth. The HTTP protocol uses more bandwidth but is more reliable for real-time communication, essential for Industry 4.0.

An Efficient Data Transmission in Cognitive Radio Networks Using Momentum Search Algorithm

Data Transmission plays an important role in the digital world. In here, We are using Cognitive Radio(CR) a concept on Wireless Sensor Networks(WSN) which is being used as an intelligent wireless Communication Technology having unique Capabilities of monitoring spectrum bands and detecting available channels to enable the usage of statically allocated spectrum Furthermore, by dynamically adjusting its operating parameters, it can utilize available channels and to attack the upcoming spectrum crunch issue. Cognitive Radios can be used to find unused licensed spectrum and it can be utilized by secondary users without causing any interference to licensed users. Existing technologies used in cognitive radio include energy sensing, spectrum databases, and spectrum sensing using pilot channels. In small networks, transmission of small packet size can be transmitted with high efficiency without delay, whereas transmission of large data packets can cause data corruption, data packet corruption and may require retransmission over higher frequency channels. To avoid this type of interference, users need higher efficiency and wider bandwidth for efficient transmission. Here we use the technique of momentum search algorithms working on the law of conservation of momentum and the law of conservation of kinetic energy. Data transferred using this method is always unaltered. The transmitted data is split into fixed-size 64-bit packets. And the channel selection will be changed accordingly for higher channel selection efficiency for lossless data transmission. The rules of the Momentum Search algorithm allow users to transmit larger data packets with higher efficiency with the same level of interference as the primary user (PU). This proposal shows how to achieve the highest level of data transmission performance using a cognitive wireless network based on a Momentum search algorithm.

A DNN-based estimate of the PRACH traffic load for massive IoT scenarios in 5G networks and beyond

The massive Internet of Things (IoT) scenario refers to a huge number of Machine Type Communications (MTC) characterized by sporadic transmissions of small-sized packets. In order to manage the uplink radio resource allocation in cellular networks, several access schemes have been proposed. These schemes are mainly based on a grant-based Random Access (RA) procedure and proper load-aware access controls, e.g., Access Class Barring (ACB) techniques, dynamic uplink radio resource allocation, and so on. The development of an efficient approach to estimate the traffic load is extremely important for the proper functioning of these access schemes. With the ever-increasing number of transmitting MTC devices, expected with Beyond 5G (B5G) and 6G networks, additional challenges to obtain a correct real-time traffic load estimation are posed. Deep learning techniques, in this context, offer learning ability and optimization capability to properly support this scenario. In this paper, we propose a current access attempts estimation, based on Deep Neural Network (DNN), which accepts as input only the information really available at the next generation Node B (gNB). The network was trained and tested with a dataset properly created and composed by more than 21 million points. The DNN-based traffic load estimation method is then compared with other benchmark schemes available in the literature, in terms of regression accuracy, both in a static analysis, which considers a stand-alone RA cycle, and through a long-term analysis with a time-varying offered load. The latter analysis was performed both by adopting a theoretical arrival process proposed by 3GPP, and by using traces of real traffic data.

Majority Decision Aggregation with Binarized Data in Wireless Sensor Networks

Wireless sensor networks (WSNs) are the cornerstone of the current Internet of Things era. They have limited resources and features, a smaller packet size than other types of networks, and dynamic multi-hop transmission. WSNs can monitor a particular area of interest and are used in many different applications. For example, during the COVID-19 pandemic, WSNs have been used to measure social distancing/contact tracing among people. However, the major challenge faced by WSN protocols is limited battery energy. Therefore, the whole WSN area is divided into odd clusters using k-means++ clustering to make a majority rule decision to reduce the amount of additional data sent to the base station (or sink) and achieve node energy-saving efficiency. This study proposes an energy-efficient binarized data aggregation (EEBDA) scheme, by which, through a threshold value, the collected sensing data are asserted with binary values. Subsequently, the corresponding cluster head (CH), according to the Hamming weight and the final majority decision, is calculated and sent to the base station (BS). The EEBDA is based on each cluster and divides the entire WSN area into four quadrants. All CHs construct a data-relay transmission link in the same quadrant; the binary value is transferred from the CHs to the sink. The EEBDA adopts a CH rotation scheme to aggregate the data based on the majority results in the cluster. The simulation results demonstrate that the EEBDA can reduce redundant data transmissions, average the energy consumption of nodes in the cluster, and obtain a better network lifetime when compared to the LEACH, LEACH-C, and DEEC algorithms.

Sequence Design and User Activity Detection for Uplink Grant-Free NOMA in mMTC Networks

Massive machine type communications (mMTC) is one of the three major scenarios in 5G wireless networks. mMTC is an uplink-dominant scenario that supports massive connectivity of small-size packets and sporadic traffic. To meet the requirement of mMTC, non-orthogonal multiple access (NOMA) with grant-free transmission is considered a promising technology because of its higher spectrum efficiency and lower signaling overhead. Request-and-grant-based scheduling process is eliminated in grant-free transmission and thus the base stations need to identify active users first before data detection. Previously, several user activity detection (UAD) algorithms were proposed and they can obtain good performance in flat-fading channels. However, the performance of these works degrades significantly in doubly selective fading channels. In this work, we propose an effective solution for uplink grant-free NOMA with a new user sequence scheme and a novel UAD algorithm suitable for practical channel scenarios. Simulation results validated that the proposed sequences can mitigate the inter-user interference at the base stations, and the proposed UAD algorithm can achieve better detection accuracy. Moreover, detailed complexity analysis showed that the proposed UAD algorithm has relatively low complexity and good scalability.

A New Contention-Based PUSCH Resource Allocation in 5G NR for mMTC Scenarios

This letter addresses the uplink radio resource allocation problem in a 5G massive Machine Type Communication (mMTC) scenario, where a large number of MTC devices generate small-sized packets. The current cellular networks are unsuitable for this scenario, due to the limited resources allocated to the Physical Random Access Channel (PRACH) and to the Physical Uplink Shared Channel (PUSCH). To overcome this issue, instead of improving the succeeded access attempts in the PRACH, as widely addressed in literature, we focus on the PUSCH. We present the innovative idea to exploit the unused PUSCH resources to serve also the MTC devices that have failed their access attempt, by assigning them a pool of resources, in a contention-based mode. The simulation results show that the proposed PUSCH Resource Reallocation Algorithm improves significantly any static and dynamic system performance in terms of number of succeeded communications, at the cost a negligible increment of energy consumption.

A novel design of energy efficient bidirectional passive optical green networks using reduced buffer with small packet size technique

AbstractEnergy saving and reduction in the emission of carbon dioxide, sulfur, etc. have become one of the prime focus for the deployment of next generation networks. Due to less power consuming, passive optical networks are the best promising solution for such networks. We have proposed different aggressive schemes to reduce the energy consumption viz. no buffer, with buffer, reduced buffer, and reduced buffer with small packet. We evaluated the performance of proposed schemes for downstream and upstream by exploring the relationship between power consumption, delay, and average traffic load. The “reduced buffer with small packet” scheme has shown a reduction of more than 35% of total leakage power at the central office with the compromise of delay in packets receiving.

A Grant-Free Method for Massive Machine-Type Communication With Backward Activity Level Estimation

Massive machine type communications (mMTC) is one of the three major scenarios of the fifth generation (5G) communication system, and raises new challenges for the development of new radio access technology. Unlike human type communications (HTC), mMTC is typically characterised by a massive number of devices, small-sized packets, low or no mobility, low energy consumption and sporadic transmission, which requires novel solutions. In this paper, we propose the 2-step random access with early data transmission (2-step-EDT) framework. To solve the optimization problem proposed in the framework, we introduce an algorithm, namely, Backward Sparsity Adaptive Matching Pursuit with Checking and Projecting (BSAMP-CP), which jointly conducts the sparsity level estimation, active device detection, channel estimation and data recovery in two phases. Specifically, in the first phase, BSAMP-CP conducts the sparsity level estimation in a backward manner exploiting the data length diversity information. In the second phase, BSAMP-CP jointly conducts activity detection, channel estimation and data recovery, taking the joint sparsity information of pilot and data symbols, the error checking information and the modulation constellation information into account. Furthermore, we provide a theoretical analysis on the convergence of the proposed BSAMP-CP in the noiseless case and the rationale for the improvement yielded by exploiting data length diversity. Simulation results demonstrate the superiority of the proposed solution in comparison to other existing methods.

Martensitic Steel Microstructure Effects on Cavitation Erosion

Abstract Cavitation and cavitation erosion are sometimes unavoidable phenomena in hydro machine operation. For example, operating hydro turbines as regulating power leads to situations in which the risk of cavitation is accepted to some extent. Cavitation-resistant materials are therefore required to reduce machine damage and maintenance. This study characterizes the microstructure of two martensitic stainless steels from Francis turbines. They were already studied for cavitation erosion resistance in a previous study, and this study reveals the reasons behind the other steel having a significantly better resistance, while they had similar chemical compositions. The electron backscatter diffraction (EBSD) method is effective in defining the martensitic microstructure, specifically the block, packet, and prior austenite grain level. In addition, the retained austenite is effectively detected with the method. A fine prior austenite grain size and small packet and block sizes were found to be among the defining factors in cavitation erosion resistance of these steels. In addition, the transformation of retained austenite to martensite was detected in the edge region where cavitation had taken place. This transformation further increases cavitation erosion resistance. The better resistance of Steel 1 against cavitation was attributed to these microstructural differences. According to these findings, the microstructure in Steel 1 would be highly beneficial in building cavitation erosion resistant hydro machines and would be of interest to manufacturers of martensitic stainless steel components.

Slotted Secondary Transmission With Adaptive Modulation and Coding Under Interweave Cognitive Radio

In this paper, we propose a discrete-time Markov model to characterize slotted secondary transmission process under interweave cognitive implementation. Stationary distribution is solved in closed form to evaluate SU-to-PU collision probability and SU successful transmission probability. Assuming that SU transmission adopts adaptive modulation and coding (AMC), we then carry out the queuing analysis in terms of throughput, queuing delay, and packet drop probability, based on a two-dimensional finite-state Markov chain for small-size packet transmission. The optimal length of secondary slot is solved by maximizing throughput subject to an SU-to-PU collision probability constraint. For large-size packet transmission, the probability mass function of extended delivery time for secondary packet transmission is also derived. Selected numerical results are presented to illustrate the mathematical formulas and to validate our research results.

Enhancement of Data Rate and Packet Size in Image Sensor Communications by Employing Constant Power 4-PAM

Image sensor communications (ISC) is a scheme to make the LED lamp replace access points or beacons in indoor environments. Its application has been limited, however, due to its low data rate and small packet size. To resolve these problems, we propose a new ISC scheme using 4-PAM modulation and a parallel packet structure. The constant power 4-PAM signal was designed to have constant optical power in each symbol to eliminate the flickering effect. The experiments show that a data rate more than 2.6 times higher than the existing on - off keying schemes was achieved. In addition, it is demonstrated that the packet length can reach more than several frames while it is limited to less than a frame using the existing schemes. The limiting factors of N-PAM levels and packet size are analyzed in this paper to further improvement. All these results are demonstrated through simulations and experiments.

Impact of Packet Size in Adaptive Cognitive Radio Sensor Network

A cognitive radio sensor network (CRSN) is a solution that enables sensor nodes to opportunistically access licensed radio channels. Data transmitted over a network are divided into packets. In machine‐to‐machine communication, which is a heterogeneous nature of wireless networks, small‐size packets are the common form of traffic. Due to the nature of CRSNs, small data packets will not allow a balance between optimal performance of the network and fulfilling the secondary network obligations towards the primary network in terms of interference. Either interference or channel’s underutilization would result from employing data packets of inadequate size. In this paper, the appropriate packet size for adaptive CRSN is investigated by examining the performances of small, medium, and large packet size. In contrast to the trends of exploiting small packets of sizes up to 128 bytes, this study demonstrates that medium‐size packets are more appropriate to yield the best performance in CRSNs. Simulation results show that packets of size 375 bytes outperform smaller and larger packets in many CRSN protocols. The induced delay that is partially caused by interference is decreased at the same time the channels are efficiently utilized.

Performance Analysis of a Novel Hybrid S-ALOHA/TDMA Protocol for Beta Distributed Massive MTC Access.

Simultaneous random access of massive machine type communications (MTC) devices are expected to cause congestion in the radio access network. Not only the performance of MTC, but the coexisting human to human (H2H) communications would also degrade dramatically without an appropriate medium access control (MAC) protocol. However, most existing solutions focus on the random access procedure without dealing with the sunsequent data transmission procedure. In this paper, we firstly derive a packet size threshold based on the capacity analysis of slotted ALOHA (S-ALOHA) and time division multiple access (TDMA) protocols. Then a novel hybrid S-ALOHA/TDMA MAC protocol (HSTMAC) is presented for massive MTC access, in which the resources are separated for beta distributed machine to machine (M2M) traffic with small size packets and high priority H2H traffic with large size packets. Considering access class barring (ACB) scheme as an overload control method, the system equilibrium under arbitrary retransmission limit is analyzed rigorously, which can provide insights on quality of service (QoS) guarantee. Finally, a dynamic pre-backoff (DPBO) algorithm is designed for load balance by adaptively scattering the highly synchronized M2M traffic over the transmission interval. Numerical and simulation results validate our analysis and show that the HSTMAC protocol is superior to pure S-ALOHA protocol and pure TDMA protocol. The proposed DPBO algorithm can achieve a higher success probability and resource utilization ratio with a much reduced average delay than that of uniform pre-backoff (UPBO) scheme.