Optimal Packet Size Research Articles

An Advanced Energy-Efficient Environmental Monitoring in Precision Agriculture Using LoRa-Based Wireless Sensor Networks.

Sensor networks, as a special subtype of wireless networks, consist of sets of wirelessly connected sensor nodes often placed in hard-to-reach environments. Therefore, it is expected that sensor nodes will not be powered from the power grid. Instead, sensor nodes have their own power sources, the replacement of which is often impractical and requires additional costs, so it is necessary to ensure minimum energy consumption. For that reason, the energy efficiency of wireless sensor networks used for monitoring environmental parameters is essential, especially in remote networking scenarios. In this paper, an overview of the latest research progress on wireless sensor networks based on LoRa was provided. Furthermore, analyses of energy consumption of sensor nodes used in agriculture to observe environmental parameters were conducted using the results of real measurements in the field, as well as simulations carried out based on collected data about real equipment. Optimization methods of energy consumption, in terms of choosing the appropriate data collection processes from the conducted field measurements, as well as the settings of network radio parameters imitating real conditions used in conducted simulations were highlighted. In the analyses, special emphasis was placed on choosing the optimal packet size. Unlike in other papers analyzing energy efficiency of LoRa communication, in this paper, it was proven that the adjustment of the transmission speed to the actual size of the packet is important for better energy efficiency of communication and that it can reduce energy consumption considerably. Moreover, in the paper, the contents of a packet that can be used in precision agriculture is suggested in order to prove that the 6-bit packet is sufficient for energy-efficient collection of parameters from the environment, in contrast to the 11-bit packets used in standard commercially available equipment.

Age and Energy Analysis for $L$th Best Relay Enabled Cooperative Status Update Systems With Short Packet Communications

In the Internet of Things monitoring systems, the fresh information delivery and efficient energy usage are two significant design concerns. However, they generally cannot be simultaneously achieved. In this paper, we investigate the fundamental tradeoff between the age of information (AoI) and energy consumption (EC) for a generalized <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula> th best relay selection policy in two-hop cooperative status update systems with automatic repeat request (ARQ), where the source delivers the sensed status update to the destination through multiple decode-and-forward relays. Among these relays, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula> th best relay (i.e., the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula> -th earliest one that correctly decodes the update packet) will be selected as a forwarder to relay the data to the sink. When a decoding failure occurs, we can either retransmit the old packet to save sensing EC or sense and transmit a new one to reduce AoI. Accordingly, the classical ARQ and truncated ARQ protocols are employed in the second hop. By considering short packet-based transmissions, the average AoI and average EC expressions are derived, and the weighted combination of them is minimized to attain the tradeoff. Numerical results demonstrate that an optimal packet size that can trade off age and energy always exists. Moreover, the best relay does not always minimize the weighted combination, and the truncated ARQ is superior to the classical one. As a promising candidate, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula> th best relay selection can be implemented when either the system energy resource is limited or the best relay is unavailable.

Multilayer Joint Optimization of Packet Size and Adaptive Transmission Scheduling of Wireless Sensor Networks for Mechanical Vibration Monitoring

Limitations pertaining to the storage capacity and bandwidth of wireless sensor networks (WSNs) for mechanical vibration monitoring (MVM) pose difficulties in the realization of reliable and energy-efficient communication of big data. To prolong the lifetime of battery-limited WSNs, this paper proposes a multi-layer joint optimization of packet size and adaptive transmission scheduling (ATS) to jointly optimize the energy consumption of acquisition nodes from the storage and transmission layers. First, owing to the frequent storage and transmission of massive mechanical vibration data in WSNs, the packet size significantly affects the energy consumption during storage and transmission. The proposed packet size optimization based on the lowest energy consumption (PSO-LEC) model optimizes the energy consumption of acquisition nodes from three aspects: writing, reading, and transmission of data. Second, when transmitting massive vibration data frequently, the direct beacon frame conflict and indirect beacon frame conflict markedly induce data conflict and delay problems. Therefore, adaptive transmission scheduling based on the time division multiple access (TDMA/ATS) method is proposed to optimize the errors in data collision and transmission delay. Thus, the packet size and ATS are considered jointly to improve the network lifetime for MVM. Comprehensive experimental results indicate that the transmission reliability and energy-efficiency of the proposed scheme are significantly improved, and the network life is effectively prolonged for MVM.

Sling‐shot spider optimization algorithm based packet length control in wireless sensor network and Internet of Things‐based networks

SummaryWireless sensor network (WSN) is a well‐developed domain suitable in the optimal collection and processing of information needed for the present world. For processing and transmitting the correct data by the network, it is affected by many disrupting factors like interference, battery life, distance between the nodes, and redundant data. There have been many methods proposed in the past. Among all the disrupting factors, routing has been the most studied problem in the WSN literature, whereas packet length sizing has been the most untouched topic compared to routing. Sizing the packet lengths to transmit it through the network is important to get error‐free data and run an energy‐efficient network. In this paper, we propose a sling‐shot spider optimization (S2SO) algorithm for packet length optimization in WSN and Internet of Things (IoT)‐based networks. The S2SO algorithm is developed based on the spider's unique behavior of catching prey. The proposed algorithm is implemented in three types of networks: 1‐hop, 2‐hop, and multi‐hop networks. A mathematical model for the communication channel, energy efficiency, and energy consumption is developed for all three types of networks. The proposed packet length optimization model is simulated in MATLAB software and compared with conventional bio‐inspired algorithms. The results show that the proposed algorithm is very fast in finding the optimal results and transmits optimal packet size with low error rate of 0.2 p.u. and a high efficiency of 98%.

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.

Efficient models for enhancing the link adaptation performance of LTE/LTE-A networks

Link adaptation (LA) is the ability to adapt the modulation scheme (MS) and the coding rate of the error correction in accordance with the quality of the radio link. The MS plays an important role in enhancing the performance of LTE/LTE-A, which is typically dependent on the received signal to noise ratio (SNR). However, using the SNR to select the proper MSs is not enough given that adaptive MSs are sensitive to error. Meanwhile, non-optimal MS selection may seriously impair the system performance and hence degrades LA. In LTE/ LTE-A, the LA system must be designed and optimized in accordance with the characteristics of the physical (e.g., MSs) and MAC layers (e.g., Packet loss) to enhance the channel efficiency and throughput. Accordingly, this study proposes using two LA models to overcome the problem. The first model, named the cross-layer link adaptation (CLLA) model, is based on the downward cross-layer approach. This model is designed to overcome the accuracy issue of adaptive modulation in existing systems and improve the channel efficiency and throughput. The second model, named the Markov decision process over the CLLA (MDP-CLLA) model, is designed to improve on the selection of modulation levels. Besides that, our previous contribution, namely the modified alpha-Shannon capacity formula, is adopted as part of the MDP-CLLA model to enhance the link adaptation of LTE/LTE-A. The effectiveness of the proposed models is evaluated in terms of throughput and packet loss for different packet sizes using the MATLAB and Simulink environments for the single input single output (SISO) mode for transmissions over Rayleigh fading channels. In addition, phase productivity, which is defined as the multiplication of the total throughput for a specific modulation with the difference between adjacent modulation SNR threshold values, is used to determine the best model for specific packet sizes in addition to determine the optimal packet size for specific packet sizes among models. Results generally showed that the throughput improved from 87.5 to 89.6% for (QPSK rightarrow 16-QAM) and from 0 to 43.3% for (16-QAM rightarrow 64-QAM) modulation transitions, respectively, using the CLLA model when compared with the existing system. Moreover, the throughput using the MDP-CLLA model was improved by 87.5–88.6% and by 0–43.2% for the (QPSK rightarrow 16-QAM)and (16-QAM rightarrow 64-QAM) modulation transitions, respectively, when compared with the CLLA model and the existing system. Results were also validated for each model via the summation of the phase productivity for every modulation at specific packet sizes, followed by the application one-way analysis of variance (ANOVA) statistical analysis with a post hoc test, to prove that the MDP-CLLA model improves with best high efficiency than the CLLA model and the existing system.

APSSR: Adaptive Packet Size Selection Based Routing Protocol for Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks offer very promising solutions to monitor the aqueous environments. Due to the distinctive characteristics of UASNs, it is very challenging to design a routing protocol that can achieve maximum data delivery ratio in the network. The main challenge is the communication medium (acoustic links) that is subject to temporary attenuation and high bit error rate (BER), which limits the throughput efficiency of the Network. Besides this, another major issue is the continuous movement of nodes due to water currents and the availability of limited resources. Due to nodes mobility distance among sensor nodes and consequently, BER varies, which have a direct impact on packet size, hence, leads to high packet loss and low data delivery ratio. To achieve a high data delivery ratio, the selection of optimal packet size is of utmost importance. Consequently, the selection of next-hop forwarding node based on optimal packet size is needed. Therefore, in this paper, we propose an adaptive routing protocol named Adaptive Packet Size Selection Based Routing (APSSR) Protocol for UASNs. APSSR determines the optimal packet size adaptively based on both varying distances between sensor nodes and BER and selects the next hop based on optimal packet size and BER. The simulation results show greater network performance in terms of Network Lifetime, Data Reception Ratio at Sink node, Average Network Delay, Packet Reception Ratio, and Packets Drop Ratio

Adaptive Packet-size Control for Improved Throughput in Dynamic Access Networks

Cognitive radio (CR) is a new intelligent wireless technology that aims at improving spectrum utilization by allowing opportunistic access to the underutilized licensed spectrum. Wireless CR operating environment is typically characterized by its unreliable and unpredictable channel conditions and time availability due to fading and the randomness of primary radio (PR) activities. In such environment, packet fragmentation is needed to enhance the probability of success/packet delivery and reduce the needed number of packet re-transmission attempts. Specifically, the quality and availability of the PR channels along with the data packet size should be considered when designing communication protocols for CR networks (CRNs) such that the packet success probability is improved. Based on the quality and availability of the PR channels, an optimal-packet size metric is derived, which is defined as the packet size that can be transmitted over a selected channel while guarantying a predefined probability of success. In this paper, we propose three fragmentation-based channel assignment algorithms: fixed-fragment size algorithm, first-fit algorithm and near-exact fit algorithm. The first algorithm divides the packet equally over the selected channels while the other algorithms use variable fragment size. The main objectives of the algorithms are to enhance network throughput, decrease the number of dropped packets and reduce the average number of retransmission attempts. This preserves more channels for potential future CR transmissions, resulting in higher network throughput with less energy consumption. Simulation results show that the proposed algorithms significantly outperform existing CRN channel assignment algorithms with no fragmentation.

Achieving reliable UDP transmission at 10 Gb/s using BSD socket for data acquisition systems

User Datagram Protocol (UDP) is a commonly used protocol for data transmission in small embedded systems. UDP as such is unreliable and packet losses can occur. The achievable data rates can suffer if optimal packet sizes are not used. The alternative, Transmission Control Protocol (TCP) guarantees the ordered delivery of data and automatically adjusts transmission to match the capability of the transmission link. Nevertheless UDP is often favored over TCP due to its simplicity, small memory and instruction footprints. Both UDP and TCP are implemented in all larger operating systems and commercial embedded frameworks. In addition UDP also supported on a variety of small hardware platforms such as Digital Signal Processors (DSP) Field Programmable Gate Arrays (FPGA). This is not so common for TCP. This paper describes how high speed UDP based data transmission with very low packet error ratios was achieved. The near-reliable communications link is used in a data acquisition (DAQ) system for the next generation of extremely intense neutron source, European Spallation Source. This paper presents measurements of UDP performance and reliability as achieved by employing several optimizations. The measurements were performed on Xeon E5 based CentOS (Linux) servers. The measured data rates are very close to the 10 Gb/s line rate, and zero packet loss was achieved. The performance was obtained utilizing a single processor core as transmitter and a single core as receiver. The results show that support for transmitting large data packets is a key parameter for good performance. Optimizations for throughput are: MTU, packet sizes, tuning Linux kernel parameters, thread affinity, core locality and efficient timers.

AI for dynamic packet size optimization of batteryless IoT nodes: a case study for wireless body area sensor networks

Packet size optimization, with the purpose of minimizing the wireless packet transmission energy consumption, is crucial for the energy efficiency of the Internet of Things nodes. Meanwhile, energy scavenging from ambient energy sources has gained a significant attraction to avoid battery issues as the number of nodes increasingly grows. Packet size optimization algorithms have so far been proposed for battery-powered networks that have limited total energy with continuous power availability to prolong their lifetime. On the other hand, batteryless networks based on energy harvesting offer unlimited total energy with the interruption in availability. This is due to changing ambient conditions or the required time for harvesting and storing in small capacitors. Packet size optimization of batteryless networks has not been addressed so far. In this paper, an AI-based packet size optimization algorithm is proposed for batteryless networks that consider the amount of harvested energy at each node. Therefore, packet size is optimized dynamically for each round of data transmission. The proposed method is then evaluated via numerical simulations for a heterogenous wireless body area sensor network as a case study, considering 1-hop, cooperative, and 2-hop communication networks. Cooperative topology yields optimum energy efficiency for highly dynamic sensors, such as ECG, while 2-hop has shown to be optimum for the same type of sensors in battery-powered networks. Also, for sensors with slower dynamics such as body temperature, 1-hop turns out to be optimum in networks solely dependent on energy scavenging while cooperative topology is optimum for battery-powered networks. The algorithm applies to any heterogeneous fully batteryless networks to dynamically optimize packet size at each transmission instance.

Energy Efficient and Optimal Packet Size based Routing for WSN Using Hybrid K-means and Ant Lion Optimization

Energy Efficient and Optimal Packet Size based Routing for WSN Using Hybrid K-means and Ant Lion Optimization

Comparative Analysis of Transmission Power Level and Packet Size Optimization Strategies for WSNs

Wireless sensor networks (WSNs) are envisioned to be a widely utilized technology in a smart grid (SG). Maximizing the network lifetime (NL) of WSNs in SG deployments is necessary to provide reliability and efficiency of the services offered to the entities involved. Harsh channel conditions in SG environments have a profound impact on the communication channel utilized by WSNs. Therefore, optimizing the transmission power level (TPL) and data packet size (DPS) is of paramount importance for prolonging the WSN NL. In both TPL and DPS optimizations, two general approaches are followed: utilizing a constant TPL and/or DPS or optimizing TPL and/or DPS for each link. However, the joint optimization of the TPL and DPS for each link has not been investigated in the literature. In this study, we present a mixed-integer programming framework, which utilizes a detailed link-layer abstraction to analyze nine TPL and DPS assignment strategies for WSNs employed in SG environments. The results of our analysis reveal that there is a large margin to be exploited in prolonging the WSN NL by an appropriate selection of the strategy to be used in TPL and DPS optimization.

Improving Throughput of Communication Link in IEEE 802.15.4 Based Energy-Harvesting Wireless Sensor Network

It is critical to design a reliable packet transmission scheme to improve throughput in Energy harvesting Wireless sensor network (EH-WSN) or Battery free Wireless sensor network (BF-WSN). We present the Optimal size and rate (OSR) scheme to improve throughput of communication links in the IEEE 802.15.4 based BF-WSN that harvests radio frequency energy. Based on the de.ned truncated geometrical distribution, we formulate the optimization problem that maximizes the e.ective throughput of communication link. The solution of the optimization problem yields the optimal triple, namely the optimal packet size, data rate, and Maximum number of transmission trials (MNTT), which is used in the OSR so that throughput is considerably improved. Simulation results show the OSR scheme can improve throughput.

Optimal Packet Size Analysis for Network Coding-Enabled Two-Hop Error-Prone Wireless Networks

Network coding has received great attention for its ability to dramatically improve the performance of wireless networks. However, there still is a lack of research on how and to which degree the packet size affects the performance of a wireless network with network coding. In this letter, we study the issue of optimal packet size for inter-flow network coding enabled two-hop error-prone wireless networks with the IEEE 802.11. We analyze the network throughput of such networks and then derive the optimal packet size for maximizing the network throughput under various cases. The simulation results validate the accuracy of our analytical results.

Packet Size Optimization for Lifetime Maximization in Underwater Acoustic Sensor Networks

Recently, underwater acoustic sensor networks (UASNs) have been proposed to explore underwater environments for scientific, commercial, and military purposes. However, long propagation delays, high transmission losses, packet drops, and limited bandwidth in underwater propagation environments make realization of reliable and energy-efficient communication a challenging task for UASNs. To prolong the lifetime of battery-limited UASNs, two critical factors (i.e., packet size and transmission power) play vital roles. At one hand, larger packets are vulnerable to packet errors, while smaller packets are more resilient to such errors. In general, using smaller packets to avoid bit errors might be a good option. However, when small packets are used, more frames should be transmitted due to the packet fragmentation, and hence, network overhead and energy consumption increases. On the other hand, increasing transmission power reduces frame errors, but this would result in unnecessary energy consumption in the network. To this end, the packet size and transmission power should be jointly considered to improve the network lifetime. In this study, an optimization framework via an integer linear programming (ILP) has been proposed to maximize the network lifetime by joint optimization of the transmission power and packet size. In addition, a realistic link-layer energy consumption model is designed by employing the physical layer characteristics of UASNs. Extensive numerical analysis through the optimization model has been also performed to investigate the tradeoffs caused by the transmission power and packet size quantitatively.

ParStream-seq: An improved method of handling next generation sequence data

The exponential growth of next generation sequencing (NGS) data has put forward the challenge for its storage as well as its efficient and faster analysis. Storing the entire amount of data for a particular experiment and its alignment to the reference genome is an essential step for any quantitative analysis of NGS data. Here, we introduce streaming access technique ‘ParStream-seq’ that splits the bulk sequence data, accessed from a remote repository into short manageable packets followed by executing their alignment process in parallel in each of the compute core. The optimal packet size with fixed number of reads is determined in the stream that maximizes system utilization. Result shows a reduction in the execution time and improvement in the memory footprint. Overall, this streaming access technique provides means to overcome the hurdle of storing the entire volume of sequence data corresponding to a particular experiment, prior to its analysis.

Packet Size Optimization Techniques and Challenges for Wireless Body Area Networks

Packet Size Optimization Techniques and Challenges for Wireless Body Area Networks

Packet Size Optimization for Energy Efficiency in Multipath Fading for Wireless Body Area Network

Recently, Wireless Body Area Network (WBAN) has drawn vast interest to many researchers due to its potential in healthcare and medical fields. In this paper, we propose the energy efficiency model of Time Diversity communication in Rician and Rayleigh fading channels emphasizing the optimal packet size. The optimal packet size to maximize energy efficiency is investigated for on-body and in-body channels. Four modulation techniques are considered including the recently proposed 16-ary Quadrature Amplitude Position Modulation (QAPM). In addition, the closed-form expression of the energy efficiency model in multipath fading is derived. Here, three evaluation metrics including the energy efficiency, the normalized throughput and the average end-to-end delay are adopted and compared to the existing 1-hop and Cooperative communications as well as our previously proposed 2-hop communication. The results show that our proposed Time Diversity communication scheme outperforms the existing ones in deep fading channel except for the average end-to-end delay.

A survey on packet size optimization for terrestrial, underwater, underground, and body area sensor networks

SummaryPacket size optimization is a critical issue in wireless sensor networks (WSNs) for improving many performance metrics (eg, network lifetime, delay, throughput, and reliability). In WSNs, longer packets may experience higher loss rates due to harsh channel conditions. On the other hand, shorter packets may suffer from greater overhead. Hence, the optimal packet size must be chosen to enhance various performance metrics of WSNs. To this end, many approaches have been proposed to determine the optimum packet size in WSNs. In the literature, packet size optimization studies focus on a specific application or deployment environment. However, there is no comprehensive and recent survey paper that categorizes these different approaches. To address this need, in this paper, recent studies and techniques on data packet size optimization for terrestrial WSNs, underwater WSNs, wireless underground sensor networks, and body area sensor networks are reviewed to motivate the research community to further investigate this promising research area. The main objective of this paper is to provide a better understanding of different packet size optimization approaches used in different types of sensor networks and applications as well as introduce open research issues and challenges in this area.

Towards Efficient Wireless Body Area Network Using Two-Way Relay Cooperation.

The fabrication of lightweight, ultra-thin, low power and intelligent body-borne sensors leads to novel advances in wireless body area networks (WBANs). Depending on the placement of the nodes, it is characterized as in/on body WBAN; thus, the channel is largely affected by body posture, clothing, muscle movement, body temperature and climatic conditions. The energy resources are limited and it is not feasible to replace the sensor’s battery frequently. In order to keep the sensor in working condition, the channel resources should be reserved. The lifetime of the sensor is very crucial and it highly depends on transmission among sensor nodes and energy consumption. The reliability and energy efficiency in WBAN applications play a vital role. In this paper, the analytical expressions for energy efficiency (EE) and packet error rate (PER) are formulated for two-way relay cooperative communication. The results depict better reliability and efficiency compared to direct and one-way relay communication. The effective performance range of direct vs. cooperative communication is separated by a threshold distance. Based on EE calculations, an optimal packet size is observed that provides maximum efficiency over a certain link length. A smart and energy efficient system is articulated that utilizes all three communication modes, namely direct, one-way relay and two-way relay, as the direct link performs better for a certain range, but the cooperative communication gives better results for increased distance in terms of EE. The efficacy of the proposed hybrid scheme is also demonstrated over a practical quasi-static channel. Furthermore, link length extension and diversity is achieved by joint network-channel (JNC) coding the cooperative link.