Transmission Rounds Research Articles

Reliability and security performances analysis of rate splitting based VLC system with HARQ

This work first attempts to investigate the reliability and physical layer security (PLS) performances of a rate splitting (RS) based visible light communication (VLC) system with one trusted user and one untrusted user. Specifically, the hybrid automatic repeat request (HARQ) protocol is adopted at the trusted user and the movement of users is assumed to be subject to the random way point (RWP) model with four decoding strategies considered at receiver side. The exact closed-form expressions of outage probability (OP) for both users are then obtained, and the analytical expressions of secrecy outage probability (SOP), reliable and secure transmission probability (RSP), and effective secrecy throughput (EST) of trusted user are also mathematically derived. Through simulations, it is found that to guarantee the reliability and PLS performances, the trusted user should first decode the untrusted user's private stream and the untrusted user should first decode the trusted user's private stream. Besides, the reliability and PLS performances of RS-VLC system could be enhanced with the appropriate increase in the maximum transmission round of HARQ with the best decoding strategy. Moreover, they could be further enhanced by the proper common stream power allocation coefficient. This work will benefit the research and development of indoor VLC system.

Optimized Energy Efficient- Hierarchical Clustering Based Routing (OEE-HCR) For Wireless Sensor Network (WSN)

The study into Wireless Sensor Network (WSN) has grown more crucial as a result of the many Internet of Things (IoT) applications. Energy – Harvesting (EH) technology can extend the lifespan of WSN; however, because the nodes would be difficult to get to during energy harvesting, an energy-efficient routing protocol should be developed. The use of clustering in this study balances energy consumption across all Sensor Node (SN) and reduces traffic and overhead throughout the data transmission phases of WSN. Cluster Head (CH) selection step of the Optimized Energy Efficient-Hierarchical Clustering Based Routing (OEE-HCR) technique involves sending data to the closest CH. In order to analyse and transmit each cluster data, CH will need to use more energy, which will hasten and asymmetrically deplete the network. Whale Optimization Algorithm (WOA) algorithm is introduced for the best number of clusters formation with dynamically selecting the CH. Experimentation analysis, results are measured using First Node Dead (FND), the Half Node Dead (HND), Last Node Dead (LND), and Maximum Lifetime Coverage (MLC) at the time of number of data transmission rounds performed in routing algorithms.

Communication Efficient Distributed Newton Method over Unreliable Networks

Distributed optimization in resource constrained devices demands both communication efficiency and fast convergence rates. Newton-type methods are getting preferable due to their superior convergence rates compared to the first-order methods. In this paper, we study a new problem in regard to the second-order distributed optimization over unreliable networks. The working devices are power-limited or operate in unfavorable wireless channels, experiencing packet losses during their uplink transmission to the server. Our scenario is very common in real-world and leads to instability of classical distributed optimization methods especially the second-order methods because of their sensitivity to the imprecision of local Hessian matrices. To achieve robustness to high packet loss, communication efficiency and fast convergence rates, we propose a novel distributed second-order method, called RED-New (Packet loss Resilient Distributed Approximate Newton). Each iteration of RED-New comprises two rounds of light-weight and lossy transmissions, in which the server aggregates the local information with a new developed scaling strategy. We prove the linear-quadratic convergence rate of RED-New. Experimental results demonstrate its advantage over first-order and second-order baselines, and its tolerance to packet loss rate ranging from 5% to 40%.

Four-party quantum secure direct communication based on hyperentangled bell states

Quantum Secure Direct Communication (QSDC) is a promising approach for secure information exchange. This paper proposes an efficient and secure four-party QSDC scheme utilizing hyperentangled Bell states in the polarization degree of freedom, the first longitudinal momentum degree of freedom and the second longitudinal momentum degree of freedom. The four participants can perform different unitary operations to independently encode their secret messages onto photons in three degrees of freedom, subsequently transmitting them directly through the quantum channel. In this proposed protocol, each degree of freedom of the photon can effectively carry two bits of information. Each round of transmission by a photon enables the four legitimate participants to obtain six classical bits of information. Notably, when compared to other photons based single-degree-of-freedom QSDC network protocols, the capacity of proposed QSDC protocol is tripled. Therefore, it significantly enhances the information transmission capability. Furthermore, comprehensive security analysis shows that our QSDC network protocol can withstand various attacks from external eavesdroppers.

Data aggregation algorithm for wireless sensor networks with different initial energy of nodes.

Data aggregation plays a critical role in sensor networks for efficient data collection. However, the assumption of uniform initial energy levels among sensors in existing algorithms is unrealistic in practical production applications. This discrepancy in initial energy levels significantly impacts data aggregation in sensor networks. To address this issue, we propose Data Aggregation with Different Initial Energy (DADIE), a novel algorithm that aims to enhance energy-saving, privacy-preserving efficiency, and reduce node death rates in sensor networks with varying initial energy nodes. DADIE considers the transmission distance between nodes and their initial energy levels when forming the network topology, while also limiting the number of child nodes. Furthermore, DADIE reconstructs the aggregation tree before each round of data transmission. This allows nodes closer to the receiving end with higher initial energy to undertake more data aggregation and transmission tasks while limiting energy consumption. As a result, DADIE effectively reduces the node death rate and improves the efficiency of data transmission throughout the network. To enhance network security, DADIE establishes secure transmission channels between transmission nodes prior to data transmission, and it employs slice-and-mix technology within the network. Our experimental simulations demonstrate that the proposed DADIE algorithm effectively resolves the data aggregation challenges in sensor networks with varying initial energy nodes. It achieves 5-20% lower communication overhead and energy consumption, 10-20% higher security, and 10-30% lower node mortality than existing algorithms.

Multi-round transmission and contention protocol in WLANs with multi-packet reception

Nowadays, there are many scenarios in Wi-Fi networks where many devices compete for network access via an Access Point to transmit their information. Thus, the ability to separate multiple packets sent simultaneously using advanced digital processing techniques in the physical layer, known as Multi-Packet Reception (MPR), has become crucial. As this feature may increase network throughput, medium access control (MAC) protocols that efficiently exploit the MPR capability have been investigated. This paper proposes a new MAC protocol that exploits the MPR capability in 802.11 RTS/CTS access mechanism networks. It is based on the use of multiple contention and transmission rounds. In this sense, the MPR MAC protocol schedules several transmission periods once the contention phase finishes. Multiple transmission rounds reduce the overhead and substantially increase throughput. The analytical expressions that support the proposed approach are derived and verified by simulation. The results show that the proposed MAC protocol can yield close to 94% of the ideal performance using only four transmission rounds, compared with 80% of the previous approaches in the literature.

WHOOPH: whale optimization-based optimal placement of hub node within a WBAN

Biosensor nodes of a wireless body area network (WBAN) transmit physiological parameter data to a central hub node, spending a substantial portion of their energy. Therefore, it is crucial to determine an optimal location for hub placement to minimize node energy consumption in data transmission. Existing methods determine the optimal hub location by sequentially placing the hub at multiple random locations within the WBAN. Performance measures like link reliability or overall node energy consumption in data transmission are estimated for each hub location. The best-performing location is finally selected for hub placement. Such methods are time-consuming. Moreover, the involvement of other nodes in the process of hub placement results in an undesirable loss of network energy. This paper shows the whale optimization algorithm (WOA)-based hub placement scheme. This scheme directly gives the best location for the hub in the least amount of time and with the least amount of help from other nodes. The presented scheme incorporates a population of candidate solutions called "whale search agents". These agents carry out the iterative steps of encircling the prey (identifying the best candidate solution), bubble-net feeding (exploitation phase), and random prey search (exploration phase). The WOA-based model eventually converges into an optimized solution that determines the optimal location for hub placement. The resultant hub location minimizes the overall amount of energy consumed by the WBAN nodes for data transmission, which ultimately results in an elongated lifespan of WBAN operation. The results show that the proposed WOA-based hub placement scheme outperforms various state-of-the-art related WBAN protocols by achieving a network lifetime of 8937 data transmission rounds with 93.8% network throughput and 9.74 ms network latency.

Average age upon decisions with truncated HARQ and optimization in the finite blocklength regime

We consider an update-and-decide IoT-based wireless network, where information packets generated from dual sources are co-stored in the transmitter’s buffer, while decisions are made at the destination. Two practical assumptions about the communications between the transmitter and destination are taken into account: the communications are operating with finite blocklength (FBL) codes, and truncated hybrid automatic repeat request (HARQ) schemes are exploited to improve the FBL reliability, i.e., the number of allowed rounds of (re)transmissions is finite. For the first time, this paper characterizes the timeliness of status updates, namely age upon decisions (AuD) (which highlights the timeliness of the information at decisions in comparison to the concept of age of information), for such truncated HARQ-assisted wireless network. First, we characterize the inter-arrival time between two adjacent successfully transmitted packets, while taking into consideration the preemption policy and the randomness of the number of preempted packets from the same source. In particular, the probability density function, statistical performance of such inter-arrival time are derived. Following these characterizations, we propose a new approach to determine the average AuD and obtain a closed-form expression accordingly. Subsequently, a joint blocklength and arrival rate optimization problem is considered to minimize the obtained average AuD. Before addressing the formulated problem, we prove the convexity of decoding error probability in CC-HARQ and IR-HARQ with respect to blocklength. Then, we prove the convexity of average AuD with respect to blocklength and arrival rate, respectively. By an efficient alternating algorithm, we obtain a efficient solution. Via simulations, we evaluate the performance and conclude a set of guidelines for designs on the considered network.

Optimization of wireless sensor networks energy consumption by the clustering method based on the firefly algorithm

Wireless sensor networks (WSNs) contain an inordinate number of sensor nodes that are spatially distributed. The network is composed of entities that determine its lifetime. The WSN nodes are equipped with a battery whose autonomy is limited in duration. In this paper, different solutions are introduced to improve the overall energy consumption of the network in order to improve its lifetime. Contrary to many works considering the clustering algorithm as one potential candidate to improve the network's lifetime, this study has investigated the firefly algorithm optimization where an optimal cluster head is selected from a group of nodes. The set-up process of the cluster head is based on a set of conditions. To measure the performance of the proposed approach, the number of dead nodes and data packets received by the base station (BS) or sink node are considered. The results are tested on 100 nodes for 5000 transmission rounds, the amount of data transported is 20 million bits a little more than the other methods. It has been shown that the proposed solution outperformed the traditional low energy adaptive clustering hierarchy (LEACH), threshold sensitive energy efficient sensor network (TEEN), and developed distributed energy-efficient clustering (DEEC) approaches.

Lower and upper bounds for deterministic convergecast with labeling schemes

In wireless networks, broadcast and convergecast are the two most used communication primitives. Broadcast instructs a specific sink (or root) node to send a message to each node in the network. Convergecast instructs each node in the network to send a message to the sink. Due to the collision, without labels, deterministic convergecast is impossible even in a three-node network. Therefore, networking solutions for convergecast are based on probabilistic approaches or use underlying probabilistic medium access protocols such as CSMA/CA or CSMA/CD.In this paper, we focus on deterministic convergecast algorithms enhanced with labeling schemes for wireless networks in collision-presence environment. We investigate two communication modes: half-duplex (nodes either transmit or receive but not both at the same time) and full-duplex (nodes can transmit and receive data at the same time). For these two modes we investigate lower and upper bounds for the time and size of labeling. Even though broadcast and convergecast are similar, we prove that, contrary to broadcast, deterministic convergecast cannot be solved with short labels for some topologies. That is, Ω(log⁡(Δ)) bits are necessary to solve deterministically convergecast where Δ is the maximal degree of a node in the network. We also prove that Ω(n) communication time slots are required, where n is the size of network. We provide solutions that are optimal in terms of time (transmission rounds), and by far, the closest to the lower bound in terms of space (message size) for arbitrary scenarios.

Latency Optimization for Luby Transform Coded Computation in Wireless Networks

Luby transform (LT) code has attracted a significant attention due to its rateless property and low decoding complexity in distributed computing networks. However, for wireless networks, the frequent interaction in LT coded computation can give rise to the latency bottleneck considering the communication overhead of interaction. In this letter, we study a novel LT coded computation scheme for heterogeneous wireless networks. Considering nodes with the disparate computation and transmission capabilities, we propose a block-design based wireless LT coded computation (BD-WLTCC) scheme to balance both computation and transmission latency. First, we pre-allocate the maximum transmission rounds due to the limited bandwidth of wireless channel. Then, we design the sub-block size for each node by formulating a nonconvex optimization problem to avoid the frequent interaction. Finally, the sub-optimal sub-block size is obtained by solving the relaxed problem iteratively. And the optimized results provably reveal the generalization of existing works. Simulation results show the superiority of our scheme.

Network Lifetime Optimization in Multi-hop Industrial Cognitive Radio Sensor Networks

Industrial cognitive radio sensor networks (ICRSNs) extend channel resources by occupying the vacant licensed channels in the absence of licensed users. In ICRSNs, industrial devices should switch to a common available channel to set up a communication link. However, channel switching leads to severe energy consumption. As the energy resources of battery-powered industrial devices are limited, it is crucial to carefully allocate channels to prolong the network lifetime of multi-hop ICRSNs. This paper is the first work that studies the channel allocation problem to optimize the network lifetime by considering the channel-switching (CS) energy consumption and the time-critical requirements of industrial applications. The problem is formulated to maximize the minimum residual energy at each round of data transmission, which is linearized as integer linear programming. As the channel allocation results will affect the residual energy at subsequent rounds, we propose a switching distance-optimized channel allocation (SDOCA) scheme that shortens the CS distances to improve the residual energy of each device. Moreover, we analyze the characteristics of SDOCA, i.e., convergent CS distance and guaranteed end-to-end delay. Extensive simulation results show that SDOCA can adaptively allocate channels according to the end-to-end delay requirement and significantly prolong the network lifetime.

An FED-Based Cluster Head Selection and Power Control Scheme for Massive MTC Networks

In cluster based massive machine type communications (MTC) networks, cluster heads (CHs) consume more energy than cluster members (CMs) to forward all data in the cluster. Therefore, inappropriate CHs will certainly aggravate the unevenness of the network energy distribution, intensively shortening the network lifetime. A well designed CH selection and subsequent power control scheme has been demonstrated to be effective in coping with this challenge. Different from the existing schemes in which the network status information of only a single round was considered to select CHs, in this article, all transmission rounds before the first death of MTC devices are taken into account to determine a CH index table. Specifically, considering that the first energy drain (FED) lifetime is a key indicator for the network to capture complete information, an FED-based CH selection scheme is proposed to optimize network lifetime, where the CH index table is obtained to predetermine the index of the CH in every round. Then, a power control scheme is also proposed to further extend the network lifetime with the constraint of transmission time. Finally, extensive simulations verify the superiority of the proposed scheme in terms of FED lifetime and successfully delivered packets in the absence and presence of the cochannel interference.

Average Operation Time of Bundle Protocol in Delay/Disruption-Tolerant Networks

Performance analysis of the Bundle Protocol (BP) in Delay/ disruption-Tolerant Networks (DTN) has gained much interest. The analytic work of the average operation time (AOT) in BP, for different channel conditions and system parameters, though critical to understanding performance and designing system, is still incomplete. Existing results, such as the average file delivery time (AFDT), provide reasonably close estimates in some cases but exhibit large discrepancies in other cases. In this paper, we provide a holistic probabilistic analysis of the BP process, particularly in the number of error bundles and the position of the last error bundle in each and the last rounds of transmission. We provide, for the first time, an exact solution for the AOT of the BP process. The derivation works for both symmetric and asymmetric channels and is in general for any given maximum number of transmissions rounds. When the unlimited number of transmission rounds is considered, AOT becomes AFDT. The results are further utilized to select the optimal bundle size that gives the minimum file delivery time. Validation via simulations and comparison with existing work are also provided.

Performance Analysis of Wireless Sensor Network by Variation in Cluster Head Selection through mLEACH-CS Algorithm

Abstract: The energy depletion at the nodes due to large volume of data transmission and data reception for large scale Wireless Sensor Networks (WSN) is one of the important areas of concern. Unbalanced energy consumption due to data traffic overhead at the nodes near the base station (BS) results in early node death and reduction in network lifetime. To balance the load at the wireless nodes during clustering, a novel hybrid clustering and routing protocol has been proposed based on mLEACH (modified Low-Energy Adaptive Clustering Hierarchy) and Cuckoo Search (CS) algorithm. Initially, mLEACH protocol is utilized to solve a novel equation designed to select the cluster heads by rotation at every round of data transmission based on the maximum permissible cluster heads in the network. In the second phase, CS algorithm is implemented for uniform distribution of the cluster heads in the network for efficient multi-hop data routing in the network based on several weighted factors. The performance of the proposed algorithm is compared with other algorithms in literature in terms of energy consumption and network lifetime for different positions of the base station and varied number of cluster heads in the model application area. The proposed mLEACH-CS algorithm shows a significant improvement by 60% considering 300 nodes in the WSN architecture while it decreased to 40% for denser network architecture. Optimal choice of the number and position of the cluster heads in certain network architecture has proved beneficial for designing an energy efficient wireless network with improved network lifetime.

Energy and Distance Based Multi-Objective Red Fox Optimization Algorithm in Wireless Sensor Network.

In modern trends, wireless sensor networks (WSNs) are interesting, and distributed in the environment to evaluate received data. The sensor nodes have a higher capacity to sense and transmit the information. A WSN contains low-cost, low-power, multi-function sensor nodes, with limited computational capabilities, used for observing environmental constraints. In previous research, many energy-efficient routing methods were suggested to improve the time of the network by minimizing energy consumption; sometimes, the sensor nodes run out of power quickly. The majority of recent articles present various methods aimed at reducing energy usage in sensor networks. In this paper, an energy-efficient clustering/routing technique, called the energy and distance based multi-objective red fox optimization algorithm (ED-MORFO), was proposed to reduce energy consumption. In each communication round of transmission, this technique selects the cluster head (CH) with the most residual energy, and finds the optimal routing to the base station. The simulation clearly shows that the proposed ED-MORFO achieves better performance in terms of energy consumption (0.46 J), packet delivery ratio (99.4%), packet loss rate (0.6%), end-to-end delay (11 s), routing overhead (0.11), throughput (0.99 Mbps), and network lifetime (3719 s), when compared with existing MCH-EOR and RDSAOA-EECP methods.

Reliable and Energy-Efficient LEO Satellite Communication with IR-HARQ via Power Allocation.

This paper examines reliable and energy-efficient transmission in low earth orbit (LEO) satellite communication systems. In particular, we analyze the link transmission characteristics of the LEO satellite to the ground user and model the channel as a combination of large-scale fading and small-scale fading. Based on this, we consider an incremental redundancy hybrid automatic repeat request (IR-HARQ) technique with a variable-power allocation method, and we call it the IR-HARQ-VPA scheme. In this method, the outage probability after each IR-HARQ round can be obtained through numerical integration based on the fast Fourier transform (NI-FFT). This method is suitable for any number of HARQ transmission rounds and can improve the accuracy compared with previous approximation methods. In addition, variable-power allocation based on the genetic algorithm (VPA-GA) is introduced to reduce the energy consumption. The simulation results show that the proposed IR-HARQ-VPA scheme cannot only meet the requirements of transmission reliability but also achieves higher energy efficiency than IR-HARQ with equal power (IR-HARQ-EP) transmission and a previously proposed variable-power allocation method. Moreover, the simulation results in a LEO satellite communication window also confirm the effectiveness of the proposed IR-HARQ-VPA scheme.

Efficient Energy Optimization Routing for WSN Based on Even-Odd Scheduling

Several routing protocols are being developed and used to develop energy-efficient wireless sensor networks. The necessity of saving energy is the need for technology as well as the scarcity of conventional energy. The wireless sensor nodes are run on battery power with energy limitations; therefore, this study needs to develop wireless sensor networks that can be kept alive for a longer period. From a computer science point of view, a routing mechanism can help in the improvement of the network. This research aims to design and develop a routing protocol that utilizes less energy and keeps sensor networks alive for longer period while using limited energy. An efficient and intelligent even-odd scheduling-based routing protocol influenced by LEACH has been proposed to achieve this goal. During transmission, this protocol alternatively considers evenly or oddly indexed nodes. The concept in this approach is to keep the node into consideration when it is ready to send data and when it is in the queue. Any node that is not in the queue or does not have data will not consume any significant energy, and thus the whole network conserves energy after each transmission round.

Body Node Coordinator Placement Algorithm for WBAN Using Multi-Objective Swarm Optimization

A Body Node Coordinator (BNC) is responsible for coordinating and receiving the data transmissions of bio-sensor nodes within a wireless body area network (WBAN). Hence, it is necessary to place BNC at an optimal location in WBAN to minimize network energy consumption in data transmission. This paper presents a complete data routing strategy for WBAN that implements a multi-objective particle swarm optimization (MO-PSO) based BNC placement scheme along with a cluster routing protocol. The proposed scheme uses a three-variable particle structure where the initial two variables specify the BNC coordinates, and the third variable determines the cluster head node. A multi-objective fitness evaluation operator estimates the fitness of MO-PSO particles in terms of network energy consumption and average bit error rate (BER) observed during a single round of data transmission. The developed model evolves into an optimal BNC location that minimizes network energy consumption and average BER simultaneously. A reduced BER further brings about a significant increase in network throughput rate. Simulation results depict that the proposed scheme achieves 67.1% energy efficiency with a 94% network throughput rate. The proposed scheme meets the requirement of a short operational period apart from minimal involvement of sensor nodes.

Age-Energy Tradeoff Optimization for Packet Delivery in Fading Channels

Power control policies that minimize the weighted combination of age of information (AoI) and total energy consumption are studied in this paper. It is assumed that the status update information is acquired at the transmitter through sensors and then sent in packets to the receiver at fixed rate over Rayleigh fading channels. Retransmission mechanism is introduced to guarantee the reliability of the received update packets, and a limit on the maximum number of transmission rounds is imposed. On the one hand, with the channel distribution information (CDI) available at the transmitter, the age-energy tradeoff is optimized by formulating the problem as a constrained Markov decision process (CMDP) which takes into account the sensing power consumption as well as the average transmission power constraint. Employing the Lagrangian relaxation, the CMDP problem is transformed into an unconstrained Markov decision process (MDP) problem. A threshold-based policy is also provided. Subsequently, a dynamic programming approach is proposed to obtain the optimal power allocation policy. On the other hand, when the environment is unknown, two probabilistic reinforcement learning algorithms are proposed to optimize the age-energy tradeoff. Through simulation results, it is shown that the age-energy tradeoffs can be improved by the proposed optimal policies compared with benchmark schemes.