Communication Collision Research Articles

Hybrid Interval Type-2 Fuzzy AHP and COPRAS-G-based trusted neighbour node Discovery in Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), reliable and rapid neighbour node discovery is considered as the crucial operation which frequently needs to be executed over the entire lifecycle. Several neighbour node discovery mechanisms are proposed for reducing the latency or extending the sensor nodes’ lifetime. But majority of the existing neighbour node discovery mechanisms failed in addressing the critical issues of real WSNs related to energy consumptions, constraints of latency, uncertainty of node behaviors, and communication collisions. In this paper, Hybrid Interval Type-2 Fuzzy Analytical Hierarchical Process (AHP) and Complex Proportional Assessment using Grey Theory (COPRAS-G)-based trusted neighbour node discovery scheme (FAHPCG) is proposed for better data dissemination process. In specific, Interval Type 2 Fuzzy AHP is applied for determining the weight of the evaluation criteria considered for neighbour node discovery, and then Grey COPRAS method is adopted for prioritizing the sensor nodes of the routing path established between the source and destination. It adopted the merits of fuzzy theory for handling the uncertainty and vagueness involved in the change in the behavior of sensor nodes during the process of neighbour discovery. It is proposed with the capability of exploring maximized number of factors that aids in exploring the possible dimensions of sensor nodes packet forwarding potential during the process of neighbour node discovery. The simulation results of the proposed FAHPCG scheme confirmed an improved neighbour node discovery rate of 23.18% and prolonged the sensor nodes lifetime to the maximum of 7.12 times better than the baseline approaches used for investigation.

A Biologically Inspired Self-Organizing Underwater Sensor Network

Wireless underwater sensor networks have various applications—such as ocean exploration and deep-sea disaster monitoring—making them a hot topic in the research field. To cover a larger area and gather more-precise information, building large-scale underwater sensor networks has become a trend. In such networks, acoustic signals are used to transmit messages in an underwater environment. Their features of low speed and narrow bandwidth make media access control (MAC) protocols unsuitable for radio communications. Furthermore, a network consists of a large number of randomly deployed nodes, making it impossible to pre-define an optimized routing table or assign a central controller to coordinate the message propagation process. Thus, optimized routing should emerge via interaction among individual nodes in the network. To address these challenges, in this paper we propose a communication coordinator under the time division multiple access (TDMA) framework. Each node in the network is equipped with such a coordinator so that messages in the network can be sent following the shortest path in a self-organized way. The coordinator consists of a slot distributor and a forwarding guide. With the slot distributor, nodes in the sensor network occupy proper communication slots and the network finally converges to the state without communication collision. This is achieved with a set of ecological niche- and pheromone-inspired laws, which encourage nodes to occupy slots that can decrease the waiting time for a node to send a message packet while weakening the enthusiasm for a node to occupy the slots that it fails to occupy several times. With the forwarding guide, a node can send the message packet to the best successor node so that the message packet can be sent to the base station along the shortest path. It has been proven that the laws in the forwarding guide are equivalent to the Dijkstra Algorithm. Simulation experiment results indicate that with our coordinator, the network can converge to the state without collision using fewer coordination messages. In addition, the time needed to send a message to the destination is shorter than that of the classical Aloha protocol.

A Collision-Avoided MAC Protocol With Time Synchronization and Power Control for Underwater Sensor Networks

In recent years, there has been a great deal of interest in underwater sensor networks (UWSNs) because they can effectively monitor the submerged environment. However, due to the long delay, high bit error rate, and limited propagation bandwidth of underwater acoustic channels, the media access control (MAC) protocol cannot function effectively in underwater acoustic sensor networks, particularly in offshore waters. To solve these issues, an MAC protocol with time synchronization and power control (TSPC) is proposed for a particular scenario. In addition, the proposed protocol is a joint channel access scheme, and the central nodes are deployed on an offshore seabed, which can be used as a synchronization reference standard time. A power control strategy is also implemented to limit the communication range of nodes. In brief, integrating TSPC with layered concepts and distributed clustering algorithms can effectively prevent communication collisions and reduce the energy consumption of UWSNs. The simulation results indicate that the TSPC MAC protocol performs well with regard to packet transmission rate, synchronization error, collision-free operation, and energy consumption.

Formation control for rectangular agents with communication maintenance and collision avoidance

Formation control for rectangular agents with communication maintenance and collision avoidance

An Aerial-Computing-Assisted Architecture for Large-Scale Sensor Networks

Wireless sensor networks have been widely adopted in various areas. However, large-scale sensor networks face four critical problems. Information transmissions through the network would cause the energy hole problem; deploying sensors in a distributed manner might cause the isolated problem; simultaneous transmissions lead to the communication collision problem; and the lack of intelligent computing incurs the limited computation problem. Due to drones' high mobility and flexibility, drone-based aerial computing emerges as a new paradigm to address these problems. In this article, we propose an aerial-computing-assisted architecture for large-scale sensor networks; the core layer contains the following modules: sensor localization, trajectory planning of drones, communication control between drones and sensors, and enabling intelligent computation on drones. The architecture significantly advances large-scale sensor networks with higher efficiency, smaller delay, larger lifetime, and more powerful computing capability.

REFORMED TIME SLOT ALLOCATION FOR DATA INTENSIVE CLUSTERED INDUSTRIAL WIRELESS SENSOR NETWORKS USING VIRTUAL GRID STRUCTURE WITH UWB

The data intensive industrial sensor networks produce excessive communication collision and introduce significant deficits. Further, a defined, appropriate scheduling methodology for transmission is desirable for mitigating the scarcity of such networks. With this declaration, here inclined a method for allocating conflict-free timeslots for transmitting the data in clustered sensor networks securing it from collision. This is lightened by partitioning the monitoring cluster regions into equal sized virtual grids and Latin square characteristics support scheduling in individual grids on ultra-wide band. This decentralised protocol follows an AODV routing and thereby each sensor is aware of the neighbouring nodes location and accepts the inherent topology changes. Moreover, the nodes that are participating in transmission remains in active state and the others become idle, thus conserving less energy. This distributed MAC scheduling method is particularly helpful in spatial usage of the communication channel for achieving scalability and efficiency and hence performance.

Reformed timeslot allocation for data intensive clustered industrial wireless sensor networks using virtual grid structure with UWB

The data intensive industrial sensor networks produce excessive communication collision and introduce significant deficits. Further, a defined, appropriate scheduling methodology for transmission is desirable for mitigating the scarcity of such networks. With this declaration, here inclined a method for allocating conflict-free timeslots for transmitting the data in clustered sensor networks securing it from collision. This is lightened by partitioning the monitoring cluster regions into equal sized virtual grids and Latin square characteristics support scheduling in individual grids on ultra-wide band. This decentralised protocol follows an AODV routing and thereby each sensor is aware of the neighbouring nodes location and accepts the inherent topology changes. Moreover, the nodes that are participating in transmission remains in active state and the others become idle, thus conserving less energy. This distributed MAC scheduling method is particularly helpful in spatial usage of the communication channel for achieving scalability and efficiency and hence performance.

LoRa Traffic Generator Based on Software Defined Radio Technology for LoRa Modulation Orthogonality Analysis: Empirical and Experimental Evaluation.

The digital revolution has changed the way we implement and use connected devices and systems by offering Internet communication capabilities to simple objects around us. The growth of information technologies, together with the concept of the Internet of Things (IoT), exponentially amplified the connectivity capabilities of devices. Up to this moment, the Long Range (LoRa) communication technology has been regarded as the perfect candidate, created to solve the issues of the IoT concept, such as scalability and the possibility of integrating a large number of sensors. The goal of this paper is to present an analysis of the communication collisions that occur through the evaluation of performance level in various scenarios for the LoRa technology. The first part addresses an empirical evaluation and the second part presents the development and validation of a LoRa traffic generator. The findings suggest that even if the packet payload increases, the communication resistance to interferences is not drastically affected, as one may expect. These results are analyzed by using a novel Software Defined Radio (SDR) technology LoRa traffic generator, that ensures a high-performance level in terms of generating a large LoRa traffic volume. Despite the use of orthogonal variable spreading factor technique, within the same communication channel, the collisions between LoRa packets may dramatically decrease the communication performance level.

MD-MAC: A Distributed TDMA Protocol Based on Desynchronization for Multi-Hop Topologies

Communication resource allocation and collision detection are important for the Ad Hoc network. Considering the existing TDMA-MAC protocol, the allocation way based on fixed time slot is mostly adapted, which cannot guarantee the performance and be not flexible about the business for different nodes in the distributed network. Desynchronization, as a biological term, can be utilized in the Ad Hoc network. It implies that sensor nodes interleave periodic events to occur in succession through negotiation and adjustment. In this paper, we design a MAC protocol(MD-MAC) in the multi-hop network based on the idea of Desynchronization to solve the problem caused by stale information and lay down the adjustment rule to allocate the communication resource. Also, we propose a scheme which the network can detect collision in a self-adapting way. Finally, we simulate the proposed protocol to evaluate the performance. The experimental results indicate that the proposed algorithm can accelerate the convergence speed of resource allocation, solve collision and improve the efficiency of the distributed network.

A Practical Neighbor Discovery Framework for Wireless Sensor Networks.

Neighbor discovery is a crucial operation frequently executed throughout the life cycle of a Wireless Sensor Network (WSN). Various protocols have been proposed to minimize the discovery latency or to prolong the lifetime of sensors. However, none of them have addressed that all the critical concerns stemming from real WSNs, including communication collisions, latency constraints and energy consumption limitations. In this paper, we propose Spear, the first practical neighbor discovery framework to meet all these requirements. Spear offers two new methods to reduce communication collisions, thus boosting the discovery rate of existing neighbor discovery protocols. Spear also takes into consideration latency constraints and facilitates timely adjustments in order to reduce the discovery latency. Spear offers two practical energy management methods that evidently prolong the lifetime of sensor nodes. Most importantly, Spear automatically improves the discovery results of existing discovery protocols, on which no modification is required. Beyond reporting details of different Spear modules, we also present experiment evaluations on several notable neighbor discovery protocols. Results show that Spear greatly improves the discovery rate from to , and prolongs the sensor nodes lifetime up to times.

State estimation for delayed neural networks with stochastic communication protocol: The finite-time case

Abstract This paper is concerned with the finite-time state estimation problem for a class of delayed artificial neural networks under the stochastic communication protocol. The underlying time delay is time-varying yet bounded. Compared with the common-used sigmoid-type nonlinearity, a more general type of nonlinearity is adopted to describe the neuron activation function and the nonlinearity of the measurement output, respectively. In order to avoid the communication collision, the stochastic communication protocol is introduced between the transmitter and the receiver, and the corresponding scheme is characterised with the help of a Markov chain. By introducing an auxiliary vector, a novel state estimator structure is proposed. The stochastic finite-time stability of the error dynamics is first analyzed via the stochastic analysis techniques and the Lyapunov stability theory, and then the sufficient condition for the existence of the desired state estimator is obtained. Subsequently, the estimator gain is parameterized by using a set of easy-to-check computational condition. Finally, a numerical example is provided to show the effectiveness of the proposed algorithm.

Performance evaluation of unmanned aerial vehicles in automatic power meter readings

Typically, the electric power companies employ a group of power meter readers to collect data on the customers energy consumption. This task is usually carried out manually, which can lead to high cost and errors, causing financial losses. Some approaches have tried to minimize these problems, using strategies such as discovering the minimal route or relying on vehicles to perform the readings. However, errors in the manual readings can occur and vehicles suffer from congestion and high fuel and maintenance costs. In this work, we go further and propose an architecture to the Automatic Meter Reading (AMR) system using Unmanned Aerial Vehicles (UAV). The main challenge of the solution is to design a robust and lightweight protocol that is capable of dealing with wireless communication collisions. Therefore, the main contribution of this work is the design of a new protocol to ensure wireless communication from UAV to the power meters. We validated and evaluated the architecture in an urban scenario, with results showing a decrease of time and distance when compared to other approaches. We also evaluated the system proposed with Linear Flight Plan, the Ant Colony Optimization and Guided Local Search metaheuristic. Our mechanism attains an improvement of 98% in reducing the message collisions and reducing the energy consumption of the power meters.

Centralized and Localized Data Congestion Control Strategy for Vehicular Ad Hoc Networks Using a Machine Learning Clustering Algorithm

In an urban environment, intersections are critical locations in terms of road crashes and number of killed or injured people. Vehicular ad hoc networks (VANETs) can help reduce the traffic collisions at intersections by sending warning messages to the vehicles. However, the performance of VANETs should be enhanced to guarantee delivery of the messages, particularly safety messages to the destination. Data congestion control is an efficient way to decrease packet loss and delay and increase the reliability of VANETs. In this paper, a centralized and localized data congestion control strategy is proposed to control data congestion using roadside units (RSUs) at intersections. The proposed strategy consists of three units for detecting congestion, clustering messages, and controlling data congestion. In this strategy, the channel usage level is measured to detect data congestion in the channels. The messages are gathered, filtered, and then clustered by machine learning algorithms. $K$ - means algorithm clusters the messages based on message size, validity of messages, and type of messages. The data congestion control unit determines appropriate values of transmission range and rate, contention window size, and arbitration interframe spacing for each cluster. Finally, RSUs at the intersections send the determined communication parameters to the vehicles stopped before the red traffic lights to reduce communication collisions. Simulation results show that the proposed strategy significantly improves the delay, throughput, and packet loss ratio in comparison with other congestion control strategies using the proposed congestion control strategy.

Target-Aware, Transmission Power-Adaptive, and Collision-Free Data Dissemination in Wireless Sensor Networks

Software update in wireless sensor networks requires the ability of disseminating bulk data to specified sensors of a network with low latency in an energy efficient manner. This paper proposes a target-aware, transmission power-adaptive, and collision-free data dissemination protocol to fulfill these requirements. This protocol disseminates data to sensors of a network by first constructing a connected dominating set (CDS) in the network. We propose a target-aware CDS construction to exclude many unnecessary non-target sensors from the data dissemination process. By allowing some dominators of the CDS to increase their transmission power to disseminate data to more dominatees, the protocol efficiently reduces the total energy consumption. In addition, we propose a collision-based channel assignment strategy to eliminate communication collisions among dominators so as to reduce latency. We have implemented the protocol and evaluated it through simulations and a real application scenario. Our experimental results show that the proposed protocol at most reduces non-target sensors by 75.3%, total energy consumption by 57.1%, and latency by 39.8% compared to existing dissemination protocols.

Design of Multi-Channel Wireless Sensor Networks Based On Compressive Sensing Theory and Spectrum Sensing Theory

The single-channel wireless sensor networks (WSNs) exists the problem of low efficiency of monitoring data transmission, however the multi-channel WSNs exists the problem of communication collision caused by the sensor node’s wireless channel competition. The paper at first introduces the causes of the above problems and selects a reasonable wireless channel resources allocation method of the multi-channel WSNs. Then to solve these questions, the theory of compressive sensing and spectrum sensing are adopted to improve the existing multi-channel WSNs. Finally, a new sensor node of the multi-channel WSNs is designed based on the above improvement. By analyzing the monitoring data of the field test, the improved multi-channel WSNs could complete monitoring mission efficiently and accurately, meanwhile it reduced power consumption of the WSNs effectively.

무선 센서 네트워크에서 서비스에 필요한 데이터 전송량을 확보하기 위한 토폴로지 관리 방법

There are various kinds of applications for wireless sensor network, and each application has difference requirements such as throughput. Topology control is the key issue to minimize energy consumption by solving communication collision and radio interference. However, existing topology control algorithms cannot support application requirement because communication efficiency and network connectivity are the main issues of topology control. In this paper, we propose a topology control algorithm that support throughput requirement of an application.

A Robust and Lightweight Protocol for Efficient and Scalable Automatic Meter Reading using an Unmanned Aerial Vehicle

Most electric power companies employs power meter reader to collect data on the customer's energy consumption. Usually, this task is carried out manually, which can lead to high cost and errors, causing financial losses. Some approaches tries to minimize these problems, such as: find the minimal route or use a car to perform the readings. However, errors associated the manual readings can still occurs and cars suffer with congestions and a high costs of the fuel consumption and to maintaining. In this work, we go further and propose an Automatic Meter Reading (AMR) system using Unmanned Aerial Vehicles (UAV). One of the challenge of this solution is design a robust and lightweight protocol that is able to deal with the wireless communication collisions. Therefore, the main contribution of this work is the design a new protocol to ensure wireless communication from UAV to the power meters. We evaluated the protocol in an urban scenario and the results show a decrease of messages collisions up to 98%.

Achieving Collision-Free Communication by Time of Charge in WRSN

The Wireless Identification and Sensing Platform (WISP) Sample et al. (IEEE T Instrum Meas 57(11):2608---2615, 2008) has become a very promising experimental platform of wireless rechargeable sensor networks (WRSN), which integrates the sensing and computation capabilities to the traditional RFID tags. In such kind of networks, the simultaneous transmission may introduce severe communication collisions, which have attracted various research efforts for resolving such collisions at the MAC layer. However, different from existing works, we avoid such communication collisions through proper reader movement by exploiting the differences in the time of charge among rechargeable sensor nodes. We formulate the optimization problem and prove that complexity of the optimal solution is NP-hard, and propose a simple yet effective algorithm to optimize both the reader stop location and stop time for minimizing the total communication delay. Extensive simulations under different system settings show that our design can largely reduce the communication delay and outperform the baseline design by at least 20 %.

Distributed Detection of Binary Decisions with Collisions in a Large, Random Network

We consider the problem of distributed detection in a large network of sensors. A random number of sensor nodes are randomly deployed. Sensor nodes perform local detection tests and communicate detections over a multiple-access channel to a fusion center. The fusion center can recognize both successful communications and communication collisions in the channel. We derive decision rules for both perfect communications and a delay-constrained communications protocol, and show that each are functions of count statistics only. We derive analytical expressions that characterize the performance of the system in terms of detection performance. We analyze performance with respect to sensor density and with respect to communications delay. Simulation examples validate theoretical predictions with numerical results. We show that the detection performance improves with network density despite increasing communication collisions. In addition, we show that detection performance using the protocol model, with imperfect communications, rapidly converges to the perfect communications case as the number of communication slots increase.

Dynamic scheduling with energy-efficient transmissions in hierarchical wireless sensor networks

This study proposes a number of scheduling schedules for data transmission in cluster-based wireless sensor networks in order to make energy-saving improvements to sensor nodes. The four states are defined in each network cycle so that sensor nodes can report the events happened in the network. A clustering mechanism creates appropriate network topologies to distribute energy consumption among energy-sufficient sensor nodes. Nodes can adjust the duty cycles for data collection during network lifetime. The scheduling schemes reduce the probabilities of communication collision and duplicate transmission using a broadcast delay. We examine the storage, communication, and computation requirements for the proposed scheduling scheme. All the overheads are sensible, given the current state of device technology of sensor nodes. The experimental results show that nodes work in high efficiency cluster-based networks by the proposed schemes.