Event-to-sink reliable transport in wireless sensor networks

Wireless sensor networks (WSNs) are event-based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. However, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. Hence, the WSN paradigm necessitates a collective event-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport in WSN has not been studied from this perspective before. In order to address this need, a new reliable transport scheme for WSN, the event-to-sink reliable transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It includes a congestion control component that serves the dual purpose of achieving reliability and conserving energy. Importantly, the algorithms of ESRT mainly run on the sink, with minimal functionality required at resource constrained sensor nodes. ESRT protocol operation is determined by the current network state based on the reliability achieved and congestion condition in the network. This self-configuring nature of ESRT makes it robust to random, dynamic topology in WSN. Furthermore, ESRT can also accommodate multiple concurrent event occurrences in a wireless sensor field. Analytical performance evaluation and simulation results show that ESRT converges to the desired reliability with minimum energy expenditure, starting from any initial network state.     

A Real-Time and Reliable Transport (RT)$^{2}$ Protocol for Wireless Sensor and Actor Networks

Wireless sensor and actor networks (WSANs) are characterized by the collective effort of heterogeneous nodes called sensors and actors. Sensor nodes collect information about the physical world, while actor nodes take action decisions and perform appropriate actions upon the environment. The collaborative operation of sensors and actors brings significant advantages over traditional sensing, including improved accuracy, larger coverage area and timely actions upon the sensed phenomena. However, to realize these potential gains, there is a need for an efficient transport layer protocol that can address the unique communication challenges introduced by the coexistence of sensors and actors. In this paper, a real-time and reliable transport (RT) protocol is presented for WSANs. The objective of the (RT) protocol is to reliably and collaboratively transport event features from the sensor field to the actor nodes with minimum energy dissipation and to timely react to sensor information with a right action. In this respect, the (RT) protocol simultaneously addresses congestion control and timely event transport reliability objectives in WSANs. To the best of our knowledge, this is the first research effort focusing on real-time and reliable transport protocol for WSANs. Performance evaluations via simulation experiments show that the (RT) protocol achieves high performance in terms of reliable event detection, communication latency and energy consumption in WSANs.     

Secured routing in wireless sensor networks using fault‐free and trusted nodes

Wireless sensor network (WSN) should be designed such that it is able to identify the faulty nodes, rectify the faults, identify compromised nodes from various security threats, and transmit the sensed data securely to the sink node under faulty conditions. In this paper, we propose an idea of integrating fault tolerance and secured routing mechanism in WSN named as fault tolerant secured routing: an integrated approach (FASRI) that establishes secured routes from source to sink node even under faulty node conditions. Faulty nodes are identified using battery power and interference models. Trustworthy nodes (non‐compromised) among fault‐free nodes are identified by using agent‐based trust model. Finally, the data are securely routed through fault‐free non‐compromised nodes to sink. Performance evaluation through simulation is carried out for packet delivery ratio, hit rate, computation overhead, communication overhead, compromised node detection ratio, end‐to‐end delay, memory overhead, and agent overhead. We compared simulation results of FASRI with three schemes, namely multi‐version multi‐path (MVMP), intrusion/fault tolerant routing protocol (IFRP) in WSN, and active node‐based fault tolerance using battery power and interference model (AFTBI) for various measures and found that there is a performance improvement in FASRI compared with MVMP, IFRP, and AFTBI. Copyright © 2014 John Wiley & Sons, Ltd.     

Queue‐based congestion detection and multistage rate control in event‐driven wireless sensor networks

Protocols for sensor networks have traditionally been designed using the best effort delivery model. However, there are many specific applications that need reliable transmissions. In event‐driven wireless sensor networks, the occurrence of an event may generate a large amount of data in a very short time. Among them, some critical urgent information needs to be transmitted reliably in a timely manner. In this scenario, congestion is inevitable because of the constraints in available resources. How to control the congestion is very important for the reliable transmission of urgent information. To address this problem, we propose a queue‐based congestion detection and a multistage rate control mechanism. In our proposed mechanism, not only the current queue length but also the queue fluctuation are adopted as indications of congestion. Each sensor node evaluates its congestion level locally and determines its congestion state with a state machine. We design a multistage rate adjustment mechanism for nodes to adjust their rates depending on their congestion states. We also distinguish high‐priority critical traffic from low‐priority non‐critical traffic. Extensive simulation results confirm the superior performance of our proposed protocol with respect to throughput, loss probability, and delay.Copyright © 2012 John Wiley & Sons, Ltd.     

E2SRT: enhanced event‐to‐sink reliable transport for wireless sensor networks

An event‐to‐sink reliable transport (ESRT) control scheme was recently proposed to address the event‐to‐sink reliability issues in wireless sensor network (WSN). In this paper, we study the performance of ESRT in the presence of ‘over‐demanding’ event reliability, using both the analytical and simulation approaches. We show that the ESRT protocol does not achieve optimum reliability and begins to fluctuate between two inefficient network states. With insights from update mechanism in ESRT, we propose a new algorithm, called enhanced ESRT (E²SRT), to solve the ‘over‐demanding’ event reliability problem and to stabilize the network. Simulation results show that E²SRT outperforms ESRT in terms of both reliability and energy consumption in the presence of ‘over‐demanding’ event reliability. Besides, it ensures robust convergence in the presence of dynamic network environments. Copyright © 2008 John Wiley & Sons, Ltd.     

RECOD: reliable detection protocol for large-scale and dynamic continuous objects in wireless sensor networks

Whether individual objects such as enemy tanks or intruders have been reliably detected typically depends on the number of data reports successfully delivered to a sink node from the sensor nodes surrounding the object. When the number of data reports exceeds a required threshold, the sink recognizes the object that is detected by sensor nodes. Thus, previous studies exploited this framework for reliable detection as event reliability for individual objects, and proposed event-to-sink reliable-transport mechanisms that can reach a required threshold. Recently, in wireless sensor networks, research has focused on coverage detection for large-scale phenomena such as biochemical material and wild fires. Such phenomena are known as continuous objects because they generally cover wide areas and frequently change their shape as a result of wind or geographical features. Since continuous objects are large-scale and alterable, they present new challenges for the event reliability. In this paper, we first define new criteria for measuring the event reliability of large-scale phenomena. Then, we propose a novel event-to-sink transport protocol that is reliable, even when excessive data is generated from many sensor nodes detecting these phenomena. Analysis and simulation results demonstrate the event reliability of our protocol.

     

Error and congestion control for wireless sensor networks

In the wireless sensors network (WSN) field, a wide variety of sensors produce a heterogeneous traffic mix, targeting diverse applications with different reliability requirements. We focus on emergency response scenarios, where a mobile rescuer moves through a, possibly disconnected, network, trying to talk to diverse sensors. We assume two types of sensors, event sensors triggered by an event and periodic sensors activated at predefined time intervals, as well as two types of transmission, either using the highest bit rate available or using predefined bit rates. Our reliable transport protocol for sensor networks with mobile sinks (RT‐SENMOS) takes into account all these parameters and tries to provide the best possible user experience under the current circumstances of the network, using a sink‐driven approach where an application‐specific sink is combined with generic sensors. RT‐SENMOS was implemented and tested over a real network with emulated losses and compared against rate‐controlled reliable transport (RCRT), a well‐known sink‐driven protocol. The results show that RT‐SENMOS fully exploits the available bandwidth in all cases, while RCRT only manages to exploit 60% to 90% of it. Furthermore, RT‐SENMOS adapts much faster to prevailing network conditions, while its protocol overhead, in terms of control messages exchanged, is much lower than that of RCRT.     

FPS‐MAC: Fuzzy priority scheduling‐based MAC protocol for intelligent monitoring systems

Recent advances in microelectronics have encouraged the implementation of a wireless sensor network (WSN) in intelligent monitoring systems (IMSs). The IMS for time‐critical applications requires timely and reliable data delivery without sacrificing the energy efficiency of the network. This paper proposes FPS‐MAC, a fuzzy priority scheduling‐based medium access control protocol, designed for event critical traffic in hierarchical WSN. The FPS‐MAC allows time‐critical event traffic to opportunistically steal the data slots allocated for periodic data traffic in event‐based situations. Additionally, a fuzzy logic‐based slot scheduling mechanism is introduced to provide guaranteed and timely medium access to emergency traffic load and ensures the quality‐of‐service (QoS) requirements of IMSs. Both analytical and simulation results for data throughput, energy consumption, and transmission delay of FPS‐MAC, TLHA, E‐BMA, and BMA‐RR have been analyzed to demonstrate the superiority of the proposed FPS‐MAC protocol.     

Simulation‐based real‐time routing protocol with load distribution in wireless sensor networks

In wireless sensor networks (WSNs), sensors gather information about the physical world and the base station makes decision and then performs appropriate actions upon the environment. This technology enables a user to effectively sense and monitor from a distance in real‐time. WSNs demand real‐time forwarding which means messages in the network are delivered according to their end‐to‐end deadlines (packet lifetime). This paper proposes a novel real‐time routing protocol with load distribution (RTLD) that ensures high packet throughput with minimized packet overhead and prolongs the lifetime of WSN. The routing depends on optimal forwarding (OF) decision that takes into account of the link quality (LQ), packet delay time and the remaining power of next hop sensor nodes. The proposed mechanism has been successfully studied through simulation work. Copyright © 2009 John Wiley & Sons, Ltd.     

Distributed audio sensing with homeostasis-inspired autonomous communication

Emerging applications of wireless sensor networks (WSN) requiring wide-band event signal communication such as multimedia surveillance sensor networks impose additional challenges including high communication bandwidth requirement and energy cost. Besides their partially or fully dependency on feedback messages from sink node, the existing protocols designed for WSN do not address the communication of wide-band event signals. Furthermore, the feedback messages may not reach in time to provide reliable communication of event information and save scarce network resources. Therefore, an autonomous communication protocol is imperative in order to provide wide-band event signal communication without any feedback from the sink. In nature, biological systems have self-organization capability, i.e., homeostasis, as they autonomously maintain a relatively stable equilibrium state for operation of vital functions. Hence, this natural phenomenon clearly gives promising inspirations in order to develop autonomous and efficient communication models and protocols for WSN domain. In this paper, the homeostasis-inspired autonomous communication (HAC) protocol is introduced for wireless audio sensor networks (WASN). Using the spectral properties of the wide-band event signal, i.e., audio signal, HAC enables WASN to maintain a relatively stable state in which sensor nodes reliably and energy-efficiently communicate the event signal to the sink node. Furthermore, with its self-organization capability, HAC does not rely on any feedback message from the sink node. Performance evaluations reveal that HAC successfully communicates wide-band event signal with minimum energy expenditure.     

PFARS: Enhancing throughput and lifetime of heterogeneous WSNs through power‐aware fusion,aggregation, and routing scheme

Heterogeneous wireless sensor networks (WSNs) consist of resource‐starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy‐efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application‐specific or too complex that make their implementation unrealistic, specifically, in a resource‐constrained environment. In this paper, we propose a novel node‐level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in‐network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real‐time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.     

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Applying multiple sink nodes in a large‐scale wireless sensor networks (WSN) can increase the scalability and lifetime of the network. The current sink selection mechanisms assume an unlimited amount of buffer and bandwidth for the sink nodes. This can be problematic in real‐world applications, especially when many cluster heads select a specific sink node and send their data to the sink at the same time. In this situation, the sink node may not have enough buffer to receive and process data; consequently, some packets are dropped. To mitigate these occasions, a fuzzy‐based controller with reduced rules is proposed for sink selection by considering the capacity of the sink nodes. The capacity of the sink nodes is estimated using the long short‐term memory (LSTM) technique. Then another fuzzy‐based controller with reduced rules is designed to select the cluster head. The fuzzy rules are reduced by employing R‐implications method. Reducing the number of fuzzy rules decreases the complexity of the fuzzy controllers. The results show the efficiency of the proposed sink selection and clustering techniques in terms of consumed energy, remaining energy, first node dead (FND), half nodes dead (HND), last node dead (LND), packet loss, and delay.     

End‐to‐end delay and packet drop rate performance for a wireless sensor network with a cluster‐tree topology

In this paper, we study the delay performance in a wireless sensor network (WSN) with a cluster‐tree topology. The end‐to‐end delay in such a network can be strongly dependent on the relative location between the sensors and the sink and the resource allocations of the cluster heads (CHs). For real‐time traffic, packets transmitted with excessive delay are dropped. Given the timeline allocations of each CH for local and inter‐cluster traffic transmissions, an analytical model is developed to find the distribution of the end‐to‐end transmission delay for packets originated from different clusters. Based on this result, the packet drop rate is derived. A heuristic scheme is then proposed to jointly find the timeline allocations of all the CHs in a WSN in order to achieve the minimum and balanced packet drop rate for traffic originated from different levels of the cluster tree. Simulation results are shown to verify the analysis and to demonstrate the effectiveness of the proposed CH timeline allocation scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

无线传感器网络突发感知的拥塞控制协议(英文)

In monitoring Wireless Sensor Networks(WSNs),the traffic usually has bursty characteristics when an event occurs.Transient congestion would increase delay and packet loss rate severely,which greatly reduces network performance.To solve this problem,we propose a Burstiness-aware Congestion Control Protocol(BCCP) for wireless sensor networks.In BCCP,the backoff delay is adopted as a congestion indication.Normally,sensor nodes work on contention-based MAC protocol(such as CSMA/CA).However,when congestion occur...     

Efficient REBTA data reporting algorithm for object tracking in wireless sensor networks

Object tracking is widely referred as one of the most interesting applications of wireless sensor networks (WSNs). This application is able to detect and track objects and report information about these objects to a central base station. One of the major drawbacks in the current research in WSNs is the quality of the data reporting where the major research focus is dedicated to localization of objects; however, few of these works were concentrated on the data reporting. An efficient data reporting algorithm for object tracking in WSNs is proposed in this paper. The main objective of this paper is to enhance the WSN lifetime by achieving both minimum energy and balancing such consumption in sensor nodes during reporting operation. Furthermore, in our model, the enhancement of network reliability is considered. Finally, it reduces the effects of congestion by sufficiently utilizing the under loaded nodes to improve the network throughput. This paper formulates the object tracking problem in large‐scale WSN into 0/1 integer linear programming problem, and then proposes a reliable energy balance traffic aware approach to solve the optimization problem. From the obtained simulation results, the proposed solution has proved to be able to enhance the network performance in network lifetime, throughput, end‐to‐end delay, energy balance, and complexity for both homogeneous and heterogeneous networks.     

A hybrid approach for the optimization of quality of service metrics of WSN

The core objective behind this research paper is to implement a hybrid optimization technique along with proactive routing algorithm to enhance the network lifetime of wireless sensor networks (WSN). The combination of two soft computing techniques viz. genetic algorithm (GA) and bacteria foraging optimization (BFO) techniques are applied individually on destination sequence distance vector (DSDV) routing protocol and after that the hybridization of GA and BFO is applied on the same routing protocol. The various simulation parameters used in the research are: throughput, end to end delay, congestion, packet delivery ratio, bit error rate and routing overhead. The bits are processed at a data rate of 512 bytes/s. The packet size for data transmission is 100 bytes. The data transmission time taken by the packets is 200 s i.e. the simulation time for each simulation scenario. Network is composed of 60 nodes. Simulation results clearly demonstrates that the hybrid approach along with DSDV outperforms over ordinary DSDV routing protocol and it is best suitable under smaller size of WSN.

     

REBTAM: reliable energy balance traffic aware data reporting algorithm for object tracking in multi-sink wireless sensor networks

Recently, Multi-sink Wireless Sensor Networks (WSNs) have received more and more attention due to their significant advantages over the single sink WSNs such as improving network throughput, balancing energy consumption, and prolonging network lifetime. Object tracking is regarded as one of the key applications of WSNs due to its wide real-life applications such as wildlife animal monitoring and military area intrusion detection. However, many object tracking researches usually focus on how to track the location of objects accurately, while few researches focus on data reporting. In this work, we propose an efficient data reporting method for object tracking in multi-sink WSNs. Due to the limited energy resource of sensor nodes, it seems especially important to design an energy efficient data reporting algorithm for object tracking in WSNs. Moreover, the reliable data transmission is an essential aspect that should be considered when designing a WSN for object tracking application, where the loss of data packets will affect the accuracy of the tracking and location estimation of a mobile object. In addition, congestion in WSNs has negative impact on the performance, namely, decreased throughput, increased per-packet energy consumption and delay, thus congestion control is an important issue in WSNs. Consequentially, this paper aims to achieve both minimum energy consumption in reporting operation and balanced energy consumption among sensor nodes for WSN lifetime extension. Furthermore, data reliability is considered in our model where the sensed data can reach the sink node in a more reliable way. Finally, this paper presents a solution that sufficiently exerts the underloaded nodes to alleviate congestion and improve the overall throughput in WSNs. This work first formulates the problem as 0/1 Integer Linear Programming problem, and proposes a Reliable Energy Balance Traffic Aware greedy Algorithm in multi-sink WSNs (REBTAM) to solve the optimization problem. Through simulation, the performance of the proposed approach is evaluated and analyzed compared with the previous work which is related to our topic such as DTAR, NBPR, and MSDDGR protocols.     

Fair data collection in wireless sensor networks: analysis and protocol

In general, wireless sensor networks (WSNs) consist of many sensors which transmit data to a central node, called the sink, possibly over multiple hops. This many-to-one data routing paradigm leads to nonuniform traffic distribution for the different sensors (e.g., nodes closer to the sink transfer more traffic than those farther away). In this paper, we perform an analysis of the fairness issue by presenting a tree-based WSN and derive the throughput, delay, and energy distribution for each sensor under the fairness constraint. Based on the analysis, we design our fair data collection protocol in which each node decides its media access and packet forwarding strategies in a distributed manner. Finally, we demonstrate the effectiveness of our solution through simulations. The results for the proposed protocol show the accuracy of the analysis and show that the protocol ensures the fair delivery of packets and reduces end-to-end delay. Based on the analysis, we also quantitatively determine the energy required for each of the nodes and show that a nonuniform energy distribution can maximize the network lifetime for the WSN scenario under study.     

Belief based data cleaning for wireless sensor networks

Wireless sensor network (WSN) data is often subjected to corruption and losses due to wireless medium of communication and presence of hardware inaccuracies in the nodes. For a WSN application to deduce an appropriate result it is necessary that the data received is clean, accurate, and lossless. WSN data cleaning systems exploit contextual associations existing in the received data to suppress data inconsistencies and anomalies. In this work we attempt to clean the data gathered from WSN by capturing the influence of changing dynamics of the environment on the contextual associations existing in the sensor nodes. Specifically, our work validates the extent of similarities among the sensed observations from contextually (spatio‐temporally) associated nodes and considers the time of arrival of data at the sink to educate the cleaning process about the WSN's behavior. We term the data cleaning technique proposed in this work as time of arrival for data cleaning (TOAD). TOAD establishes belief on spatially related nodes to identify potential nodes that can contribute to data cleaning. By using information theory concepts and experiments on data sets from a real‐time scenario we demonstrate and establish that validation of contextual associations among the sensor nodes significantly contributes to data cleaning. Copyright © 2010 John Wiley & Sons, Ltd.     

Energy Efficient Reliable Multi-path Data Transmission in WSN for Healthcare Application

In healthcare applications of WSN, the data loss due to congestion may cause death alarm for a patient in critical condition. Therefore, an efficient congestion avoidance or otherwise an efficient congestion control mechanism is required. In this paper, we present an energy efficient reliable multi-path data transmission protocol for reliable data transport over WSN for the health care application. The emergency data and sensitive data packets are transmitted through an alternate path having minimum correlation with transmission interference during congestion. The proposed protocol attempts to avoid congestion by computing the probability of congestion at the intermediate nodes and transmission rate at the intermediate node is adjusted. The buffer of each node is partitioned to support fair and efficient data delivery. The reliability of the proposed protocol is achieved through hop-by-hop loss recovery and acknowledgement. The performance of the proposed protocol is evaluated through extensive simulations. The simulation results reveal that it outperforms the existing congestion control protocols for healthcare application in terms of energy efficiency, reliability and end-to-end delivery ratio.