A Robust and Efficient Cross-Layer Optimal Design in Wireless Sensor Networks

When using wireless sensor networks (WSNs) for data transmission, some critical respects should be considered. These respects are limited computational power, storage capability and energy consumption. To save the energy in WSNs and prolong the network lifetime, we design for the signal control input, routing selection and capacity allocation by the optimization model based on compressed sensing (CS) framework. The reasonable optimization model is decomposed into three subsections for three layers in WSNs: congestion control in transport layer, scheduling in link layer and routing algorithm in network layer, respectively. These three functions interact and are regulated by congestion ratio so as to achieve a global optimality. Congestion control can be robust and stable by CS theory that a relatively small number of the projections for a sparse signal contain most of its salient information. Routing selection is abided by fair resource allocation principle. The resources can be allocated more and more to the channel in the case of not causing more severe congestion, which can avoid conservatively reducing resources allocation for eliminating congestion. Simulation results show the stability of our algorithm, the accurate ratio of CS, the throughput, as well as the necessity of considering congestion in WSNs.     

Controlling Congestion in Wireless Sensor Networks Through Imperialist Competitive Algorithm

Wireless Personal Communications - Congestion control is one of the most important in wireless sensor networks (WSNs) due to inherent limited resources. In WSNs congestion leads to the loss of...     

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.     

A survey of transport protocols for wireless sensor networks

In this article we present a survey of transport protocols for wireless sensor networks (WSNs). We first highlight several unique aspects of WSNs, and describe the basic design criteria and challenges of transport protocols, including energy-efficiency, quality of service, reliability, and congestion control. We then provide a summary and comparison of existing transport protocols for WSNs. Finally, we discuss several open research problems.     

Upstream congestion control in wireless sensor networks through cross-layer optimization

Congestion in wireless sensor networks not only causes packet loss, but also leads to excessive energy consumption. Therefore congestion in WSNs needs to be controlled in order to prolong system lifetime. In addition, this is also necessary to improve fairness and provide better quality of service (QoS), which is required by multimedia applications in wireless multimedia sensor networks. In this paper, we propose a novel upstream congestion control protocol for WSNs, called priority-based congestion control protocol (PCCP). Unlike existing work, PCCP innovatively measures congestion degree as the ratio of packet inter-arrival time along over packet service time. PCCP still introduced node priority index to reflect the importance of each sensor node. Based on the introduced congestion degree and node priority index, PCCP utilizes a cross-layer optimization and imposes a hop-by-hop approach to control congestion. We have demonstrated that PCCP achieves efficient congestion control and flexible weighted fairness for both single-path and multi-path routing, as a result this leads to higher energy efficiency and better QoS in terms of both packet loss rate and delay.     

Adaptive Load-Aware Congestion Control Protocol for Wireless Sensor Networks

Congestion control in wireless sensor networks (WSNs) is crucial. In this article, we discuss congestion control and the adaptive load-aware problem for sensor nodes in WSNs. When the traffic load of a specific node exceeds its the available capacity of the node, a congestion problem occurs because of buffer memory overflow. Congestion may cause serious problems such as packet loss, the consumption of power, and low network throughput for sensor nodes. To address these problems, we propose a distributed congestion control protocol called adaptive load-aware congestion control protocol (ALACCP). The protocol can adaptively allocate the appropriate forwarding rate for jammed sensor nodes to mitigate the congestion load. Through the buffer management mechanism, the congestion index of neighboring sensor nodes, and an adjustment of the adaptive forwarding rate, the degree of congestion is alleviated markedly. The performance in allocating the forwarding rate effectively to neighboring sensor nodes also improves. The ALACCP can avoid packet loss because of traffic congestion, reduce the power consumption of nodes, and improve the network throughput. Simulation results revealed that the proposed ALACCP can effectively improve network performance and maintain the fairness of networks.     

无线传感器网络中基于拥塞程度分级的速率调节机制

文中提出一种基于拥塞程度分级的速率调节算法.首先,对缓冲区进行多尺度排队分析,计算出缓冲区的溢出概率.其次,根据溢出概率的值,把节点拥塞程度分成三级.最后,针对每一级拥塞采取相应的速率调节方案来缓解拥塞.实验结果表明,该算法可以有效缓解拥塞,提高无线传感器网络的数据包投递率.     

Hierarchical Tree Alternative Path (HTAP) algorithm for congestion control in wireless sensor networks

Recent advances in wireless sensor networks (WSNs) have lead to applications with increased traffic demands. Research is evolving from applications where performance is not considered as a crucial factor, to applications where performance is a critical factor. There are many cases in the fields of automation, health monitoring, and disaster response that demand wireless sensor networks where performance assurances are vital, especially for parameters like power, delay, and reliability. Due to the nature of these networks the higher amount of traffic is observed when the monitored event takes place. Exactly at this instance, there is a higher probability of congestion appearance in the network. Congestion in WSNs is tackled by the employment of two methods: either by reducing the load (“traffic control”), or by increasing the resources (“resource control”). In this paper we present the Hierarchical Tree Alternative Path (HTAP) algorithm, a “resource control” algorithm that attempts, through simple steps and minor computations, to mitigate congestion in wireless sensor networks by creating dynamic alternative paths to the sink. HTAP is evaluated in several scenarios in comparison with another “resource control” algorithm (TARA), as well as with a “traffic control” algorithm (SenTCP), and also the case where no congestion control exists in the network (“no CC”). Results show that HTAP is a simple and efficient algorithm capable of dealing successfully with congestion in WSNs, while preserving the performance characteristics of the network.     

Throughput Evaluation of a Novel Scheme to Mitigate the Congestion over WSNs

In recent years, due to fast development of wireless sensor networks (WSNs), the numbers of nodes are increasing, and their scope of applications is continuously expanding, including environmental monitoring, military and smart home applications. The power supply, memory and computing power of wireless sensor nodes are greatly hampered in WSNs so that the WSNs are classified as a task-oriented framework. This study focused on exploring problems caused by traffic congestion on the WSNs with a large amount of flow, such as packet loss, bandwidth reduction, and waste of energy on the sensor nodes. On the other hand, a cooperative strong node mechanism is presented and named as Cooperative Strong Node Mechanism, in which a threshold is set to determine whether the node traffic is over or not. When the load exceeds, the privilege of corresponding sensor nodes is upgraded so that it can command its child nodes to change the transmission path to distribute the traffic effectively. Furthermore, when the traffic exceeds preset overall network flow, new sensor nodes are added in the network to relieve the traffic. This novel proposed mechanism can not only increase network throughput and effectively prevent the occurrence from congestion problems, but is suitable for a variety of routing protocols.     

基于无线传感器网络的跨层拥塞控制协议

无线传感器网络(WSN)中由拥塞引起的大量分组重传以及重传多次失败后的分组丢弃会导致较长的时延、较高的分组丢失率和较多的能量消耗.为了准确探测和控制网络拥塞,提出了一种基于跨层设计的拥塞控制协议,即上行拥塞控制(UCC)协议.该协议利用节点在媒质接人控制(MAC)层中未占用的缓冲器区间大小和所预测的通信流量作为该节点的...     

Congestion control in wireless sensor and 6LoWPAN networks: toward the Internet of Things

The Internet of Things (IoT) is the next big challenge for the research community where the IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is a key part of the IoT. Recently, the IETF ROLL and 6LoWPAN working groups have developed new IP based protocols for 6LoWPAN networks to alleviate the challenges of connecting low memory, limited processing capability, and constrained power supply sensor nodes to the Internet. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects such as throughput, latency, energy consumption, reliability, and packet delivery. In this paper, we overview the protocol stack of 6LoWPAN networks and summarize a set of its protocols and standards. Also, we review and compare a number of popular congestion control mechanisms in wireless sensor networks (WSNs) and classify them into traffic control, resource control, and hybrid algorithms based on the congestion control strategy used. We present a comparative review of all existing congestion control approaches in 6LoWPAN networks. This paper highlights and discusses the differences between congestion control mechanisms for WSNs and 6LoWPAN networks as well as explaining the suitability and validity of WSN congestion control schemes for 6LoWPAN networks. Finally, this paper gives some potential directions for designing a novel congestion control protocol, which supports the IoT application requirements, in future work.

     

Finding an appropriate radio propagation model for rate aware congestion control mechanism in wireless sensor networks

Wireless Networks - Congestion control techniques are considered to be one of the most imperative ways to overcome various challenges in wireless sensor networks (WSNs). Undeniably, congestion has...     

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...     

Optimizing routing based on congestion control for wireless sensor networks

Along with the increasing demands for the applications running on the wireless sensor network (WSN), energy consumption and congestion become two main problems to be resolved urgently. However, in most scenes, these two problems aren’t considered simultaneously. To address this issue, in this paper a solution that sufficiently maintains energy efficiency and congestion control for energy-harvesting WSNs is presented. We first construct a queuing network model to detect the congestion degree of nodes. Then with the help of the principle of flow rate in hydraulics, an optimizing routing algorithm based on congestion control (CCOR) is proposed. The CCOR algorithm is designed by constructing two functions named link gradient and traffic radius based on node locations and service rate of packets. Finally, the route selection probabilities for each path are allocated according to the link flow rates. The simulation results show that the proposed solution significantly decreases the packet loss rate and maintains high energy efficiency under different traffic load.     

A Game Theory Based Multi Layered Intrusion Detection Framework for Wireless Sensor Networks

Most of the existing intrusion detection frameworks proposed for wireless sensor networks (WSNs) are computation and energy intensive, which adversely affect the overall lifetime of the WSNs. In addition, some of these frameworks generate a significant volume of IDS traffic, which can cause congestion in bandwidth constrained WSNs. In this paper, we aim to address these issues by proposing a game theory based multi layered intrusion detection framework for WSNs. The proposed framework uses a combination of specification rules and a lightweight neural network based anomaly detection module to identify the malicious sensor nodes. Additionally, the framework models the interaction between the IDS and the sensor node being monitored as a two player non-cooperative Bayesian game. This allows the IDS to adopt probabilistic monitoring strategies based on the Bayesian Nash Equilibrium of the game and thereby, reduce the volume of IDS traffic introduced into the sensor network. The framework also proposes two different reputation update and expulsion mechanisms to enforce cooperation and discourage malicious behavior among monitoring nodes. These mechanisms are based on two different methodologies namely, Shapley Value and Vickery–Clark–Grooves (VCG) mechanism. The complexity analysis of the proposed reputation update and expulsion mechanisms have been carried out and are shown to be linear in terms of the input sizes of the mechanisms. Simulation results show that the proposed framework achieves higher accuracy and detection rate across wide range of attacks, while at the same time minimizes the overall energy consumption and volume of IDS traffic in the WSN.     

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.     

Optimized Congestion Management Protocol for Healthcare Wireless Sensor Networks

The application of Wireless Sensor Networks (WSNs) in healthcare is dominant and fast growing. In healthcare WSN applications (HWSNs) such as medical emergencies, the network may encounter an unpredictable load which leads to congestion. Congestion problem which is common in any data network including WSN, leads to packet loss, increasing end-to-end delay and excessive energy consumption due to retransmission. In modern wireless biomedical sensor networks, increasing these two parameters for the packets that carry EKG signals may even result in the death of the patient. Furthermore, when congestion occurs, because of the packet loss, packet retransmission increases accordingly. The retransmission directly affects the lifetime of the nodes. In this paper, an Optimized Congestion management protocol is proposed for HWSNs when the patients are stationary. This protocol consists of two stages. In the first stage, a novel Active Queue Management (AQM) scheme is proposed to avoid congestion and provide quality of service (QoS). This scheme uses separate virtual queues on a single physical queue to store the input packets from each child node based on importance and priority of the source’s traffic. If the incoming packet is accepted, in the second stage, three mechanisms are used to control congestion. The proposed protocol detects congestion by a three-state machine and virtual queue status; it adjusts the child’s sending rate by an optimization function. We compare our proposed protocol with CCF, PCCP and backpressure algorithms using the OPNET simulator. Simulation results show that the proposed protocol is more efficient than CCF, PCCP and backpressure algorithms in terms of packet loss, energy efficiency, end-to-end delay and fairness.     

A Secure Routing Protocol with Trust and Energy Awareness for Wireless Sensor Network

Nodes in most of the deployments of Wireless Sensor Networks (WSNs) remain un-administered and exposed to variety of security attacks. Characterized by constrained resources and dynamically changing behavior of sensor nodes, reliable data delivery in WSNs is nontrivial. To counter node misbehavior attacks, traditional cryptographic and authentication based solutions have proved to be inappropriate due to high cost and incapability factors. Recently, trust based solutions have appeared to be viable solutions to address nodes’ misbehavior attacks. However, the existing trust based solutions incur high cost in trust estimation and network-wide dissemination which significantly increases traffic congestion and undermines network lifetime. This paper presents a Trust and Energy aware Secure Routing Protocol (TESRP) for WSN that exploits a distributed trust model for discovering and isolating misbehaving nodes. TESRP employs a multi-facet routing strategy that takes into consideration the trust level, residual energy, and hop-counts of neighboring nodes while making routing decisions. This strategy not only ensures data dissemination via trusted nodes but also balances out energy consumption among trusted nodes while traversing through shorter paths. Demonstrated by simulation results in NS-2, TESRP achieves improved performance in terms of energy consumption, throughput and network lifetime as compared to existing solutions.     

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.     

China's national research project on wireless sensor networks

China is experiencing rapid economic growth, but is also facing serious social and environmental problems, such as safety threats in the mining industry, environmental pollution, and transportation congestion. The advance of wireless sensor networks (WSNs) has made it possible to deploy low-cost networked sensors to address many huge challenges. A national research project, supported by the prestigious National 973 Program of China, was launched in September 2006. The project adopts an application-driven methodology and aims to address the real-world critical problems facing Chinese society. This project will follow a systematic approach, integrating technologies as a system solution to critical problems. Although this is a basic research project, the project has an ambitious goal of solving practical problems with the potential of commercialization. The success of this project will bring significant benefits to China's sustainable economic and social development.