Congestion control protocols in wireless sensor networks: A survey

The performance of wireless sensor networks (WSN) is affected by the lossy communication medium, application diversity, dense deployment, limited processing power and storage capacity, frequent topology change. All these limitations provide significant and unique design challenges to data transport control in wireless sensor networks. An effective transport protocol should consider reliable message delivery, energy-efficiency, quality of service and congestion control. The latter is vital for achieving a high throughput and a long network lifetime. Despite the huge number of protocols proposed in the literature, congestion control in WSN remains challenging. A review and taxonomy of the state-of-the-art protocols from the literature up to 2013 is provided in this paper. First, depending on the control policy, the protocols are divided into resource control vs. traffic control. Traffic control protocols are either reactive or preventive (avoiding). Reactive solutions are classified following the reaction scale, while preventive solutions are split up into buffer limitation vs. interference control. Resource control protocols are classified according to the type of resource to be tuned. © 2014 IEEE

Congestion and medium access control in 6LoWPAN WSN

In computer networks, congestion is a condition in which one or more egressinterfaces are offered more packets than are forwarded at any given instant [1]. In wireless sensor networks, congestion can cause a number of problems including packet loss, lower throughput and poor energy efficiency. These problems can potentially result in a reduced deployment lifetime and underperforming applications. Moreover, idle radio listening is a major source of energy consumption therefore low-power wireless devices must keep their radio transceivers off to maximise their battery lifetime. In order to minimise energy consumption and thus maximise the lifetime of wireless sensor networks, the research community has made significant efforts towards power saving medium access control protocols with Radio Duty Cycling. However, careful study of previous work reveals that radio duty cycle schemes are often neglected during the design and evaluation of congestion control algorithms. This thesis argues that the presence (or lack) of radio duty cycle can drastically influence the performance of congestion control mechanisms. To investigate if previous findings regarding congestion control are still applicable in IPv6 over low power wireless personal area and duty cycling networks; some of the most commonly used congestion detection algorithms are evaluated through simulations. The research aims to develop duty cycle aware congestion control schemes for IPv6 over low power wireless personal area networks. The proposed schemes must be able to maximise the networks goodput, while minimising packet loss, energy consumption and packet delay. Two congestion control schemes, namely DCCC6 (Duty Cycle-Aware Congestion Control for 6LoWPAN Networks) and CADC (Congestion Aware Duty Cycle MAC) are proposed to realise this claim. DCCC6 performs congestion detection based on a dynamic buffer. When congestion occurs, parent nodes will inform the nodes contributing to congestion and rates will be readjusted based on a new rate adaptation scheme aiming for local fairness. The child notification procedure is decided by DCCC6 and will be different when the network is duty cycling. When the network is duty cycling the child notification will be made through unicast frames. On the contrary broadcast frames will be used for congestion notification when the network is not duty cycling. Simulation and test-bed experiments have shown that DCCC6 achieved higher goodput and lower packet loss than previous works. Moreover, simulations show that DCCC6 maintained low energy consumption, with average delay times while it achieved a high degree of fairness. CADC, uses a new mechanism for duty cycle adaptation that reacts quickly to changing traffic loads and patterns. CADC is the first dynamic duty cycle pro- tocol implemented in Contiki Operating system (OS) as well as one of the first schemes designed based on the arbitrary traffic characteristics of IPv6 wireless sensor networks. Furthermore, CADC is designed as a stand alone medium access control scheme and thus it can easily be transfered to any wireless sensor network architecture. Additionally, CADC does not require any time synchronisation algorithms to operate at the nodes and does not use any additional packets for the exchange of information between the nodes (For example no overhead). In this research, 10000 simulation experiments and 700 test-bed experiments have been conducted for the evaluation of CADC. These experiments demonstrate that CADC can successfully adapt its cycle based on traffic patterns in every traffic scenario. Moreover, CADC consistently achieved the lowest energy consumption, very low packet delay times and packet loss, while its goodput performance was better than other dynamic duty cycle protocols and similar to the highest goodput observed among static duty cycle configurations

Security for the Industrial IoT: The Case for Information-Centric Networking

Industrial production plants traditionally include sensors for monitoring or documenting processes, and actuators for enabling corrective actions in cases of misconfigurations, failures, or dangerous events. With the advent of the IoT, embedded controllers link these `things' to local networks that often are of low power wireless kind, and are interconnected via gateways to some cloud from the global Internet. Inter-networked sensors and actuators in the industrial IoT form a critical subsystem while frequently operating under harsh conditions. It is currently under debate how to approach inter-networking of critical industrial components in a safe and secure manner. In this paper, we analyze the potentials of ICN for providing a secure and robust networking solution for constrained controllers in industrial safety systems. We showcase hazardous gas sensing in widespread industrial environments, such as refineries, and compare with IP-based approaches such as CoAP and MQTT. Our findings indicate that the content-centric security model, as well as enhanced DoS resistance are important arguments for deploying Information Centric Networking in a safety-critical industrial IoT. Evaluation of the crypto efforts on the RIOT operating system for content security reveal its feasibility for common deployment scenarios.Comment: To be published at IEEE WF-IoT 201

Leveraging Resources on Anonymous Mobile Edge Nodes

Smart devices have become an essential component in the life of mankind. The quick rise of smartphones, IoTs, and wearable devices enabled applications that were not possible few years ago, e.g., health monitoring and online banking. Meanwhile, smart sensing laid the infrastructure for smart homes and smart cities. The intrusive nature of smart devices granted access to huge amounts of raw data. Researchers seized the moment with complex algorithms and data models to process the data over the cloud and extract as much information as possible. However, the pace and amount of data generation, in addition to, networking protocols transmitting data to cloud servers failed short in touching more than 20% of what was generated on the edge of the network. On the other hand, smart devices carry a large set of resources, e.g., CPU, memory, and camera, that sit idle most of the time. Studies showed that for plenty of the time resources are either idle, e.g., sleeping and eating, or underutilized, e.g. inertial sensors during phone calls. These findings articulate a problem in processing large data sets, while having idle resources in the close proximity. In this dissertation, we propose harvesting underutilized edge resources then use them in processing the huge data generated, and currently wasted, through applications running at the edge of the network. We propose flipping the concept of cloud computing, instead of sending massive amounts of data for processing over the cloud, we distribute lightweight applications to process data on users\u27 smart devices. We envision this approach to enhance the network\u27s bandwidth, grant access to larger datasets, provide low latency responses, and more importantly involve up-to-date user\u27s contextual information in processing. However, such benefits come with a set of challenges: How to locate suitable resources? How to match resources with data providers? How to inform resources what to do? and When? How to orchestrate applications\u27 execution on multiple devices? and How to communicate between devices on the edge? Communication between devices at the edge has different parameters in terms of device mobility, topology, and data rate. Standard protocols, e.g., Wi-Fi or Bluetooth, were not designed for edge computing, hence, does not offer a perfect match. Edge computing requires a lightweight protocol that provides quick device discovery, decent data rate, and multicasting to devices in the proximity. Bluetooth features wide acceptance within the IoT community, however, the low data rate and unicast communication limits its use on the edge. Despite being the most suitable communication protocol for edge computing and unlike other protocols, Bluetooth has a closed source code that blocks lower layer in front of all forms of research study, enhancement, and customization. Hence, we offer an open source version of Bluetooth and then customize it for edge computing applications. In this dissertation, we propose Leveraging Resources on Anonymous Mobile Edge Nodes (LAMEN), a three-tier framework where edge devices are clustered by proximities. On having an application to execute, LAMEN clusters discover and allocate resources, share application\u27s executable with resources, and estimate incentives for each participating resource. In a cluster, a single head node, i.e., mediator, is responsible for resource discovery and allocation. Mediators orchestrate cluster resources and present them as a virtually large homogeneous resource. For example, two devices each offering either a camera or a speaker are presented outside the cluster as a single device with both camera and speaker, this can be extended to any combination of resources. Then, mediator handles applications\u27 distribution within a cluster as needed. Also, we provide a communication protocol that is customizable to the edge environment and application\u27s need. Pushing lightweight applications that end devices can execute over their locally generated data have the following benefits: First, avoid sharing user data with cloud server, which is a privacy concern for many of them; Second, introduce mediators as a local cloud controller closer to the edge; Third, hide the user\u27s identity behind mediators; and Finally, enhance bandwidth utilization by keeping raw data at the edge and transmitting processed information. Our evaluation shows an optimized resource lookup and application assignment schemes. In addition to, scalability in handling networks with large number of devices. In order to overcome the communication challenges, we provide an open source communication protocol that we customize for edge computing applications, however, it can be used beyond the scope of LAMEN. Finally, we present three applications to show how LAMEN enables various application domains on the edge of the network. In summary, we propose a framework to orchestrate underutilized resources at the edge of the network towards processing data that are generated in their proximity. Using the approaches explained later in the dissertation, we show how LAMEN enhances the performance of applications and enables a new set of applications that were not feasible

A Novel Approach To Intelligent Navigation Of A Mobile Robot In A Dynamic And Cluttered Indoor Environment

The need and rationale for improved solutions to indoor robot navigation is increasingly driven by the influx of domestic and industrial mobile robots into the market. This research has developed and implemented a novel navigation technique for a mobile robot operating in a cluttered and dynamic indoor environment. It divides the indoor navigation problem into three distinct but interrelated parts, namely, localization, mapping and path planning. The localization part has been addressed using dead-reckoning (odometry). A least squares numerical approach has been used to calibrate the odometer parameters to minimize the effect of systematic errors on the performance, and an intermittent resetting technique, which employs RFID tags placed at known locations in the indoor environment in conjunction with door-markers, has been developed and implemented to mitigate the errors remaining after the calibration. A mapping technique that employs a laser measurement sensor as the main exteroceptive sensor has been developed and implemented for building a binary occupancy grid map of the environment. A-r-Star pathfinder, a new path planning algorithm that is capable of high performance both in cluttered and sparse environments, has been developed and implemented. Its properties, challenges, and solutions to those challenges have also been highlighted in this research. An incremental version of the A-r-Star has been developed to handle dynamic environments. Simulation experiments highlighting properties and performance of the individual components have been developed and executed using MATLAB. A prototype world has been built using the WebotsTM robotic prototyping and 3-D simulation software. An integrated version of the system comprising the localization, mapping and path planning techniques has been executed in this prototype workspace to produce validation results

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

Wireless Sensor Networks

The aim of this book is to present few important issues of WSNs, from the application, design and technology points of view. The book highlights power efficient design issues related to wireless sensor networks, the existing WSN applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and make a contribution in this field for themselves. It is believed that this book serves as a comprehensive reference for graduate and undergraduate senior students who seek to learn latest development in wireless sensor networks

A mobile agent and message ferry mechanism based routing for delay tolerant network

Delay Tolerant Network (DTN) is a class of networks characterized by long delays, frequent disconnections and partitioning of communication paths between network nodes. Due to the frequent disconnection and network partitioning, the overall performance of the network will be deteriorated sharply. The problem is how to make the network fairly connected to optimize data routing and enhance the performance of a network. The aim of this study is to improve the performance of DTN by minimizing end-to-end delivery time and increasing message delivery ratio. Therefore, this research tackles the problem of intermittent connectivity and network partitioning by introducing Agents and Ferry Mechanism based Routing (AFMR). The AFMR comprises of two stages by applying two schemes: mobile agents and ferry mechanism. The agents' scheme is proposed to deal with intermittent connectivity and network partitioning by collecting the basic information about network connection such as signal strength, nodes position in the network and distance to the destination nodes to minimize end-to-end delivery time. The second stage is to increase the message delivery ratio by moving the nodes towards the path with available network connectivity based on agents' feedback. The AFMR is evaluated through simulations and the results are compared with those of Epidemic, PRoPHET and Message Ferry (MF). The findings demonstrate that AFMR is superior to all three, with respect to the average end-to-end delivery time, message delivery ratio, network load and message drop ratio, which are regarded as extremely important metrics for the evaluation of DTN routing protocols. The AFMR achieves improved network performance in terms of end-to-end delivery time (56.3%); enhanced message delivery ratio (60.0%); mitigation of message drop (63.5%) and reduced network load (26.1 %). The contributions of this thesis are to enhance the performance of DTN by significantly overcoming the intermittent connectivity and network partitioning problems in the network