Chieh-Yih Wan

CODA: congestion detection and avoidance in sensor networks

Event-driven sensor networks operate under an idle or light load and then suddenly become active in response to a detected or monitored event. The transport of event impulses is likely to lead to varying degrees of congestion in the network depending on the sensing application. It is during these periods of event impulses that the likelihood of congestion is greatest and the information in transit of most importance to users. To address this challenge we propose an energy efficient congestion control scheme for sensor networks called CODA (COngestion Detection and Avoidance) that comprises three mechanisms: (i) receiver-based congestion detection; (ii) open-loop hop-by-hop backpressure; and (iii) closed-loop multi-source regulation. We present the detailed design, implementation, and evaluation of CODA using simulation and experimentation. We define two important performance metrics (i.e., energy tax and fidelity penalty) to evaluate the impact of CODA on the performance of sensing applications. We discuss the performance benefits and practical engineering challenges of implementing CODA in an experimental sensor network testbed based on Berkeley motes using CSMA. Simulation results indicate that CODA significantly improves the performance of data dissemination applications such as directed diffusion by mitigating hotspots, and reducing the energy tax with low fidelity penalty on sensing applications. We also demonstrate that CODA is capable of responding to a number of congestion scenarios that we believe will be prevalent as the deployment of these networks accelerates.

PSFQ: a reliable transport protocol for wireless sensor networks

We propose PSFQ (Pump Slowly, Fetch Quickly), a reliable transport protocol suitable for a new class of reliable data applications emerging in wireless sensor networks. For example, currently sensor networks tend to be application specific and are typically hard-wired to perform a specific task efficiently at low cost; however, there is an emerging need to be able to re-task or reprogram groups of sensors in wireless sensor networks on the fly (e.g., during disaster recovery). Due to the application-specific nature of sensor networks, it is difficult to design a single monolithic transport system that can be optimized for every application. PSFQ takes a different approach and supports a simple, robust and scalable transport that is customizable to meet the needs of different reliable data applications. To our knowledge there has been little or no work on the design of an efficient reliable transport protocol for wireless sensor networks, even though some techniques found in IP networks have some relevance to the solution space, such as, the body of work on reliable multicast. We present the design and implementation of PSFQ, and evaluate the protocol using the ns-2 simulator and an experimental wireless sensor testbed based on Berkeley motes. We show through simulation and experimentation that PSFQ can out perform existing related techniques (e.g., an idealized SRM scheme) and is highly responsive to the various error conditions experienced in wireless sensor networks, respectively.

Design, implementation, and evaluation of cellular IP

Wireless access to Internet services will become typical, rather than the exception as it is today. Such a vision presents great demands on mobile networks. Mobile IP represents a simple and scalable global mobility solution but lacks the support for fast handoff control and paging found in cellular telephony networks. In contrast, second- and third-generation cellular systems offer seamless mobility support but are built on complex and costly connection-oriented networking infrastructure that lacks the inherent flexibility, robustness, and scalability found in IP networks. In this article we present cellular IP, a micro-mobility protocol that provides seamless mobility support in limited geographical areas. Cellular IP, which incorporates a number of important cellular system design principles such as paging in support of passive connectivity, is built on a foundation of IP forwarding, minimal signaling, and soft-state location management. We discuss the design, implementation, and evaluation of a cellular IP testbed developed at Columbia University over the past several years. Built on a simple, low-cost, plug-and-play systems paradigm, cellular IP software enables the construction of arbitrary-sized access networks scaling from picocellular to metropolitan area networks.

Comparison of IP micromobility protocols

We present a performance comparison of a number of key micromobility protocols that have been discussed in the IETF Mobile IP Working Group over the past several years. IP micromobility protocols complement Mobile IP by offering fast and seamless handoff control in limited geographical areas, and IP paging in support of scalability and power conservation. We show that despite the apparent differences between IP micromobility protocols, the operational principles that govern them are largely similar. We use this observation to establish a generic micromobility model to better understand design and performance trade offs. A number of key design choices are identified within the context of the generic model related to handoff quality and route control messaging. We present simulation results for Cellular IP, Hawaii, and Hierarchical Mobile IP, and evaluate the handoff performance of these protocols. Simulation results presented in this article are based on the Columbia IP Micromobility Software (CIMS), which is freely available from the Web (comet.columbia. edu/micromobility) for experimentation.

Siphon: overload traffic management using multi-radio virtual sinks in sensor networks

There is a critical need for new thinking regarding overload traffic management in sensor networks. It has now become clear that experimental sensor networks (e.g., mote networks) and their applications commonly experience periods of persistent congestion and high packet loss, and in some cases even congestion collapse. This significantly impacts application fidelity measured at the physical sinks, even under light to moderate traffic loads, and is a direct product of the funneling effect; that is, the many-to-one multi-hop traffic pattern that characterizes sensor network communications. Existing congestion control schemes are effective at mitigating congestion through rate control and packet drop mechanisms, but do so at the cost of significantly reducing application fidelity measured at the sinks. To address this problem we propose to exploit the availability of a small number of all wireless, multi-radio virtual sinks that can be randomly distributed or selectively placed across the sensor field. Virtual sinks are capable of siphoning off data events from regions of the sensor field that are beginning to show signs of high traffic load. In this paper, we present the design, implementation, and evaluation of Siphon, a set of fully distributed algorithms that support virtual sink discovery and selection, congestion detection, and traffic redirection in sensor networks. Siphon is based on a Stargate implementation of virtual sinks that uses a separate longer-range radio network (based on IEEE 802.11) to siphon events to one or more physical sinks, and a short-range mote radio to interact with the sensor field at siphon points. Results from analysis, simulation and an experimental 48 Mica2 mote testbed show that virtual sinks can scale mote networks by effectively managing growing traffic demands while minimizing the impact on application fidelity.

Overload traffic management for sensor networks

There is a critical need for new thinking regarding overload traffic management in sensor networks. It has now become clear that experimental sensor networks (e.g., mote networks) and their applications commonly experience periods of persistent congestion and high packet loss, and in some cases even congestion collapse. This significantly impacts application fidelity measured at the physical sinks, even under light to moderate traffic loads, and is a direct product of the funneling effect; that is, the many-to-one multihop traffic pattern that characterizes sensor network communications. Existing congestion control schemes are effective at mitigating congestion through rate control and packet drop mechanisms, but do so at the cost of significantly reducing application fidelity measured at the sinks. To address this problem we propose to exploit the availability of a small number of all wireless, multiradio virtual sinks that can be randomly distributed or selectively placed across the sensor field. Virtual sinks are capable of siphoning off data events from regions of the sensor field that are beginning to show signs of high traffic load. In this paper, we present the design, implementation, and evaluation of Siphon, a set of fully distributed algorithms that support virtual sink discovery and selection, congestion detection, and traffic redirection in sensor networks. Siphon is based on a Stargate implementation of virtual sinks that uses a separate longer range radio network (based on IEEE 802.11) to siphon events to one or more physical sinks, and a short-range mote radio to interact with the sensor field at siphon points. Results from analysis, simulation and an experimental 48 Mica2 mote testbed show that virtual sinks can scale mote networks by effectively managing growing traffic demands while minimizing any negative impact on application fidelity. Additionally, we show the scheme is competitive with respect to energy consumption compared to a network composed of only motes.

Energy-efficient congestion detection and avoidance in sensor networks

Event-driven sensor networks operate under an idle or light load and then suddenly become active in response to a detected or monitored event. The transport of event impulses is likely to lead to varying degrees of congestion in the network depending on the distribution and rate of packet sources in the network. It is during these periods of event impulses that the likelihood of congestion is greatest and the information in transit of most importance to users. To address this challenge we propose an energy-efficient congestion control scheme for sensor networks called CODA (COngestion Detection and Avoidance) that comprises three mechanisms: (i) receiver-based congestion detection; (ii) open-loop hop-by-hop backpressure; and (iii) closed-loop multisource regulation. We present the detailed design, implementation, and evaluation of CODA using simulation and experimentation. We define three important performance metrics (i.e., energy tax, fidelity penalty, and power) to evaluate the impact of CODA on the performance of sensing applications. We discuss the performance benefits and practical engineering challenges of implementing CODA in an experimental sensor network testbed based on Berkeley motes using CSMA. Simulation results indicate that CODA significantly improves the performance of data dissemination applications such as directed diffusion by mitigating hotspots, and reducing the energy tax and fidelity penalty on sensing applications. We also demonstrate that CODA is capable of responding to a number of congestion scenarios that we believe will be prevalent as the deployment of these networks accelerates.

A cellular IP testbed demonstrator

Cellular IP is a wireless Internet access technology that operates on mobile hosts, base stations and Internet gateways. Cellular IP combines the capability of cellular networks to provide high performance handoff and efficient location management of active and idle mobile users with the inherent flexibility, robustness and scalability found in IP networks. We provide an overview of the cellular IP routing, handoff and paging algorithms and their implementation in a pico-cellular testbed. The protocol has been under development at Columbia University for the past several years initially as a joint project between the Center for Telecommunications Research and Ericsson Research.

A case for all-wireless, dual-radio virtual sinks

Wireless sensor networks are emerging technologies that offer low cost, distributed monitoring solutions for a wide variety of applications and systems. One application driving the development of sensor networks is the reporting of conditions within a region of interest where the environment can abruptly change due to an sudden event, such as enemy and target movements on the battlefield, or biochemical attacks, fires, etc. Our work focuses on sensor systems that need to efficiently deliver information during and immediately following an event that triggers such an abrupt change. Congestion control and load balancing are critical issues in such sensor networks where the sensor field can move instantaneously from almost zero load to overload conditions. It is during these impulse or overload periods that the events in transit are of most importance and most likely to be lost due to congestion. Existing congestion control algorithms [1] [2] [3] are limited under these conditions because they rely on rate control or packet drop mechanisms at source or intermediate sensor nodes that can significantly impact the application’s fidelity, as measured at one or more physical sinks. We propose randomly distributing a small number of allwireless dual radio virtual sinks throughout the sensor field that are capable of offering the existing low-power sensor network enhanced congestion avoidance support when persistent congestion is detected. In essence virtual sinks operate as safety valves in the sensor field to selectively siphon off high load traffic in order to maintain the fidelity of the application signal at the physical sink and to alleviate the funneling effect, as discussed in Section 2.1. We call these specialized nodes virtual sinks to distinguish them from physical sinks, which typically have a wireline

Reliable Transport for Sensor Networks

We propose PSFQ (Pump Slowly, Fetch Quickly), a reliable transport protocol suitable for a new class of reliable data applications emerging in wireless sensor networks. For example, currently sensor networks tend to be application specific and are typically hard-wired to perform a specific task efficiently at low cost; however, there is an emerging need to be able to re-task or reprogram groups of sensors in wireless sensor networks on the fly (e.g., during disaster recovery). Due to the application-specific nature of sensor networks, it is difficult to design a single monolithic transport system that can be optimized for every application. PSFQ takes a different approach and supports a simple, robust and scalable transport that is customizable to meet the needs of different reliable data applications. To our knowledge there has been little work on the design of an efficient reliable transport protocol for wireless sensor networks, even though some techniques found in IP networks have some relevance to the solution space, such as, the body of work on reliable multicast. We present the design and implementation of PSFQ, and evaluate the protocol using the ns-2 simulator and an experimental wireless sensor testbed based on Berkeley motes. We show through simulation and experimentation that PSFQ can out perform existing related techniques (e.g., an idealized SRM scheme) and is highly responsive to the various error conditions experienced in wireless sensor networks, respectively.