Omprakash Gnawali

Macro-programming wireless sensor networks using Kairos

The literature on programming sensor networks has focused so far on providing higher-level abstractions for expressing local node behavior. Kairos is a natural next step in sensor network programming in that it allows the programmer to express, in a centralized fashion, the desired global behavior of a distributed computation on the entire sensor network. Kairos’ compile-time and runtime subsystems expose a small set of programming primitives, while hiding from the programmer the details of distributed-code generation and instantiation, remote data access and management, and inter-node program flow coordination. In this paper, we describe Kairos’ programming model, and demonstrate its suitability, through actual implementation, for a variety of distributed programs—both infrastructure services and signal processing tasks—typically encountered in sensor network literature: routing tree construction, localization, and object tracking. Our experimental results suggest that Kairos does not adversely affect the performance or accuracy of distributed programs, while our implementation experiences suggest that it greatly raises the level of abstraction presented to the programmer.

Routing without routes: the backpressure collection protocol

Current data collection protocols for wireless sensor networks are mostly based on quasi-static minimum-cost routing trees. We consider an alternative, highly-agile approach called backpressure routing, in which routing and forwarding decisions are made on a per-packet basis. Although there is a considerable theoretical literature on backpressure routing, it has not been implemented on practical systems to date due to concerns about packet looping, the effect of link losses, large packet delays, and scalability. Addressing these concerns, we present the Backpressure Collection Protocol (BCP) for sensor networks, the first ever implementation of dynamic backpressure routing in wireless networks. In particular, we demonstrate for the first time that replacing the traditional FIFO queue service in backpressure routing with LIFO queues reduces the average end-to-end packet delays for delivered packets drastically (75% under high load, 98% under low load). Further, we improve backpressure scalability by introducing a new concept of floating queues into the backpressure framework. Under static network settings, BCP shows a more than 60% improvement in max-min rate over the state of the art Collection Tree Protocol (CTP). We also empirically demonstrate the superior delivery performance of BCP in highly dynamic network settings, including conditions of extreme external interference and highly mobile sinks.

CTP: An efficient, robust, and reliable collection tree protocol for wireless sensor networks

We describe CTP, a collection routing protocol for wireless sensor networks. CTP uses three techniques to provide efficient, robust, and reliable routing in highly dynamic network conditions. CTPs link estimator accurately estimates link qualities by using feedback from both the data and control planes, using information from multiple layers through narrow, platform-independent interfaces. Second, CTP uses the Trickle algorithm to time the control traffic, sending few beacons in stable topologies yet quickly adapting to changes. Finally, CTP actively probes the topology with data traffic, quickly discovering and fixing routing failures. Through experiments on 13 different testbeds, encompassing seven platforms, six link layers, and multiple densities and frequencies, and detailed observations of a long-running sensor network application that uses CTP, we study how these three techniques contribute to CTPs overall performance.

Interaction of retransmission, blacklisting, and routing metrics for reliability in sensor network routing

Unpredictable and heterogeneous links in a wireless sensor network require techniques to avoid low delivery rate and high delivery cost. Three commonly used techniques to help discover high quality paths include (1) link-layer retransmission, (2) blacklisting bad links, and (3) end-to-end routing metrics. Using simulation and testbed experiments, we present the first systematic exploration of the tradeoffs of combinations of these approaches, quantifying the effects of each of these three techniques. We identify several key results: one is that per-hop retransmissions (ARQ) is a necessary addition to any other mechanism if reliable data delivery is a goal. Additional interactions between the services are more subtle. First, in a multihop network, either blacklisting or reliability metrics like ETX can provide consistent high-reliability paths when added to ARQ. Second, at higher deployment densities, blacklisting has a lower routing overhead than CTX. But at lower densities, blacklisting becomes less stable as the network partitions. These results are consistent across both simulation and testbed experiments. We conclude that ETX with retransmissions is the best choice in general, but that blacklisting may be worth considering at higher densities, either with or without ETX.

Structural damage detection and localization using NETSHM

Structural health monitoring (SHM) is an important application area for wireless sensor networks. SHM techniques attempt to autonomously detect and localize damage in large civil structures. Structural engineers often implement and test SHM algorithms in a higher level language such as C/Matlab. In this paper, we describe the design and evaluation of NETSHM, a sensor network system that allows structural engineers to program SHM applications in Mat-lab or C at a high level of abstraction. In particular, structural engineers do not have to understand the intricacies of wireless networking, or the details of sensor data acquisition. We have implemented a damage detection technique and a damage localization technique on a complete NETSHM prototype. Our experiments on small and medium-scale structures show that NETSHM is able to detect and localized damage perfectly with very few false-positives and no false negatives, and that it is robust even in realistic wireless environments

Data stashing: energy-efficient information delivery to mobile sinks through trajectory prediction

In this paper, we present a routing scheme that exploits knowledge about the behavior of mobile sinks within a network of data sources to minimize energy consumption and network congestion. For delay-tolerant network applications, we propose to route data not to the sink directly, but to send it instead to a relay node along an announced or predicted path of the mobile node that is close to the data source. The relay node will stash the information until the mobile node passes by and picks up the data. We use linear programming to find optimal relay nodes that minimize the number of necessary transmissions while guaranteeing robustness against link and node failures, as well as trajectory uncertainty. We show that this technique can drastically reduce the number of transmissions necessary to deliver data to mobile sinks. We derive mobility and association models from real-world data traces and evaluate our data stashing technique in simulations. We examine the influence of uncertainty in the trajectory prediction on the performance and robustness of the routing scheme.

The impact of network topology on collection performance

The network topology has a significant impact on the performance of collection protocols in wireless sensor networks. In this paper, we introduce an unobtrusive methodology to quantify the impact of the topology on the performance of collection protocols. Specifically, we propose a protocol-independent metric, the Expected Network Delivery, that quantifies the delivery performance that a collection protocol can be expected to achieve given the network topology. Experimental evidence obtained with two collection protocols on numerous topologies on testbeds shows that our approach enables a systematic evaluation of protocol performance.

Language independent analysis and classification of discussion threads in Coursera MOOC forums

In this work, we analyze the discussion threads from the forums of 60 Massive Open Online Courses (MOOCs) offered by Coursera and taught in 4 different languages. The types of interactions in such threads vary: there are discussions on close ended problems (e.g. solutions to assignments), open ended topics, course logistics, or just small talk among fellow students. We first study the evolution of the forum activities with respect to the normalized course duration. Then we investigate several language independent features to classify the discussion threads based on the types of the interactions among the users. We use default Coursera subforum categories (Study Groups, Assignments, Lectures, ...) to define the classes of interest and so the labels. We extract features related to structure, popularity, temporal dynamics of threads and diversity of the ids of the users. Text related features, word count aside, are avoided to apply the methods across discussion threads written in different languages and with various technical terminologies. Experiments show a classification performance with ROCAUC between 0.58 and 0.89, depending on the subforum class considered and with possibly noisy labels.

DualMOP-RPL: Supporting Multiple Modes of Downward Routing in a Single RPL Network

RPL is an IPv6 routing protocol for low-power and lossy networks (LLNs) designed to meet the requirements of a wide range of LLN applications including smart grid AMIs, home and building automation, industrial and environmental monitoring, health care, wireless sensor networks, and the Internet of Things (IoT) in general with thousands and millions of nodes interconnected through multihop mesh networks. RPL constructs tree-like routing topology rooted at an LLN border router (LBR) and supports bidirectional IPv6 communication to and from the mesh devices by providing both upward and downward routing over the routing tree. In this article, we focus on the interoperability of downward routing and supporting its two modes of operations (MOPs) defined in the RPL standard (RFC 6550). Specifically, we show that there exists a serious connectivity problem in RPL protocol when two MOPs are mixed within a single network, even for standard-compliant implementations, which may result in network partitions. To address this problem, this article proposes DualMOP-RPL, an enhanced version of RPL, which supports nodes with different MOPs for downward routing to communicate gracefully in a single RPL network while preserving the high bidirectional data delivery performance. DualMOP-RPL allows multiple overlapping RPL networks in the same geographical regions to cooperate as a single densely connected network even if those networks are using different MOPs. This will not only improve the link qualities and routing performances of the networks but also allow for network migrations and alternate routing in the case of LBR failures. We evaluate DualMOP-RPL through extensive simulations and testbed experiments and show that our proposal eliminates all the problems we have identified.

Forwarder Selection in Multi-transmitter Networks

Recent work has shown that network protocols which rely on precisely-timed concurrent transmissions can achieve reliable, energy-efficient, and conceptually simple network flooding. While these multi-transmitter schemes work well, they require all nodes in the network to forward every data packet, which has inherent inefficiencies for non-flooding traffic patterns (where not all nodes need to receive the data). In this work, we formalize the concept of the “useful” forwarder set for point-to-point transmissions in low power multi-transmitter networks, those nodes which help forward data to the destination. We present a mechanism for approximating membership in this set based on simple heuristics. Incorporating forwarder selection on our 66-node testbed reduced radio duty cycle by 30% and increased throughput by 49% relative to concurrent flooding while preserving a 99.4% end-to-end packet reception ratio under the collection traffic pattern. We envision forwarder selection as a fundamental task in an efficient multi-transmitter networking stack. This work demonstrates that adding forwarder selection can improve energy efficiency and throughput while providing similar end-to-end packet delivery rates to flooding.