We present Sprinkler, a reliable data dissemination service for wireless embedded devices which are constrained in energy, processing speed, and memory. Sprinkler embeds a virtual grid over the network whereby it can locally compute a connected dominating set of the devices to avoid redundant transmissions ,and a transmission schedule to avoid collisions. Sprinkler transmits O(1) times the optimum number of packets in O(1) of the optimum latency; its time complexity is O(1). Thus, Sprinkler is suitable for resource-constrained wireless embedded devices.

A number of multi-hop, wireless, network programming systems have emerged for sensor network retasking but none of these systems support a cryptographically-strong, publickey-based system for source authentication and integrity verification. The traditional technique for authenticating a program binary, namely a digital signature of the program hash, is poorly suited to resource-contrained sensor nodes. Our solution to the secure programming problem leverages authenticated streams, is consistent with the limited resources of a typical sensor node, and can be used to secure existing network programming systems. Under our scheme, a program binary consists of several code and data segments that are mapped to a series of messages for transmission over the network. An advertisement, consisting of the program name, version number, and a hash of the very first message, is digitally signed and transmitted first. The advertisement authenticates the first message, which in turn contains a hash of the second message. Similarly, the second message contains a hash of the third message, and so on, binding each message to the one logically preceding it in the series through the hash chain. We augmented the Deluge network programming system with our protocol and evaluated the resulting system performance.

With sensor networks expected to be deployed for long periods of time, the ability to reprogram them remotely is necessary for providing new services, fixing bugs, and enhancing applications and system software. Given the envisioned scales of future sensor network deployments, their restricted accessibility, and the limited energy and computing resources of sensors, transmitting raw binary images is inefficient. We present a technique to minimize the cost of application evolution by remotely and incrementally linking updated modules at the base station, and distributing deltas of the pre-linked software modules. This paper provides details of our implementation, some preliminary results, and surveys critical research issues in developing a comprehensive framework for reprogramming sensor networks. 1.

Wireless sensor networks need an efficient and reliable reprogramming service to facilitate management and maintenance tasks. In this article we first outline a framework to examine different functions in reprogramming, followed by an analysis of reprogramming challenges. We then provide a comprehensive survey of the state-of-the-art reprogramming systems, and discuss different approaches to address these challenges. Finally we explore performance, protocol behavior, and the impact of several design factors. A typical wireless sensor network (WSN) consists of a large number of small-sized battery-powered sensor nodes that integrate sensing, computing, and communication capabilities. WSN applications include geophysical/structural/habitat monitoring, security surveillance, disaster area or battlefield information collection,

Reliable dissemination of bulk data is one of the important problems in sensor net-works. For example, programming or upgrading the software in sensors at run-time requires reliable dissemination of a new program across the network. In this paper, we present Infuse, a time division multiple access (TDMA) based reliable data dis-semination protocol. Infuse takes two input parameters: (i) the choice of the recovery algorithm (from one of two presented in this paper) to deal with unexpected channel errors (e.g., message corruption, varying signal strength), and (ii) whether a sensor should listen only to a subset of its neighbors to reduce the amount of active radio time. Based on these parameters, we obtain four possible versions of Infuse. We com-pare the performance of these versions to assist a designer in selecting the appropriate version based on the network characteristics. Furthermore, we demonstrate Infuse in the context of network programming.

In this paper, we present Flask, a new programming language for sensor networks that is focused on providing an easy-to-use dataflow programming model. In Flask, programmers build applications by composing chains of operators into a dataflow graph that may reside on individual nodes or span multiple nodes in the network. To compose dataflow graphs across sensor nodes, Flask supports a lean, general-purpose communication abstraction, called Flows, that provides publish/subscribe semantics over efficient routing trees. At the heart of Flask is a programmatic wiring language, based on the functional language OCaml [13]. Flask’s wiring language allows dataflow graphs to be synthesized programmatically. The Flask wiring program is interpreted at compile time to generate a sensor node program in NesC, which is then compiled to a binary. Our design of Flask makes three main contributions. First, Flask allows the programmer to specify distributed dataflow applications in a high-level language while retaining the efficiency of compiled binaries and full access to TinyOS components. Second, Flask provides a unified framework for distributing dataflow applications across the network, allowing programmers to focus on application logic rather than details of routing code. Finally, Flask’s programmatic wiring language enables rich composition of dataflow operators, making it possible to develop higher-level programming models or languages directly in Flask. In this paper, we describe the design and implementation of the Flask language, its runtime system, the Flows communication interface, and a compiler that produces NesC code. We evaluate Flask through two motivating applications: a distributed detector of seismic activity (e.g., for studying earthquakes), and an implementation of the TinyDB query language built using Flask, showing that using Flask considerably reduces code complexity and memory size while achieving high runtime efficiency.

Abstract — Over-the-air programming (OAP) is a fundamental service in sensor networks that relies upon reliable broadcast for efficient dissemination. As such, existing OAP protocols become decidedly inefficient (with respect to energy, communication or delay) in unreliable broadcast environments, such as those with relatively high node density or noise. In this paper, we consider OAP approaches based on rateless codes, which significantly improve OAP in such environments by drastically reducing the need for packet rebroadcasting. We thus design and implement two rateless OAP protocols, rateless Deluge and ACKless Deluge, both of which replace the data transfer mechanism of the established OAP Deluge protocol with rateless analogs. Experiments with Tmote Sky motes on single-hop networks with packet loss rates of 7 % show these protocols to save significantly in communication over regular Deluge (roughly 15-30 % savings in the data plane, and 50-80 % in the control plane), and multi-hop experiments reveal similar trends. Simulations further shows that our new protocols scale better than standard Deluge (in terms of communication and energy) to high network density. TinyOS code for our implementation can be found at

We present an actor platform for wireless sensor networks (WSNs). A typical WSN may consist of hundreds to tens of thousands of tiny nodes embdedded in an environment. Hence, manual reprogramming of nodes for development, fixing bugs and updating features is an arduous process; moreover, in some cases physical access to nodes is simply out of the question. In an attempt to address this problem, network reprogramming tools such as Deluge and MNP [10, 14] have been developed. Unfortunately, these bulk reprogramming services incur significant costs in terms of energy usage, latency, and loss of sensing coverage when nodes are rebooted into a new program image. ActorNet, in contrast, provides an environment for lightweight concurrent object-oriented mobile code on WSNs. As such, actorNet enables a wide range of new dynamic applications on WSNs, including support for fully customizable queries and aggregation functions, in-network interactive debugging facilities, and high-level concurrent programming on the inherently parallel sensor network platform. Moreover, actorNet cleanly integrates all of these features into a fine-tuned, multi-threaded embedded Scheme interpreter which supports compact, maintainable programs – a significant advantage over primitive stack-based virtual machines [15, 8]. 1

Abstract. We present Typhoon, a protocol designed to reliably deliver large objects to all the nodes of a wireless sensor network (WSN). Typhoon uses a combination of spatially-tuned timers, prompt retransmissions, and frequency diversity to reduce contention and promote spatial re-use. We evaluate the performance benefits these techniques provide through extensive simulations and experiments in an indoor testbed. Our results show that Typhoon is able to reduce dissemination time and energy consumption by up to three times compared to Deluge. These improvements are most prominent in sparse and lossy networks that represent real-life WSN deployments. 1

Network protocols are typically designed and tested individually. In practice, however, applications use multiple protocols concurrently. This discrepancy can lead to failures from unanticipated interactions between protocols. In this paper, we argue that sensor network communication stacks should have an isolation layer, whose purpose is to make each protocol’s perception of the wireless channel independent of what other protocols are running. We identify two key mechanisms the isolation layer must provide: shared collision avoidance and fair channel allocation. We present an example design of an isolation layer that builds on the existing algorithms of grant-to-send and fair queueing. However, the complexities of wireless make these mechanisms insufficient by themselves. We therefore propose two new mechanisms that address these limitations: channel decay and fair cancellation. Incorporating these new mechanisms reduces the increase in end-to-end delivery cost associated with concurrently operating two protocols by more than 60%. The isolation layer improves median protocol fairness from 0.52 to 0.96 in Jain’s fairness index. Together, these results show that using an isolation layer makes protocols more efficient and robust.