ACM Transactions on Sensor Networks (TOSN)

Langendoen, Koen; Meier, Andreas

doi: 10.1145/1806895.1806905pmid: N/A

The fundamental wireless sensors network (WSN) requirement to be energy-efficient has produced a whole range of specialized medium access control (MAC) protocols. They differ in how performance (latency, throughput) is traded off for a reduction in energy consumption. The question “which protocol is best?” is difficult to answer because (i) this depends on specific details of the application requirements and hardware characteristics involved, and (ii) protocols have mainly been assessed individually with each outperforming the canonical S-MAC protocol, but with different simulators, hardware platforms, and workloads. This article addresses that void for low data-rate applications where collisions are of little concern, making an analytical approach tractable in which latency and energy consumption are modeled as functions of key protocol parameters (duty cycle, slot length, number of slots, etc.). By exhaustive search we determine the Pareto-optimal protocol settings for a given workload (data rate, network topology). Of the protocols compared we find that WiseMAC strikes the best latency versus energy-consumption tradeoff across the range of workloads considered. In particular, its random access scheme in combination with local synchronization not only minimizes protocol overhead, but also maximizes the available channel bandwidth.

Kwon, Youngmin; Mechitov, Kirill; Sundresh, Sameer; Kim, Wooyoung; Agha, Gul

doi: 10.1145/1806895.1806898pmid: N/A

The process of determining the physical locations of nodes in a wireless sensor network is known as localization . Self-localization is critical for large-scale sensor networks, because manual or assisted localization is often impractical due to time requirements, economic constraints, or inherent limitations of the deployment scenarios. We propose scalable solutions for reliably localizing wireless sensor networks in environments conducive to several types of ranging errors. We follow a hybrid hardware-software approach for acoustic ranging or radio interferometry to acquire internode distance measurements, and a resilient self-localization algorithm to compute the node location estimates. The acoustic ranging method improves on previous work, extending the practical measurement range up to 35 m in grassy outdoor environments, achieving a distance-invariant median measurement error of about 1% (33 cm). The localization algorithm is based on least-squares scaling with soft constraints. Empirical evaluation using ranging results obtained from sensor network field experiments and simulations confirms that our approach is more resilient than multidimensional scaling (MDS) algorithms against large-magnitude ranging errors and sparse range measurements: conditions that are common in large-scale outdoor sensor network deployments.

Kalpakis, Konstantinos

doi: 10.1145/1806895.1806904pmid: N/A

We consider two related data gathering problems for wireless sensor networks (WSNs). The MLDA problem is concerned with maximizing the system lifetime T so that we can perform T rounds of data gathering with in-network aggregation, given the initial available energy of the sensors. The M 2 EDA problem is concerned with minimizing the maximum energy consumed by any one sensor when performing T rounds of data gathering with in-network aggregation, for a given T . We provide an effective algorithm for finding an everywhere sparse integral solution to the M 2 EDA problem which is within a factor of α = 1+ 4 n / T of the optimum, where n is the number of nodes. A solution is everywhere sparse if the number of communication links for any subset X of nodes is O ( X ), in our case at most 4| X |. Since often T = ω( n ), we obtain the first everywhere sparse, asymptotically optimal integral solutions to the M 2 EDA problem. Everywhere sparse solutions are desirable since then almost all sensors have small number of incident communication links and small overhead for maintaining state. We also show that the MLDA and M 2 EDA problems are essentially equivalent, in the sense that we can obtain an optimal fractional solution to an instance of the MLDA problem by scaling an optimal fractional solution to a suitable instance of the M 2 EDA problem. As a result, our algorithm is effective at finding everywhere sparse, asymptotically optimal, integral solutions to the MLDA problem, when the initial available energy of the sensors is sufficient for supporting optimal system lifetime which is ω( n ).

Kusý, Branislav; Amundson, Isaac; Sallai, Janos; Völgyesi, Peter; Lédeczi, Akos; Koutsoukos, Xenofon

doi: 10.1145/1806895.1806896pmid: N/A

Mobile wireless sensors require position updates for tracking and navigation. We present a localization technique that uses the Doppler shift in radio transmission frequency observed by stationary sensors. We consider two scenarios. In the first, the mobile node is carried by a person. In the second, the mobile node controls a robot. In both approaches the mobile node transmits an RF signal, and infrastructure nodes measure the Doppler-shifted frequency. Such measurements enable us to calculate the position and velocity of the mobile transmitter. Our experimental results demonstrate that this technique is viable and accurate for resource-constrained mobile sensor tracking and navigation.

Wang, Chao; Ramanathan, Parameswaran; Saluja, Kewal K.

doi: 10.1145/1806895.1806903pmid: N/A

Two important measures of performance for the surveillance applications of the mobile sensor networks are detection latency and system lifetime. Previous work on modeling detection delay has assumed that sensor measurements are delivered to the fusion center with zero delay. Such approaches can require excessive energy, resulting into reduced lifetime. This article argues that a trade-off between detection latency and system lifetime can be made by employing an energy aware transmission scheme. The article formulates the trade-off as an optimization problem, and presents an analytic method to model both detection latency and system lifetime. The model is substantiated by using simulation.

Hu, Wen; Tan, Hailun; Corke, Peter; Shih, Wen Chan; Jha, Sanjay

doi: 10.1145/1806895.1806900pmid: N/A

This article presents the design and implementation of a trusted sensor node that provides Internet-grade security at low system cost. We describe trustedFleck, which uses a commodity Trusted Platform Module (TPM) chip to extend the capabilities of a standard wireless sensor node to provide security services such as message integrity, confidentiality, authenticity , and system integrity based on RSA public-key and XTEA-based symmetric-key cryptography. In addition trustedFleck provides secure storage of private keys and provides platform configuration registers (PCRs) to store system configurations and detect code tampering. We analyze system performance using metrics that are important for WSN applications such as computation time, memory size, energy consumption and cost. Our results show that trustedFleck significantly outperforms previous approaches (e.g., TinyECC) in terms of these metrics while providing stronger security levels. Finally, we describe a number of examples, built on trustedFleck, of symmetric key management, secure RPC, secure software update, and remote attestation .

Miller, Chris; Poellabauer, Christian

doi: 10.1145/1806895.1806901pmid: N/A

Retasking and remote programming of sensor networks is an essential functionality to make these networks practical and effective. As the availability of more capable sensor nodes increases and new functional implementations continue to be proposed, these large collections of wireless nodes will need the ability to update and upgrade the software packages they are running. In order to do this, the new binary file must be distributed to all nodes in the network. Making a physical connection with each individual node is impractical in large wireless networks. Standard flooding mechanisms are too energy-costly and computationally expensive and they may interfere with the network's current tasks. A reliable method for distributing new code or binary files to every node in a wireless sensor network is needed. We propose a reprogramming/retasking framework for sensor networks that is energy efficient, responsive, and reliable, while maintaining a stable network.

Zhang, Jun; Jia, Xiaohua; Xing, Guoliang

doi: 10.1145/1806895.1806897pmid: N/A

We investigate the problem of delay constrained maximal information collection for CSMA-based wireless sensor networks. We study how to allocate the maximal allowable transmission delay at each node, such that the amount of information collected at the sink is maximized and the total delay for the data aggregation is within the given bound. We formulate the problem by using dynamic programming and propose an optimal algorithm for the optimal assignment of transmission attempts. Based on the analysis of the optimal solution, we propose a distributed greedy algorithm. It is shown to have a similar performance as the optimal one.

Sugihara, Ryo; Gupta, Rajesh K.

doi: 10.1145/1806895.1806899pmid: N/A

Unlike traditional multihop forwarding among stationary sensor nodes, use of mobile devices for data collection in wireless sensor networks has recently been gathering more attention. The use of mobility significantly reduces the energy consumption at sensor nodes, elongating the functional lifetime of the network. However, a drawback is an increased data delivery latency. Reducing the latency through optimizing the motion of data mules is critical for this approach to thrive. In this article, we focus on the problem of motion planning, specifically, determination of the speed of the data mule and the scheduling of the communication tasks with the sensors. We consider three models of mobility capability of the data mule to accommodate different types of vehicles. Under each mobility model, we design optimal and heuristic algorithms for different problems: single data mule case, single data mule with periodic data generation case, and multiple data mules case. We compare the performance of the heuristic algorithm with a naive algorithm and also with the multihop forwarding approach by numerical experiments. We also compare one of the optimal algorithms with a previously proposed method to see how our algorithm improves the performance and is also useful in practice. As far as we know, this study is the first of a kind that provides a systematic understanding of the motion planning problem of data mules.

Lim, Jun Bum; Jang, Beakcheol; Yoon, Suyoung; Sichitiu, Mihail L.; Dean, Alexander G.

doi: 10.1145/1806895.1806902pmid: N/A

Advances in microprocessors, memory, and radio technology have enabled the emergence of embedded systems that rely on communication systems to exchange information and coordinate their activities in spatially distributed applications. However, developing embedded communication systems that satisfy specific application requirements is a challenge due to the many tradeoffs imposed by different choices of underlying protocols and their parameters. Furthermore, evaluating the correctness and performance of the design and implementation before deploying it is a nontrivial task due to the complexity of the resulting system. This article presents the design and implementation of RaPTEX, a rapid prototyping tool for embedded communication systems, especially well suited for wireless sensor networks (WSNs), consisting of three major subsystems: a toolbox, an analytical performance estimation framework, and an emulation environment. We use a hierarchical approach in the design of the toolbox to facilitate the composition of the network stack. For fast exploration of the tradeoff space at design time, we build an analytical performance estimation model for energy consumption, delay, and throughput. For realistic performance evaluation, we design and implement a hybrid, accurate, yet scalable, emulation environment. Through three use cases, we study the tradeoff space for different protocols and topologies, and highlight the benefits of using RaPTEX for designing and evaluating embedded communication systems for WSNs.