Saving energy is one of the principal challenges in wireless sensor networks. Dynamic voltage and frequency scaling (DVFS) is often used to reduce energy consumption in systems where sleep is not an option. We show that changing the CPU frequency introduces sudden changes in clock behavior, thereby affecting the time-keeping functionality. This anomalous phenomenon is observed in different sensor platforms and causes a loss of time synchronization among nodes that is unacceptable to applications such as structural health monitoring that require tightly synchronized clocks over extended periods. The paper provides experimental measurements of the clock value shift anomaly in three widely used wireless sensor platforms and its impact on clock synchronization costs. A general framework balancing the need to save energy against the need to keep clocks synchronized is developed. Our system is implemented and evaluated on a network of sensors deployed on a truss bridge and running a high-fidelity structural health monitoring application. Experimental measurements confirm the efficacy of the solution in saving energy while maintaining an acceptable level of synchronization.

In this paper, a diverse range of routing algorithms is classified into a new family of routings called zone-ordered label-based routing algorithms. The proposed classification is based on three common steps (factors) for generating such routings, namely, graph labeling, deadlock-free zones, and zone ordering. The main goal of this classification is to define several new routing concepts and streamline the knowledge on routing algorithms. Following the classification, a novel methodology is proposed to generate routing algorithms for irregular networks. The methodology uses the three mentioned steps to generate deadlock-free routings. Consequently, the methodology-based routings fall into the category of zone-ordered label-based routings. However, the graph labeling method (first step) used in the methodology is based on multiple spanning tree construction on the network. The simulation results show that constructing further spanning trees may result in routing algorithm with better performance.

Troubleshooting unresponsive sensor nodes is a significant challenge in remote sensor network deployments. This paper introduces the tele-diagnostic powertracer, an in-situ troubleshooting tool that uses external power measurements to determine the internal health condition of an unresponsive host and the most likely cause of its failure. We developed our own low-cost power meter with low-bandwidth radio to report power measurements and findings, hence allowing remote (i.e., tele-) diagnosis. The tool was deployed and tested in a remote solar-powered sensing network for acoustic and visual environmental monitoring. It was shown to successfully distinguish between several categories of failures that cause unresponsive behavior including energy depletion, antenna damage, radio disconnection, system crashes, and anomalous reboots. It was also able to determine the internal health conditions of an unresponsive node, such as the presence or absence of sensing and data storage activities (for each of multiple sensors). The paper explores the feasibility of building such a remote diagnostic tool from the standpoint of economy, scale and diagnostic accuracy. To the authors' knowledge, this is the first paper that presents a remote diagnostic tool that uses power measurements to diagnose sensor system failures.

In this paper, we consider the problem of searching a network for intruders. We propose a strategy for capturing the intruder in the popular interconnection topology, the star network. According to the proposed strategy, a team of collaborative software agents are responsible for capturing a hostile intruder (e.g. a virus). These agents asynchronously move along the network links and the intruder has the capability of escaping arbitrarily fast.

In a large system, it is neither economical nor efficient to equip each node with a copy of the resource, and it is desirable to distribute the copies of the resource so that certain performance measure is obtained. In this paper we consider the problem of distributing resources in the edge product of networks. The algorithms presented in this paper make use of the known placements for the basic graphs composing the product graph. Therefore, in these placements we avoid the additional costs needed for deploying and rescaling the network.

So far, many analytical models have been proposed in the literature to evaluate the performance of networks with different topologies such as hypercube,torus, mesh, hypermesh, Cartesian product networks, star graph, and k-ary n-cube; however, to the best of our knowledge, no mathematical model has been presented for irregular networks. Therefore, as an effort to fill this gap, this paper presents a comprehensive mathematical model for fully adaptive routing in wormhole-switched irregular networks. Moreover, since our approach holds no assumption for the network topology, the proposed analytical model covers all the a forementioned models (i.e. it covers both regular and irregular topologies). Furthermore, the model makes no preliminary assumption about the deadlock-free routing algorithm applied to the network. Finally, besides the generality of the model regarding the topology and routing algorithm, our analysis shows that the analytical model exhibits high accuracy which enables it to be used for almost all topologies with all traffic loads.