Detailed Diagnosis of Performance Anomalies in Sensornets

We address the problem of analysing performance anomalies in sensor networks. In this paper, we propose an approach that uses the local flash storage of the motes for logging system data, in combination with online statistical analysis. Our results show not only that this is a feasible method but that the overhead is significantly lower than that of communication-centric methods, and that interesting patterns can be revealed when calculating the correlation of large data sets of separate event types.GINSENGCONE

Car-Park Management using Wireless Sensor Networks

A complete wireless sensor network solution for car-park management is presented in this paper. The system architecture and design are first detailed, followed by a description of the current working implementation, which is based on our DSYS25z sensing nodes. Results of a series of real experimental tests regarding connectivity, sensing and network performance are then discussed. The analysis of link characteristics in the car park scenario shows unexpected reliability patterns which have a strong influence on MAC and routing protocol design. Two unexpected link reliability patterns are identified and documented. First, the presence of the objects (cars) being sensed can cause significant interference and degradation in communication performance. Second, link quality has a high temporal correlation but a low spatial correlation. From these observations we conclude that a) the construction and maintenance of a fixed topology is not useful and b) spatial rather than temporal message replicates can improve transport reliability

Analysis of NAMCS data for multiple sclerosis, 1998–2004

BACKGROUND: To our knowledge, no study to date has investigated the prescribing patterns of immunomodulatory agents (IMAs) in an outpatient setting in the United States. To address this issue, we performed retrospective data analyses on National Ambulatory Medical Care Survey (NAMCS) data for MS patient visits between 1998 and 2004. METHODS: NAMCS data are a weighted estimate of the nationwide frequency of patients' outpatient clinic visits. We analyzed NAMCS data in the following categories: (1) the proportion of MS patient visits to neurologists, family practitioners or internists, (2) age/gender/race/geographical distribution patterns in patient visits, and (3) the proportion of patients on IMA treatment among established MS patients. RESULTS: There were an estimated 6.7 million multiple sclerosis (MS) patient visits to the clinics between 1998–2004. Neurologists recorded the most patient visits, 50.7%. Patient visits were mostly in the fourth and fifth decade age group (57.9%). The male to female ratio was 1:4. No statistical evidence was observed for a decline or increase in IMA usage. About 62% patients visiting neurologists and 92% seen by family practitioners/internists were not using IMAs. Our results suggest that between the years 1998–2003, the use of interferon-1a tended to decline while the use of interferon-1b and glatiramer acetate, increased. CONCLUSION: Strategies that lead to improved use of IMAs in the management of MS in the outpatient setting are needed

Reliability Control for Aggregation in Wireless Sensor Networks

Data aggregation is a method used in sensor networks to reduce the amount of messages transported. By aggregating, the data contained in several messages is fused into one single message. If such a message, containing the equivalent of many individual messages, is lost due to transmission errors then this has a detrimental effect on the application quality experienced. In many sensor network applications a constant supply of data is needed and therefore application quality is severely effected by excessive data loss. This paper proposes and evaluates the use of an in-network control mechanism to offset this disadvantageous effect. The control mechanism analytically calculates the correct reliability that an aggregate of given size must be forwarded at in order to meet application specific goals

Opportunistic Aggregation over Duty Cycled Communications in Wireless Sensor Networks

To implement duty cycles with packet based transceivers, a sender transmits a trail of identical packets (which we call framelets) of which the receiver is able to catch one in its active listening phase. This communication concept is used in the standard low power listening (LPL) protocol shipped with TinyOS 2.x. This existing solution has many shortcomings which result in a very limited network performance. In this paper, we firstly present an alternative framelet based low power listening implementation called Framelet Communications (FrameComm) that eliminates these shortcomings. Secondly, we present a novel additional improvement to FrameComm - Interception and Aggregation of Framelet Communications i-FrameComm) - that further improves network performance by opportunistically aggregating packets over the radio channel. A prototype implementation of the proposed FrameComm mechanism in TinyOS 2.02 is used for evaluation and comparison. The experiments show that the interception and aggregation method increases network throughput and lifetime as communication resources are used more efficiently

Priority interrupts of Duty Cycled communications in wireless sensor networks

FrameComm is a contention based, duty cycled, MAC protocol that ensures a message will be transmitted during the receiverpsilas listen phase by sending a packet, followed by a short gap, repeatedly for a precalculated number of times or until an acknowledgment is received. While introducing duty cycled communications can yield large power savings it does so at the cost of increased delay and decreased throughput. Many WSNs may incorporate several distinct message types of varying priority. A node with a high priority message to send may find the channel to be busy with a lesser priority message from another node and must therefore dasiaback-offpsila leading to further delays. In a multi-hop environment, these delays are compounded and may become unacceptably large. This paper proposes adding a high priority interrupt message to FrameComm that allows a node with important data to send to interrupt another nodepsilas lesser priority transmission giving immediate access to the channel. The priority interrupt mechanism is evaluated using an implementation in TinyOS 2 on a small laboratory testbed

Self-adaptive framelet-based communication for wireless sensor networks

Wireless sensor nodes employ a duty cycle to conserve energy. To implement a duty cycle, a sensor node constantly switches the communication transceiver between listen and sleep states. If a listen/sleep cycle of the receiver is known, a sender can transmit a trail of identical packets, called framelets, of which the receiver is guaranteed to receive one. Such framelet-based communication mechanisms are currently used in sensor networks. However, the framelet communication mechanisms that are currently used are static and unable to adapt to changing traffic requirements or traffic bursts. In this paper, we present three new framelet communication enhancements that can be used to overcome this limitation and allow us to construct a self-adaptive framelet-based communication protocol. Our framelet mechanisms are evaluated using testbed and simulation experiments. The results show that our self-adaptive communication protocol is able to accommodate varying traffic patterns with low energy cost

WSN Evaluation in Industrial Environments First results and lessons learned

The GINSENG project develops performance-controlled wireless sensor networks that can be used for time-critical applications in hostile environments such as industrial plant automation and control. GINSENG aims at integrating wireless sensor networks with existing enterprise resource management solutions using a middleware. A cornerstone is the evaluation in a challenging industrial environment — an oil refinery in Portugal. In this paper we first present our testbed. Then we introduce our solution to access, debug and flash the sensor nodes remotely from an operations room in the plant or from any location with Internet access. We further present our experimental methodology and show some exemplary results from the refinery testbed