698 research outputs found

    Implementation and evaluation of the sensornet protocol for Contiki

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    Sensornet Protocol (SP) is a link abstraction layer between the network layer and the link layer for sensor networks. SP was proposed as the core of a future-oriented sensor node architecture that allows flexible and optimized combination between multiple coexisting protocols. This thesis implements the SP sensornet protocol on the Contiki operating system in order to: evaluate the effectiveness of the original SP services; explore further requirements and implementation trade-offs uncovered by the original proposal. We analyze the original SP design and the TinyOS implementation of SP to design the Contiki port. We implement the data sending and receiving part of SP using Contiki processes, and the neighbor management part as a group of global routines. The evaluation consists of a single-hop traffic throughput test and a multihop convergecast test. Both tests are conducted using both simulation and experimentation. We conclude from the evaluation results that SP's link-level abstraction effectively improves modularity in protocol construction without sacrificing performance, and our SP implementation on Contiki lays a good foundation for future protocol innovations in wireless sensor networks

    Detailed Diagnosis of Performance Anomalies in Sensornets

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    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

    Integrating Symbolic Execution with Sensornet Simulation for Efficient Bug Finding

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    High-coverage testing of sensornet applications is vital for pre-deployment bug cleansing, but has previously been difficult due to the limited set of available tools. We integrate the KleeNet symbolic execution engine with the COOJA network simulator to allow for straight-forward and intuitive high-coverage testing initiated from a simulation environment. A tight coupling of simulation and testing helps detect, narrow down, and fix complex interaction bugs in an early development phase. We demonstrate the seamless transition between COOJA simulation and KleeNet symbolic execution. Our framework enables future research in how high coverage testing tools could be used in cooperation with simulation tools

    Dynamic Routing Framework for Wireless Sensor Networks

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    Numerous routing protocols have been proposed for wireless sensor networks. Each such protocol carries with it a set of assumptions about the trafï¬c type that it caters to, and hence has limited interoperability. Also, most protocols are validated over workloads which only form a fraction of an actual deployment’s requirement. Most real world and commercial deployments, however, would generate multiple trafï¬c types simultaneously throughout the lifetime of the network. For example, most deployments would want all of the following to happen concurrently from the network: periodic reliable sense and disseminate, real time streams, patched updates, network reprogramming, query-response dialogs, mission critical alerts and so on. Naturally, no one routing protocol can completely cater to all of a deployments requirements. This chapter presents a routing framework that captures the communication intent of an application by using just three bits. The traditional routing layer is replaced with a collection of routing components that can cater to various communication patterns. The framework dynamically switches routing component for every packet in question. Data structure requirements of component protocols are regularized, and core protocol features are distilled to build a highly composable collection of routing modules. This creates a framework for developing, testing, integrating, and validating protocols that are highly portable from one deployment to another. Communication patterns can be easily described to lower layer protocols using this framework. One such real world application scenario is also investigated: that of predictive maintenance (PdM). The requirements of a large scale PdM are used to generate a fairly complete and realistic trafï¬c workload to drive an evaluation of such a framework

    Towards epistemic autonomy in adaptive biomimetic middleware for cooperative sensornets

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    University of Technology, Sydney. Faculty of Engineering and Information Technology.The importance of studying biomimetic models of software infrastructure for sensornet systems lies in the fact that they are not entirely formal models and thus have to cover a range of issues of epistemic autonomy as well as linguistic and mental adaptation. This adaptation considers the context of software ability to reflect upon the verifiability and validity of its actions and measurements. This research elucidates and explores epistemological consequences of embodying biological autonomic patterns in software architectural models. Autonomy in software systems is a complex issue that raises many fundamental inquiries. The proposal is to initially concentrate on transformations of biological paradigms into epistemological queries and then adapt suitable biomimetic mechanisms into the development of software structure and ethology. Such methodology has proven to be very successful in the design of many engineering systems. The approach leads to a better understanding of the ontology of biomimetic patterns in software as well as a confirmation of requirements validity and design verifiability of autonomous software systems. In a dynamic, cooperative but often hostile environment, a software system infrastructure requires autonomic abilities to execute its normal operations, detect faults and perform necessary recovery actions without the need for external intervention. We approach this problem from the point of view of cognitive and mimetic systems research. The simplest way to make an autonomous and adaptive sensornet system is to include a hierarchy of layers in its middleware, not only to monitor activities of its components but to learn and adapt new behavioural patterns of these components in a changing environment. There are situations, however, where the components will not be able to adapt, learn new behaviour and evolve by themselves. For instance, these may not have yet encountered the new situation while others already have. A solution to this problem is to distribute the new behaviour to neighbouring elements via direct and indirect stigmergy mechanisms so that collaborating components can mutually improve their individual and team performance. The main objective is to disallow distribution of multiple versions of the software components and rather allow each software component to acquire and share with others, new “skills”. The components have to compare/verify these new behavioural patterns against their own set of beliefs, desires and intentions. In this thesis we intend to present simulations to test the learning capability of biomimetic algorithms, build a proof-of-concept middleware solution and demonstrate that such systems can not only adapt and evolve but they are robust and highly interoperable (co-operative). The thesis also assesses the suitability of various biomimetic design patterns and algorithms for building autonomic software infrastructure systems for cooperative networked agents
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