Jonathan Tate

Evolutionary and Principled Search Strategies for Sensornet Protocol Optimization

Interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown; finding optimal solutions is generally difficult. However, protocol tuning can yield significant gains in energy efficiency and resource requirements, which is of particular importance for sensornet systems in which resource availability is severely restricted. We address this multi-objective optimization problem for two dissimilar routing protocols and by two distinct approaches. First, we apply factorial design and statistical model fitting methods to reject insignificant factors and locate regions of the problem space containing near-optimal solutions by principled search. Second, we apply the Strength Pareto Evolutionary Algorithm 2 and Two-Archive evolutionary algorithms to explore the problem space, with each iteration potentially yielding solutions of higher quality and diversity than the preceding iteration. Whereas a principled search methodology yields a generally applicable survey of the problem space and enables performance prediction, the evolutionary approach yields viable solutions of higher quality and at lower experimental cost. This is the first study in which sensornet protocol optimization has been explicitly formulated as a multi-objective problem and solved with state-of-the-art multi-objective evolutionary algorithms.

Sensornet Protocol Tuning Using Principled Engineering Methods

Sensornet designers seek to maximize energy efficiency while maintaining acceptable Quality of Service. However, the interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown, and combinatorial explosion renders impossible any exhaustive search approach. Most work published to date employs seemingly arbitrary choices of protocol parameters, derived by informal judgement and limited trial and error experiments. This lack of rigour may lead to sub-optimal parameter selection and sub-optimal network behaviour, and may mask the real performance differences of dissimilar protocols. We describe a reusable engineering method to address this multi-dimensional optimization problem, based on sound engineering principles widely recognized and applied beyond Computer Science. We provide a mechanism with which to de-risk deployment of sensornets tuned within training environments, and evaluate the robustness of these tunings to changing environments. The mechanism is also useful for comparative evaluation of protocols within a fixed deployment context.

An improved lightweight synchronisation primitive for sensornets

Sensornets must allocate limited computation and energy resources efficiently to maximise utility and lifetime. This task is complicated by the need to coordinate activity between nodes as sensornets are necessarily real-time collaborative systems. In this paper we present and evaluate lightweight adaptive protocols based on pulse-coupled oscillators to synchronise tasks within a unicellular sensornet. A near-optimal schedule is constructed and dynamically maintained under non-ideal network conditions.

Comparing design of experiments and evolutionary approaches to multi-objective optimisation of sensornet protocols

The lifespan, and hence utility, of sensornets is limited by the energy resources of individual motes. Network designers seek to maximise energy efficiency while maintaining an acceptable network Quality of Service. However, the interactions between multiple tunable protocol parameters and multiple sensornet performance metrics are generally complex and unknown. In this paper we address this multi-dimensional optimisation problem by two distinct approaches. Firstly, we apply a Design Of Experiments approach to obtain a generalised linear interaction model, and from this derive an estimated near-optimal solution. Secondly, we apply the Two-Archive evolutionary algorithm to improve solution quality for a specific problem instance. We demonstrate that, whereas the first approach yields a more generally applicable solution, the second approach yields a broader range of viable solutions at potentially lower experimental cost.

Energy Efficient Duty Allocation Protocols for Wireless Sensor Networks

Wireless sensor networks require shared medium access management to prevent collisions, message corruption and other unhelpful effects. Cellular sensornets require minimal energy consumption to maximise network lifetime, and management of interaction with base stations and other cells. We present a protocol which dynamically generates a near-optimal duty schedule within a cell such that communication duty is shared evenly between participating nodes with exactly one node on-duty at any given time.

Maintaining Stable Node Populations in Long-Lifetime Sensornets

Sensornets provide coverage of physical phenomena over extended periods, perhaps months or years. However, active nodes may deplete finite batteries within days, and are prone to failure. The sensornet application may require a given number of active nodes within each region to provide appropriate sensor redundancy and processing capacity. If many nodes are deployed, at any given time a smaller working set of the correct size can be selected for duty. In this paper we present a lightweight approach to active population management. An omniscient overview of network state is not required, and expensive communication activity is minimised. Probabilistic methods are employed, ensuring that individual nodes can make appropriate decisions using only locally available information.

Understanding Behavioural Tradeoffs in Large-Scale Sensornet Design

When designing a complex system such as a sensornet it is not always practical to build and deploy a realistically sized prototype. At the same time many of the interesting behaviours are hard to observe in small scale simulation and many of the current simulators do not scale well. In this paper we use present an efficient but effective simulator which, when combined with modern day large-scale computational capabilities, allow us to measure the impact of tuning an existing protocol and evaluate the necessary tradeoffs.

A feedback-driven timing synchronisation protocol for cellular sensornets

Interaction between sensornet nodes and the physical environment in which they are embedded implies realtime requirements. Application tasks must be executed in the correct place, and in the correct order, for correct application behaviour. Sensornets generally have no global clock, and incur unacceptable cost if traditional synchronisation protocols are implemented. We present a lightweight primitive which generates a periodic sequence of synchronisation events which are coordinated across large sensornets structured into clusters or cells. Two biologically-inspired mechanisms are combined; desynchronisation within cells, and synchronisation between cells. This hierarchical coordination provides a global basis for local application-driven timing decisions at each node.

Tuning Complex Sensornet Systems Using Principled Engineering Methods

Sensornet lifespan and utility is limited by the energy resources of individual motes. Network designers seek to maximise energy efficiency while maintaining acceptable Quality of Service. However, the interactions between multiple tunable protocol parameters and multiple performance metrics are generally complex and unknown, and combinatorial explosion renders impossible any exhaustive search approach. In this paper we describe an engineering method to address this multi-dimensional optimisation problem. We apply a Design Of Experiments approach to sample the entire search space. Statistical models are fitted to experimental results to define relationships between inputs and outputs, and to obtain near-optimal solutions.

LIPS: A Protocol Suite for Homeostatic Sensornet Management

Sensornets are often deployed into inaccessible, dangerous, or changeable physical environments. Centralised control and management is generally infeasible. Autonomous, self-configuring, and self-managing mechanisms are required to provide a suitable infrastructure which reliably supports distributed applications, hiding any underlying instability. The Lightweight Integrated Protocol Suite (LIPS) coordinates time-sensitive activity, and regulates network size and density, in self-managing cellular sensornets. Although components can be implemented in isolation, each contributes part of a larger, integrated solution.