Bio-Inspired Tools for a Distributed Wireless Sensor Network Operating System

The problem which I address in this thesis is to find a way to organise and manage a network of wireless sensor nodes using a minimal amount of communication. To find a solution I explore the use of Bio-inspired protocols to enable WSN management while maintaining a low communication overhead. Wireless Sensor Networks (WSNs) are loosely coupled distributed systems comprised of low-resource, battery powered sensor nodes. The largest problem with WSN management is that communication is the largest consumer of a sensor node’s energy. WSN management systems need to use as little communication as possible to prolong their operational lifetimes. This is the Wireless Sensor Network Management Problem. This problem is compounded because current WSN management systems glue together unrelated protocols to provide system services causing inter-protocol interference. Bio-inspired protocols provide a good solution because they enable the nodes to self-organise, use local area communication, and can combine their communication in an intelligent way with minimal increase in communication. I present a combined protocol and MAC scheduler to enable multiple service protocols to function in a WSN at the same time without causing inter-protocol interference. The scheduler is throughput optimal as long as the communication requirements of all of the protocols remain within the communication capacity of the network. I show that the scheduler improves a dissemination protocol’s performance by 35%. A bio-inspired synchronisation service is presented which enables wireless sensor nodes to self organise and provide a time service. Evaluation of the protocol shows an 80% saving in communication over similar bio-inspired synchronisation approaches. I then add an information dissemination protocol, without significantly increasing communication. This is achieved through the ability of our bio-inspired algorithms to combine their communication in an intelligent way so that they are able to offer multiple services without requiring a great deal of inter-node communication.Open Acces

Farmer groups for animal health and welfare planning in European organic dairy herds

A set of common principles for active animal health and welfare planning in organic dairy farming has been developed in the ANIPLAN project group of seven European countries. Health and welfare planning is a farmer‐owned process of continuous development and improvement and may be practised in many different ways. It should incorporate health promotion and disease handling, based on a strategy where assessment of current status and risks forms the basis for evaluation, action and review. Besides this, it should be 1) farm-specific, 2) involve external person(s) and 3) external knowledge, 4) be based on organic principles, 5) be written, and 6) acknowledge good aspects in addition to targeting the problem areas in order to stimulate the learning process. Establishing farmer groups seems to be a beneficial way of stimulating a dynamic development on the farms towards continuous improvement, as in this case with focus on animal health and welfare planning. Various factors influence the process in different contexts, e.g. geographical, cultural, traditional factors, and a proper analysis of the situation as well as the purpose of the group is necessary, and can relevantly be negotiated and co‐developed with farmers as well as facilitators before being implemented. Farmer groups based on farmer‐to‐farmer advice and co‐development need a facilitator who takes on the role of facilitating the process and ‘decodes’ him‐ or herself from being ‘expert’

Brooking no excuses: university staff and students are encouraged to develop their engagement

Brooking no excuses: university staff and students are encouraged to develop their engagement This paper will explore the internal and external factors that have prompted the University of East Anglia's decision to give Public Engagement into a more central role within the Universities Corporate Plan. It will illustrate how the SEARCH Action Learning Programme facilitated the design, implementation and delivery of new Staff and Student Development Programmes that aim to provide the confidence, skills and mentorship that will encourage staff to develop their engagement activities. We will use a SWOT analysis to discuss the strengths, weaknesses, opportunities and threats of the Public Engagement Practitioner. As part of this, we will explore how many of the issues we face as Science communicators with the public are similar to issues encountered by Communicators within the Arts and Humanities disciplines. Finally we will outline and detail our future plans, opportunities and vision that will enable us to move this agenda forward

Farmer groups for animal health and welfare planning in European organic dairy hers

A set of common principles for active animal health and welfare planning in organic dairy farming has been developed in the ANIPLAN project group of seven European countries. Health and welfare planning is a farmer‐owned process of continuous development and improvement and may be practised in many different ways. It should incorporate health promotion and disease handling, based on a strategy where assessment of current status and risks forms the basis for evaluation, action and review. Besides this, it should be 1) farmspecific, 2) involve external person(s) and 3) external knowledge, 4) be based on organic principles, 5) be written, and 6) acknowledge good aspects in addition to targeting the problem areas in order to stimulate the learning process

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa