Starfish: Policy Driven Self-management in Wireless Sensor Networks

Wireless sensor networks are a key aspect of many pervasive systems designed to aid people in their normal activities and adapt to their current context. However, these systems also need to be self-managing in discovering and configuring devices for services, detecting and responding to attacks, determining errors and faults and reconfiguring the system to mitigate these. In this paper we describe the Starfish framework for specifying and dynamically managing policies in sensor nodes. We discuss the components in the framework which include the Finger2 policy system for specifying dynamic adaptivity, a module library to simplify the programming the basic funtionality of nodes and a client side editor for managing policies. We describe policies for an adaptive healthcare body network then focus on policies for self-healing aspects of sensor networks and give examples of policy-based reconfigurations to deal with faults. © 2010 ACM

Towards Self-Healing in Wireless Sensor Networks.

Faults in WSN are very common and appear in different levels of the system. For pervasive applications to be adopted by end-users there is a need for autonomic selfhealing. This paper discusses our initial approach to selfhealing in WSN and describes experiments with two case studies of body sensor deployment. We evaluate the impact of sensor faults on activity and gesture classification accuracy respectively and develop mechanisms that will allow detection of those faults during systems operation. © 2009 IEEE

Autonomic Role and Mission Allocation Framework for Wireless Sensor Networks.

Pervasive applications incorporate physical components that are exposed to everyday use and a large number of conditions and external factors that can lead to faults and failures. It is also possible that application requirements change during deployment and the network needs to adapt to a new context. Consequently, pervasive systems must be capable to autonomically adapt to changing conditions without involving users becoming a transparent asset in the environment. In this paper, we present an autonomic mechanism for initial task assignment in sensor networks, an NP-hard problem. We also study on-line adaptation of the original deployment which considers real-time metrics for maximising utility and lifetime of applications and smooth service degradation in the face of component failures. © 2011 IEEE

Self-adaptive Routing in Multi-hop Sensor Networks

Sensor networks are used for applications in monitoring harsh environments including reconnaissance and surveillance of areas that may be inaccessible to humans. Such applications depend on reliable collection, distribution and delivery of information to processing centres which may involve multi-hop wireless networks which experience disruptions in communication and exhibit packet drops, connectivity loss and congestion. Some of these faults are periodic, attributed to external, recurring factors. In this paper, we study an effective way to forecast such repetitive conditions using time-series analysis. We, further, present an application-level, autonomic routing service that adapts sensor readings routes to avoid areas in which failures or congestion are expected. A prototype system of the approach is developed based on an existing middleware solution for sensor network management. Simulation results on the performance of this approach are also presented. © 2011 IFIP.Accepted versio

Heroin-induced changes of catecholamine-containing particles in male rat cerebellar cortex

The content and distribution of catecholamine-containing formations in the cerebellum of untreated and heroin-treated male rats, was visualized by glyoxylic acid-induced histofluorescence, in an attempt to define the adaptive mechanisms leading to heroin dependent tolerance as well as identify a biological role for these formations. Repeated heroin administration increased the number of specifically organized intracellular catecholamine containing particles, including grain (diameter less than 0.8 μm) and aggregate (diameter greater than 1 μm) forms, in all cerebellar cortical layers examined one hour after the last injection of the drug, relative to controls. The number of grains in all cerebellar cortical layers examined and aggregates in the granular layer, returned to normal or near normal baseline levels within twenty four hours after the last injection of the drug. The analogous baseline of the aggregates in the Purkinje cell layer primarily and the Molecular layer secondarily remained significantly elevated by 86% and 50% respectively, relative to controls. Catecholamine-heroin interactions most likely mediated this elevation that was related directly to the heroin-dependent state of tolerance. These findings indicate that heroin administration to heroin-tolerant rats leads to the formation of unusually large intracellular aggregates with catecholamines in the Purkinje cells of the cerebellum primarily and support a direct role for these formations in the modulation of biogenic amine bio-availability. We conclude that adaptation to drug exposure involves multiple homeostatic interactions, with sympathetic activation at the level of catecholamine reorganization and redistribution playing a major role in rat cerebellar cortex. © 2001 Elsevier Science Inc