A Distributed Query Processing Engine

Wireless sensor networks (WSNs) are formed of tiny, highly energy-constrained sensor nodes that are equipped with wireless transceivers. They may be mobile and are usually deployed in large numbers in unfamiliar environments. The nodes communicate with one another by autonomously creating ad-hoc networks which are subsequently used to gather sensor data. WSNs also process the data within the network itself and only forward the result to the requesting node. This is referred to as in-network data aggregation and results in the substantial reduction of the amount of data that needs to be transmitted by any single node in the network. In this paper we present a framework for a distributed query processing engine (DQPE) which would allow sensor nodes to examine incoming queries and autonomously perform query optimisation using information available locally. Such qualities make a WSN the perfect tool to carryout environmental\ud monitoring in future planetary exploration missions in a reliable and cost effective manner

Dependability in Aggregation by Averaging

Aggregation is an important building block of modern distributed applications, allowing the determination of meaningful properties (e.g. network size, total storage capacity, average load, majorities, etc.) that are used to direct the execution of the system. However, the majority of the existing aggregation algorithms exhibit relevant dependability issues, when prospecting their use in real application environments. In this paper, we reveal some dependability issues of aggregation algorithms based on iterative averaging techniques, giving some directions to solve them. This class of algorithms is considered robust (when compared to common tree-based approaches), being independent from the used routing topology and providing an aggregation result at all nodes. However, their robustness is strongly challenged and their correctness often compromised, when changing the assumptions of their working environment to more realistic ones. The correctness of this class of algorithms relies on the maintenance of a fundamental invariant, commonly designated as "mass conservation". We will argue that this main invariant is often broken in practical settings, and that additional mechanisms and modifications are required to maintain it, incurring in some degradation of the algorithms performance. In particular, we discuss the behavior of three representative algorithms Push-Sum Protocol, Push-Pull Gossip protocol and Distributed Random Grouping under asynchronous and faulty (with message loss and node crashes) environments. More specifically, we propose and evaluate two new versions of the Push-Pull Gossip protocol, which solve its message interleaving problem (evidenced even in a synchronous operation mode).Comment: 14 pages. Presented in Inforum 200

Towards distributed reasoning for behavioral optimization

We propose an architecture which supports the behavioral self-optimization of complex systems. In this architecture we bring together specification-based reasoning and the framework of ant colony optimization (ACO). By this we provide a foundation for distributed reasoning about different properties of the solution space represented by different viewpoint specifications. As a side-effect of reasoning we propagate the information about promising areas in the solution space to the current state. Consequently the system’s decisions can be improved by considering the long term values of certain behavioral trajectories (given a certain situational horizon). We consider this feature to be a contribution to autonomic computing1st IFIP International Conference on Biologically Inspired Cooperative Computing - Biological Inspiration 1Red de Universidades con Carreras en Informática (RedUNCI

Towards distributed reasoning for behavioral optimization

We propose an architecture which supports the behavioral self-optimization of complex systems. In this architecture we bring together specification-based reasoning and the framework of ant colony optimization (ACO). By this we provide a foundation for distributed reasoning about different properties of the solution space represented by different viewpoint specifications. As a side-effect of reasoning we propagate the information about promising areas in the solution space to the current state. Consequently the system’s decisions can be improved by considering the long term values of certain behavioral trajectories (given a certain situational horizon). We consider this feature to be a contribution to autonomic computing1st IFIP International Conference on Biologically Inspired Cooperative Computing - Biological Inspiration 1Red de Universidades con Carreras en Informática (RedUNCI

Programming a Sensor Network as an Amorphous Medium

In many sensor network applications, the network is deployedto approximate a physical space. The network itself is not ofinterest: rather, we are interested in measuring the propertiesof the space it fills, and of establishing control over thebehavior of that space.The spatial nature of sensor network applications meansthat many can be expressed naturally and succinctly in termsof the global behavior of an amorphous medium---a continuouscomputational material filling the space of interest. Althoughwe cannot construct such a material, we can approximateit using a sensor network.Using this amorphous medium abstraction separates sensornetwork problems into two largely independent domains.Above the abstraction barrier we are concerned with longrangecoordination and concise description of applications,while below the barrier we are concerned with fast, efficient,and robust communication between neighboring devices.We apply the amorphous medium abstraction with Proto,a high-level language for programming sensor/actuator networks.Existing applications, such as target tracking andthreat avoidance, can be expressed in only a few lines of Protocode. The applications are then compiled for execution on akernel that approximates an amorphous medium. Programswritten using our Proto implementation have been verified insimulation on over ten thousand nodes, as well as on a networkof Berkeley Motes

Security in Wireless Sensor Networks - Improving the LEAP Protocol

Wireless sensor networks are becoming significantly vital to many applications, and they were initially used by the military for surveillance purposes. One of the biggest concerns of WSNs is that they are very defenceless to security threats. Due to the fact that these networks are susceptible to hackers; it is possible for one to enter and render a network. For example, such networks may be hacked into in the military, using the system to attack friendly forces. Leap protocol offers many security benefits to WSNs. However, with much research it became apparent that LEAP only employs one base station and always assumes that it is trustworthy. It does not consist of defence against hacked or compromised base stations. In this paper, intensive research was undertaken on LEAP protocols, finding out its security drawbacks and limitations. A solution has been proposed in order to overcome the security issues faced in implementing this protocol whilst employing more than one base station. The performance of the proposed solution has been evaluated and simulated to provide a better network performance

Amorphous Medium Language

Programming reliable behavior on a large mesh network composed of unreliable parts is difficult. Amorphous Medium Language addresses this problem by abstracting robustness and networking issues away from the programmer via language of geometric primitives and homeostasis maintenance.AML is designed to operate on a high diameter network composed of thousands to billions of nodes, and does not assume coordinate, naming, or routing services. Computational processes are distributed through geometric regions of the space approximated by the network and specify behavior in terms of homeostasis conditions and actions to betaken when homeostasis is violated.AML programs are compiled for local execution using previously developed amorphous computing primitives which provide robustness against ongoing failures and joins and localize the impact of changes in topology. I show some examples of how AML allows complex robust behavior to be expressed in simple programs and some preliminary results from simulation