On the selection of connectivity-based metrics for WSNs using a classification of application behaviour

This paper addresses a subset of Wireless Sensor Network (WSN) applications in which data is produced by a set of resource-constrained source nodes and forwarded to one or more sink nodes. The performance of such applications is affected by the connectivity of the WSN, since nodes must remain connected in order to transfer data from sources to sinks. Designers use metrics to measure and improve the efficacy of WSN applications. We aim to facilitate the choice of connectivity-based metrics by introducing a classification of WSN applications based on their data collection behaviour and indicating the metrics best suited to the evaluation of particular application classes. We argue that no suitable metric currently exists for a significant class of applications with the following characteristics: 1) application data is periodically routed or disseminated from source nodes to one or more sink nodes, and 2) the application can continue to function with the loss of source nodes although its useful network lifetime diminishes as a result. We present a new metric, known as Connectivity Weighted Transfer, which may be used to evaluate WSN applications with these characteristics.Preprin

Hosting Byzantine Fault Tolerant Services on a Chord Ring

In this paper we demonstrate how stateful Byzantine Fault Tolerant services may be hosted on a Chord ring. The strategy presented is fourfold: firstly a replication scheme that dissociates the maintenance of replicated service state from ring recovery is developed. Secondly, clients of the ring based services are made replication aware. Thirdly, a consensus protocol is introduced that supports the serialization of updates. Finally Byzantine fault tolerant replication protocols are developed that ensure the integrity of service data hosted on the ring.Comment: Submitted to DSN 2007 Workshop on Architecting Dependable System

Applying constraint solving to the management of distributed applications

Submitted to DOA08We present our approach for deploying and managing distributed component-based applications. A Desired State Description (DSD), written in a high-level declarative language, specifies requirements for a distributed application. Our infrastructure accepts a DSD as input, and from it automatically configures and deploys the distributed application. Subsequent violations of the original requirements are detected and, where possible, automatically rectified by reconfiguration and redeployment of the necessary application components. A constraint solving tool is used to plan deployments that meet the application requirements.Postprin

A Dataflow Language for Decentralised Orchestration of Web Service Workflows

Orchestrating centralised service-oriented workflows presents significant scalability challenges that include: the consumption of network bandwidth, degradation of performance, and single points of failure. This paper presents a high-level dataflow specification language that attempts to address these scalability challenges. This language provides simple abstractions for orchestrating large-scale web service workflows, and separates between the workflow logic and its execution. It is based on a data-driven model that permits parallelism to improve the workflow performance. We provide a decentralised architecture that allows the computation logic to be moved "closer" to services involved in the workflow. This is achieved through partitioning the workflow specification into smaller fragments that may be sent to remote orchestration services for execution. The orchestration services rely on proxies that exploit connectivity to services in the workflow. These proxies perform service invocations and compositions on behalf of the orchestration services, and carry out data collection, retrieval, and mediation tasks. The evaluation of our architecture implementation concludes that our decentralised approach reduces the execution time of workflows, and scales accordingly with the increasing size of data sets.Comment: To appear in Proceedings of the IEEE 2013 7th International Workshop on Scientific Workflows, in conjunction with IEEE SERVICES 201

A Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications

We propose a framework for deployment and subsequent autonomic management of component-based distributed applications. An initial deployment goal is specified using a declarative constraint language, expressing constraints over aspects such as component-host mappings and component interconnection topology. A constraint solver is used to find a configuration that satisfies the goal, and the configuration is deployed automatically. The deployed application is instrumented to allow subsequent autonomic management. If, during execution, the manager detects that the original goal is no longer being met, the satisfy/deploy process can be repeated automatically in order to generate a revised deployment that does meet the goal.Comment: Submitted to ICAC-0

A Middleware Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications

We propose a middleware framework for deployment and subsequent autonomic management of component-based distributed applications. An initial deployment goal is specified using a declarative constraint language, expressing constraints over aspects such as component-host mappings and component interconnection topology. A constraint solver is used to find a configuration that satisfies the goal, and the configuration is deployed automatically. The deployed application is instrumented to allow subsequent autonomic management. If, during execution, the manager detects that the original goal is no longer being met, the satisfy/deploy process can be repeated automatically in order to generate a revised deployment that does meet the goal.Comment: Submitted to Middleware 0

Workflow Partitioning and Deployment on the Cloud using Orchestra

Orchestrating service-oriented workflows is typically based on a design model that routes both data and control through a single point - the centralised workflow engine. This causes scalability problems that include the unnecessary consumption of the network bandwidth, high latency in transmitting data between the services, and performance bottlenecks. These problems are highly prominent when orchestrating workflows that are composed from services dispersed across distant geographical locations. This paper presents a novel workflow partitioning approach, which attempts to improve the scalability of orchestrating large-scale workflows. It permits the workflow computation to be moved towards the services providing the data in order to garner optimal performance results. This is achieved by decomposing the workflow into smaller sub workflows for parallel execution, and determining the most appropriate network locations to which these sub workflows are transmitted and subsequently executed. This paper demonstrates the efficiency of our approach using a set of experimental workflows that are orchestrated over Amazon EC2 and across several geographic network regions.Comment: To appear in Proceedings of the IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC 2014

H2O: An Autonomic, Resource-Aware Distributed Database System

This paper presents the design of an autonomic, resource-aware distributed database which enables data to be backed up and shared without complex manual administration. The database, H2O, is designed to make use of unused resources on workstation machines. Creating and maintaining highly-available, replicated database systems can be difficult for untrained users, and costly for IT departments. H2O reduces the need for manual administration by autonomically replicating data and load-balancing across machines in an enterprise. Provisioning hardware to run a database system can be unnecessarily costly as most organizations already possess large quantities of idle resources in workstation machines. H2O is designed to utilize this unused capacity by using resource availability information to place data and plan queries over workstation machines that are already being used for other tasks. This paper discusses the requirements for such a system and presents the design and implementation of H2O.Comment: Presented at SICSA PhD Conference 2010 (http://www.sicsaconf.org/

Autonomic Management of Maintenance Scheduling in Chord

This paper experimentally evaluates the effects of applying autonomic management to the scheduling of maintenance operations in a deployed Chord network, for various membership churn and workload patterns. Two versions of an autonomic management policy were compared with a static configuration. The autonomic policies varied with respect to the aggressiveness with which they responded to peer access error rates and to wasted maintenance operations. In most experiments, significant improvements due to autonomic management were observed in the performance of routing operations and the quantity of data transmitted between network members. Of the autonomic policies, the more aggressive version gave slightly better results

From missions to systems : generating transparently distributable programs for sensor-oriented systems

Early Wireless Sensor Networks aimed simply to collect as much data as possible for as long as possible. While this remains true in selected cases, the majority of future sensor network applications will demand much more intelligent use of their resources as networks increase in scale and support multiple applications and users. Specifically, we argue that a computational model is needed in which the ways that data flows through networks, and the ways in which decisions are made based on that data, is transparently distributable and relocatable as requirements evolve. In this paper we present an approach to achieving this using high-level mission specifications from which we can automatically derive transparently distributable programs.Postprin