'Re-using an existing wheel' developing data architecture for cooperating autonomous and semi-autonomous, agent-based web services

This short position paper considers issues in developing Data Architecture for the Internet of Things (IoT) through the medium of an exemplar project, Domain Expertise Capture in Authoring and Development ­Environments (DECADE). A brief discussion sets the background for IoT, and the development of the ­distinction between things and computers. The paper makes a strong argument to avoid reinvention of the wheel, and to reuse approaches to distributed heterogeneous data architectures and the lessons learned from that work, and apply them to this situation. DECADE requires an autonomous recording system, ­local data storage, semi-autonomous verification model, sign-off mechanism, qualitative and ­quantitative ­analysis ­carried out when and where required through web-service architecture, based on ontology and analytic agents, with a self-maintaining ontology model. To develop this, we describe a web-service ­architecture, ­combining a distributed data warehouse, web services for analysis agents, ontology agents and a ­verification engine, with a centrally verified outcome database maintained by certifying body for qualification/­professional status.

The determinants of business performance of estate agency in England and Wales

Purpose: This paper seeks to investigate the factors influencing the business performance of estate agency in England and Wales. Design/methodology/approach: The paper investigates the effect of housing market, company size and pricing policy on business performance in the estate agency sector in England and Wales. The analysis uses the survey data of Woolwich Cost of Moving Survey (a survey of transactions costs sponsored by the Woolwich/Barclays Bank) from 2003 to 2005 to test the hypothesis that the business performance of estate agency is affected by industry characteristics and firm factors. Findings: The empirical analysis indicates that the business performance of estate agency is subject to market environment volatility such as market uncertainty, housing market liquidity and house price changes. The firm factors such as firm size and the level of agency fee have no explanatory power in explaining business performance. The level of agency fee is positively associated with firm size, market environment and liquidity. Research limitations/implications: The research is limited to the data received and is based on a research project on transaction costs designed prior to this analysis. Originality/value: There is little other research that investigates the factors determining the business performance of estate agency, using consecutive data of three years across England and Wales. The findings are useful for practitioners and/or managers to allocate resources and adjust their business strategy to enhance business performance in the estate agency sector.

Performance evaluation of the register insertion protocol for voice-data integration

The performance of the register insertion protocol for mixed voice-data traffic is investigated by simulation. The simulation model incorporates a common insertion buffer for station and ring packets. Bandwidth allocation is achieved by imposing a queue limit at each node. A simple priority scheme is introduced by allowing the queue limit to vary from node to node. This enables voice traffic to be given priority over data. The effect on performance of various operational and design parameters such as ratio of voice to data traffic, queue limit and voice packet size is investigated. Comparisons are made where possible with related work on other protocols proposed for voice-data integration. The main conclusions are: (a) there is a general degradation of performance as the ratio of voice traffic to data traffic increases, (b) substantial improvement in performance can be achieved by restricting the queue length at data nodes and (c) for a given ring utilisation, smaller voice packets result in lower delays for both voice and data traffic.

Self-optimising data farming for web applications

Many Web applications walk the thin line between the need for dynamic data and the need to meet user performance expectations. In environments where funds are not available to constantly upgrade hardware inline with user demand, alternative approaches need to be considered. This paper introduces a ‘Data farming’ model whereby dynamic data, which is ‘grown’ in operational applications, is ‘harvested’ and ‘packaged’ for various consumer markets. Like any well managed agricultural operation, crops are harvested according to historical and perceived demand as inferred by a self-optimising process. This approach aims to make enhanced use of available resources through better utlilisation of system downtime - thereby improving application performance and increasing the availability of key business data.