DIAMOnDS - DIstributed Agents for MObile & Dynamic Services

Distributed Services Architecture with support for mobile agents between services, offer significantly improved communication and computational flexibility. The uses of agents allow execution of complex operations that involve large amounts of data to be processed effectively using distributed resources. The prototype system Distributed Agents for Mobile and Dynamic Services (DIAMOnDS), allows a service to send agents on its behalf, to other services, to perform data manipulation and processing. Agents have been implemented as mobile services that are discovered using the Jini Lookup mechanism and used by other services for task management and communication. Agents provide proxies for interaction with other services as well as specific GUI to monitor and control the agent activity. Thus agents acting on behalf of one service cooperate with other services to carry out a job, providing inter-operation of loosely coupled services in a semi-autonomous way. Remote file system access functionality has been incorporated by the agent framework and allows services to dynamically share and browse the file system resources of hosts, running the services. Generic database access functionality has been implemented in the mobile agent framework that allows performing complex data mining and processing operations efficiently in distributed system. A basic data searching agent is also implemented that performs a query based search in a file system. The testing of the framework was carried out on WAN by moving Connectivity Test agents between AgentStations in CERN, Switzerland and NUST, Pakistan.Comment: 7 pages, 4 figures, CHEP03, La Jolla, California, March 24-28, 200

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

A monitoring approach for runtime service discovery

Effective runtime service discovery requires identification of services based on different service characteristics such as structural, behavioural, quality, and contextual characteristics. However, current service registries guarantee services described in terms of structural and sometimes quality characteristics and, therefore, it is not always possible to assume that services in them will have all the characteristics required for effective service discovery. In this paper, we describe a monitor-based runtime service discovery framework called MoRSeD. The framework supports service discovery in both push and pull modes of query execution. The push mode of query execution is performed in parallel to the execution of a service-based system, in a proactive way. Both types of queries are specified in a query language called SerDiQueL that allows the representation of structural, behavioral, quality, and contextual conditions of services to be identified. The framework uses a monitor component to verify if behavioral and contextual conditions in the queries can be satisfied by services, based on translations of these conditions into properties represented in event calculus, and verification of the satisfiability of these properties against services. The monitor is also used to support identification that services participating in a service-based system are unavailable, and identification of changes in the behavioral and contextual characteristics of the services. A prototype implementation of the framework has been developed. The framework has been evaluated in terms of comparison of its performance when using and when not using the monitor component