Integrating multimedia streams into a distributed computing system

Continuous media, such as audio and video, are quickly becoming an integral part of distributed computing environments. A shortcoming of such environments is their lack of support for continuous flows of information. What is missing is the notion of an on-going communication activity with an associated quality of service. This paper describes a model for integrating multimedia flows into a distributed computing system. The model permits explicit bindings to be established between type-checked stream interfaces. The stream binding is represented in the computational model as a first-class object which encapsulates configuration rules and QoS attributes. An operational interface supplied by the binding object allows other objects within the system to manage the binding, to renegotiate QoS parameters, to control the flows across the binding, and to register interest in stream events such as flow reports and communication errors. The in-band stream interface is an abstract C++ wrapper around transport mechanisms that include intra-host IPC and network transport protocols such as TCP and XTP. A prototype implementation of this model is described using the Common Object Request Broker Architecture (CORBA). The implementation environment comprises a local area ATM network with directly attached multimedia peripherals and general purpose workstations

Model Based Development of Quality-Aware Software Services

Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

Reducing Packet Overhead in Mobile IPv6

Common Mobile IPv6 mechanisms, Bidirectional tunneling and Route optimization, show inefficient packet overhead when both nodes are mobile. Researchers have proposed methods to reduce packet overhead regarding to maintain compatible with standard mechanisms. In this paper, three mechanisms in Mobile IPv6 are discussed to show their efficiency and performance. Following discussion, a new mechanism called Improved Tunneling-based Route Optimization is proposed and due to performance analysis, it is shown that proposed mechanism has less overhead comparing to common mechanisms. Analytical results indicate that Improved Tunneling-based Route Optimization transmits more payloads due to send packets with less overhead

Extending sensor networks into the cloud using Amazon web services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution