Resource Discovery Framework Research Articles

A Novel Framework for Resource Discovery and Self-Configuration in Software Defined Wireless Mesh Networks

A novel framework is proposed for software defined wireless mesh networks involving mobile switches and controllers operating under in-band control in order to self-configure depending on the network dynamics. Besides the addition/removal of nodes (including switches and controllers) to/from the network in real-time, the problem becomes more challenging for switches to select an appropriate controller from multiple physical controllers. Therefore, first we design a resource discovery scheme to address the dynamic addition and removal of nodes with a software defined optimized link state routing (SD-OLSR) protocol. Apart from resource discovery, SD-OLSR captures the network dynamism and provides a global network view to the controller. Further, two controller handoff schemes, controller-initiated handoff (CIH) and switch-initiated handoff (SIH), are designed for switches to efficiently handover to a suitable controller. The framework and handoff schemes are tested using a software defined wireless mesh network testbed involving mobile switches and controllers operating under in-band control. The results show that SIH performs better in terms of SDN control overhead and PacketIn-FlowMod delay, while CIH outperforms SIH in terms of the number of handoffs and controller handoff time. A fair trade-off between the number of handoffs and the desired performance metric can be achieved by tuning the handoff threshold in both CIH and SIH schemes. As an added benefit, our framework provides better load sharing among the controllers in terms of flow-rule requests.

A service oriented broker-based approach for dynamic resource discovery in virtual networks

Abstract In the past few years, the concept of network virtualization has received significant attention from industry and research fora. This concept applies virtualization to networking infrastructures by enabling the dynamic creation of several co-existing logical network instances (or virtual networks) over a shared physical network infrastructure (or substrate network). Due to the potential it offers in terms of diversifying existing networks and ensuring the co-existence of heterogeneous network architectures on top of shared substrates, network virtualization is often considered as an enabler of a polymorphic Internet and a cornerstone of the future Internet architecture. One of the challenges associated with the network virtualization concept is the description, publication, and discovery of virtual resources that can be composed to form virtual networks. To achieve those tasks, there is a need for an expressive information model facilitating information representation and sharing, as well as an efficient resource publication and discovery framework. In this paper, we propose a service oriented, broker-based framework for virtual resource description, publication, and discovery. This framework relies on a novel service-oriented hierarchical business model and an expressive information model for resources/services description. The detailed framework’s architecture is presented, and its operation is illustrated using a REST-based content distribution scenario. Furthermore, a proof-of-concept prototype implementation realized using various technologies/tools (e.g. Jersey, JAXB, PostgreSQL, and Xen cloud platform) is presented along with a detailed performance analysis of the system. When compared to existing virtual resource discovery frameworks, our broker-based virtual resource discovery framework offers signification performance improvements of the virtual resources’ discovery operation, in terms of response time (92.8% improvement) and incurred network load (77.3% improvement), when dealing with multiple resource providers. Furthermore, relying on a broker as intermediary role simplifies the resources’ discovery and selection operations, and improves the overall efficiency of the virtual network embedding process.

An efficient resource discovery framework for pure unstructured peer-to-peer systems

In this paper, we propose an efficient resource discovery framework allowing pure unstructured peer-to-peer systems to respond to requests at run time with a high success rate while preserving the local autonomy of member machines. There are five units in the proposed framework that respectively gather information about the status of resources, make decisions, detect the states of member machines, discover resources to respond to requests in normal and dynamic conditions, and balance the load of local machines. Efficient resource discovery is achieved by the deployment of a newly introduced mechanism that is placed on every machine allowing it to figure out its states before and after accepting other machines’ requests for its resources using a state model and deciding whether to accept or reject those requests. This state model accurately estimates the machine’s state based on the resources and processes of the machine before and after accepting the request. We have experimentally compared the proposed mechanism with random, learning-based, and state-based search mechanisms with regard to the number of missed requests, network bandwidth due to transferred messages, number of associated machines in a discovery operation, time required to process information in discovery operation, processing time in machines, and the number of faults per request. The results show significant improvement of some of these parameters, specially network bandwidth and the number of missed requests in a dynamic condition, under our framework.

A performance, semantic and service quality-enhanced distributed search engine for improving geospatial resource discovery

Geospatial resource discovery is a critical step for developing geographic science applications. With the increasing number of geospatial resources available online, many Spatial Data Infrastructure (SDI) components (e.g. catalogues and portals) have been developed to help manage and discover geospatial resources. However, efficient and accurate geospatial resource discovery is still a big challenge because of the heterogeneity and complexity of decentralized network environments and interdisciplinary semantics. In this article, we report a search engine framework for efficient geospatial resource discovery, which reduces integration costs by leveraging existing Geospatial Cyberinfrastructure (GCI) components. Specifically, (1) the framework provides integration capability and flexibility by adopting the brokering approach, implementing a ‘plug-in’-based framework for metadata processing and proposing a dynamically configurable search workflow; (2) the asynchronous messaging and batch processing-based metadata record retrieval mode enhances the search performance and user interactivity; (3) an embedded semantic support system improves the discovery recall level and precision by providing semantic-based search rule creation and result similarity evaluation functions and (4) the engine assists user decision-making by integrating a service quality monitoring and evaluation system, data/service visualization tools, multiple views and additional information. Experiments and a search example show that the proposed engine helps both scientists and general users search for more accurate results with enhanced performance and user experience through a user-friendly interface.

Research of Grid Resource Discovery Mechanism Based on P2P

To solve the Grid resource discovery framework problem, this paper proposes the resource discovery mechanism based on Peer-to-Peer (P2P). The mechanism introduces the concept of super-node (SN) and virtual organization (VO), which combines both the advantage of decentralized and centralized resource discovery, and makes up a layered resource management model: SN manages user and storages resource information by MDS(Meta Data Service) mechanism in the VO; a P2P virtual level is composed of a large amount of peer service (PS) among VOs, which utilizes the querying and transmitting policy based on historical information and control the diffusion algorithm in resource discovery mechanism. And the simulation shows that the algorithm can find the most suitable resources and improve resource discovery efficiency.

Semantic-based resource discovery, composition and substitution in IEEE 802.11 mobile ad hoc networks

We present a general framework for resource discovery, composition and substitution in mobile ad-hoc networks, exploiting knowledge representation techniques. Key points of the proposed approach are: (1) reuse of discovery information at network layer in order to build a fully unified semantic-based discovery and routing framework; (2) use of semantic annotations in order to perform the orchestration of elementary resources for building personalized services adopting a concept covering procedure, and to allow the automatic substitution of no more suitable/available components. Using ns-2 simulator, we evaluated performances of the proposed framework with reference to a disaster recovery scenario. In particular, the impact of the number of available services and active clients has been investigated in various mobility conditions and for several service covering threshold levels. Obtained results show that: (1) the proposed framework is highly scalable, given that its overall performance is improved by increasing the number of active clients; (2) the traffic load due to clients is negligible; (3) also for a very small number of available service providers very high hit ratios can be reached; (4) increasing the number of providers can lead to hit ratios very close to 100% at the expense of an increased traffic load. Finally, the effectiveness of cross-layer interaction between routing and resource discovery protocols has been also evaluated and discussed.

Hierarchy-based resource discovery algorithm in grid environment

In order to solve the problems of conventional resource discovery framework, a hierarchy-based model was discussed, which combined super-peer model and contact node, a membership join protocol was introduced, and a resource discovery algorithm was proposed based on Time To Live (TTL) limit and cache list. The network framework with good scalability can adapt to complexity and heterogeneity of grid resources. The simulation shows that the algorithm works well, query time is minimized and efficiency of resource discovery is improved in grid environment.

If objects could talk: a novel resource discovery approach for pervasive environments

We propose to extend standard Radio Frequency IDentification (RFID) usage by storing semantically annotated data within RFID tags memory, so that objects may actually 'describe themselves' in a variety of scenarios. In particular here we exploit our approach to carry out an advanced matchmaking process using metadata stored in RFIDs. A 'fully backward compatible' modification to the original RFID data exchange protocol is presented, allowing to implement an advanced resource discovery framework. A compression algorithm specifically devised to ease embedding of annotated DIG description is also proposed. Motivations and benefits of the approach are outlined in a tracking of agricultural and food products case study.

Semantic-enhanced Bluetooth discovery protocol for m-commerce applications

In this paper, we present a novel resource discovery framework for m-commerce. We extend the original Bluetooth service discovery protocol by integrating a semantic layer within the application level of the standard. Given a request, this layer makes possible an enhanced discovery process exploiting the semantics of the resource descriptions exposed by a hotspot. The enhancement is compatible with the basic discovery protocol, thus allowing the smooth coexistence of the service discovery approaches. We present and motivate our semantic-based discovery protocol in an innovative m-commerce framework and show its benefits.

Intelligent resource discovery using ontology-based resource profiles

Successful resource discovery across heterogeneous repositories is highly dependent on the semantic and syntactic homogeneity of the associated resource descriptions in each repository. Ideally, consistent resource descriptions are easily extracted from each repository, expressed using standard syntactic and semantic structures, and managed and accessed within a distributed, flexible, and scalable software framework. In practice however, seldom do all three of these elements exist. To help address this situation, the Object Oriented Data Technology (OODT) project at the Jet Propulsion Laboratory has developed an extensible, standards-based resource description scheme that provides the necessary description and management facilities for the discovery of resources across heterogeneous repositories. The OODT resource description scheme can be used across scientific domains to describe any resource. It uses a small set of generally accepted, broadly-scoped descriptors while also providing a mechanism for the inclusion of domain-specific descriptors. In addition, the OODT scheme can be used to capture hierarchical, relational and recursive relationships between resources. In this paper we expand on prior work and describe an intelligent resource discovery framework that consists of separate software and data architectures focusing on the standard resource description scheme. We illustrate intelligent resource discovery using a case study that provides efficient search across distributed repositories using common interfaces and a hierarchy of resource descriptions derived from a complex, domain-specific ontology.

A unified framework for resource discovery and QoS-aware provider selection in ad hoc networks

With the rising popularity of network-based applications and the potential use of mobile ad hoc networks in civilian life, an efficient resource discovery service is needed in such networks for quickly locating resource providers. In addition, to improve user experience, QoS awareness is also crucial. In this paper, we identify the challenges when basic resource discovery techniques for the Internet are used in mobile ad hoc networks. We then propose a framework that provides a unified solution to the discovery of resources and QoS-aware selection of resource providers. The key entities of this framework are a set of self-organized discovery agents. These agents manage the directory information of resources using hash indexing. They also dynamically partition the network into domains and collect intra- and inter-domain QoS information to select appropriate providers. Simulation results show that our framework improves the QoS delivered to the clients, while the cost and response time are kept at a low level.