1,910 research outputs found
Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System
Resource Discovery (RD) is a key issue in Internet-based distributed sytems such as
grid. RD is about locating an appropriate resource/service type that matches the user's
application requirements. This is very important, as resource reservation and task
scheduling are based on it. Unfortunately, RD in grid is very challenging as resources
and users are distributed, resources are heterogeneous in their platforms, status of the
resources is dynamic (resources can join or leave the system without any prior notice)
and most recently the introduction of a new type of grid called intergrid (grid of grids)
with the use of multi middlewares. Such situation requires an RD system that has rich
interoperability, scalability, decentralization and dynamism features. However,
existing grid RD systems have difficulties to attain these features. Not only that, they
lack the review and evaluation studies, which may highlight the gap in achieving the
required features. Therefore, this work discusses the problem associated with intergrid
RD from two perspectives. First, reviewing and classifying the current grid RD
systems in such a way that may be useful for discussing and comparing them. Second,
propose a novel RD framework that has the aforementioned required RD features. In
the former, we mainly focus on the studies that aim to achieve interoperability in the
first place, which are known as RD systems that use semantic information (semantic
technology). In particular, we classify such systems based on their qualitative use of
the semantic information. We evaluate the classified studies based on their degree of
accomplishment of interoperability and the other RD requirements, and draw the
future research direction of this field. Meanwhile in the latter, we name the new
framework as semantic-based scalable decentralized dynamic RD. The framework
further contains two main components which are service description, and service
registration and discovery models. The earlier consists of a set of ontologies and
services. Ontologies are used as a data model for service description, whereas the
services are to accomplish the description process. The service registration is also based on ontology, where nodes of the service (service providers) are classified to
some classes according to the ontology concepts, which means each class represents a
concept in the ontology. Each class has a head, which is elected among its own class
I
nodes/members. Head plays the role of a registry in its class and communicates with
I
the other heads of the classes in a peer to peer manner during the discovery process.
We further introduce two intelligent agents to automate the discovery process which
are Request Agent (RA) and Description Agent (DA). Eaclj. node is supposed to have
both agents. DA describes the service capabilities based on the ontology, and RA
I
carries the service requests based on the ontology as well. We design a service search
I
algorithm for the RA that starts the service look up from the class of request origin
first, then to the other classes.
We finally evaluate the performance of our framework ~ith extensive simulation
experiments, the result of which confirms the effectiveness of the proposed system in
satisfying the required RD features (interoperability, scalability, decentralization and
dynamism). In short, our main contributions are outlined new key taxonomy for the
semantic-based grid RD studies; an interoperable semantic description RD component
model for intergrid services metadata representation; a semantic distributed registry
architecture for indexing service metadata; and an agent-qased service search and
selection algorithm.
Vll
Clustering objectives in wireless sensor networks: A survey and research direction analysis
Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio
Adaptive firefly algorithm for hierarchical text clustering
Text clustering is essentially used by search engines to increase the recall and precision in information retrieval. As search engine operates on Internet content that is constantly being updated, there is a need for a clustering algorithm that offers automatic grouping of items without prior knowledge on the collection. Existing clustering methods have problems in determining optimal number of clusters and producing compact clusters. In this research, an adaptive hierarchical text clustering
algorithm is proposed based on Firefly Algorithm. The proposed Adaptive Firefly Algorithm (AFA) consists of three components: document clustering, cluster refining, and cluster merging. The first component introduces Weight-based Firefly Algorithm (WFA) that automatically identifies initial centers and their clusters for any given text collection. In order to refine the obtained clusters, a second algorithm, termed as Weight-based Firefly Algorithm with Relocate (WFAR), is proposed. Such an approach allows the relocation of a pre-assigned document into a newly created cluster. The third component, Weight-based Firefly Algorithm with Relocate and
Merging (WFARM), aims to reduce the number of produced clusters by merging nonpure clusters into the pure ones. Experiments were conducted to compare the proposed algorithms against seven existing methods. The percentage of success in
obtaining optimal number of clusters by AFA is 100% with purity and f-measure of 83% higher than the benchmarked methods. As for entropy measure, the AFA produced the lowest value (0.78) when compared to existing methods. The result indicates that Adaptive Firefly Algorithm can produce compact clusters. This research contributes to the text mining domain as hierarchical text clustering
facilitates the indexing of documents and information retrieval processes
FRTRUST: a fuzzy reputation based model for trust management in semantic P2P grids
Grid and peer-to-peer (P2P) networks are two ideal technologies for file
sharing. A P2P grid is a special case of grid networks in which P2P
communications are used for communication between nodes and trust management.
Use of this technology allows creation of a network with greater distribution
and scalability. Semantic grids have appeared as an expansion of grid networks
in which rich resource metadata are revealed and clearly handled. In a semantic
P2P grid, nodes are clustered into different groups based on the semantic
similarities between their services. This paper proposes a reputation model for
trust management in a semantic P2P Grid. We use fuzzy theory, in a trust
overlay network named FR TRUST that models the network structure and the
storage of reputation information. In fact we present a reputation collection
and computation system for semantic P2P Grids. The system uses fuzzy theory to
compute a peer trust level, which can be either: Low, Medium, or High. Our
experimental results demonstrate that FR TRUST combines low (and therefore
desirable) a good computational complexity with high ranking accuracy.Comment: 12 Pages, 10 Figures, 3 Tables, InderScience, International Journal
of Grid and Utility Computin
Self-Healing Protocols for Connectivity Maintenance in Unstructured Overlays
In this paper, we discuss on the use of self-organizing protocols to improve
the reliability of dynamic Peer-to-Peer (P2P) overlay networks. Two similar
approaches are studied, which are based on local knowledge of the nodes' 2nd
neighborhood. The first scheme is a simple protocol requiring interactions
among nodes and their direct neighbors. The second scheme adds a check on the
Edge Clustering Coefficient (ECC), a local measure that allows determining
edges connecting different clusters in the network. The performed simulation
assessment evaluates these protocols over uniform networks, clustered networks
and scale-free networks. Different failure modes are considered. Results
demonstrate the effectiveness of the proposal.Comment: The paper has been accepted to the journal Peer-to-Peer Networking
and Applications. The final publication is available at Springer via
http://dx.doi.org/10.1007/s12083-015-0384-
Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System
Resource Discovery (RD) is a key issue in Internet-based distributed sytems such as
grid. RD is about locating an appropriate resource/service type that matches the user's
application requirements. This is very important, as resource reservation and task
scheduling are based on it. Unfortunately, RD in grid is very challenging as resources
and users are distributed, resources are heterogeneous in their platforms, status of the
resources is dynamic (resources can join or leave the system without any prior notice)
and most recently the introduction of a new type of grid called intergrid (grid of grids)
with the use of multi middlewares. Such situation requires an RD system that has rich
interoperability, scalability, decentralization and dynamism features. However,
existing grid RD systems have difficulties to attain these features. Not only that, they
lack the review and evaluation studies, which may highlight the gap in achieving the
required features. Therefore, this work discusses the problem associated with intergrid
RD from two perspectives. First, reviewing and classifying the current grid RD
systems in such a way that may be useful for discussing and comparing them. Second,
propose a novel RD framework that has the aforementioned required RD features. In
the former, we mainly focus on the studies that aim to achieve interoperability in the
first place, which are known as RD systems that use semantic information (semantic
technology). In particular, we classify such systems based on their qualitative use of
the semantic information. We evaluate the classified studies based on their degree of
accomplishment of interoperability and the other RD requirements, and draw the
future research direction of this field. Meanwhile in the latter, we name the new
framework as semantic-based scalable decentralized dynamic RD. The framework
further contains two main components which are service description, and service
registration and discovery models. The earlier consists of a set of ontologies and
services. Ontologies are used as a data model for service description, whereas the
services are to accomplish the description process. The service registration is also based on ontology, where nodes of the service (service providers) are classified to
some classes according to the ontology concepts, which means each class represents a
concept in the ontology. Each class has a head, which is elected among its own class
I
nodes/members. Head plays the role of a registry in its class and communicates with
I
the other heads of the classes in a peer to peer manner during the discovery process.
We further introduce two intelligent agents to automate the discovery process which
are Request Agent (RA) and Description Agent (DA). Eaclj. node is supposed to have
both agents. DA describes the service capabilities based on the ontology, and RA
I
carries the service requests based on the ontology as well. We design a service search
I
algorithm for the RA that starts the service look up from the class of request origin
first, then to the other classes.
We finally evaluate the performance of our framework ~ith extensive simulation
experiments, the result of which confirms the effectiveness of the proposed system in
satisfying the required RD features (interoperability, scalability, decentralization and
dynamism). In short, our main contributions are outlined new key taxonomy for the
semantic-based grid RD studies; an interoperable semantic description RD component
model for intergrid services metadata representation; a semantic distributed registry
architecture for indexing service metadata; and an agent-qased service search and
selection algorithm.
Vll
A Survey on Underwater Acoustic Sensor Network Routing Protocols
Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research
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