A Modified Shared-tree Multicast Routing Protocol in Ad Hoc Network

Mobile ad hoc network is a wireless mobile network that does not have any base station or other central control infrastructure. Design of efficient multicast routing protocols in such network is challenging, especially when the mobile hosts move faster. Shared tree routing protocol is a widely used multicast routing protocol in ad hoc network. However, there are problems in end-to-end delay and network throughput for this protocol. In this paper, we propose a protocol to improve the inherent problem of large end-to-end delay in shared tree method as a modification to the existing multicast Ad hoc On-demand Distance Vector (MAODV) routing for low mobility network. The protocol uses n-hop local ring search to establish new forwarding path and limit flooding region. We then propose an extension to our proposed protocol, which uses periodic route discovery message to improve the network throughput for high mobility network. Simulation results demonstrate the improvement with average end-to-end delay in low mobility case as well as high packet delivery ratio in high mobility cas

An Intelligence-Aware Process Calculus for Multi-Agent System Modeling

In this paper we propose an agent modeling language named CAML that provides a comprehensive framework for representing all relevant aspects of a multi-agent system: specially, its configuration and the reasoning abilities of its constituent agents. The configuration modeling aspect of the language supports natural grouping and mobility, and the reasoning framework is inspired by an extension of the popular BDI theory of modeling cognitive skills of agents. We present the motivation behind the development of the language, its syntax, and an informal semantics

A Fault-Tolerant Multicast Routing Protocol for Mobile Ad–Hoc Networks

In this work, we propose an efficient multicast routing protocol for mobile ad hoc networks. To achieve high efficiency with low channel and storage overhead, the proposed protocol employs the following mechanism: (1) on-demand invocation of route setup and route maintenance process to avoid periodical control packet transmissions, thus reducing channel overhead, (2) creation of “forwarding group” to forward multicast packets, thus reducing storage overhead, (3) exploration of multiple possible routes from a single flooded query to reduce the frequency of route discovery, thus further reducing channel overhead, (4) a new route setup mechanism that allows a newly joining node to find the nearest forwarding node to minimize the number of added forwarding nodes, thus further reducing storage overhead. To provide the capability of fault tolerance, we introduce the alternate route together with the primary route. We observe that for multicasting the channel and storage overheads of the presented approach are less than those of the DVMRP approach. Also, the channel overhead is less than that in the FGMP approach for multicasting in low mobility scenario, while the storage overheads are the same in the presented approach and in the FGMP approach

Radical Agent-based Approach for Intelligence Analysis

This paper presents a novel agent-based framework as a decision aid tool for intelligence analysis. This technology extends net-centric information processing and abstraction as well as fusion and multi-source integration strategies. Our information agents traverse and mediate disparate ontologies in different formats providing a foundation for semantic interoperability. The presented system provides knowledge discovery by accessing a large number of information sources in a particular domain and organizing them into a network of information agents. Each agent provides expertise on a specific topic by drawing on relevant information from other information agents in related knowledge domains. Unique advantages include net-centric scalability, principled information assurance, as well as ground breaking knowledge discovery in service of intelligence analysis

A Recovery Scheme for Cluster Federations Using Sender-based Message Logging

A cluster federation is a union of clusters and is heterogeneous. Each cluster contains a certain number of processes. An application running in such a computing environment is divided into communicating modules so that these modules can run on different clusters. To achieve fault-tolerance different clusters may employ different check pointing schemes. For example, some may use coordinated schemes, while some other may use communication-induced schemes. It may complicate the recovery process. In this paper, we have addressed the complex problem of recovery for cluster computing environment. The proposed approach handles both inter cluster orphan and lost messages unlike the existing works in this area. We first propose an algorithm to determine a recovery line so that there does not exist any inter cluster orphan message between any pair of the cluster level check points belonging to the recovery line. The main feature of the proposed algorithm is that it can be executed simultaneously by all clusters in the cluster federation. Next we apply the sender-based message logging idea to effectively handle all inter cluster lost messages to ensure correctness of computation

Extracting Web User Profiles Using a Modified CARD Algorithm

Clustering algorithms are widely used methods for organizing data into useful information. The Competitive Agglomeration for Relational Data (CARD) Algorithm is one such clustering algorithm that is designed to organize user sessions into profiles, where each profile would highlight a particular type of user. The CARD algorithm is a viable candidate for web clustering; however, it does have limitations such as an extended execution time. In addition, the methods that prepare the input data for the CARD algorithm’s use employs concepts which seem to be incomplete. These limitations of the CARD algorithm are explored and modifications are introduced to yield a more practical and efficient algorithm

A Modified Competitive Agglomeration for Relational Data Algorithm

Clustering algorithms are invaluable methods for organizing data into useful information. The CARD Algorithm [11 is one such algorithm that is designed to organize user sessions into profiles, where each profile would highlight a particular type of user. The CARD algorithm is a viable candidate for web clustering. However it does have limitations such as long execution time. In addition, the data preparation for the algorithm\u27s requirements employs concepts that are incomplete. These limitations of the algorithm will be explored and modified to yield a more practical and efficient algorithm