7,111 research outputs found
Distributed Topology Control for Stable Path Routing in Multi-hop Wireless Networks
In this paper, we introduce the stable path topology control problem for routing in mobile multi-hop networks. We formulate the topology control problem of selective link-state broadcast as a graph pruning problem with restricted local neighborhood information. We develop a multi-agent optimiza- tion framework where the decision policies of each agent are restricted to local policies on incident edges and independent of the policies of the other agents. We show that under a condition called the positivity condition, these independent local policies preserve the stable routing paths globally. We then provide an efficient algorithm to compute an optimal local policy that yields a minimal pruned graph, which we call the Stable Path Topology Control (SPTC) algorithm. Using simulations, we demonstrate that this algorithm, when used with the popular ETX metric, outperforms topology control mechanisms commonly used for Mobile Ad Hoc Networks
QoS routing in ad-hoc networks using GA and multi-objective optimization
Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs) and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks) to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing).Peer ReviewedPostprint (published version
An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applications
Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes
or terminals with wireless communications and networking capability that
communicate with each other without the aid of any centralized administrator
also the wireless nodes that can dynamically form a network to exchange
information without using any existing fixed network infrastructure. And it's
an autonomous system in which mobile hosts connected by wireless links are free
to be dynamically and some time act as routers at the same time, and we discuss
in this paper the distinct characteristics of traditional wired networks,
including network configuration may change at any time, there is no direction
or limit the movement and so on, and thus needed a new optional path Agreement
(Routing Protocol) to identify nodes for these actions communicate with each
other path, An ideal choice way the agreement should not only be able to find
the right path, and the Ad Hoc Network must be able to adapt to changing
network of this type at any time. and we talk in details in this paper all the
information of Mobile Ad Hoc Network which include the History of ad hoc,
wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc
networks, and then we present more than 13 types of the routing Ad Hoc Networks
protocols have been proposed. In this paper, the more representative of routing
protocols, analysis of individual characteristics and advantages and
disadvantages to collate and compare, and present the all applications or the
Possible Service of Ad Hoc Networks.Comment: 24 Pages, JGraph-Hoc Journa
Intrusion Detection in Mobile Ad Hoc Networks Using Classification Algorithms
In this paper we present the design and evaluation of intrusion detection
models for MANETs using supervised classification algorithms. Specifically, we
evaluate the performance of the MultiLayer Perceptron (MLP), the Linear
classifier, the Gaussian Mixture Model (GMM), the Naive Bayes classifier and
the Support Vector Machine (SVM). The performance of the classification
algorithms is evaluated under different traffic conditions and mobility
patterns for the Black Hole, Forging, Packet Dropping, and Flooding attacks.
The results indicate that Support Vector Machines exhibit high accuracy for
almost all simulated attacks and that Packet Dropping is the hardest attack to
detect.Comment: 12 pages, 7 figures, presented at MedHocNet 200
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