29,577 research outputs found

    Data-Gathering and Aggregation Protocol for Networked Carrier Ad Hoc Networks: The Optimal and Heuristic Approach

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    In this chapter, we address the problem of data-gathering and aggregation (DGA) in navigation carrier ad hoc networks (NC-NET), in order to reduce energy consumption and enhance network scalability and lifetime. Several clustering algorithms have been presented for vehicle ad hoc network (VANET) and other mobile ad hoc network (MANET). However, DGA approach in harsh environments, in terms of long-range transmission, high dynamic topology and three-dimensional monitor region, is still an open issue. In this chapter, we propose a novel clustering-based DGA approach, namely, distributed multiple-weight data-gathering and aggregation (DMDG) protocol, to guarantee quality of service (QoS)-aware DGA for heterogeneous services in above harsh environments. Our approach is explored by the synthesis of three kernel features. First, the network model is addressed according to specific conditions of networked carrier ad hoc networks (NC-NET), and several performance indicators are selected. Second, a distributed multiple-weight data-gathering and aggregation protocol (DMDG) is proposed, which contains all-sided active clustering scheme and realizes long-range real-time communication by tactical data link under a time-division multiple access/carrier sense multiple access (TDMA/CSMA) channel sharing mechanism. Third, an analytical paradigm facilitating the most appropriate choice of the next relay is proposed. Experimental results have shown that DMDG scheme can balance the energy consumption and extend the network lifetime notably and outperform LEACH, PEACH and DEEC in terms of network lifetime and coverage rate, especially in sparse node density or anisotropic topologies

    Use of context-awareness in mobile peer-to-peer networks

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    Mobile ad-hoc network are an emerging research field due to the potential range of applications that they support and for the problems they present due to their dynamic nature. Peer-to-peer is an example of a class of applications that have recently been deployed on top of ad-hoc networks. In this paper we propose an approach based on context-awareness to allow peer-to-peer applications to exploit information on the underlying network context to achieve better performance and better group organization. Information such as availability of resources, battery power, services in reach and relative distances can be used to improve the routing structures of the peer-to-peer network, thus reducing the routing overhead

    Making On-Demand Routing Efficient with Route-Request Aggregation

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    In theory, on-demand routing is very attractive for mobile ad hoc networks (MANET), because it induces signaling only for those destinations for which there is data traffic. However, in practice, the signaling overhead of existing on-demand routing protocols becomes excessive as the rate of topology changes increases due to mobility or other causes. We introduce the first on-demand routing approach that eliminates the main limitation of on-demand routing by aggregating route requests (RREQ) for the same destinations. The approach can be applied to any existing on-demand routing protocol, and we introduce the Ad-hoc Demand-Aggregated Routing with Adaptation (ADARA) as an example of how RREQ aggregation can be used. ADARA is compared to AODV and OLSR using discrete-event simulations, and the results show that aggregating RREQs can make on-demand routing more efficient than existing proactive or on-demand routing protocols

    Resilient networking in wireless sensor networks

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    This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

    A Survey on Wireless Sensor Network Security

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    Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table
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