33,304 research outputs found

    Denial of service mitigation approach for IPv6-enabled smart object networks

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    Denial of service (DoS) attacks can be defined as any third-party action aiming to reduce or eliminate a network's capability to perform its expected functions. Although there are several standard techniques in traditional computing that mitigate the impact of some of the most common DoS attacks, this still remains a very important open problem to the network security community. DoS attacks are even more troublesome in smart object networks because of two main reasons. First, these devices cannot support the computational overhead required to implement many of the typical counterattack strategies. Second, low traffic rates are enough to drain sensors' battery energy making the network inoperable in short times. To realize the Internet of Things vision, it is necessary to integrate the smart objects into the Internet. This integration is considered an exceptional opportunity for Internet growth but, also, a security threat, because more attacks, including DoS, can be conducted. For these reasons, the prevention of DoS attacks is considered a hot topic in the wireless sensor networks scientific community. In this paper, an approach based on 6LowPAN neighbor discovery protocol is proposed to mitigate DoS attacks initiated from the Internet, without adding additional overhead on the 6LoWPAN sensor devices.This work has been partially supported by the Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Portugal, and by National Funding from the FCT - Fundacao para a Ciencia e Tecnologia through the Pest-OE/EEI/LA0008/2011.Oliveira, LML.; Rodrigues, JJPC.; De Sousa, AF.; Lloret, J. (2013). Denial of service mitigation approach for IPv6-enabled smart object networks. Concurrency and Computation: Practice and Experience. 25(1):129-142. doi:10.1002/cpe.2850S129142251Gershenfeld, N., Krikorian, R., & Cohen, D. (2004). The Internet of Things. Scientific American, 291(4), 76-81. doi:10.1038/scientificamerican1004-76Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393-422. doi:10.1016/s1389-1286(01)00302-4Karl, H., & Willig, A. (2005). Protocols and Architectures for Wireless Sensor Networks. doi:10.1002/0470095121IEEE Std 802.15.4-2006 Part 15.4: wireless medium access control (MAC) and physical layer (PHY) specificationsfor low-rate wireless personal area networks (LR-WPANs) 2006ZigBee Alliance ZigBee Specification 2007WirelessHARThomepage 2012 http://www.hartcomm.org/Hui, J. W., & Culler, D. E. (2008). Extending IP to Low-Power, Wireless Personal Area Networks. IEEE Internet Computing, 12(4), 37-45. doi:10.1109/mic.2008.79Kushalnagar N Montenegro G Schumacher C IPv6 over Low-Power Wireless Personal Area Networks (6LoWPANs): Overview, Assumptions, Problem Statement, and Goals 2007Montenegro G Kushalnagar N Hui J Culler D Transmission of IPv6 Packets over IEEE 802.15.4 Networks 2007Shelby Z Thubert P Hui J Chakrabarti S Bormann C Nordmark E 6LoWPAN Neighbor Discovery 2011Zhou, L., Chao, H.-C., & Vasilakos, A. V. (2011). Joint Forensics-Scheduling Strategy for Delay-Sensitive Multimedia Applications over Heterogeneous Networks. IEEE Journal on Selected Areas in Communications, 29(7), 1358-1367. doi:10.1109/jsac.2011.110803Roman, R., & Lopez, J. (2009). Integrating wireless sensor networks and the internet: a security analysis. Internet Research, 19(2), 246-259. doi:10.1108/10662240910952373Wang, Y., Attebury, G., & Ramamurthy, B. (2006). A survey of security issues in wireless sensor networks. IEEE Communications Surveys & Tutorials, 8(2), 2-23. doi:10.1109/comst.2006.315852Xiaojiang Du, & Hsiao-Hwa Chen. (2008). Security in wireless sensor networks. IEEE Wireless Communications, 15(4), 60-66. doi:10.1109/mwc.2008.4599222Pelechrinis, K., Iliofotou, M., & Krishnamurthy, S. V. (2011). Denial of Service Attacks in Wireless Networks: The Case of Jammers. IEEE Communications Surveys & Tutorials, 13(2), 245-257. doi:10.1109/surv.2011.041110.00022Zhou, L., Wang, X., Tu, W., Muntean, G., & Geller, B. (2010). Distributed scheduling scheme for video streaming over multi-channel multi-radio multi-hop wireless networks. IEEE Journal on Selected Areas in Communications, 28(3), 409-419. doi:10.1109/jsac.2010.100412Lin, K., Lai, C.-F., Liu, X., & Guan, X. (2010). Energy Efficiency Routing with Node Compromised Resistance in Wireless Sensor Networks. Mobile Networks and Applications, 17(1), 75-89. doi:10.1007/s11036-010-0287-xLi, H., Lin, K., & Li, K. (2011). Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks. Computer Communications, 34(4), 591-597. doi:10.1016/j.comcom.2010.02.026Oliveira, L. M. L., de Sousa, A. F., & Rodrigues, J. J. P. C. (2011). Routing and mobility approaches in IPv6 over LoWPAN mesh networks. International Journal of Communication Systems, 24(11), 1445-1466. doi:10.1002/dac.1228Narten T Nordmark E Simpson W Soliman H Neighbor Discovery for IP version 6 (IPv6) 2007Singh H Beebee W Nordmark E IPv6 Subnet Model: The Relationship between Links and Subnet Prefixes 2010Roman, R., Lopez, J., & Gritzalis, S. (2008). Situation awareness mechanisms for wireless sensor networks. IEEE Communications Magazine, 46(4), 102-107. doi:10.1109/mcom.2008.4481348Sakarindr, P., & Ansari, N. (2007). Security services in group communications over wireless infrastructure, mobile ad hoc, and wireless sensor networks. IEEE Wireless Communications, 14(5), 8-20. doi:10.1109/mwc.2007.4396938Tsao T Alexander R Dohler M Daza V Lozano A A Security Framework for Routing over Low Power and Lossy Networks 2009Karlof C Wagner D Secure Routing in Wireless Sensor Networks: Attacks and Countermeasures First IEEE International Workshop on Sensor Network Protocols and Applications 2003 113 127 10.1109/SNPA.2003.1203362Hui J Thubert P Compression Format for IPv6 Datagrams in 6LoWPAN Networks 2009Elaine Shi, & Perrig, A. (2004). Designing Secure Sensor Networks. IEEE Wireless Communications, 11(6), 38-43. doi:10.1109/mwc.2004.1368895Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3(3), 325-349. doi:10.1016/j.adhoc.2003.09.01

    A two-way radio communication across a multi-hop wireless sensor network based on a commercial IEEE 802.15.4 compliant platform

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    Wireless Sensor Networks, and especially IEEE 802.15.4, are originally defined for low cost applications, with low bit rates and power restrictions in mind. However, the ubiquity of the nodes and their easy connectivity also enable them to be used in supporting real time services, for instance, emergency scenarios, where TETRA is usually the employed audio technology. Focusing on voice transmission, we present a performance evaluation of audio streaming over a multi-hop Low-Rate Wireless Personal Area Network in order to provide bidirectional audio communication using a commercial IEEE 802.15.4 compliant platform. This paper includes an assessment of different software protocols and compression algorithms to support audio transmission on a CC2530 System-on-Chip WSN mote. The results establish the maximum number of hops of a bidirectional single-route network under real- time voice quality constraints.Peer ReviewedPostprint (published version

    A Survey on Communication Networks for Electric System Automation

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    Published in Computer Networks 50 (2006) 877–897, an Elsevier journal. The definitive version of this publication is available from Science Direct. Digital Object Identifier:10.1016/j.comnet.2006.01.005In today’s competitive electric utility marketplace, reliable and real-time information become the key factor for reliable delivery of power to the end-users, profitability of the electric utility and customer satisfaction. The operational and commercial demands of electric utilities require a high-performance data communication network that supports both existing functionalities and future operational requirements. In this respect, since such a communication network constitutes the core of the electric system automation applications, the design of a cost-effective and reliable network architecture is crucial. In this paper, the opportunities and challenges of a hybrid network architecture are discussed for electric system automation. More specifically, Internet based Virtual Private Networks, power line communications, satellite communications and wireless communications (wireless sensor networks, WiMAX and wireless mesh networks) are described in detail. The motivation of this paper is to provide a better understanding of the hybrid network architecture that can provide heterogeneous electric system automation application requirements. In this regard, our aim is to present a structured framework for electric utilities who plan to utilize new communication technologies for automation and hence, to make the decision making process more effective and direct.This work was supported by NEETRAC under Project #04-157

    A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

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    In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

    Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

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    Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

    Service and device discovery of nodes in a wireless sensor network

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    Emerging wireless communication standards and more capable sensors and actuators have pushed further development of wireless sensor networks. Deploying a large number of sensor\ud nodes requires a high-level framework enabling the devices to present themselves and the resources they hold. The device and the resources can be described as services, and in this paper, we review a number of well-known service discovery protocols. Bonjour stands out with its auto-configuration, distributed architecture, and sharing of resources. We also present a lightweight implementation in order to demonstrate that an emerging standards-based device and service discovery protocol can actually be deployed on small wireless sensor nodes

    IETF standardization in the field of the Internet of Things (IoT): a survey

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    Smart embedded objects will become an important part of what is called the Internet of Things. However, the integration of embedded devices into the Internet introduces several challenges, since many of the existing Internet technologies and protocols were not designed for this class of devices. In the past few years, there have been many efforts to enable the extension of Internet technologies to constrained devices. Initially, this resulted in proprietary protocols and architectures. Later, the integration of constrained devices into the Internet was embraced by IETF, moving towards standardized IP-based protocols. In this paper, we will briefly review the history of integrating constrained devices into the Internet, followed by an extensive overview of IETF standardization work in the 6LoWPAN, ROLL and CoRE working groups. This is complemented with a broad overview of related research results that illustrate how this work can be extended or used to tackle other problems and with a discussion on open issues and challenges. As such the aim of this paper is twofold: apart from giving readers solid insights in IETF standardization work on the Internet of Things, it also aims to encourage readers to further explore the world of Internet-connected objects, pointing to future research opportunities

    Architectures for Wireless Sensor Networks

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    Various architectures have been developed for wireless sensor networks. Many of them leave to the programmer important concepts as the way in which the inter-task communication and dynamic reconfigurations are addressed. In this paper we describe the characteristics of a new architecture we proposed - the data-centric architecture. This architecture offers an easy way of structuring the applications designed for wireless sensor nodes that confers them superior performances
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