Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

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

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. 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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. 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