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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jss.2010.03.080 Byline: Mohamed Alnas, Irfan Awan, R.D.W. Holton Keywords: Mobile IPv6; Fast Handover; Mobility Management; Link-Layer Information; Handover Latency Abstract: Handover latency is the primary cause of packet loss resulting in performance degradation of standard Mobile IPv6. Mobile IPv6 with fast Handover enables a Mobile Node (MN) to quickly detect at the IP layer that it has moved to a new subnet by receiving link-related information from the link-layer; furthermore it gathers anticipative information about the new Access Point (AP) and the associated subnet prefix when the MN is still connected to the previous Corresponding Node (CN). This paper proposes an enhancement to Fast Mobile IPv6 handover (FMIPv6), based on link layer information, we also present performance evaluations in terms of the packet loss and handover latency using evaluation models. Author Affiliation: Mobile Computing, Networks and Security Research Group, School of Informatics, University of Bradford, Bradford, West Yorkshire, BD7 1DP, UK Article History: Received 9 November 2009; Revised 18 January 2010; Accepted 30 March 2010

Internet of Things (IoT) platforms are responsible for overall data processing in the IoT System. This ranges from analytics and big data processing to gathering all sensor data over time to analyze and produce long‐term trends. However, this comes with prohibitively high demand for resources such as memory, computing power and bandwidth, which the highly resource constrained IoT devices lack to send data to the platforms to achieve efficient operations. This results in poor availability and risk of data loss due to single point of failure should the cloud platforms suffer attacks. The integrity of the data can also be compromised by an insider, such as a malicious system administrator, without leaving traces of their actions. To address these issues, we propose in this work an edge‐based blockchain enabled anomaly detection technique to prevent insider attacks in IoT. The technique first employs the power of edge computing to reduce the latency and bandwidth requirements by taking processing closer to the IoT nodes, hence improving availability, and avoiding single point of failure. It then leverages some aspect of sequence‐based anomaly detection, while integrating distributed edge with blockchain that offers smart contracts to perform detection and correction of abnormalities in incoming sensor data. Evaluation of our technique using real IoT system datasets showed that the technique remarkably achieved the intended purpose, while ensuring integrity and availability of the data which is critical to IoT success. [ABSTRACT FROM AUTHOR]

Efficient and adaptive buffer management will play crucial role in the future integrated mobile network (e.g., 4th Generation). One of the main features of the future mobile networks will be their capability of providing different levels of quality of service to the different types of services. Some of these services will be delay and delay variation sensitive such as real-time voice and video. Others will be loss sensitive such as data transfer. But the most challenging will be the sort of multimedia traffic that owns both types of sensitivity. Another source of difficulty stems from the heterogeneous wireless air interface technologies that will act as border nodes to the network providing different traffic streams with different data rates and QoS requirements (e.g, WLAN provides data rates of 11Mbbps while UMTS can only provide 384Kbps). Although improved call admission control algorithms on the border of the network will provide a sort of protection from extensive traffic over the network, however, they will only operate on mean traffic volumes and will not cope with the variability of actual instantaneous traffic entering the network. Furthermore, as the core part of the mobile network will be packet switched based on IP, the QoS can only be maintained through efficient buffer management at the border and inside the network. This paper proposes and analytically evaluates a buffer management scheme that is based on multi-level priority and Partial Buffer Sharing (PBS) policy for all buffers at the border and inside the wireless network. The analytical model is based on the G/G/1/N censored queue with single server and R ( R2) priority classes under the Head of Line (HOL) service rule for the PBS scheme. The traffic is modelled using the Generalised Exponential distribution. The paper presents an analytical solution based on the approximation using the Maximum Entropy (ME) principle. The numerical results show the capability of the space prioritised buffer management scheme to provide higher QoS for the higher priority service classes [ABSTRACT FROM AUTHOR]