Fast Reroute (FRR) and other forms of immediate failover have long been used to recover from certain classes of failures without invoking the network control plane. While the set of such techniques is growing, the level of resiliency to failures that this approach can provide is not adequately understood. In this paper, we embarked upon a systematic algorithmic study of the resiliency of forwarding tables in a variety of models (i.e., deterministic/probabilistic routing, with packet-header-rewriting, with packet-duplication). Our results show that the resiliency of a routing scheme depends on the "connectivity" k of a network, i.e., the minimum number of link deletions that partition a network. We complement our theoretical result with extensive simulations. We show that resiliency to 4 simultaneous link failures, with limited path stretch, can be achieved without any packet modification/duplication or randomization. Furthermore, our routing schemes provide resiliency against k−1 failures, with limited path stretch, by storing log(k) bits in the packet header, with limited packet duplication, or with randomized forwarding technique.

Fast Reroute (FRR) and other forms of immediate failover have long been used to recover from certain classes of failures without invoking the network control plane. While the set of such techniques is growing, the level of resiliency to failures that this approach can provide is not adequately understood. We embark upon a systematic algorithmic study of the resiliency of immediate failover in a variety of models (with/without packet marking/duplication, etc.). We leverage our findings to devise new schemes for immediate failover and show, both theoretically and experimentally, that these outperform existing approaches.

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Mobile health (m-Health) scenarios and Internet of Things (IoT) technologies form an important direction for enhancing medical systems for Ambient Assisted Living (AAL). Yet current development meets with two challenges: 1) use of patient's health data with strong security guarantees in mobile network and resource-constrained assumptions and in emergency situations, 2) inclusion of personal data to the entire system for “smart” service construction and delivery. This paper presents a smart space based architectural model that adopts emerging IoT technologies to enable security of personal mobile data and their intelligent utilization in health services. To support the service intelligence, the authors employ the smart spaces approach with its prominent technologies adopted from IoT and Semantic Web. The intelligence and security solutions are considered symbiotic to present better user-experience, security level, and utility of a system.