In this Thesis, we present a fault recovery mechanism by considering both local and global repairs for real-time traffic conveyed over MPLS networks. To meet the end-to-end time constraints of real-time traffic flows, once a link failure occurs, the real-time packets are sent via the most nearby local repair path if one can be identified, while at the same time the probe packets are sent to the Egress router over every possible local repair paths. By monitoring all of the incoming probe packets, the Egress router can determine which path is the most suitable repair path using the minimum-delay-deviation criterion and then sends out all the remaining packets over the new path. To fulfill the delay requirements of real-time flows whenever link failures occur, the probe packets need to be periodically sent out to reflect the dynamic change of traffic loads on the pre-established LSPs. The simulation results, after running on the MSN, have demonstrated that our recovery scheme not only forwards the packets of real-time flows in time over the local repair paths, but also prevents them from possible out-of-order situations. Besides, the proposed scheme of dynamic rerouting assist us in achieving the end-to-end delay guarantee for real-time traffic on MPLS networks.

Mobile Ad hoc NETworks (MANETs) have attracted great research interest in recent years. Among many issues, lack of motivation for participating nodes to collaborate forms a major obstacle to the adoption of MANETs. Many contemporary collaboration enforcement techniques employ reputation mechanisms for nodes to avoid and penalize malicious participants. Reputation information is propagated among participants and updated based on complicated trust relationships to thwart false accusation of benign nodes. The aforementioned strategy suffers from low scalability and is likely to be exploited by adversaries. To address these problems, we first propose a finite state model. With this technique, no reputation information is propagated in the network and malicious nodes cannot cause false penalty to benign hosts. Misbehaving node detection is performed on-demand; and malicious node punishment and avoidance are accomplished by only maintaining reputation information within neighboring nodes. This scheme, however, requires that each node equip with a tamper-proof hardware. In the second technique, no such restriction applies. Participating nodes classify their one-hop neighbors through direct observation and misbehaving nodes are penalized within their localities. Data packets are dynamically rerouted to circumvent selfish nodes. In both schemes, overall network performance is greatly enhanced. Our approach significantly simplifies the collaboration enforcement process, incurs low overhead, and is robust against various malicious behaviors. Simulation results based on different system configurations indicate that the proposed technique can significantly improve network performance with very low communication cost.