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Sinkhole attack is an active routing disruption attack in the routing layer of the mobile ad hoc networks. A sinkhole node attempts to entice all the network traffic towards it by broadcasting bogus routing information to other nodes in the network. On demand routing protocols such as dynamic source routing protocol and ad hoc on demand distance vector protocol are vulnerable to this attack. Sinkhole attack makes use of the route discovery and the route maintenance phases of these protocols. Sinkhole attack often facilitates other attacks such as blackhole attack, greyhole attack, wormhole attack and Sybil attack on MANETs. In this paper, we present a secondary cache based approach to prevent the sinkhole attack in DSR MANETs. The simulation results show that the proposed approach improves the performance of DSR even in the presence of multiple sinkhole attacks.

Security in mobile ad hoc networks is difficult to achieve, because of the dynamic topologies, limited resources, the absence of a certification authority and the lack of a centralized monitoring point [1]. Most of the attacks in MANETs are routing protocol attacks. The sinkhole effect is caused by attempts to draw all network traffic to malicious nodes that broadcast fake shortest path routing information. The sinkhole nodes should be detected and detached as early as possible. The detection mechanism should also guarantee higher detection rate and lower cross over error rate. In this paper we propose a novel technique to detect the sinkholes which uses the mutual understanding among the mobile nodes.

Though cloud data center is highly adapted for flexible, scalable and highly available computing and storage resources, it is vulnerable to failures. Predicting the occurrence of server failure and taking appropriate preventive measures are essential in the cloud data center. In order to develop fault-tolerant cloud data center, a Fault Tree Analysis (FTA) based failure aware virtual machine (VM) migration technique is proposed. A fault tree is constructed for server failure event. The server failure is estimated by analyzing the fault tree and the virtual machines are migrated proactively to an alternate server before the failure. Simulations have been carried out and performance of the proposed technique is analyzed in terms of throughput. The results show that the proposed technique outperforms the other state of art techniques.