Abstract. Exhaustive verification often suffers from the state-explosion problem, where the reachable state space is too large to fit in main memory. For this reason, and because of disk swapping, once the main memory is full very little progress is made, and the process is not scalable. To alleviate this, partial verification methods have been proposed, some based on randomized exploration, mostly in the form of random walks. In this paper, we enhance partial, randomized state-space exploration methods with the concept of resource-awareness: the exploration algorithm is made aware of the limits on resources, in particular memory and time. We present a memory-aware algorithm that by design never stores more states than those that fit in main memory. We also propose criteria to compare this algorithm with similar other algorithms. We study properties of such algorithms both theoretically on simple classes of state spaces and experimentally on some preliminary case studies.
In this paper, optimal and suboptimal routing protocols are proposed for cognitive radio networks. We first investigate optimal routing protocol that consists in searching among all available paths, the one that minimises the end-to-end outage while verifying interference constraint to primary receiver. A suboptimal one-hop routing protocol is proposed where the best relay is selected in each hop. The last routing protocol consists in decomposing the network in many subnetworks composed of K hops. Then, the best route is determined in each of these subnetworks so that the K-hops outage probability is minimised. The proposed K-hops routing protocol allows a good compromise between complexity and performance. The outage probability of the different routing protocols is evaluated theoretically and through simulation results.
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