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This paper considers the problem of self-diagnosis of wireless ad-hoc networks using the comparison approach. In this approach, a MANET consists of a collection of n independent heterogeneous mobile hosts interconnected via wireless links, and it is assumed that at most σ of these mobile hosts are faulty. In order to diagnose the state of the wireless ad hoc network, tasks are assigned to pairs of mobiles and the outcomes of these tasks are compared. The agreements and disagreements among mobiles are the basis for identifying the faulty mobiles. The comparison approach is believed to be one of the most practical diagnosis approaches. We describe a new distributed self-diagnosis protocol for wireless ad hoc networks that is able to identify hard and soft faults in a finite amount of time. We then analyze the time and communication complexities of wireless ad hoc networks and show that it performs better, from a communication complexity viewpoint, than the existing protocols.

This paper considers the problem of self-diagnosis of wireless mesh networks (WMNs) and mobile ad-hoc networks (MANETs) using the comparison approach. In this approach, the network consists of a collection of n independent heterogeneous mobile or stationary hosts interconnected via wireless links, and it is assumed that at most σ of these hosts are faulty. In order to diagnose the state of the wireless mesh and ad-hoc network, tasks are assigned to pairs of hosts and the outcomes of these tasks are compared. The agreements and disagreements among hosts are the basis for identifying the faulty ones. We develop a new distributed self-diagnosis protocol, called Adaptive-DSDP, for MANETs and WMNs that identifies both hard and soft faults in a finite amount of time. We analyze the time and communication complexities of our protocol and compare it to existing self-diagnosis protocols.

This paper considers the problem of self-diagnosis of mobile ad-hoc networks (MANETs) using the comparison approach. In this approach, a MANET consists of a collection of n independent heterogeneous mobile hosts interconnected via wireless links, and it is assumed that at most σ of these mobile hosts are faulty. In order to diagnose the state of the MANET, tasks are assigned to pairs of mobiles and the outcomes are compared. The agreements and disagreements among mobiles are the basis for identifying the faulty ones. We describe a new distributed self-diagnosis protocol for MANETs that is able to identify hard and soft faults in a finite time, and we show that it performs better than the existing protocols.

No abstract