Modeling Responsiveness of Decentralized Service Discovery in Wireless Mesh Networks
In modern service networks, discovery plays a crucial role as a layer where providing instances of a given service can be published and enumerated. Since successful discovery is mandatory for service usage, comprehensive service dependability assessment needs to incorporate the dependability of the discovery layer. This work focuses on the responsiveness of the discovery layer, the probability to operate successfully within a deadline, even in the presence of faults. It proposes a hierarchy of stochastic models for decentralized discovery and uses it to describe the discovery of a single service using three well-known discovery protocols: domain name system based service discovery (DNS-SD), simple service discovery protocol (SSDP) and service location protocol (SLP). Further, a methodology to use the model hierarchy in wireless mesh networks is introduced. Given a pair service requester and provider, a discovery protocol and a deadline, it estimates packet loss probabilities and transmission time distributions for each link on the communication paths between the pair, generates specific model instances and calculates the expected responsiveness. Finally, the paper introduces a new metric, the expected responsiveness distance d_er to estimate the maximum distance from a provider where requesters are still able to discover it with a required responsiveness. The models and their methodology are demonstrated using monitoring data from the distributed embedded systems (DES) testbed at Freie Universität Berlin. It is shown how the responsiveness and d_er of the protocols change depending on the position of requester and provider and the overall link quality in the network.
MMB \& DFT
Springer International Publishing Switzerland
Lecture Notes in Computer Science
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Fischbach, K. and Krieger, U. R.
fault tolerance, Markov Models, Real time systems, Responsiveness, Service Discovery, Wireless mesh networks