Never Say Never Probabilistic & Temporal Failure Detectors (Extended)

The failure detector approach for solving distributed computing problems has been celebrated for its modularity. This approach allows the construction of algorithms using abstract failure detection mechanisms, defined by axiomatic properties, as building blocks. The minimal synchrony assumptions on communication, which enable to implement the failure detection mechanism, are studied separately. Such synchrony assumptions are typically expressed as eventual guarantees that need to hold, after some point in time, forever and deterministically. But in practice, they never do. Synchrony assumptions may hold only probabilistically and temporarily. In this paper, we study failure detectors in a realistic distributed system N, with asynchrony inflicted by probabilistic synchronous communication. We address the following paradox about the weakest failure detector to solve the consensus problem (and many equivalent problems), i.e., S: an implementation of “consensus with probability 1” is possible in N without using randomness in the algorithm itself, while an implementation of “S with probability 1” is impossible to achieve in N. We circumvent this paradox by introducing a new failure detector S*, a variant of S with probabilistic and temporal accuracy. We prove that S* is implementable in N and we provide an optimal S* implementation. Interestingly, we show that S* can replace S , in several existing deterministic consensus algorithms using S, to yield an algorithm that solves “consensus with probability 1”. In fact, we show that such result holds for all decisive problems (not only consensus) and also for failure detector P (not only S). The resulting algorithms combine the modularity of distributed computing practices with the practicality of networking ones

Heterogeneous multi-interface routing: networking stack and simulator extensions

Abstract: Most IP routing solutions have been designed to work well for a single communication technology. However, many communication networks consist of a multitude of legacy and new devices using heterogeneous technologies, such as copper wires, optical fibers, wireless and power line communication. In order to leverage the existence of multiple technologies between two devices to achieve availability and robustness, a routing protocol has to solve the problem of addressing multiple interfaces (where each interface supports one communication technology such as copper or wireless), maintaining and exchanging information regarding the involved links and the decision making process when forwarding packets. In this paper we present our extension of the Contiki networking stack uiP with the 1Pv6 routing protocol RPL and of the network simulator Cooja for multiple interfaces, followed by a description and evaluation of a smart grid scenario simulation and a hardware demonstrator

Never Say Never Probabilistic & Temporal Failure Detectors

The failure detector approach for solving distributed computing problems has been celebrated for its modularity. This approach allows the construction of algorithms using abstract failure detection mechanisms, defined by axiomatic properties, as building blocks. The minimal synchrony assumptions on communication, which enable to implement the failure detection mechanism, are studied separately. Such synchrony assumptions are typically expressed as eventual guarantees that need to hold, after some point in time, forever and deterministically. But in practice, they never do. Synchrony assumptions may hold only probabilistically and temporarily. In this paper, we study failure detectors in a realistic distributed system N, with asynchrony inflicted by probabilistic synchronous communication. We address the following paradox: an implementation of "consensus with probability 1" is possible in N without using randomness in the algorithm itself, while an implementation of "lozenge S with probability 1" is impossible to achieve in N (lozenge S being the weakest failure detector to solve the consensus problem and many equivalent problems). We circumvent this paradox by introducing a new failure detector lozenge S*, a variant of lozenge S with probabilistic and temporal accuracy. We prove that lozenge S* is implementable in N and we provide an optimal lozenge S* algorithm. Interestingly, we show that lozenge S* can replace lozenge S, in several existing deterministic consensus algorithms using lozenge S, to yield an algorithm that solves "consensus with probability 1". In fact, we show that such result holds for all decisive problems (not only consensus) and also for failure detector lozenge P (not only lozenge S). The resulting algorithms combine the modularity of distributed computing practices with the practicality of networking ones