Abstract We study the problem of privately emulating shared memory in message-passing networks. The system includes clients that store and retrieve replicated information on N servers, out of which e are data-corrupting malicious . When a client accesses a data-corrupting malicious server, the data field of that server response might be different from the value it originally stored. However, all other control variables in the server reply and protocol actions are according to the server algorithm. For the coded atomic storage algorithms by Cadambe et al., we present an enhancement that ensures no information leakage and data-corrupting malicious fault-tolerance. We also consider recovery after the occurrence of transient faults that violate the assumptions according to which the system was designed to operate. After their last occurrence, transient faults leave the system in an arbitrary state (while the program code stays intact). We present a self-stabilizing algorithm, which recovers after the occurrence of transient faults. This addition to Cadambe et al. considers asynchronous settings as long as no transient faults occur. The recovery from transient faults that bring the system counters (close) to their maximal values may include the use of a global reset procedure, which requires the system run to be controlled by a fair scheduler. After the recovery period, the safety properties are provided for asynchronous system runs that are not necessarily controlled by fair schedulers. Since the recovery period is bounded and the occurrence of transient faults is extremely rare, we call this design criteria self-stabilization in the presence of seldom fairness. Our self-stabilizing algorithm uses a bounded amount of storage during asynchronous executions (that are not necessarily controlled by fair schedulers). To the best of our knowledge, we are the first to address privacy, data-corrupting malicious behavior, and self-stabilization in the context of emulating atomic shared memory in message-passing systems.

We study a combinatorial optimization problem that is motivated by the scenario of autonomous cars driving on a multi-lane highway: some cars need to change lanes before the next intersection, and if there is congestion, cars need to slow down to make space for those who are changing lanes. There are two natural objective functions to minimize: (1) how long does it take for all traffic to clear the road, and (2) the total number of maneuvers. In this work, we present an approximation algorithm for solving these problems in the two-lane case and a hardness result for the multi-lane case.

The performance of low-cost RTK (real-time kinematic) GPS receivers has been compared to a state-of-the-art system as well to each other. Both static and dynamic performances have been compared. The dynamic performance has been evaluated using a vehicle with driving robot on the AstaZero proving ground. The assembly of the low-cost RTK GPS receivers is presented, and the test set-ups described. Besides having a lower data output frequency, two of the low-cost receivers have static and dynamic performance not far from that of the state-of-the-art system.

We study the problem of privately emulating shared memory in message passing networks. The system includes $N$ servers, and at most e semi-Byzantine servers that can deviate from the algorithm by sending corrupted data. Moreover, at most f servers can fail and stop.