In many applications of multi-agent systems (MAS), a set of leader agents acts as a control input to the remaining follower agents. In this paper, we introduce an analytical approach to selecting leader agents in order to minimize the total mean-square error of the follower agent states from their desired value in steady-state in the presence of noisy communication links. We show that the problem of choosing leaders in order to minimize this error can be solved using supermodular optimization techniques, leading to efficient algorithms that are within a provable bound of the optimum. We formulate two leader selection problems within our framework, namely the problem of choosing a fixed number of leaders to minimize the error, as well as the problem of choosing the minimum number of leaders to achieve a tolerated level of error. We study both leader selection criteria for different scenarios, including MAS with static topologies, topologies experiencing random link or node failures, switching topologies, and topologies that vary arbitrarily in time due to node mobility. In addition to providing provable bounds for all these cases, simulation results demonstrate that our approach outperforms other leader selection methods, such as node degree-based and random selection methods, and provides comparable performance to current state of the art algorithms.
In a leader-follower multi-agent system (MAS), the leader agents act as control inputs and influence the states of the remaining follower agents. The rate at which the follower agents converge to their desired states, as well as the errors in the follower agent states prior to convergence, are determined by the choice of leader agents. In this paper, we study leader selection in order to minimize convergence errors experienced by the follower agents, which we define as a norm of the distance between the follower agents' intermediate states and the convex hull of the leader agent states. By introducing a novel connection to random walks on the network graph, we show that the convergence error has an inherent supermodular structure as a function of the leader set. Supermodularity enables development of efficient discrete optimization algorithms that directly approximate the optimal leader set, provide provable performance guarantees, and do not rely on continuous relaxations. We formulate two leader selection problems within the supermodular optimization framework, namely, the problem of selecting a fixed number of leader agents in order to minimize the convergence error, as well as the problem of selecting the minimum-size set of leader agents to achieve a given bound on the convergence error. We introduce algorithms for approximating the optimal solution to both problems in static networks, dynamic networks with known topology distributions, and dynamic networks with unknown and unpredictable
In RFID literature, most "privacy-preserving" protocols require the reader to search all tags in the system in order to identify a single tag. In another class of protocols, the search complexity is reduced to be logarithmic in the number of tags, but it comes with two major drawbacks: it requires a large communication overhead over the fragile wireless channel, and the compromise of a tag in the system reveals secret information about other, uncompromised, tags in the same system. In this work, we take a different approach to address time complexity of private identification in large-scale RFID systems. We utilize the special architecture of RFID systems to propose a symmetric-key privacy-preserving authentication protocol for RFID systems with constant-time identification. Instead of increasing communication overhead, the existence of a large storage device in RFID systems, the database, is utilized for improving the time efficiency of tag identification.
In RFID literature, most "privacy-preserving" protocols require the reader to search all tags in the system in order to identify a single tag. In another class of protocols, the search complexity is reduced to be logarithmic in the number of tags, but it comes with two major drawbacks: it requires a large communication overhead over the fragile wireless channel, and the compromise of a tag in the system reveals secret information about other, uncompromised, tags in the same system. In this work, we take a different approach to address time-complexity of private identification in large-scale RFID systems. We utilize the special architecture of RFID systems to propose the first symmetric-key privacy-preserving authentication protocol for RFID systems with constant-time identification. Instead of increasing communication overhead, the existence of a large storage device in RFID systems, the database, is utilized for improving the time efficiency of tag identification.
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