人口协议中的时空权衡
Time-Space Trade-offs in Population Protocols
摘要：
群体协议是分布式计算的一种流行模型，在该模型中，具有较小计算能力的随机交互代理合作以共同执行计算任务。受分子计算，特别是DNA计算的发展的启发，最近的算法工作集中在解决人口模型中简单而基本的任务的复杂性，如领导者选举（需要稳定到一个特殊的“领导者”状态的单个代理），和多数（其中代理必须稳定到两个可能的初始状态中的哪一个具有更高的初始计数）。已知的结果指向这样的算法的时间复杂度和空间复杂度（即，每个代理可用的存储器的大小）之间的固有权衡。在本文中，我们探讨了这种权衡，并提供了新的上限和下限的多数和领导人选举。首先，我们证明了一个统一的下界，它涉及到每个节点的可用空间与协议实现的时间复杂度：例如，我们的结果意味着，任何协议解决这些任务的$n$代理使用$O( \log \log n )$状态必须采取$Ω( n / \rm{polylog} n )$预期的时间。这是第一个结果来表征时间复杂度的协议，采用超常数的状态数，每个节点，并证明了快速，多对数运行时间要求协议有相对较大的空间成本。在积极的一面，我们给出的算法表明，快速，多对数稳定时间可以实现每个节点使用$O( \log^2 n )$空间，在这两个任务的情况下。总体而言，我们的研究结果突出了人口协议中多数选举和领导选举的$O(\log \log n)$和$Θ( \log^2 n )$状态空间大小之间的时间复杂度分离，并引入了新的技术，这应该是适用更广泛。
英文摘要：
Population protocols are a popular model of distributed computing, in which randomly-interacting agents with little computational power cooperate to jointly perform computational tasks. Inspired by developments in molecular computation, and in particular DNA computing, recent algorithmic work has focused on the complexity of solving simple yet fundamental tasks in the population model, such as leader election (which requires stabilization to a single agent in a special "leader" state), and majority (in which agents must stabilize to a decision as to which of two possible initial states had higher initial count). Known results point towards an inherent trade-off between the time complexity of such algorithms, and the space complexity, i.e. size of the memory available to each agent. In this paper, we explore this trade-off and provide new upper and lower bounds for majority and leader election. First, we prove a unified lower bound, which relates the space available per node with the time complexity achievable by a protocol: for instance, our result implies that any protocol solving either of these tasks for $n$ agents using $O( \log \log n )$ states must take $Ω( n / \rm{polylog} n )$ expected time. This is the first result to characterize time complexity for protocols which employ super-constant number of states per node, and proves that fast, poly-logarithmic running times require protocols to have relatively large space costs. On the positive side, we give algorithms showing that fast, poly-logarithmic stabilization time can be achieved using $O( \log^2 n )$ space per node, in the case of both tasks. Overall, our results highlight a time complexity separation between $O(\log \log n)$ and $Θ( \log^2 n )$ state space size for both majority and leader election in population protocols, and introduce new techniques, which should be applicable more broadly.
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