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Contention Resolution, With and Without a Global Clock

Zixi Cai, Kuowen Chen, Shengquan Du, Tsvi Kopelowitz, Seth Pettie, Ben Plosk

TL;DR

This paper investigates contention resolution with and without a global clock, focusing on memoryless randomized protocols under adversarial wake-ups and acknowledgment feedback. It introduces a first randomized GlobalClock protocol that achieves near-linear latency, proving a separation from the LocalClock model where latency scales more poorly. In the LocalClock setting, it provides sharp asymptotics for both expected latency and high-probability latency, and proves that one cannot achieve optimality under both metrics simultaneously. The work also develops a counter-game framework to bound LocalClock upper bounds and extends lower-bound techniques through probabilistic thresholds and layered adversaries. Together, these results clarify the advantage of a global clock and chart the fundamental limits of memoryless contention-resolution strategies in both clock models, with open questions about achieving truly linear-time performance in the GlobalClock setting.

Abstract

In the Contention Resolution problem $n$ parties each wish to have exclusive use of a shared resource for one unit of time. The problem has been studied since the early 1970s, under a variety of assumptions on feedback given to the parties, how the parties wake up, knowledge of $n$, and so on. The most consistent assumption is that parties do not have access to a global clock, only their local time since wake-up. This is surprising because the assumption of a global clock is both technologically realistic and algorithmically interesting. It enriches the problem, and opens the door to entirely new techniques. Our primary results are: [1] We design a new Contention Resolution protocol that guarantees latency $$O\left(\left(n\log\log n\log^{(3)} n\log^{(4)} n\cdots \log^{(\log^* n)} n\right)\cdot 2^{\log^* n}\right) \le n(\log\log n)^{1+o(1)}$$ in expectation and with high probability. This already establishes at least a roughly $\log n$ complexity gap between randomized protocols in GlobalClock and LocalClock. [2] Prior analyses of randomized ContentionResolution protocols in LocalClock guaranteed a certain latency with high probability, i.e., with probability $1-1/\text{poly}(n)$. We observe that it is just as natural to measure expected latency, and prove a $\log n$-factor complexity gap between the two objectives for memoryless protocols. The In-Expectation complexity is $Θ(n \log n/\log\log n)$ whereas the With-High-Probability latency is $Θ(n\log^2 n/\log\log n)$. Three of these four upper and lower bounds are new. [3] Given the complexity separation above, one would naturally want a ContentionResolution protocol that is optimal under both the In-Expectation and With-High-Probability metrics. This is impossible! It is even impossible to achieve In-Expectation latency $o(n\log^2 n/(\log\log n)^2)$ and With-High-Probability latency $n\log^{O(1)} n$ simultaneously.

Contention Resolution, With and Without a Global Clock

TL;DR

This paper investigates contention resolution with and without a global clock, focusing on memoryless randomized protocols under adversarial wake-ups and acknowledgment feedback. It introduces a first randomized GlobalClock protocol that achieves near-linear latency, proving a separation from the LocalClock model where latency scales more poorly. In the LocalClock setting, it provides sharp asymptotics for both expected latency and high-probability latency, and proves that one cannot achieve optimality under both metrics simultaneously. The work also develops a counter-game framework to bound LocalClock upper bounds and extends lower-bound techniques through probabilistic thresholds and layered adversaries. Together, these results clarify the advantage of a global clock and chart the fundamental limits of memoryless contention-resolution strategies in both clock models, with open questions about achieving truly linear-time performance in the GlobalClock setting.

Abstract

In the Contention Resolution problem parties each wish to have exclusive use of a shared resource for one unit of time. The problem has been studied since the early 1970s, under a variety of assumptions on feedback given to the parties, how the parties wake up, knowledge of , and so on. The most consistent assumption is that parties do not have access to a global clock, only their local time since wake-up. This is surprising because the assumption of a global clock is both technologically realistic and algorithmically interesting. It enriches the problem, and opens the door to entirely new techniques. Our primary results are: [1] We design a new Contention Resolution protocol that guarantees latency in expectation and with high probability. This already establishes at least a roughly complexity gap between randomized protocols in GlobalClock and LocalClock. [2] Prior analyses of randomized ContentionResolution protocols in LocalClock guaranteed a certain latency with high probability, i.e., with probability . We observe that it is just as natural to measure expected latency, and prove a -factor complexity gap between the two objectives for memoryless protocols. The In-Expectation complexity is whereas the With-High-Probability latency is . Three of these four upper and lower bounds are new. [3] Given the complexity separation above, one would naturally want a ContentionResolution protocol that is optimal under both the In-Expectation and With-High-Probability metrics. This is impossible! It is even impossible to achieve In-Expectation latency and With-High-Probability latency simultaneously.
Paper Structure (43 sections, 38 theorems, 82 equations, 1 algorithm)

This paper contains 43 sections, 38 theorems, 82 equations, 1 algorithm.

Key Result

Theorem 1.1

There is an acknowledgment-based Contention Resolution protocol in the GlobalClock model that achieves latency $O(n \zeta(4\log\log n)) = n(\log\log n)^{1+o(1)}$ with high probability, where

Theorems & Definitions (74)

  • Theorem 1.1
  • Corollary 1.2
  • Conjecture 1.3
  • Theorem 1.4: In-Expectation vs. With-High-Probability
  • Theorem 1.5
  • Lemma 3.1
  • Lemma 4.1
  • Lemma 4.2
  • proof
  • Lemma 4.3
  • ...and 64 more