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Concurrent objects play a key role in the design of applications for multi-core architectures, making it imperative to precisely understand their complexity requirements. For some objects, it is known that implementations can be significantly more efficient when their usage is restricted. However, apart from the specific restriction of one-shot implementations, where each process may apply only a single operation to the object, very little is known about the complexities of objects under general restrictions. This paper draws a more complete picture by defining a large class of objects for which an operation applied to the object can be "perturbed" L consecutive times, and proving lower bounds on the time and space complexity of deterministic implementations of such objects. This class includes bounded-value max registers, limited-use approximate and exact counters, and limited-use collect and compare-and-swap objects; L depends on the number of times the object can be accessed or the maximum value it supports. For implementations that use only historyless primitives, we prove lower bounds of Omega(min(log L, n)) on the worst-case step complexity of an operation, where n is the number of processes; we also prove lower bounds of Omega( min( L, n )) on the space complexity of these objects. When arbitrary primitives can be used, we prove that either some operation incurs Omega( min( log L, n)) memory stalls or some operation performs Omega( min( log L, n)) steps. In addition to these deterministic lower bounds, the paper establishes a lower bound on the expected step complexity of restricted-use randomized approximate counting in a weak oblivious adversary model.

Lower bounds for restricted-use objects