Title
On Optimal Deadlock Detection Scheduling
Abstract
Deadlock detection scheduling is an important, yet often overlooked problem that can significantly affect the overall performance of deadlock handling. Excessive initiation of deadlock detection increases overall message usage, resulting in degraded system performance in the absence of deadlocks, while insufficient initiation of deadlock detection increases the deadlock persistence time, resulting in an increased deadlock resolution cost in the presence of deadlocks. The investigation of this performance trade-off, however, is missing in the literature. This paper studies the impact of deadlock detection scheduling on the overall performance of deadlock handling. In particular, we show that there exists an optimal deadlock detection frequency that yields the minimum long-run mean average cost, which is determined by the message complexities of the deadlock detection and resolution algorithms being used, as well as the rate of deadlock formation, denoted as lambda. For the best known deadlock detection and resolution algorithms, we show that the asymptotically optimal frequency of deadlock detection scheduling that minimizes the overall message overhead is O((lambdan)1/3) when the total number n of processes is sufficiently large. Furthermore, we show that, in general, fully distributed (uncoordinated) deadlock detection scheduling cannot be performed as efficiently as centralized (coordinated) deadlock detection scheduling
Year
DOI
Venue
2010
10.1109/TC.2006.151
Computers, IEEE Transactions
Keywords
DocType
Volume
optimal deadlock detection frequency,overall message overhead,deadlock persistence time.,scheduling,deadlock formation,minimum long-run mean average cost,deadlock formation rate,optimal deadlock detection scheduling,system performance,degraded system performance,deadlock detection,deadlock handling,deadlock detection scheduling,system recovery,overall performance,increased deadlock resolution cost,deadlock persistence time,resolution algorithm,cluster computing
Journal
abs/1008.0451
Issue
ISSN
Citations 
9
0018-9340
4
PageRank 
References 
Authors
0.41
26
3
Name
Order
Citations
PageRank
Yibei Ling141261.81
Shigang Chen22568187.11
Cho-Yu Jason Chiang3277.41