2.5 KiB
2.5 KiB
Peterson's algorithm cost O(n^2)
A first way to reduce this cost is by using a tournament of MUTEX between pairs of processes:
!Pasted image 20250304082459.png
Of course this is a binary tree, and the height of a binary tree is logaritmic to the number of leaves. A process then wins after \lceil \log_{2}n \rceil
competitions \to O(\log n)
cost.
But we can do better. Let's see an idea of a constant-time algorithm.
Initialize Y at ⊥, X at any value (e.g., 0)
lock(i) :=
x <- i
if Y != ⊥ then FAIL
else Y <- i
if X = i then return
else FAIL
unlock(i) :=
Y <- ⊥
return
Problems:
- we don't want the FAIL
- it is possible to have an execution where nobody accesses its CS, if repeated forever it entails a deadlock
Initialize Y at ⊥, X at any value (e.g., 0)
lock(i) :=
* FLAG[i] <- up
X <- i
if Y ≠ ⊥ then FLAG[i] <- down
wait Y = ⊥
goto *
else Y <- i
if X = i then return
else FLAG[i] <- down
∀j.wait FLAG[j] = down
if Y = i then return
else wait Y = ⊥
goto *
unlock(i) :=
Y <- ⊥
FLAG[i] <- down
return
MUTEX proof
Deadlock freedom
Let p_i
invoke lock
- If it eventually wins -> √
- If it is blocked forever, where can it be blocked?
- In the second wait Y = ⊥
- in this case, it read a value in Y different from i
- there is a
p_h
that wrote Y afterp_i
- let us consider the last of such
p_h \to
it will eventually win
- In the ∀j.wait FLAG[j] = down
- this wait cannot block a process forever
- if
pj
doesn't lock, it flag is down - if
pj
doesn't find Y at ⊥, it puts its flag down - if pj doesn't find X at j, it puts its flag down, otherwise pj enters its CS and eventually unlocks (flag down)
- In the second wait Y = ⊥
esercizio: prova che NON soddisfa starvation freedom
From deadlock freedom to bounded bypass
-> Round Robin algorithm
Let DLF be any deadlock free protocol for MUTEX. Let's see how we can make it satisfy bounded bypass:
lock(i) :=
FLAG[i] <- up
wait (TURN = i OR FLAG[TURN] = down)
DLF.lock(i)
return
unlock(i) :=
FLAG[i] <- down
if FLAG[TURN] = down then
TURN <- (TURN + 1) mod n
DLF.unlock(i)
return