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CMFA.py
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CMFA.py
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from SPARTA_CC import *
class Graph:
def __init__(self, vertices):
self.vertices = vertices
self.graph = [[0] * vertices for _ in range(vertices)]
def add_edge(self, u, v, capacity=1):
self.graph[u][v] = capacity
def bfs(self, source, sink, parent, graph):
visited = [False] * self.vertices
queue = [source]
visited[source] = True
while queue:
u = queue.pop(0)
for v in range(self.vertices):
if not visited[v] and graph[u][v] > 0:
queue.append(v)
visited[v] = True
parent[v] = u
if v == sink:
return True
return False
def ford_fulkerson(self, source, sink):
self.temp_graph = [[self.graph[i][j] for j in range(self.vertices)] for i in range(self.vertices)]
parent = [-1] * self.vertices
max_flow = 0
while self.bfs(source, sink, parent, self.temp_graph):
path_flow = float("Inf")
s = sink
while s != source:
path_flow = min(path_flow, self.temp_graph[parent[s]][s])
s = parent[s]
max_flow += path_flow
v = sink
while v != source:
u = parent[v]
self.temp_graph[u][v] -= path_flow
self.temp_graph[v][u] += path_flow
v = parent[v]
return max_flow
class Vertex:
def __init__(self, V, index):
"""
V: a Cluster object since each cluster is a vertex in the graph
"""
self.V = V
self.deg = 0
self.index = index
class Edge:
def __init__(self, A, B):
"""
A, B: Two Vertex objects
"""
self.V1 = A
self.V2 = B
self.dist = dist(A.V.Center.v, B.V.Center.v)
class Cluster:
def __init__(self, Center, Targets, Qmax):
"""
Center: a Target object which is the center of the cluster
Targets: list[Targets]: all targets in the cluster (except the center)
"""
self.Center = Center
self.Targets = Targets
self.e = -1
if type(Center) == Base:
self.e = Qmax
else:
for Ti in [Center] + self.Targets:
if Ti.q > self.e:
self.e = Ti.q
def insert_anchor_node(self, S, Rn, Rs):
for i in range(self.e - self.Center.q):
temp_s = Sensor(self.Center.v, Rs, [self.Center])
self.Center.Sensors.append(temp_s)
S.append(temp_s)
Rn.append(self.Center.v)
def put_relay(self, S, Rn, Rc, Rs):
ans = []
self.insert_anchor_node(S, Rn, Rs)
for Ti in self.Targets:
used = []
for Sij in Ti.Sensors:
for Sk in self.Center.Sensors:
if Sk not in used:
ans.append([Sij, Sk])
used.append(Sk)
break
for Si, Sj in ans:
c = dist(Si.v, Sj.v)
add = int((c - 0.0001) // Rc)
for j in range(add):
x = Si.v[0] + (j + 1) * (Sj.v[0] - Si.v[0]) / (add + 1)
y = Si.v[1] + (j + 1) * (Sj.v[1] - Si.v[1]) / (add + 1)
z = Si.v[2] + (j + 1) * (Sj.v[2] - Si.v[2]) / (add + 1)
sensor = (x, y, z)
Rn.append(sensor)
return ans
def clustering(T, Rcl, Qmax):
C = []
used = []
while True:
maxneigh = float("-inf")
bestT = None
bestNeighs = []
for Ti in T:
if Ti not in used:
center = Ti
neighbours = []
for Tj in T:
if Ti != Tj and Tj not in used:
if dist(Ti.v, Tj.v) <= Rcl:
neighbours.append(Tj)
if len(neighbours) > maxneigh:
maxneigh = len(neighbours)
bestT = center
bestNeighs = neighbours
if bestT == None:
break
C.append(Cluster(bestT, bestNeighs, Qmax))
used.append(bestT)
used += bestNeighs
return C
def construct_edge(C, base, Qmax):
B = Cluster(base, [], Qmax)
V = [Vertex(B, 0)] + [Vertex(C[i], i + 1) for i in range(len(C))]
L = []
E = []
for i in range(1, len(V)):
for j in range(i):
L.append(Edge(V[i], V[j]))
L.sort(key=lambda x: x.dist)
for Li in L:
V1, V2 = Li.V1, Li.V2
if V1.deg < V1.V.e or V2.deg < V2.V.e:
E.append(Li)
V1.deg += 1
V2.deg += 1
for r in E:
L.remove(r)
for i in range(1, len(V)):
G = Graph(len(C) + 1)
for Ei in E:
G.add_edge(Ei.V1.index, Ei.V2.index)
G.add_edge(Ei.V2.index, Ei.V1.index)
source = V[i].index
sink = V[0].index
max_flow_value = G.ford_fulkerson(source, sink)
if max_flow_value < V[i].V.e:
while max_flow_value < V[i].V.e:
E.append(L[0])
G.add_edge(L[0].V1.index, L[0].V2.index)
G.add_edge(L[0].V2.index, L[0].V1.index)
max_flow_value = G.ford_fulkerson(source, sink)
L.remove(L[0])
return E
def put_relay_along_edges(A, B, Rn, Rc):
P1 = A.v
P2 = B.v
c = dist(P1, P2)
add = int((c - 0.0001) // Rc)
for j in range(add):
x = A.v[0] + (j + 1) * (B.v[0] - A.v[0]) / (add + 1)
y = A.v[1] + (j + 1) * (B.v[1] - A.v[1]) / (add + 1)
z = A.v[2] + (j + 1) * (B.v[2] - A.v[2]) / (add + 1)
sensor = (x, y, z)
Rn.append(sensor)
return 0
def CMFA(base, T, S, Rc, Rcl, Rs, Qmax):
C = clustering(T, Rcl, Qmax)
Rn = []
intra_conn = []
for Ci in C:
intra_conn.extend(Ci.put_relay(S, Rn, Rc, Rs))
E = construct_edge(C, base, Qmax)
inter_conn = []
for Ei in E:
put_relay_along_edges(Ei.V1.V.Center, Ei.V2.V.Center, Rn, Rc)
inter_conn.append([Ei.V1.V.Center, Ei.V2.V.Center])
conn = intra_conn + inter_conn
return Rn, conn