def _demandEstimator(self, flows, hostsList): ''' Estimate flows' demands. ''' estimated_flows = demand_estimation(flows, hostsList) for flow in estimated_flows: if flow['demand'] > 0.1: self._GlobalFirstFit(flow)
def _demandEstimator(self, flows, hostsList):
'''
Estimate flows' demands.
'''
estimated_flows = demand_estimation(flows, hostsList)
for flow in estimated_flows:
if flow['demand'] > 0.1:
if not Hedera.is_multicast_addr(flow['dst']):
self._GlobalFirstFit(flow)
def _demandEstimator(self, flows, hostsList):
'''
Estimate flows' demands.
'''
estimated_flows = demand_estimation(flows, hostsList)
for flow in estimated_flows:
if flow['demand'] > 0.1:
# Thread(target=self._GlobalFirstFit,args=(flow,)).start()
self._GlobalFirstFit(flow)
def _demandEstimator(self):
'''estimate the actual flow demands here'''
temp = self.flows
temp = sorted(temp, key=lambda temp: temp['src'])
self.flows = temp
self.bwReservation = {}
M, estFlows = demand_estimation(self.flows, sorted(self.hostsList))
for flow in estFlows:
demand = flow['demand']
if demand >= 0.1:
self._GlobalBestFit(flow)
def _demandEstimator(self):
'''estimate the actual flow demands here'''
temp = self.flows
temp = sorted(temp, key=lambda temp: temp['src'])
self.flows = temp
self.bwReservation = {}
M, estFlows = demand_estimation(self.flows, sorted(self.hostsList))
for flow in estFlows:
demand = flow['demand']
if demand >= self.ratio:
self._HederaSimulatedAnnealing(flow)
def _demandEstimator(self):
'''estimate the actual flow demands here'''
temp = self.flows
temp = sorted(temp, key=lambda temp:temp['src'])
self.flows = temp
self.bwReservation = {}
M, estFlows = demand_estimation(self.flows, sorted(self.hostsList))
for flow in estFlows:
demand = flow['demand']
if demand >= 0.1:
self._GlobalBestFit(flow)
def link_status(self):
"""
check load of links
"""
if self.elephant_number >= 6:
self.logger.info(self.elephant_number)
self.hostsList = []
self.flows = []
for key in self.elephant_info:
speed = self.elephant_info[key][0]
if speed > setting.MAX_CAPACITY * 0.1:
src_ip = key[0]
dst_ip = key[1]
flow = self.elephant_info[key]
# flow_info = (speed, flow[1], flow[2])
stat = flow[3]
priority = flow[2]
self.flows.append({
'src': src_ip,
'dst': dst_ip,
'demand': speed,
'converged': False,
'receiver_limited': False,
'match': stat,
'priority': priority
})
if src_ip not in self.hostsList:
self.hostsList.append(src_ip)
if dst_ip not in self.hostsList:
self.hostsList.append(dst_ip)
flows = sorted([flow for flow in self.flows],
key=lambda flow: (flow['src'], flow['dst']))
hostsList = sorted(self.hostsList)
estimated_flows = demand_estimation(flows, hostsList)
for flow in estimated_flows:
if flow['demand'] > 0.1:
src_ip = flow['src']
dst_ip = flow['dst']
flow_info = (round(setting.MAX_CAPACITY * flow['demand'],
2), flow['match']['eth_type'],
flow['priority'])
self.find_new_path(src_ip, dst_ip, flow_info)
self.flow_path_number = self.flow_path_number + 1
def _demandEstimator(self, flows, hostsList):
estimated_flows = demand_estimation(flows, hostsList)
self._reroute(estimated_flows)
def _demandEstimator(self, flows, hostsList):
'''
Estimate flows' demands.
'''
estimated_flows = demand_estimation(flows, hostsList)
