def __init__(self, topology, log_dir, scenario_id):
"""
Constructor
"""
# create logging objects
# for running on clay or EE lab, open logging files in /tmp
# and then (compress it) and move it to home. This is to avoid frequent
# NFS writes, so I write on tmp which is on local drive and copy to home
# (NFS) only when the simulation is over.
# Compression may be needed on EE lab machine because there is a 5 GB
# quota that might be exceeded by logs
self.log_dir = log_dir
self.scenario_id = scenario_id
self.link_logger = LinkLogger(path.join(log_dir, 'RESULTS_%s_LINK.txt' % scenario_id))
self.cache_logger = CacheLogger(path.join(log_dir, 'RESULTS_%s_CACHE.txt' % scenario_id))
self.delay_logger = DelayLogger(path.join(log_dir, 'RESULTS_%s_DELAY.txt' % scenario_id))
self.topology = topology
# calc shortest paths
self.shortest_path = nx.all_pairs_dijkstra_path(topology, weight='weight')
# get location of caches and content sources
self.content_location = {} # dict of location of contents keyed by content ID
self.cache_size = {} # dict of cache sizes keyed by node
# Link type: internal or external
self.link_type = dict([((u,v), topology.edge[u][v]['type'])
for u in topology.edge
for v in topology.edge[u]])
for node in topology.nodes_iter():
stack_name, stack_props = get_stack(topology, node)
if stack_name == 'cache':
self.cache_size[node] = stack_props['size']
elif stack_name == 'source':
contents = stack_props['contents']
for content in contents:
self.content_location[content] = node
# create actual cache objects
self.caches = dict([(node, Cache(self.cache_size[node])) for node in self.cache_size])
