import networkx as nx import graphviz as gv from broadcast import * import pandas as pd import time import functools import graphviz as gv GBIT_PER_GBYTE = 8 class Timer: def __init__(self, print_desc=None): self.print_desc = print_desc self.start = time.time() self.end = None def __enter__(self): return self def __exit__(self, exc_typ, exc_val, exc_tb): self.end = time.time() @property def elapsed(self): if self.end is None: end = time.time() return end - self.start else: return self.end - self.start @functools.lru_cache(maxsize=None) def get_path_cost(src, dst, src_tier="PREMIUM", dst_tier="PREMIUM"): from skyplane import compute assert src_tier == "PREMIUM" and dst_tier == "PREMIUM" return compute.CloudProvider.get_transfer_cost(src, dst) def make_nx_graph(cost_path=None, throughput_path=None, num_vms=1): """ Default graph with capacity constraints and cost info nodes: regions, edges: links per edge: throughput: max tput achievable (gbps) cost: $/GB flow: actual flow (gbps), must be < throughput, default = 0 """ if cost_path is None: cost = pd.read_csv("profiles/cost.csv") else: cost = pd.read_csv(cost_path) if throughput_path is None: throughput = pd.read_csv("profiles/throughput.csv") else: throughput = pd.read_csv(throughput_path) G = nx.DiGraph() for _, row in throughput.iterrows(): if row["src_region"] == row["dst_region"]: continue G.add_edge(row["src_region"], row["dst_region"], cost=None, throughput=num_vms * row["throughput_sent"] / 1e9) for _, row in cost.iterrows(): if row["src"] in G and row["dest"] in G[row["src"]]: G[row["src"]][row["dest"]]["cost"] = row["cost"] # some pairs not in the cost grid no_cost_pairs = [] for edge in G.edges.data(): src, dst = edge[0], edge[1] if edge[-1]["cost"] is None: no_cost_pairs.append((src, dst)) print("Unable to get costs for: ", no_cost_pairs) return G def push_flow_helper(src, g, ingress_limit=10 * 5, egress_limit=10 * 5): """ Push positive flows in the constructed paths (g) under constraints TODO: fix this """ for child in list(g.successors(src)): dfs_edges = [edge for edge in nx.dfs_edges(g, source=child)] dfs_min = float("inf") if not dfs_edges else min([g[t[0]][t[1]]["throughput"] for t in dfs_edges]) min_flow = min([dfs_min, g[src][child]["throughput"], ingress_limit, egress_limit]) # assign flows g[src][child]["flow"] = min_flow for t in dfs_edges: g[t[0]][t[1]]["flow"] = min_flow return g def append_src_dst_paths(src, dsts, G, bc_topology): # Append src dst paths for partitions (all partitions follow the same path) for dst in dsts: for path in list(nx.all_simple_paths(G, src, dst)): for i in range(0, len(path) - 1): s, t = path[i], path[i + 1] for j in range(bc_topology.num_partitions): bc_topology.append_dst_partition_path(dst, j, [s, t, G[s][t]]) return bc_topology def networkx_to_graphviz(g, src, dsts, label="partitions"): """Convert `networkx` graph `g` to `graphviz.Digraph`. @type g: `networkx.Graph` or `networkx.DiGraph` @rtype: `graphviz.Digraph` """ if g.is_directed(): h = gv.Digraph() else: h = gv.Graph() for u, d in g.nodes(data=True): # u = u.split(",")[0] if u.split(",")[0] == src: h.node(str(u.replace(":", " ")), fillcolor="red", style="filled") elif u.split(",")[0] in dsts: h.node(str(u.replace(":", " ")), fillcolor="green", style="filled") h.node(str(u.replace(":", " "))) for u, v, d in g.edges(data=True): # print('edge', u, v, d) h.edge(str(u.replace(":", " ")), str(v.replace(":", " ")), label=str(d[label])) return h