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https://github.com/vacp2p/wakurtosis.git
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nomos graph & minor fixes (#96)
* nomos node & minor fixes * nomos node & minor fixes
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0xFugue
@@ -19,9 +19,8 @@ from enum import Enum
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# To add a new node type, add appropriate entries to the nodeType and nodeTypeSwitch
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class nodeType(Enum):
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NWAKU = "nwaku" # waku desktop config
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GOWAKU = "gowaku" # waku mobile config
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NOMOS = "nomos"
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NWAKU = "nwaku" # waku desktop config
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GOWAKU = "gowaku" # waku mobile config
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nodeTypeToToml = {
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@@ -31,8 +30,7 @@ nodeTypeToToml = {
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nodeTypeToDocker = {
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nodeType.NWAKU: "nim-waku",
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nodeType.GOWAKU: "go-waku",
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nodeType.NOMOS: "nomos"
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nodeType.GOWAKU: "go-waku"
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}
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# To add a new network type, add appropriate entries to the networkType and networkTypeSwitch
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@@ -43,6 +41,7 @@ class networkType(Enum):
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NEWMANWATTSSTROGATZ = "newmanwattsstrogatz" # mesh, smallworld
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BARBELL = "barbell" # partition
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BALANCEDTREE = "balancedtree" # committees?
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NOMOSTREE = "nomostree" # balanced binary tree with even # of leaves
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STAR = "star" # spof
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@@ -66,7 +65,7 @@ def write_toml(dirname, node_name, toml):
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# Draw the network and output the image to a file; does not account for subnets yet
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def draw(dirname, H):
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def draw_network(dirname, H):
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nx.draw(H, pos=nx.kamada_kawai_layout(H), with_labels=True)
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fname = os.path.join(dirname, NW_DATA_FNAME)
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plt.savefig(f"{os.path.splitext(fname)[0]}.png", format="png")
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@@ -121,34 +120,65 @@ def get_random_sublist(topics):
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### network processing related fns #################################################
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# Network Types
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def generate_config_model(n):
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# |G| = n
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def generate_config_model(ctx):
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n = ctx.params["num_nodes"]
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# degrees = nx.random_powerlaw_tree_sequence(n, tries=10000)
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degrees = [random.randint(1, n) for i in range(n)]
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if (sum(degrees)) % 2 != 0: # adjust the degree to be even
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degrees[-1] += 1
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return nx.configuration_model(degrees) # generate the graph
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def generate_scalefree_graph(n):
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# |G| = n
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def generate_scalefree_graph(ctx):
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n = ctx.params["num_nodes"]
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return nx.scale_free_graph(n)
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# |G| = n; n must be larger than k=D=3
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def generate_newmanwattsstrogatz_graph(ctx):
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n = ctx.params["num_nodes"]
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fanout = ctx.params["fanout"]
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return nx.newman_watts_strogatz_graph(n, fanout, 0.5)
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# n must be larger than k=D=3
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def generate_newmanwattsstrogatz_graph(n):
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return nx.newman_watts_strogatz_graph(n, 3, 0.5)
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def generate_barbell_graph(n):
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# |G| = n (if odd); n+1 (if even)
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def generate_barbell_graph(ctx):
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n = ctx.params["num_nodes"]
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return nx.barbell_graph(int(n / 2), 1)
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def generate_balanced_tree(n, fanout=3):
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# |G| > fanout^{\floor{log_n} + 1}
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def generate_balanced_tree(ctx):
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n = ctx.params["num_nodes"]
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fanout = ctx.params["fanout"]
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height = int(math.log(n) / math.log(fanout))
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return nx.balanced_tree(fanout, height)
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# nomostree is a balanced binary tree with even number of leaves
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# |G| = n (if odd); n+1 (if even)
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def generate_nomos_tree(ctx):
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n = ctx.params["num_nodes"]
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fanout = ctx.params["fanout"]
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# nomos currently insists on binary trees
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assert(fanout == 2)
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height = int(math.log(n) / math.log(fanout))
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G = nx.balanced_tree(fanout, height)
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i, diff = 0, G.number_of_nodes() - n
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leaves = [x for x in G.nodes() if G.degree(x) == 1]
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nleaves = len(leaves)
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if (nleaves - diff) % 2 != 0 :
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diff -= 1
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for node in leaves :
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if i == diff:
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break
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G.remove_node(node)
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i += 1
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G = nx.convert_node_labels_to_integers(G)
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return G
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def generate_star_graph(n):
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return nx.star_graph(n)
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# |G| = n
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def generate_star_graph(ctx):
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n = ctx.params["num_nodes"]
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return nx.star_graph(n-1)
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networkTypeSwitch = {
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@@ -157,13 +187,15 @@ networkTypeSwitch = {
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networkType.NEWMANWATTSSTROGATZ: generate_newmanwattsstrogatz_graph,
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networkType.BARBELL: generate_barbell_graph,
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networkType.BALANCEDTREE: generate_balanced_tree,
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networkType.NOMOSTREE: generate_nomos_tree,
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networkType.STAR: generate_star_graph
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}
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# Generate the network from nw type
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def generate_network(n, network_type):
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return postprocess_network(networkTypeSwitch.get(network_type)(n))
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def generate_network(ctx):
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network_type = networkType(ctx.params["network_type"])
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return postprocess_network(networkTypeSwitch.get(network_type)(ctx))
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# Label the generated network with prefix
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@@ -333,17 +365,19 @@ def _num_subnets_callback(ctx: typer, Context, num_subnets: int):
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def main(ctx: typer.Context,
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benchmark: bool = False,
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container_size: int = 1, # TODO: reduce container packer memory consumption
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output_dir: str = "network_data",
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prng_seed: int = 3,
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num_nodes: int = 4,
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num_topics: int = 1,
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node_type_distribution: str = typer.Argument("{\"nwaku\" : 100 }" ,callback=ast.literal_eval),
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network_type: networkType = networkType.NEWMANWATTSSTROGATZ.value,
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num_subnets: int = typer.Option(1, callback=_num_subnets_callback),
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num_partitions: int = typer.Option(1, callback=_num_partitions_callback),
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config_file: str = typer.Option("", callback=conf_callback, is_eager=True)):
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benchmark: bool = typer.Option(False, help="Measure CPU/Mem usage of Gennet"),
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draw: bool = typer.Option(False, help="Draw the generated network"),
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container_size: int = typer.Option(1, help="Set the number of nodes per container"), # TODO: reduce container packer memory consumption
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output_dir: str = typer.Option("network_data", help="Set the output directory for Gennet generated files"),
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prng_seed: int = typer.Option(41, help="Set the random seed"),
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num_nodes: int = typer.Option(4, help="Set the number of nodes"),
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num_topics: int = typer.Option(1, help="Set the number of topics"),
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fanout: int = typer.Option(3, help="Set the arity for trees & newmanwattsstrogatz"),
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node_type_distribution: str = typer.Argument("{\"nwaku\" : 100 }" ,callback=ast.literal_eval, help="Set the node type distribution"),
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network_type: networkType = typer.Option(networkType.NEWMANWATTSSTROGATZ.value, help="Set the node type"),
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num_subnets: int = typer.Option(1, callback=_num_subnets_callback, help="Set the number of subnets"),
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num_partitions: int = typer.Option(1, callback=_num_partitions_callback, help="Set the number of network partitions"),
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config_file: str = typer.Option("", callback=conf_callback, is_eager=True, help="Set the input config file (JSON)")):
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# Benchmarking: record start time and start tracing mallocs
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if benchmark :
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@@ -372,18 +406,20 @@ def main(ctx: typer.Context,
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# Generate the network
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G = generate_network(num_nodes, networkType(network_type))
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# G = generate_network(num_nodes, networkType(network_type), tree_arity)
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G = generate_network(ctx)
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# Do not complain if folder exists already
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# Do not complain if the folder already exists
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os.makedirs(output_dir, exist_ok=True)
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# Generate file format specific data structs and write the files
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generate_and_write_files(ctx, G)
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#generate_and_write_files(output_dir, num_topics, num_subnets, node_type_distribution, G)
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#draw(G, outpur_dir)
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if draw :
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draw_network(output_dir, G)
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end = time.time()
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time_took = end - start
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print(f"For {num_nodes} nodes, network generation took {time_took} secs.\nThe generated network is under ./{output_dir}")
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print(f"For {G.number_of_nodes()}/{num_nodes} nodes, network generation took {time_took} secs.\nThe generated network is under ./{output_dir}")
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# Benchmarking. Record finish time and stop the malloc tracing
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if benchmark :
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