示例#1
0
def f_plot():
    Node.n = 60
    init()
    (G, N) = deba()
    plot.display_topology(G, N, "DEBA")

    (G, N) = my(1)
    plot.display_topology(G, N, "EFTCG-1")

    (G, N) = my(2)
    plot.display_topology(G, N, "EFTCG-2")
示例#2
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def standard_all():
    Node.n = 100
    #    np.random.seed(521)
    init()
    a = dia()
    b = mlpt()
    c = deba()
    d = my(1)
    Node_G = [[a, "DIA"], [b, "MLPT"], [c, "DEBA"], [d, "EFTCG"]]
    standard_algorithm(Node.n, Node_G)
示例#3
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def avg_power():
    x = range(30, 110, 10)
    y = []
    y_dia = []
    y_mlpt = []
    y_deba = []
    y_eftcg = []
    for i in x:
        print("The number of nodes:", i)
        Node.n = i
        y_dia_ = []
        y_mlpt_ = []
        y_deba_ = []
        y_eftcg_ = []
        for j in range(3):
            print("The count:", j)
            np.random.seed(j)
            init()

            G, N = dia()
            a = Simulator.average_power(len(N), N)
            y_dia_.append(a)

            G, N = mlpt()
            a = Simulator.average_power(len(N), N)
            y_mlpt_.append(a)

            G, N = deba()
            a = Simulator.average_power(len(N), N)
            y_deba_.append(a)

            G, N = my(1)
            a = Simulator.average_power(len(N), N)
            y_eftcg_.append(a)
        ###########################################
        y_dia.append(np.mean(y_dia_))
        y_mlpt.append(np.mean(y_mlpt_))
        y_deba.append(np.mean(y_deba_))
        y_eftcg.append(np.mean(y_eftcg_))
    ###############################################
    y = [[y_dia, "DIA"], [y_mlpt, "MLPT"], [y_deba, "DEBA"],
         [y_eftcg, "EFTCG"]]
    plot.plot_performance(x, y, ylabel="Avarage Power")
示例#4
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def performance_k():
    x = range(40, 110, 10)
    num = 5  # number of evaluation-index
    times = 10  # number of iterations
    y_deba = [[] for x in range(num)]
    y_k1 = [[] for x in range(num)]
    y_k2 = [[] for x in range(num)]
    for i in x:
        print("The number of nodes:", i)
        Node.n = i
        y_deba_ = [[] for x in range(num)]
        y_k1_ = [[] for x in range(num)]
        y_k2_ = [[] for x in range(num)]
        for j in range(times):
            print("The count:", j)
            init()
            n = Node.n
            size_ = 10
            fault_node = random.sample(range(n - 2), size_)

            G, N = deba()
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.survival_time(len(N), N, G)
            d, e = fault_k(len(N), G, fault_node)
            y_deba_[0].append(a)
            y_deba_[1].append(b)
            y_deba_[2].append(c)
            y_deba_[3].append(d)
            y_deba_[4].append(e)

            G, N = my(1)
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.survival_time(len(N), N, G)
            d, e = fault_k(len(N), G, fault_node)
            y_k1_[0].append(a)
            y_k1_[1].append(b)
            y_k1_[2].append(c)
            y_k1_[3].append(d)
            y_k1_[4].append(e)

            G, N = my(2)
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.survival_time(len(N), N, G)
            d, e = fault_k(len(N), G, fault_node)
            y_k2_[0].append(a)
            y_k2_[1].append(b)
            y_k2_[2].append(c)
            y_k2_[3].append(d)
            y_k2_[4].append(e)
        ###########################################
        # power
        ##########################################
        y_deba[0].append(np.mean(y_deba_[0]))
        y_k1[0].append(np.mean(y_k1_[0]))
        y_k2[0].append(np.mean(y_k2_[0]))
        ###########################################
        # degree
        ##########################################
        y_deba[1].append(np.mean(y_deba_[1]))
        y_k1[1].append(np.mean(y_k1_[1]))
        y_k2[1].append(np.mean(y_k2_[1]))
        ##########################################
        # survive time
        ##########################################
        y_deba[2].append(np.mean(y_deba_[2]))
        y_k1[2].append(np.mean(y_k1_[2]))
        y_k2[2].append(np.mean(y_k2_[2]))
        ###########################################
        # failure rate
        ##########################################
        y_deba[3].append(np.mean(y_deba_[3]))
        y_k1[3].append(np.mean(y_k1_[3]))
        y_k2[3].append(np.mean(y_k2_[3]))
        ###########################################
        # links rate
        ##########################################
        y_deba[4].append(np.mean(y_deba_[4]))
        y_k1[4].append(np.mean(y_k1_[4]))
        y_k2[4].append(np.mean(y_k2_[4]))
    ###############################################
    y0 = [
        [y_deba[0], "DEBA"],
        [y_k1[0], "EFTCG-1"],
        [y_k2[0], "EFTCG-2"],
    ]

    y1 = [
        [y_deba[1], "DEBA"],
        [y_k1[1], "EFTCG-1"],
        [y_k2[1], "EFTCG-2"],
    ]
    y2 = [
        [y_deba[2], "DEBA"],
        [y_k1[2], "EFTCG-1"],
        [y_k2[2], "EFTCG-2"],
    ]
    y3 = [
        [y_deba[3], "DEBA"],
        [y_k1[3], "EFTCG-1"],
        [y_k2[3], "EFTCG-2"],
    ]
    y4 = [
        [y_deba[4], "DEBA"],
        [y_k1[4], "EFTCG-1"],
        [y_k2[4], "EFTCG-2"],
    ]

    plot.plot_performance(x, y0, ylabel="Average Transmit Power")
    plot.plot_performance(x, y1, ylabel="Average Node Degree")
    plot.plot_performance(x, y2, ylabel="Network Lifetime")
    plot.plot_performance(x, y3, ylabel="Rate of Survival Nodes")
    plot.plot_performance(x, y4, ylabel="Rate of Connectable Node Pairs")
示例#5
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def plot_my(k=1):
    (Gmy, Nmy) = my(k)
    plot.display_topology(Gmy, Nmy, "EFTCG-" + str(k))
示例#6
0
def performance():
    x = range(30, 110, 10)
    num = 4  # number of evaluation-index
    times = 10  # number of iterations
    y_dia = [[] for x in range(num)]
    y_mlpt = [[] for x in range(num)]
    y_deba = [[] for x in range(num)]
    y_eftcg = [[] for x in range(num)]
    for i in x:
        print("The number of nodes:", i)
        Node.n = i
        y_dia_ = [[] for x in range(num)]
        y_mlpt_ = [[] for x in range(num)]
        y_deba_ = [[] for x in range(num)]
        y_eftcg_ = [[] for x in range(num)]
        for j in range(times):
            print("The count:", j)
            init()

            G, N = dia()
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.average_hop(len(N), G)
            d = Simulator.survival_time(len(N), N, G)
            y_dia_[0].append(a)
            y_dia_[1].append(b)
            y_dia_[2].append(c)
            y_dia_[3].append(d)

            G, N = mlpt()
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.average_hop(len(N), G)
            d = Simulator.survival_time(len(N), N, G)
            y_mlpt_[0].append(a)
            y_mlpt_[1].append(b)
            y_mlpt_[2].append(c)
            y_mlpt_[3].append(d)

            G, N = deba()
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.average_hop(len(N), G)
            d = Simulator.survival_time(len(N), N, G)
            y_deba_[0].append(a)
            y_deba_[1].append(b)
            y_deba_[2].append(c)
            y_deba_[3].append(d)

            G, N = my(1)
            a = Simulator.average_power(len(N), N)
            b = Simulator.average_degree(len(N), G)
            c = Simulator.average_hop(len(N), G)
            d = Simulator.survival_time(len(N), N, G)
            y_eftcg_[0].append(a)
            y_eftcg_[1].append(b)
            y_eftcg_[2].append(c)
            y_eftcg_[3].append(d)
        ###########################################
        # power
        ##########################################
        y_dia[0].append(np.mean(y_dia_[0]))
        y_mlpt[0].append(np.mean(y_mlpt_[0]))
        y_deba[0].append(np.mean(y_deba_[0]))
        y_eftcg[0].append(np.mean(y_eftcg_[0]))
        ###########################################
        # degree
        ##########################################
        y_dia[1].append(np.mean(y_dia_[1]))
        y_mlpt[1].append(np.mean(y_mlpt_[1]))
        y_deba[1].append(np.mean(y_deba_[1]))
        y_eftcg[1].append(np.mean(y_eftcg_[1]))
        ###########################################
        # hop
        ##########################################
        y_dia[2].append(np.mean(y_dia_[2]))
        y_mlpt[2].append(np.mean(y_mlpt_[2]))
        y_deba[2].append(np.mean(y_deba_[2]))
        y_eftcg[2].append(np.mean(y_eftcg_[2]))
        ##########################################
        y_dia[3].append(np.mean(y_dia_[3]))
        y_mlpt[3].append(np.mean(y_mlpt_[3]))
        y_deba[3].append(np.mean(y_deba_[3]))
        y_eftcg[3].append(np.mean(y_eftcg_[3]))
    ###############################################
    y0 = [[y_dia[0], "DIA"], [y_mlpt[0], "MLPT"], [y_deba[0], "DEBA"],
          [y_eftcg[0], "EFTCG"]]
    y1 = [[y_dia[1], "DIA"], [y_mlpt[1], "MLPT"], [y_deba[1], "DEBA"],
          [y_eftcg[1], "EFTCG"]]
    y2 = [[y_dia[2], "DIA"], [y_mlpt[2], "MLPT"], [y_deba[2], "DEBA"],
          [y_eftcg[2], "EFTCG"]]
    y3 = [[y_dia[3], "DIA"], [y_mlpt[3], "MLPT"], [y_deba[3], "DEBA"],
          [y_eftcg[3], "EFTCG"]]
    plot.plot_performance(x, y0, ylabel="Average Transmit Power")
    plot.plot_performance(x, y1, ylabel="Average Node Degree")
    plot.plot_performance(x, y2, ylabel="Average Hop")
    plot.plot_performance(x, y3, ylabel="Network Lifetime")
示例#7
0
def fault():
    size_ = 10
    n = 60
    times = 1
    k1_in_num_ = []
    k1_links_ = []

    k2_in_num_ = []
    k2_links_ = []

    deba_in_num_ = []
    deba_links_ = []
    ###########################################################
    for i in range(times):
        Node.n = n
        init()
        n = Node.n
        size_ = 10
        fault_node = random.sample(range(n - 2), size_)  #= fault_node
        print("Fault Node is:", fault_node)
        #######################################################
        # EFTCG-1                                             #
        #######################################################
        G, N = my(1)
        in_num, links = robust(n, G, fault_node)
        #        ad_1 = Simulator.average_degree(n, G)
        #        st_1 = Simulator.survival_time(n, N, G)

        k1_in_num_.append(in_num)
        k1_links_.append(links)
        #######################################################
        # EFTCG-2                                             #
        #######################################################
        G, N = my(2)
        in_num, links = robust(n, G, fault_node)
        #        ad_2 = Simulator.average_degree(n, G)
        #        st_2 = Simulator.survival_time(n, N, G)

        k2_in_num_.append(in_num)
        k2_links_.append(links)
        #######################################################
        # DEBA                                                #
        #######################################################
        G, N = deba()
        in_num, links = robust(n, G, fault_node)
        #        ad_3 = Simulator.average_degree(n, G)
        #        st_3 = Simulator.survival_time(n, N, G)

        deba_in_num_.append(in_num)
        deba_links_.append(links)
    ##############################################################
    def avg(*lst):
        #        global size_
        avg_ = 0
        for x in lst:
            avg_ += x / size_
        return avg_

    def fr(x):
        #        global n
        return x / n * 100

    def rl(x):
        #        global n
        return x / (n * (n - 1)) * 100

    #############################################################
    # failure rate
    #############################################################
    k1_fr = list(map(fr, list(map(avg, *(k1_in_num_)))))
    k2_fr = list(map(fr, list(map(avg, *(k2_in_num_)))))
    deba_fr = list(map(fr, list(map(avg, *(deba_in_num_)))))

    #############################################################
    # links
    #############################################################
    k1_rl = list(map(rl, list(map(avg, *(k1_links_)))))
    k2_rl = list(map(rl, list(map(avg, *(k2_links_)))))
    deba_rl = list(map(rl, list(map(avg, *(deba_links_)))))

    #############################################################
    x = list(range(1, size_ + 1))
    y0 = [
        [deba_fr, "DEBA"],
        [k1_fr, "EFTCG-1"],
        [k2_fr, "EFTCG-2"],
    ]
    y1 = [
        [[100 - x for x in deba_fr], "DEBA"],
        [[100 - x for x in k1_fr], "EFTCG-1"],
        [[100 - x for x in k2_fr], "EFTCG-2"],
    ]
    y2 = [
        [deba_rl, "DEBA"],
        [k1_rl, "EFTCG-1"],
        [k2_rl, "EFTCG-2"],
    ]
    #    plot.plot_performance(x,y0,xlabel="Number of fault nodes",ylabel="Rate of Failure Nodes")
    plot.plot_performance(x,
                          y1,
                          xlabel="Number of fault nodes",
                          ylabel="Rate of Survival Nodes")
    plot.plot_performance(x,
                          y2,
                          xlabel="Number of fault nodes",
                          ylabel="Rate of Connectable Node Pairs")
    pass