Bio-Inspired ACO-based Traffic Aware QoS Routing in Software Defined Internet of Things

Figures & data

Figure 1. SDN-based system architecture.

Figure 2. Proposed controller architecture.

Table

Algorithm 1 QoS Route computation algorithm for delay(ds), loss(ls) and jitter (jt) flows
1: Inputs: Graph, Gp
2: Network flows sets $\mathit{F}$ with their associated QoS requirements
3: Max rules can be inserted at a switch-$R_m$
4: Priority of $\mathit{dsf}-\mathit{A}1$, $\mathit{lsf}-\mathit{A}2$, and $\mathit{jtf}-\mathit{A}3$
5: Output: Network set Paths {SP} on which $\mathit{dsf}$, $\mathit{lsf}$, and $\mathit{jtf}$ can be routed
6: for (k $\in$ Gp) do
7: rls(k) $\leftarrow$ $R_m$▹Initialize rule-capacity
8: $\mathit{x},\mathit{y},\mathit{z}$ $\leftarrow$ $1$
9: while (flows $\mathit{f}\_\mathit{k}$ $\in$ F that have not been routed) do
⊳ round robin scheduling for $\mathit{ds}$, $\mathit{ls}$ and $\mathit{jt}$ flows to make equal allocation
10: if (($\mathit{ds}$ $\in$ $\mathit{dsf}$) not in routed matrix) then
11: for $\mathit{i}$ $\leftarrow$ 1 to $\mathit{A}1$ do
12: path $\leftarrow$ getPath($t_m$, $s_m$, ${\lambda }_m$ $\leftarrow$ $d_s$, $q_m$)
13: x $\leftarrow$ x + 1▹Route $x^{\mathit{th}}$ $\mathit{ds}$ path flow
14: if (($\mathit{ls}$ $\in$ $\mathit{lsf}$) not in routed matrix) then
15: for $\mathit{j}$ $\leftarrow$ 1 to $\mathit{A}2$ do
16: path $\leftarrow$ getPath($s_n$, $t_n$, ${\lambda }_n$ $\leftarrow$ $l_s$, $q_n$)
17: y $\leftarrow$ y + 1⊳Route $y^{\mathit{th}}$ ds flow using path
18: if (($\mathit{jt}$ $\in$ $\mathit{jtf}$) not in routed matrix) then
19: for $\mathit{j}$ $\leftarrow$ 1 to $\mathit{A}3$ do
20: path $\leftarrow$ getPath($s_p$, $t_p$, ${\lambda }_n$ $\leftarrow$ $l_s$, $q_p$)
21: z $\leftarrow$ z + 1⊳Route $p^{\mathit{th}}$ ds flow using path
22:
23: function getPath(src, targ, $\mathit{\lambda }$, q)
24: if (type == $\mathit{ds}$) then
25: for path in K-SHORTEST-PATHS (src, targ, $f_d$) do
26: if (ValidateQoS (path, q)) then⊳delay satisfied
27: network best-path $\leftarrow$ path
28: else if (type == $\mathit{ls}$) then
29: for path in K-SHORTEST-PATHS (src, trg, fl) do
30: if ValidateQOS (path, q) then then⊳loss satisifed
31: network best-path $\leftarrow$ path
32: else if (type == $\mathit{jt}$) then
33: for path in K-SHORTEST-PATHS (src, trg, fp) do
34: if (ValidateQoS (path, q)) then⊳jitter satisifed
35: network best-path $\leftarrow$ path
36: else
37: return previous best-path
38: else
39: return new best-path
40:
41: function Validate QOS (demand, path)
42: if (Check_Delay, Check_Bandwidth, Check_Jitter, Check_Loss and Check_Rules) then
43: return $1$
44: else
45: return $0$

Table

Algorithm 2 Ant Inspired K Shortest Path Routing Algorithm
1: Initialize the parameters of the algorithm and the value of pheromones according to the traffic conditions
2: for i = 1 to constant number of Iteration do
3: Place the m ants on the original node
4: Ants start moving from original node
5: for k = 1 to m ants do
6: if $k^{\mathit{th}}$ ant searches the path to the destination using the transition rule then
7: update pheromone of path
8: Return k shortest path

Figure 3. Flow chart of Traffic-Aware QoS routing.

Figure 4. Flow chart of Ant inspired K shortest path routing.

Table 1. Simulation parameters.

Parameter	Value
Topology	Goodnet, Attmpls
Number of switches	30, 45
Number of links	55, 70
Bandwidth	1–10kpbs
Delay of a flow	1–50ms
Packet loss	0–30%
Jitter of flow	1–30ms

Figure 5. Average delay comparison in Attmpls.

Figure 6. Average delay comparison in Goodnet.

Figure 7. QoS Violated Flows comparison in Attmpls.

Figure 8. QoS Violated Flows comparison in Goodnet.

Figure 9. Packet loss in Attmpls.

Figure 10. Packet loss in Goodnet.

Figure 11. Average jitter in Attmpls.

Figure 12. Average jitter in Goodnet.

Data Availability Statement

All data generated or analyzed during this study are included in this article.