1) The document proposes an energy-efficient heuristic algorithm for service function chaining path allocation in SDN networks. The goal is to minimize energy consumption by switching off unused servers while meeting quality of service constraints. 2) It formulates the problem as a mixed integer linear program to find optimal resource allocations and then develops a low-complexity heuristic to solve larger problem instances in reasonable time. 3) Results show the heuristic finds near-optimal solutions with much less computation time compared to the optimal approach as problem size increases in terms of network size and number of flows.

1. Energy-efficient Path Allocation Heuristic
for Service Function Chaining
Mohammad Mahdi Tajiki(1), Stefano Salsano(2, 3,*), Mohammad Shojafar(2), Luca Chiaraviglio(2, 3), Behzad Akbari(1)
(1) TMU, Iran
(2) CNIT, Italy – (3) Univ. of Rome Tor Vergata, Italy
(*) Project coordinator of the EU H2020 Superfluidity project http://superfluidity.eu/
21st Conference on Innovation in Clouds, Internet and Networks (ICIN 2018)
February, 19-22 2018 - Paris, France
A super-fluid, cloud-native, converged edge system

2. Outline
• Problem Definition / Reference Architecture
• Problem Formulation
• Heuristic Algorithm
• Results
• Conclusion & Future works
2

3. Problem Definition
• Scope:
– Service Function Chaining Problem
– SDN-based networks
• Goal:
– Minimize the energy consumption of the network
– Subject to QoS constraints (maximum utilization of links and server processing
capabilities)
• Approach:
– Mathematical formulation (MILP Optimization Problem)
– A low complexity heuristic algorithm
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4. Virtual Network Functions (VNFs) examples: Deep Packet Inspection, NAT, Firewalls, CDN
nodes, HTTP proxies, Antivirus, Parental control, Video optimizer, Video transcoding
A Flow between two end-points needs to be served by a set of
Virtual Network Functions (VNFs)
Flow 1 : { VNF1, VNF3}
Problem Definition
4
VNF1 VNF2 VNF3 VNF4

5. The Network Operator needs to serve a set of flows, with different SFC requirements:
Flow 1 : { VNF1, VNF3}
Flow 2 : { VNF2, VNF3}
Flow 3 : { VNF1, VNF4}
…
Problem Definition
5
VNF1 VNF2 VNF3 VNF4
F1
F2
F3

6. Problem Definition
6
1
2
3
5
4Server
Network node
The infrastructure is composed of Servers that can host VNFs and Network nodes
VNF1 VNF2 VNF3 VNF4

7. Problem Definition
7
1
2
3
5
4Server
Network node
The infrastructure is composed of Servers that can host VNFs and Network nodes
The operator needs to allocate VNF into Servers (a Server supports a set of VNFs)
VNF1 VNF2 VNF3 VNF4

8. Problem Definition
8
1
2
3
5
4Server
Network node
The infrastructure is composed of Servers that can host VNFs and Network nodes
The operator needs to allocate VNF into Servers (a Server supports a set of VNFs)
and select the path from the flows (e.g. F1)
VNF1 VNF2 VNF3 VNF4
F1

9. Problem Definition
9
1
2
3
5
4Server
Network node
The operator wants to minimize energy consumption (a Server with no mapped
VNFs can be switched off and does not consume energy)
VNF1 VNF2 VNF3 VNF4
F1

10. Problem Definition
10
1
2
3
5
4Server
Network node
The operator wants to minimize energy consumption (a Server with no mapped
VNFs can be switched off and does not consume energy)
VNF1 VNF2 VNF3 VNF4
F1

11. Problem Definition
11
1
2
3
5
4Server
Network node
The operator wants to minimize energy consumption (a Server with no mapped
VNFs can be switched off and does not consume energy)
VNF1 VNF2 VNF3 VNF4
F1

12. Problem Definition
12
1
2
3
5
4Server
Network node
The operator wants to minimize energy consumption (a Server with no mapped
VNFs can be switched off and does not consume energy)
Constraints on maximum link capacity and maximum server capacity are taken into
account.
VNF1 VNF2 VNF3 VNF4
F1

13. Architecture
13
Common Routing Algorithm
(Configuration Element)
Proposed Algorithm
(Reconfiguration Element)
Centralized SDN Controller
North Bound Protocol
South Bound Protocol
1 2
3
4
5

14. Problem Formulation - Notation
14

15. Problem Formulation
15
Objective Function : minimize the
number of servers that are switched ON
Constraint: each flow crosses all the
required VNFs
Constraint: if a VNF provides service to
a flow, the flow crosses the node in
which the VNF is hosted

16. Problem Formulation
16
Constraint: a VNF is supported by a
given server
Constraint: each VNF is delivered only
once to each flow

17. Problem Formulation
17
Constraint: maximum processing
capacity in a server
Constraint: maximum link utilization

18. Problem Formulation
18
Constraint: flow conservation
Constraint: loop avoidance
Constraint: only servers that deliver at
least one services to a flow are ON

19. Recap of main assumptions
• We consider “aggregated” flows, the allocation process is relatively
“long term”
• We know the requested bandwidth of the flows
• There are no “ordering constraints” among the VNFs
• The servers can be ON or OFF (no “hot standby”), the power
consumption does not depend on the actual load.
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20. Heuristic Algorithm – HNR Heuristic Network Reconfiguration
20
• The flows are considered sequentially
one after the other
• For each flow a “optimal” feasible
solution (path and VNF allocation) is
found, based on the previous choices

21. Results – Reference Topology (Abilene)
21
• We designed a generator of traffic demands (the set of flows with their
VNF requirements), we can tune several parameters (overall load, relative
size of flows, average number of VNFs…)
• In each experiment we increase the load in 5 steps and run the allocation
• We considered 4 different scenarios

22. Results – Optimal Solution vs. Heuristic Algorithm
22
Power consumption Average path lenght

23. Results – Optimal Solution vs. Heuristic Algorithm
23
Comparison of average and maximum utilization for servers and links

24. Results – Optimal Solution vs. Heuristic Algorithm
24
# of Flows ONR (s) HNR (s)
10 16 0.007
250 1382 0.080
500 > 61000 0.163
750 > 61000 0.250
1000 > 61000 0.346
1500 > 61000 0.502
2000 > 61000 0.755
Computational Complexity (Total Solution Time)

25. Conclusion
• We considered an SFC allocation problem for an SDN-based architecture
• We mathematically formulated the resource allocation problem considering the
minimization of energy consumption, the SFC requirements, and QoS constraints.
• The MILP formulation cannot be solved in reasonable time when the problem size
(network dimension and number of flows) increases.
• We proposed a heuristic algorithm which can solve problems of realistic size.
• We implemented a traffic demand generator which offers several tunable
parameters (e.g., VNF requirements, flow size, node functionality, tolerable delay,
and etc.) and compared the optimal solution with the heuristic algorithm.
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26. Ongoing and Future Work
• SFC ordering constraints
• Additional QoS constraints such as end-to-end delay
• Additional operating mode for the servers : ON, OFF and IDLE (Hot Standby)
• Considering failure probability
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27. Thank you. Questions?
Contacts
Mohammad Mahdi Tajiki
University of Tarbiat Modares, Iran
mahdi.tajiki@modares.ac.ir
Stefano Salsano
University of Rome Tor Vergata / CNIT
stefano.salsano@uniroma2.it
http://superfluidity.eu/ 27

28. References
• M. M. Tajiki, S. Salsano, M. Shojafar, L. Chiaraviglio, B. Akbari,
“Energy-efficient Path Allocation Heuristic for Service Function Chaining”,
21st Conference on Innovation in Clouds, Internet and Networks (ICIN 2018), February 20-22,
2018, Paris, France
http://netgroup.uniroma2.it/Stefano_Salsano/papers/18-icin-energy-efficient-sfc.pdf
• M. M. Tajiki, S. Salsano, M. Shojafar, L. Chiaraviglio, B. Akbari,
“Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function
Chaining”, extended version, submitted paper
https://arxiv.org/abs/1710.02611
• SUPERFLUIDITY project Home Page http://superfluidity.eu/
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29. The SUPERFLUIDITY project has received funding from the European Union’s Horizon
2020 research and innovation programme under grant agreement No.671566
(Research and Innovation Action).
The information given is the author’s view and does not necessarily represent the view
of the European Commission (EC). No liability is accepted for any use that may be
made of the information contained.
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