New Approach for Mobility Management in
Openflow/Software-Defined Networks
N. Omheni
1
, F. Zarai
1
, B. Sadoun
2
and M. S. Obaidat
3,*
1
New Technologies and Telecommunications Systems Research Unit, ENET’COM, Tunisia
2
College of Engineering, Al-Balqa Applied University, Jordan, ECE Department,
Nazarbayev University, Astana, Kazakhstan
3
Kazakhstan and King Abdullah II School of Information Technology, University of Jordan, Jordan
Keywords: Software-Defined Networking, Distributed Mobility Management, Proxy Mobile Ipv6, Media Independent
Handover, Openflow, SDN Controller, Signaling Cost.
Abstract: The Software-Defined Networking (SDN) paradigm predicts that the evolution of cellular and wireless
networks will bring a considerable increase of two factors, the densification of the Radio Access Network
(RAN) part and the progressive demand for traffic. This rapid evolution has led to the emergence of extremely
complicated systems, where a large number of logic modules must interact to lead to the desired behavior and
the desired quality of service. The key advantage of SDNs is the simplicity of networking and the deployment
of new mechanisms and applications. Furthermore, the programmable aspect on the traffic and devices in
SDNs makes them more efficient and flexible than traditional networks. In this context, Distributed Mobility
Management (DMM) has been recently presented as a new trend to solve the issues of the today’s mobility
management protocols. In this paper, we propose a partially distributed Mobility Management for
OpenFlow/SDN networks. According to simulation results, our approach guarantees a significant reduction
of the number of handover and the signaling cost.
1 INTRODUCTION
*
We are witnessing in recent years to an explosion of
mobile communications, together with an exponential
usage of Internet for all kinds of applications. It is
expected that by the year 2020, more than 50 billion
smart devices around the world should be connected
and the annual revenues of this new market will
exceed US $8.9 trillion (IoT, 2016). In this evolved
context, a wide range of wireless technologies has
gradually emerged indicating a great diversity in
communication needs in various application domains
and new standards have regularly been proposed.
Moreover, the massive volume of traffic and the
evolutionary aspect of the size of such systems make
any study carried out on these networks a very
difficult task. Thus, both mobile operators, industry
and research communities are trying to discover
innovative solutions and mechanisms to improve
their network efficiency and performance as well as
*
Fellow of IEEE and Fellow of SCS.
to moderate the costs of new service deployment and
network operation maintenance.
Software-Defined Networking (SDN) and
Network Function Virtualization (NFV) are two
important recent innovations that are expected to
offer such solutions. SDN is a new paradigm for
programmable networking and is adopted extensively
in enterprise networks and data centers. (Ahn, 2017).
Figure 1 depicts the SDN network. In such network,
control and data forwarding functions are managed
separately in order to permit centralized and
programmable network control (Kreutz, 2015).
The major components of the SDN architecture
comprise a data plane involving network resources
for data forwarding, a control plane including SDN
controllers permitting a centralized control of
network resources, and a management applications to
program network operations over a controller. The
interface between the data and the control forwarding
plans is called the southbound interface while the
Omheni, N., Zarai, F., Sadoun, B. and Obaidat, M.
New Approach for Mobility Management in Openflow/Software-Defined Networks.
DOI: 10.5220/0006847800250033
In Proceedings of 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2018), pages 25-33
ISBN: 978-989-758-323-0
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
25
control-application interface is called the northbound
interface.
Mobility management plays a crucial role in such
environments, where mobiles can easily experience
numerous handovers during the same connectivity
session. Consequently, there is a real need to propose
novel mobility management approaches.
Figure 1: Overall main components of SDN architecture.
Mobility management approaches have to be
distributed to provide better reliability and avoid any
network bottleneck or single point of failure.
Here the DMM paradigm presents most of the
above-mentioned features, and specifically accounts
for distributed IP flow mobility managed via
distributed anchoring by separating data and control
planes to address the limitations of current centralized
mobility management such as scalability, reliability
and sub-optimal routing (Liu, 2014).
Several DMM-oriented solutions have been
proposed in the literature as, for example, the
Distributed Mobility Anchoring (DMA) (Seite,
2013), Double NAT (D-NAT) (Liebsc, 2011), Inter-
domain DMM, and Local IP Access (LIPA)/Selected
IP Traffic Offload (SIPTO) (3GPP, 2015).
OpenFlow-based SDN architecture is another
candidate solution that supports DMM features and
outperforms existing solutions. Advantages provided
by OpenFlow, as the most joint communication
protocol used in SDN approach, would be an enabler
to reach the forwarding plane of OpenFlow switches
through the network and reconfigure it in line with the
necessities of applications and network services (The
OpenFlow, 2017).
In this paper, we present a new SDN/OpenFlow
based partially DMM. First, we introduce the
proposed architecture components. Then, we describe
our suggested mobility management procedures for
SDN/OpenFlow composed by two stages: (a)
preparation and registration stage and (b) handover
execution. Our approach belongs to the category of
partially distributed mobility management. The SDN
Controller handles the control plane in a centralized
way. While, the DMM-ARs (Distributed Mobility
management-Access Routers) manage the data plane
in a distributed manner.
The rest of this paper is organized as follows.
Section 2 presents the related work. In section 3, the
new Software Defined Networking (SDN)/OpenFlow
based partially DMM is detailed.OpenFlow
operations, which are executed in the DMM-AR are
detailed in section 4. Performance evaluation is
discussed in Section 5. Finally, Section 6 concludes
the paper.
2 RELATED WORK
2.1 Software-Defined Networking
(SDN)
In this section, we discuss different projects dealing
with wireless and cellular networks that integrate
SDN paradigm. In SoftCell (Jin, 2013), SDN
principles are incorporated in LTE (Long Term
Evolution) core networks. The aim of this framework
is to build simple programmable core switches inside
mobile network while the most of functionalities are
pushed to access switches in the radio access network.
This division between access and other core switches
creates real scalability.
Contrary to SoftCell, which is interested in the
dimensioning of the core network, SoftRAN project
makes use of SDN functionalities to remodel the LTE
radio access network (Gudipati, 2013). In traditional
radio access networks, interference and handovers are
handled using distributed protocols. While this
concept is acceptable in light networks, in ultra-dense
environment it leads to bad performance in terms of
interferences and latencies. In SoftRAN, the entire
LTE network is controlled in a centralized manner.
All e-Node B co-located in a geographical area are
managed as a virtual big-base station. Radio
resources are abstracted out as three-dimensional grid
of space, time and frequency slots. Periodically, all
radio interfaces send information about local network
state to SDN controller. The latter determines the way
SIMULTECH 2018 - 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
26
to assign radio resources block and transmit power for
each radio element.
Work in (Tomovic, 2017) was recently published.
The authors proposed a new architecture for IoT
(Internet of Thing) combining the two evolving
technologies: Fog computing and SDN. Their goal
was to support a high level of scalability, real-time
data delivery and mobility. Fog computing policy is
considered as the suitable platform for IoT thanks to
its capability to reduce latency for services that need
fast analysis and decision-making. While, SDN is
used due to its centralized aspect to manage control
plane, which permits the execution of sophisticated
techniques for resource management and traffic
control.
In (Ahmad, 2016), authors proposed a new
solution in the form of Software-Defined Mobile
Networks (SDMN) including SDN, NFV (Network
Function Virtualization) and cloud technologies. The
goal is to answer the issues confronted by current
mobile network architectures in integrating diverse
services.
Authors in (Knaesel, 2013) proposed an
OpenFlow based IEEE 802.21 Media Independent
Handover (MIH) to perform link connectivity
establishment in SDN. Nevertheless, 3GPP or ETSI
NFV architectures are not considered in their
framework. In this work, a MIH-enabled Evolved
Packet System was proposed to offer seamless
handovers between 3GPP and non-3GPP wireless
technologies. However, their work does not consider
programmable or virtualized mobile concepts.
2.2 Distributed Mobility Management
(DMM)
There are already many works that have treated
Distributed Mobility Management in the context of
SDN. In (Chen, 2016), a mobility management
approach called Mobility SDN (M-SDN) was
proposed to decrease the traffic pause time produced
by a host-initiated layer-2 handover. The key idea of
this work is that the handover preparation is
performed in parallel with layer-2 handover and
active flows are sent to each potential handover
target. In (Costa, 2013), the authors considered the 5G
as an application group and suggested that mobility
management can be treated as a service on top of the
SDN controller. In (Hampel, 2013), the authors
focused on forwarding data across networking layers
and discussed how to relate SDN to the Telecom
domain. Authors of (Jeon, 2013) presented a new
architecture for SDN based mobile networking with
two kinds of controller model: hierarchical and single
controller. In (Nguyen, 2016), authors proposed a
new DMM solution in the context of 5G networks
based on SDN architecture called S-DMM. In their
proposed architecture, DMM is delivered as a service
deployed on top of SDN controller. Mobile Access
Routers (MAR) are considered as a simple
forwarding hardware and do not necessitate any
mobility-related module. The centralized control
controller permits the operators to control the network
at a reduced complexity level.
In the rest of this subsection, we describe briefly
three main types of DMM solutions, which have been
published as extensions or improvements of already
published standards.
The first type of solutions is known as PMIPv6-
based DMM solution. It is based on amelioration of
classical IP mobility protocols and mainly PMIPv6
(Proxy Mobile IPv6). This protocol manages mobility
in a centralized way where the Local Mobility Anchor
(LMA) in the core network creates bidirectional
tunnels to Mobile Access Gateways (MAGs) fixed in
the radio access networks. More details about this
protocol can be founded in (Bernardos, 2014).
The second family of solutions is inspired by the
SDN context and named SDN-based DMM. In SDN,
network control and data forwarding functions are
managed separately to permit centralized and
programmable network control. With this paradigm,
network administrators are able to program the
comportment of the traffic and the network in a
centralized manner.
The last category of solutions is the routing-based
DMM. The main idea of this kind of solutions is to
eliminate any anchor point from the network
architecture; permitting all nodes in the network to re-
establish a new routing map when terminals change
their location. This family of solutions belongs to the
IP routing protocols.
3 SDN-BASED PARTIALLY
DISTRIBUTED MM (S-PDMM)
3.1 Proposed Architecture Components
In this section, we introduce in detail the proposed
system model for SDN-based partially distributed
MM and we describe the suggested mobility
management procedures. The proposed architecture
is shown in Figure 2. Our SDN mobility management
architecture relies on three main levels:
New Approach for Mobility Management in Openflow/Software-Defined Networks
27
Figure 2: Proposed architecture.
the RANs (Radio Access Networks), the DMM-AR
and the SDN Controller. The proposed architecture is
shown in Figure 2. Our SDN mobility management
architecture relies on three main levels: the RANs
(Radio Access Networks), the DMM-AR and the
SDN Controller.
The first level is composed of SDN enabled WiFi
access points and 3GPP LTE radio access network.
RANs are the heterogeneous access networks, which
include different access technologies such as WiFi
and LTE.
These radio access networks can be
programmable and under the supervision of SDN
Controller in the core network.
The DMM-AR is an access router which not only
delivers connectivity to the RANs (default gateway),
it is also boosted with some specific DMM
functionalities. DMM-ARs act as OpenFlow switches
(OFS) and communicates with the SDN controller
with the southbound Application Program Interfaces
(APIs) to achieve the packet processing and
forwarding feature. The SDN controller with the use
of OpenFlow protocol can apply a set of actions such
as adding, deleting or updating flow entries to the
flow tables in the DMM-AR.
One of the issues that can be observed in the first
level is the coexistence of various complementary
technologies (cellular vs WiFi), in terms of
connection type, shared/dedicated medium and QoS
requirements. In order to closer incorporate QoS
signaling and mobility for these various technologies,
we combined the IEEE 802.21 MIH functions with
the proposed SDN-based partially distributed MM.
The reason of this mapping between MIH and SDN is
that WiFi RANs allow handover only to the same
network types and behind the same domain.
Furthermore, mobility management at upper layers
does not tolerate significant delays to get technology-
independent handover triggers and to select the best
candidate AP.
The aims of MIH standard are to facilitate
mobility management by delivering a technology-
independent interface under the network layer. The
IEEE 802.21 proposes a MIH specification for
achieving seamless handover for mobile users in the
same or in different networks.
The main functionality offered by MIH is a
seamless connection to different RATs. The control
messages are relayed by the Function (MIHF) located
in the protocol stack between layer 2 wireless
technologies and IP layer. This type of deployment
makes it easy for mobile nodes to move between
different Points of Attachment (PoAs).
The third level is composed of SDN controller
which is the key entity in our architecture. The role of
this controller is the management and the
configuration of DMM-ARs through the Southbound
common application programming interface as
mentioned earlier. The northbound API is reserved
for communications between the SDN controller and
the network applications. The Mobility Management
Entity (MME) side core network is integrated in the
SDN controller. The latter interacts with the AAA
server to get the MN’s profile for authentication.
Furthermore, SDN controller supports others control
plane features related to LTE networks such as
Serving Gateway (S-GW), Home Subscriber System
(HSS) and others nodes.
3.2 SDN-based Partially Distributed
MM Procedures
The suggested mobility management procedures are
divided into two stages: (a) The preparation and
registration stage and (b) the handover execution
stage. In the first step, we take advantage of the MIH
standard in SDN context for the optimization of the
MN attachment detection.
In the second stage, the proposed mobility
management approach uses the PMIPv6 protocol for
handover execution. The SDN controller will play the
role of LMA in the PMIPv6 context.
SIMULTECH 2018 - 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
28
Figure 3: Mobility management operations.
The MAG is replaced by the DMM-AR. Figure 3
shows the proposed mobility management operations.
3.2.1 Preparation and Registration Stage
For the preparation stage, the DMM-AR must be able
to be aware of the existing RANs status. These
actions can be achieved by applying
MIH_Link_Get_Parameters primitives between the
MIHF and its users. MIH_Get_Information message
primitives can ask Handover policies and network
context information from the SDN and the MIIS at
the core network. Upper layers can also command
specific actions for a given radio interface such as
Link Power Up or Link Power down operation.
When a MN moves inside an LTE RAN network,
the radio interface is switched on by running MIH
Link Power Up primitive. This will trigger the
network attachment of the LTE interface to the
DMM-AR and an IP route will be established to the
MN. Registration occurs when the MN changes its
attachment from a previous DMM-AR (p-DMM-AR)
to a new DMM-AR (n-DMM-AR) to preserve
connectivity with the correspondent node (CN). Two
types of messages are exchanged between the MME,
which is integrated in the SDN controller, and the
new DMM-AR. The latter acts as the HA (Home
Agent) of the MN in the PMIPv6 domain during this
process; proxy binding update (PBU) and proxy
binding acknowledgement (PBA) processes.
A DMM-AR incorporates either mobility
anchoring features and is able to forward MN’IP
flows without disruption before moving to a new
DMM-AR. The SDN controller will play the role of
LMA (Local Mobility Anchor) in the PMIPv6 context
and maintain the mobile node’s (MN) reachability
when it is away from home. The MN sends a Router
Solicitation message to its DMM-AR. The latter
exchanges PBU and PBA messages with the SDN
controller. The MN attachment detection is achieved
and new IPv6 prefix is assigned to the MN.
3.2.2 Handover Execution
PMIPv6, in the original version, suffers from several
limitations such as packet loss and long handover
latencies. For that reason, our approach takes benefit
from the wireless link layer triggers to anticipate the
next handover when the MN changes its attachment.
IP flows are directly forwarded to the new DMM-AR
in a pre-established tunnel between the two DMM-
ARs before the new attachment.
In the following, we give the different steps of
handover execution. After the registration stage, the
SDN Controller creates a new entry for the MN. After
receiving the PBU message from the current DMM-
AR, the MN updates its location with the new DMM-
AR. As mentioned previously, IP flows are directly
forwarded to the new DMM-AR in a pre-established
tunnel between the two DMM-AR before the new
attachment. After that, DMM-ARs act as OpenFlow
switches (OFS) and communicates with the SDN
controller with the APIs to achieve the packet
New Approach for Mobility Management in Openflow/Software-Defined Networks
29
processing and forwarding feature and the OpenFlow
rules in the new DMM-AR are configured.
The final step of handover is achieved when rules
on DMM-AR are translated and forwarded. The
visited DMM-AR changes the IP destination address
with the last MN’s IP address to forward traffic in the
new MN’s domain.
Our approach belongs to the category of partially
distributed mobility management. The SDN
Controller handles the control plane in a centralized
way. While, the DMM-ARs manage the data plane in
a distributed manner.
4 OPENFLOW OPERATIONS
DMM-ARs act as OpenFlow switches (OFS). The
comportment of OFS is wholly determined by the
contents of Flow Tables, whose entries identify flows
and the way to analyze packets of these flows. Each
entry comprises three features:
(1) Rules: to match incoming packets to current
flows. Each entry must contain a set of header
values. These are used to look for the flows to
which incoming packets belong.
(2) Actions: This entry determines how to handle
packets belonging to the flows. A packet can be
either forwarded, dropped, or modified.
(3) Statistics: This feature covers statistical data,
which can be used by the SDN controller to adjust
policies.
The flow-table format is illustrated in the Figure
4. Counters field indicates some statistics such as
number of received packets, received bytes and
duration. Three actions are defined depending on the
case (forward the packet, encapsulate and forward the
packet or drop the packet. The priority field in our
approach gives priority of the used radio network.
Figure 4: Flow-table format.
The OpenFlow protocol allows handling different
nodes in the network in right time by executing
configuration changes in the data plane. In OFS, the
latency experienced by data plane features to treat
packets increases due to the transmission delay
between OpenFlow switch and the SDN Controller,
the performance of the latter in terms of processing
speed and finally the receptiveness of OpenFlow
switches in creating new flow and updating their
tables after receiving information from the SDN
Controller (He, 2016).
DMM-ARs check the SDN controller for the first
packet of each new flow. Later all packets belonging
to the same flow will be processed in line with the
flow-table entry (rules) fixed after receiving the first
packet. The traffic between the SDN controller and
DMM-ARs is then considerably reduced by flow-
based traffic.
We consider that the OFSs adopt a pipeline
treatment of the received packets as mentioned in
(Javed, 2017). Three components are defined in this
pipeline treatment. A flow-table to manage and
forward packets, a safe channel to connect a DMM-
AR and the SDN Controller and finally the OpenFlow
protocol, an open standard for communication
between the SDN Controller and DMM-ARs.
Figure 5 illustrates the different steps that the
DMM-AR takes to process a packet. When a packet
Figure 5: Packet processing steps.
SIMULTECH 2018 - 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
30
arrives at DMM-AR, which acts as an OpenFlow
switch, it checks whether there is an entry matchin its
flow-table. In case of correspondence, one of these
three actions will be excuted (forward the packet,
encapsulate and forward the packet or drop the
packet). If not, the packet will be sent to the SDN
Controller to update the flow-table.
5 SIMULATIONS RESULTS
5.1 Simulation Setup
The proposed approach is evaluated through
simulation. The implementation of the proposed
framework is performed in OMNeT++ 5.0. The
simulation scenarios are as follows: one eNodeB, one
DMM-AR and UEs, where the UEs are dynamically
moving from one place to another.
We conduct the simulation in the area of about
2000 m x 2000 m. To simplify the simulation, we
assume that control messages are of the same size of
a unit length and the distance between the SDN
controller and the DMM-AR is set to 1 hop. Table 1
shows the simulations parameters.
Table 1: Simulations parameters.
Parameters Values
Simulation area
Mobility model
UE distribution
Transmission rate
Distance between eNB and
DMM-AR (hops)
Radius of eNB coverage
Velocity of UEs
2000 m x 2000 m
random walk model
Uniform randomly
100 Mbps
1
500 m
2 m/s
The performance of our proposed S-PDMM
framework is evaluated based on a comparison of
signaling cost and number of handovers with the
work in (Javed, 2017)
The Signaling Cost (SC) represents the cost of
mobility-related signaling messages for a mobile
node per unit time. The Signaling Cost (SC) can be
calculated as:
 =

×

Where Message j is the size (in bytes) of a
signaling message j, and Hops j are the average
number of hops traversed by message j. The number
of hops changes for each type of transmission based
on the path selected. Here, one hop is assumed to be
set as the distance between the SDN Controller and
the DMM-AR.The Overall handover indicates the
number of networks that are involved in handover.
5.2 Simulation Results
5.2.1 Signaling Cost
Figure 6 shows the performance results of signaling
cost in the network over the time interval. We can
observe that when the MN moves far away from its
DMM-AR, the signaling cost is notably increased
because it is proportional to the number of switches
along the path from the source to the destination.
We can clearly see that our proposed S-PDMM
framework outperforms the other existing system in
terms of signaling cost. Compared with the (Javed,
2017), signaling cost is approximately reduced by
around 10%.
Figure 6: Signaling cost.
Our approach takes benefit from the wireless link
layer triggers to anticipate the next handover when
the MN changes its attachment.
IP flows are directly forwarded to the new DMM-
AR in a pre-established tunnel between the two
DMM-ARs before the new attachment and without
recourse to additional signaling messages exchange.
This act significantly reduces the signaling cost. In
conclusion, the low signaling cost makes the
proposed scheme more scalable in comparison with
other competing approaches.
5.2.2 Overall Handovers
Overall handover indicates the number of networks
that are involved in handover. Figure 7 shows the
simulation results for the overall handover process in
the network. It can be observed that our proposed
scheme reduces the overall unnecessary handover.
New Approach for Mobility Management in Openflow/Software-Defined Networks
31
Figure 7: Overall Handover.
Even in the cases of increasing load (number of
UEs); the overall handover has been minimized. This
result backs up the innate advantages of the combined
the IEEE 802.21 MIH functions with the proposed
SDN-based partially distributed MM, implied in our
framework.
6 CONCLUSION
In this paper, we have presented an SDN-based
partially distributed mobility management in cellular
and wireless networks. Our solution benefits from the
scalability and the flexibility provided by SDN and
DMM schemes. The proposed solution belongs to the
category of partially distributed mobility
management. The SDN Controller handles the control
plane in a centralized way, while, the DMM-ARs
manage the data plane in a distributed manner.
Moreover, we combined the IEEE 802.21 MIH
functions with the proposed SDN-based partially
distributed MM in order to incorporate QoS signaling
and mobility for the various technologies in the
network. Simulation results prove that our scheme
can guarantee a significant reduction of the number
of handovers and the signaling cost. As a future work,
we will introduce the OpenFlow v1.3.1 software in a
real testbed to better study the performance of the
proposed approach.
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