Dynamic Anchor Points Selection for Mobility Management in

Transcription

Dynamic Anchor Points Selection for Mobility Management in
Dynamic Anchor Points Selection for Mobility
Management in Software Defined Networks
Abbas Bradai, Kamal D. Singh, Abderrahim Benslimane and Toufik Ahmed
Abstract — Today consumers want to stay connected to
networking services anywhere and at anytime. Managing
consumers' mobility to ensure session and service continuity
in efficient and effective manner is more and more challenging
due to the increasing number of mobile devices and their high
mobility pattern. Different solutions have been proposed in the
literature to tackle this problem. They are based on a single
mobility management point, called mobility anchor.
Unfortunately, most of these solutions suffer from long packets
delivery delay and high overhead ratio. In this work, we
propose a new mobility management called Software Defined
Mobility Management (SDMM) based on the Software Defined
network (SDN) paradigm. The proposed solution is network
based, where the mobility is managed by network entities. In
opposite to existing approaches, the anchor point is
dynamically selected for each flow by a virtual function
implemented at the top of the SDN controller which has a
global view of the network. The main advantages of our
approach are threefold: first reducing packet delivery delay,
second reducing the handover latency and third minimizing
the tunneling overhead1.
convergence of networks to all-IP is inevitable due to several
benefits of all-IP such as reduced cost, efficiency, network
resilience, natural integration with Internet, etc.
The above scenarios and evolutions have also given rise to
new challenges that need to be tackled by the research
community. Challenges include QoS management when using
all-IP for different services such as VoIP and IPTV, mobility
management due to users wanting to remain connected
anywhere and at anytime and increasing network complexity
due to multitudes of services and growing number of network
equipment.
A. Motivations
In this paper we focus on mobility management, improving
performance in terms of packet delivery delay experienced by
the consumers and tackling network complexity to ensure
seamless user mobility from a network to another. Mobility
management focuses on assuring service continuity and
connectivity even when the user is mobile and changes
networks (Figure 1).
Index Terms — Mobility management, Handover, Latency,
Software Defined Network
I. INTRODUCTION
Today people want to remain connected to network services
anywhere and at anytime. This has led to explosive growth of
traffic in mobile and wireless networks. Moreover, this has
induced the convergence of network and services as all kinds
of services VoIP, IPTV, data, etc. are expected these days
from telecom as well as data networks.
Figure 1: Example of mobility management problem
Network infrastructures are evolving as well and all
networks are converging towards an all-IP network. The
Many mobility management mechanisms have been
proposed in the literature [1]. Some mechanisms have been
proposed by IETF such as Mobile IP (MIP), Mobile IPv6
(MIPv6), Proxy-Mobile IPv6 (PMIPv6), etc. These
mechanisms utilize IP tunneling and mobility anchors to
assure session continuity. The mobile user is able to keep its
IP address as the IP packet having the original IP address,
often called Home Address (HoA) is tunneled to the new IP
address which is often called the Care of address (CoA).
However, the use of mobility anchor means that all the traffic
related to corresponding mobile consumer has to pass through
same network equipment which leads to sub optimal routing,
1
Abbas Bradai is with the Grenoble Computer Science Laboratory (LIG),
38041 Grenoble, France (e-mail: [email protected]).
Kamal D. Singh is with Telecom Saint Etienne / Université Jean Monnet,
Saint Etienne, France (e-mail: [email protected])
Abderrahim Benslimane is with CERI – University of Avignon, 84911
Avignon Cedex 9, France (email: [email protected])
Toufik Ahmed is with CNRS-LaBRI University of Bordeaux, 33400
Talence, France (e-mail: [email protected])
1
knowledge, we are the first to introduce the dynamic
anchor points’ selection for mobility management.
increased delays experienced by the consumers and creation of
a networking bottleneck. Moreover, the increasing number of
mobile devices and their increasing mobility behavior are
making the management of mobility as well as management of
related network devices more and more complex and
challenging.
3) We prove that the problem of assigning switches to
different flows is NP hard and we propose a heuristic
algorithm to resolve it.
Unlike traditional approaches, our solution avoids single
bottlenecks and does not suffer from sub-optimal routing. This
leads to improved packet forwarding and load balancing
which results in improved performance experienced by the
user. This central approach significantly reduces the effort
required to configure a complex network and at the same time
improves upon the performance of traditional mobility
management mechanisms.
B. Contributions
In this work, we propose a mobility management scheme,
based on Software Defined Networking (SDN), to tackle the
today’s mobility management protocols problems. The
philosophy of software defined networking is to separate the
control and the data plane. The control plane is logically
centralized which controls the data forwarding elements in the
network using an open interface. SDN originated from the
need to solve the problem of increasing complexity of today's
networks which are hard to evolve and manage. The key to
solve the above problem is through the virtualization of the
network by hiding the detailed configuration process from the
network control. SDN is one of the ways towards the network
virtualization and it provides a flexible and centralized way to
configure the network elements.
C. Paper Organization
This paper is organized as follows. Section II provides the
state of the art, Section III provides the details of the proposed
SDN based mobility management solution, Section IV uses
simulation to provide the results and Section V concludes this
paper.
II. RELATED WORKS AND BACKGROUND
Our SDN based mobility management solution takes
optimal decisions related to establishing tunneling points in
the network. Thus, we propose Virtual Mobility Anchor
(VMA) functions and we use the SDN controller for optimal
creation of IP tunneling points in the network. SDN capability
is used to compile the above optimal configuration decisions
into network forwarding rules. The SDN controller sends these
rules to SDN switches which in turn implement them.
Mobility management is important for ensuring session
continuity when a mobile node changes its network
attachment point during handover.
Various
mobility
management
mechanisms
are
implemented in different protocol layers to target different
functionalities [2]. In the physical layer, mobility management
carries out the procedures of detach and attach to different
access points during handover. In the network layer, mobility
support deals with the change of the sub-network. Mobility
support in this layer may be based on routing (for example
used in Cellular IP [3]) or mapping (used in Mobile IP
(MIP) [4] and Proxy Mobile IP (PMIP) [5]). In the transport
layer, mobility management focuses on keeping the on-going
TCP connection, even though the IP address changes (for
example used in Mobile Stream Control Transmission
Protocol (M-SCTP) [6]). In the application layer, different
mobility management approaches are used which can be
specific to each application type (used e.g., in the Session
Initiation Protocol (SIP) [7]), or a middle-ware may be
implemented between applications of two nodes to manage
mobility, such as WiSwitch [8]. The network layer based
scheme is the most popular one offering transparent mobility
support to all kinds of applications. MIP [9], PMIP [10], and
3GPP mobility management [11], are examples of such
scheme.
In this work, we takes advantage of the global view of the
network provided by the SDN controller to optimally decide
the placement of tunneling points in the network, as a function
of optimal route to the mobile node and as a function of load
on prospective tunneling point routers for load balancing.
Our main contributions in this paper are as follows:
1) We propose a new architecture for user mobility
management. The proposed architecture relies on the
SDN paradigm, where the traditional mobility
management equipment, such as the mobility anchor
and the mobility access gateway, are virtualized.
Toward this goal, we introduce a set of virtual mobility
management functions implemented on top of the SDN
controller. These virtual functions, combined with SDN
switches, play the role of the different mobility
management equipment.
2) We model the problem of mobility management in
SDN based architectures as a problem of dynamic
selection of a set of switches, which will play the role
of anchor points, for a given set of flows. The selection
of anchor points should be optimal in such a way which
minimizes the packets delay and leads to load
balancing between the switches. To the best of our
In the network layer, the Internet Engineering Task Force
(IETF) has defined some IP mobility support protocols. In
general there are host based mobility management protocols
and network based mobility management protocols.
2
mobility management makes it more complex for deployment.
For host based mobility protocols, Mobile IPv6
(MIPv6) [11] [1] has been proposed for a single node mobility
support. In order to support mobility of a set of nodes Network
Mobility protocol (NEMO) [13] has been proposed by
extending MIPv6. With MIPv6 when a mobile node (MN)
changes its network during handover, it registers its new
address with a mobility anchor, home agent (HA). Then a bidirectional tunnel between the MN and the HA is established
for forwarding packets to the new location of MN. However,
the signaling cost between MN and HA is high, mostly has to
be done over the last mile wireless link and significantly adds
to the handover delay as HA can be far from MN.
Recently, many research works aiming to tackle the
limitations in centralized mobility management have been
proposed such as Distributed Mobility Anchoring
(DMA) [18], Double NAT (D-NAT) [19], Inter-domain
DMM, Local IP Access (LIPA)/Selected IP Traffic Offload
(SIPTO) [20]. In this context, Software Defined Networking
(SDN)/OpenFlow based approaches have been shown to
outperform existing solutions.
Thus, some approaches have been proposed to implement
existing mobility management protocols using software
defined networking framework. PMIPv6 implementation
using SDN is proposed in [21]. In this work, authors
implement the standardized mobility management PMIPv6
using SDN, where the PMIPv6 components are implemented
as virtual functions in the control plane, on the top of the SDN
controller. Indeed, the proposed mobility management
framework is composed of one switch which plays the role of
the Local Mobility Anchor (LMA) and several border
switches which play the role of the Mobility Access Gateways
(MAGs). Each one of these switches is associated to its
corresponding virtual function in the control plane. The
protocol executed in the control plane is the same executed in
the classic PMIPv6. If a mobile node moves from a switch
(SW1) domain to another switch (SW2) domain, the virtual
function MAG2 is notified by SW2 and handover procedure is
initiated. MAG2 sends a Proxy Binding Update (PBU)
message to the LMA which updates its binding cache, where
the mobile node becomes associated with MAG2. These
modifications are translated to forwarding rules pushed to
SW1. Thus a tunnel is created between SW1 and the LMA
switch and between the LMA and SW2. We note that authors
in this work do not take advantage of the global view offered
by the controller to enhance the performance of PMIPv6
performance. They only translate the protocol to the SDN
domain. Thus, the proposed solution suffers from the same
drawbacks of PMIPv6. They consider a single mobility anchor
which suffers from scalability problem as all control and data
traffic has to pass through a single point. The single anchor
becomes the performance bottleneck and single point of
failure. In addition the proposed solution suffers from the
problem of non-optimal routing. Moreover, an approach using
cloud computing to process the massive mobility management
data is left for future work.
To reduce the long delay of signaling messages exchanged
between a MN and a HA, Hierarchical Mobile IPv6 (HMIPv6)
was proposed and standardized by IETF [25]. HMIPv6 sets up
a local HA called Mobility Anchor Point (MAP), to handle
MN mobility while the MN is still in the local region. In
addition, in HMIPv6, a hierarchy of MAPs is set up in the
form of tree. If the MN leaves the domain of a local MAP,
then it will be assigned to the MAP’s parent in the tree
hierarchy and so forth. In this way HMIPv6 reduces the
handover delay and efficiently use the resources.
In more recent works, the distributed mobility
management [1] aims to reduce the distance between the MN
and the mobility anchor point. However, the selection of the
mobility anchor stays rigid and fixed while the MN moves
continually. This results in non-optimal routing, known as
“triangle routing” problem, as packets always have to pass
through the mobility anchor irrespective of the optimal route.
The network based mobility management approaches, such
as Proxy Mobile IPv6 (PMIPv6) [14]-[17] do not require a
signaling directly from the mobile nodes to a mobility anchor.
With PMIPv6, a MN does not register its location information
to a mobility anchor, called as a Local Mobility Anchor
(LMA), but the registration is done by a network element
called Mobility Access Gateway (MAG). MAG may be
implemented in an access router (AR). When the MN changes
its network then its movement is detected by the MAG
belonging to the new network. The MAG belonging to the
new network then sends the signaling message to the
Localized Mobility Anchor (LMA) to update the location of
the MN. LMA in turn establishes the bidirectional tunnel with
the MAG for forwarding the packets related to MN. Note that
here the tunnel terminates at MAG, instead to going till the
MN in the case of host based mobility management.
Compared to the host-based mobility support protocols,
PMIPv6 provides a better performance in terms of handover
latency and signaling cost [16].
Another work [22] uses SDN to implement PMIPv6.
However it only implements the MAG on the top of SDN
controller and other mobility management elements are not
considered. This paper just shows that the mobility
management can be done using the SDN paradigm without
any in depth study, and practical solution.
Nevertheless, the above mobility management approaches
are difficult to be deployed in real networks [16]. They usually
require new functions to be implemented or updated on
several network devices such as routers, servers and mobile
nodes. Additionally the signaling and overhead related to
Compared to the above two SDN based solutions for
mobility management, our proposed framework takes
advantage of the main feature of the SDN paradigm, namely
3
the programmability of the forwarding devices, and the global
view provided by the SDN controller. Indeed, the anchor
points in our solution are allocated dynamically in such a way
to respect the capacity of the different switches and to avoid
the non-optimal routing problem. We note that in our solution
one or more flows are assigned to a switch which plays the
role of anchor point for this (these) flow(s). In addition,
depending on the traffic load in the network, a flow
assignment to a switch can be dynamically shifted from one
switch to another to ensure low delay for the user and load
balancing between the different switches.
interface.
In this work, we are interested into specific network
functionality, namely Mobility Management (MM). We
investigate an SDN based solution to manage the mobility of a
Mobile Node (MN) and how to ensure the session continuity
while reducing the deployment complexity, reducing the
handoff delay and optimizing the resource utilization. In this
context, if we take the cellular network as a case study, the
mobility management methods such as PMIPv6 [14], can be
implemented by using SDN to establish tunnels between the
FEs. These tunnels are driven by the network application
which interacts with the Mobility Database (MD). In order to
manage MNs mobility binding and status information, the MD
needs to be centralized with a well-defined interface between
the mobility management network application and the MD.
We call this model a fully-separated mobile SDN with a single
controller. This approach allows high flexibility for data flow
management, rapid detection of network events and rapid
network response by enforcing and updating the relevant rules
in the FEs.
In the following section, we present in detail our
architecture for mobility management using SDN paradigm.
III. HOW SDN ARCHITECTURE COULD BE USED TO
ENHANCE IP MOBILITY?
Software Defined Network (SDN) is a new promising
network paradigm where control plane is decoupled from
forwarding plane, making the network forwarding elements
programmable and allowing a good abstraction of the
infrastructure [23]. A simplified SDN architecture is presented
in Figure 2, which is composed of virtual network
applications, a centralized control entity (Controller or CE)
and forwarding entities (switches or FEs).
A. System overview: Fully separated control plane
architecture
Figure 3 provides an overview of the proposed mobility
management framework based on the SDN paradigm. The
network topology in the figure corresponds to a single
Mobility Management domain which in turn corresponds to a
SDN domain. At the application layer, virtual machines are
running the mobility management protocol. Two virtual
functions are defined: the V_LMA function which, associated
with a FE, plays the role of Localized Mobility Anchor
(LMA), and the V_MAG function which, associated with
another FE, plays the role of Mobile Access Gateway (MAG).
In the example of Figure 3, V_MAG is mapped to two FEs,
MAG1 which is the initial point of attachment of the MN and
MAG2 which is the point of attachment of the MN after
movement. We call MAG1 as Home MAG and MAG2 as
Foreign MAG.
SDN is one of the first steps toward network virtualization.
Different network functions such as routing, Authentication
Authorization Accounting (AAA) and security functions can
be implemented as software functions. These functions use the
centralized controller to configure the programmable FEs
according to the needs of applications and network services.
We note that all the network switches are Openflow
enabled. OpenFlow is used to monitor the state of the network
and manage the network resources by enforcing the relevant
rules on the FEs involved in the packet forwarding of the flow.
In our solution, the Mobility Anchor point is flexibly
determined by the V_LMA based on routing optimality and
network load conditions of the forwarding elements. At the
end of this operation, an IP tunnel is established between the
LMA and the foreign MAG of the MN, in order to ensure the
continuity of the session for the MN even in its new position
(the MN keeps its initial IP address). Furthermore, thanks to
the Openflow protocol, link failure between the forwarding
elements can be rapidly detected and instantly reported to the
controller, and thus an alternative route and tunnel can be set
up.
Figure 2: SDN Architecture
The standard communication protocol in SDN is
OpenFlow [23], which allows communication between the
network applications and the controller through the interface
known as Northbound interface, and between the controller
and the FEs through the interface known as Southbound
4
Table I illustrates a simple example of flow tables in the
FEs to support mobility of the MN visiting the SW4’s area as
shown in Figure 3. If a packet is received at SW6 with
destination address as MN, SW6 encapsulates and forwards
the packet to MAG2 through port 2 (Rule 1 of SW6). When
receiving the packet, SW4 decapsulates it and forwards the
packet to the MN through port 2 (Rule 2 of SW4). A packet
sent by MN arriving at port 2 of SW4, is encapsulated and
forwarded to SW6 through port 1 (Rule 1 of SW4). When an
encapsulated packet arrives from SW4, SW6 decapsulates it
and forwards the packet through the packet path specified by
the routing protocol, through port 1 (Rule 2 of SW6).
TABLE I
EXAMPLE OF FLOW TABLES IN FORWARDING ELEMENTS
Flow table in SW6/LMA
Rule
1
Action
IP destination = MN,
incoming port = P2
stat
Encapsulate packet (From LMA
to MAG2)
Forward packet to port P1
Figure 3: System architecture overview
2
Packet encapsulated (From
MAG2 to LMA)
Decapsulate packet
Forward to port P2
IP source = MN
B. SDN Mobility Management protocol
…
In this work, we propose network based mobility
management mechanism using SDN, inspired from the
PMIPv6. Initially a MN, when connected for the first time to
the network via SDN switch (SW2 in the example of Figure
3), sends an ICMP router solicitation (RS) message to the
switch (SW2). This message is delivered to the V_MAG
function, which updates the Mobility Database (MD) and
associates the MN with the concerned switch (SW2). This
latter plays the role of the home MAG (MAG1).
Flow table in SW4/MAG2
Rule
1
IP source = MN, incoming
port = P2
Action
stat
Encapsulate packet (From MAG2
to LMA)
Forward packet to port P1
When the MN moves from the area of the initial switch
(SW2) to a new switch (SW4) area, the MN sends a RS
message to the new switch, called foreign MAG (SW4) which
delivers it to the V_MAG function. V_MAG updates the MD
and detects that the MN is in mobility. V_MAG sends then, a
mobility alert message to V_LMA, which selects the FE
which will play the role of the mobility anchor point, and sets
up a tunnel between the selected mobility anchor point and the
foreign MAG. We note that the mobility anchor point is
selected among the SDN domain’s FEs in the optimal path
from the source node to the home MAG, in order to intercept
the packets destined to the MN and forward them to foreign
MAG through a tunnel. The foreign MAG receiving the
encapsulated packets, decapsulates and forwards them to the
port from which the MN is connected.
2
Packet encapsulated (From
LMA to MAG2)
Decapsulate packet
Forward to port P2
IP destination = MN
…
In the following section, we detail our proposed mobility
anchor selection mechanism.
C. Mobility anchor selection
Mobility anchor selection is the main issue in mobility
management since it affects the handover performance and
network resource utilization. In contrast, our SDN-based
solution for mobility management proposes flexible anchor
selection and control as a function of optimal route, MN
mobility and varying network conditions.
The V_LMA’s instructions are translated, by the controller,
into OpenFlow rules. These rules are immediately installed to
the new LMA (SW6) and the foreign MAG (SW4) through
OpenFlow protocol.
In our solution, as mentioned in section III.A, the anchor
point (LMA) is selected among the FEs situated in the optimal
5
path between the corresponding node (CN) and the home
MAG (Figure 4), in order to intercept the packets destined to
the MN, encapsulate and forward them to the foreign MAG.
Besides, the mobility anchor point is selected in such a way to
balance the load between the FEs and reduce the packets
delivery delay between the MN and the CN. In the next
section, we detail the mobility anchor selection mechanism in
our solution, ensured by the V_LMA function that we
propose.
, a Boolean variable that indicates whether the switch i is
the anchor point for the flow j:
1
0
if switch is anchor point for flow ,
otherwise.
We also define the variable which represents the delivery
cost of a packet from the tunneled flow j, when switch i is the
anchor point.
In IP networks, the packet delivery cost is the sum of the
transmission cost and the processing cost. The transmission
cost is related to the hop distance from the source node to the
destination node. While the processing cost is related to the
packet processing, such as routing table look up, routes
calculation, etc. In the context of SDN based networks, the
routing algorithm is executed at the application level and
forwarding rules are mapped into the forwarding elements
which are layer 2 equipment. Thus the routing table lookup
and route calculation cost in FEs is insubstantial. We can
argue then, that the packet delivery cost in SDN based
architectures can be approximated by the packet transmission
cost.
Figure 4: Example of anchor point selection problem
Thus, we can set:
D. Problem formulation and modelling
(1)
The V_LMA function is responsible for establishing LMA
for each tunneled flow in the network. The function of
V_LMA is to select a set of switches in the network to play
the role of a mobility anchor and perform the tunneling of the
flow to the MNs. This function is called each time when a new
anchor node is requested in the network. Then, V_LMA
dynamically selects the optimal anchor point. We note that the
anchor point for a certain flow can change dynamically after
each selection round.
Where:
: The packet transmission cost from the source to the
anchor point in the flow j using the anchor point i.
: The packet transmission cost from the anchor point i to
the destination, which is the number of hops from the anchor
point to the MN’s foreign MAG. The path to the foreign MAG
is already computed using the routing protocol adopted in the
network.
The anchor nodes are selected in such a way to reduce the
overall packet delivery cost while considering optimal routes
as well as the processing and bandwidth capacity of the
switches.
We now present the core of our anchor points’ selection
heuristic. Using
as defined in (1), we propose the
aggregate priority Π of the network as follow:
In this work, we assume that an admission control
mechanism is performed at the foreign MAG, in such a way
that the MAG is able to process all the encapsulated packets
and its bandwidth is sufficient to support the accepted mobile
nodes. This way the problem lies solely in the selection of
LMA nodes. We also assume a routing protocol running in the
network, which provides the optimal route and performs load
balancing in order to avoid bottlenecks and avoid the packets
loss. Thus the problem of mobility anchor node selection can
be reduced to an assignment of a set of LMAs jobs (tunneling
functions) to a set of switches while taking into consideration
the processing capacity (encapsulation) and the available
bandwidth of the different switches. The main goal is to
optimize the over-all packet delivery delay and reduce the
packet loss rate.
%
Π
"
!!
#$ #$
(2)
Subject to:
"
!&
#$
' ( , ∀ ∈ +1, ,-
(3)
and
%
!
For our mobility anchor point selection solution, we define
6
#$
' 1 , ∀ ∈ +1, .-
(4)
knapsack capacity as the switches capacity and the item set as
the set of flows (Figure 5). Also
and & can be regarded as
the profit and weight of items, respectively. Therefore, for
each switch (knapsack) a set of flows (items) should be
assigned with regards to the switch capacity and the flow size,
while maximizing the profit, i.e. reduce the overall packet
cost. In MMKP all the components of the problem including
knapsack capacity, items, profits, etc. are known and the
question is which items to put in the knapsack. Similarly in the
SDMM, the only unknown in equations (2)-(4) is the decision
variable . & is the flow capacity in terms of processing and
bandwidth, which is in turn known, ( is the capacity of the
switch and it is also known, and
is computed as in (1).
Therefore, SDMM is a type of Multi-choice Multidimensional
Knapsack Problem and its NP-hardness of it follows by a
trivial transformation from the MMKP.
Where:
-
S is the number of switches available in the
network
-
F represents the number of flows generated by
mobile nodes
& represents the processing capacity allocated
from the switch i to the flow j if the switch i is
selected as anchor point for the flow
-
-
Pi represents the switch i processing capacity, in
term of packets encapsulation, per time unit.
The condition (3) ensures that the processing capacity of
each switch is not violated, while the condition (4) ensures
that each flow is processed by at most one anchor point.
We note that =∞ if the switch i is not an anchor point
candidate for the flow j. We remember that a switch i can be
an anchor point for the flow j if it is in the initial path from the
CN to the home MAG of the MN (see Figure 4).
Flow
Flow1
Switch
E
$
…
…
…
…
;<=
Subject to
@
?=
@
…
! ! >0 50 ' 1
#$ 0#$
?=
! >0
0#$
A … BC
A … DC >0
A
E
E
…
E
?G$
…
E
?
…
Flowm-1
Flowm
FG$
$
FG$
E
…
FG$
?G$
FG$
?
F
$
F
E
…
F
?G$
F
?
Figure 5: SDMM modeled as MMKP problem
IV. SEARCH ALGORITHM FOR ANCHOR POINTS’ SELECTION
To solve MMKP there exist two approaches: exact and
heuristic. Exact solution is based on branch-and-bound [25].
The computational complexity of these algorithms is
J
H(27 @ ). Therefore, branch-and-bound linear programming
approach (BBLP) is often too slow to be useful [28]. An
alternative is to use heuristic approach. There are some
heuristic algorithms in the literature like the ones in [29]
and [30]. In this paper we propose a sub-optimal heuristic
algorithm based on [30], with reasonable computational
complexity. In [30] it has also been shown that in almost all
trials the achieved solution is very close to the optimal
solution.
By introducing Lagrange multipliers, authors in [31] show
that the solution for the optimization problem (2) under the
constraint (3) is equivalent to the solution of the following
problem:
(6)
C
$
?
SWn
(5)
#$ 0#$
$
?G$
SWn-1
?=
! ! >0 /0
$
E
SW2
Proof: We show that the anchor points’ selection can be
modelled as the Multi-choice Multidimensional Knapsack
Problem (MMKP), which is known to be NP-hard [27]. An
MMKP is the problem where there is an M-dimensional
knapsack with M total allowable volumes of Wl, W2, ..., WM
and there are N groups of items. Group j has nj items. Each
item has a value and M volumes corresponding to knapsack’s
M dimensions. The objective of the MMKP is to pick up
exactly one item from each group while maximizing the total
value of the selected items, subject to volume constraints of
knapsack’s dimensions. In mathematical representation, let
22230
/0 be the value of the kth item of the Jth group, 1
th
(50 $ … 50 7 ) be the required volume of the k item of the
2223
jth group corresponding to M dimensions, and 1
(1$ … 17 ) be the volume constraints of different knapsack’s
dimensions. Then the problem is:
…
$
$
SW1
Theorem: The anchor points’ selection in Software Defined
Mobility Management (SDMM) is NP-hard.
Flow2
%
"
K! !
#$ #$
(7)
SDMM can be mapped to MMKP by regarding the
7
%
%
"
− ! λ0 ! ! &
0#$
#$ #$
N
(8)
Subject to:
%
"
!!&
#$ #$
∗
%
"
'!!&
∗
#$ #$
are satisfied. Since each flow always has an item whose value
and M-dimension volume are zero the solution is always
feasible.
(9)
After completion of the Progress phase, there may be some
space left in the switches. This space may be utilized to
improve the solution by replacing some selected flows with
more valuable ones. Therefore, in Adjustment phase, each
item k of every flow j is checked against the selected flow of
_^
that switch ]
is the optimal solution. Therefore, the
Where the
∑%#$ ∑"#$ & ∗ corresponds to the optimal capacity of the
switches used by the optimal solution. Therefore, if the
Lagrange multipliers λ0 are known, the optimization problem
is easily solved. By a simple manipulation of the equations,
the equation (8) can be written as:
%
%
"
KQ! !
%
"
− ! λ0 ! ! & R
#$ #$
0#$
#$ #$
N
It is verified whether item k is more valuable than the
selected item, and if k can replace the selected item without
violating the volume constraints. Among all exchangeable
items, the item ]′of flow j' causing the largest increase of the
switch value is exchanged with the selected item of that flow
i
]
^h . This process is repeated until no more exchanges are
possible. It can be shown that the complexity of the algorithm
is H(.E , E(,
)).
(10)
This implies that the solutions are:
∗
S
T
%
− ! λ0 & >
0#$
VWℎYZ5 [Y
(11)
Algorithm 1: An heuristic for flows allocation in the switches
I- Initialization
λ0 ←
Since we have another constraint in equation (4), among
the possible solutions, we have to find the one which satisfies
(4) and is optimal at the same time. Therefore, the only step to
do is to compute the Lagrange multipliers λ0 . It is worth
noting that if these multipliers are computed such that the
terms
%
"
P −!!&
#$ #$
…,
_
]
and R m_ ← ,
& ← & o(
( ← ∑"#$ &m_
∗
…,
n
n
….
….
II. Progress Phase
While (( >
are non-negative, the solution is feasible. The algorithm is
given in algorithm 1, which is executes in three steps:
Ia
In the Initialization step, the algorithm starts with the most
_^ ), i.e.,
valuable switch of each flow j as the selected switch (]
the switch which maximize the utility of the flow j. The
Lagrange multipliers are initialized to zero such that the
constraints in (11) and (3) are satisfied.
A( C
_
for b |]
)
Iad
∆0
In general, however, the switch capacity constraints will
now be violated, the initial choice of selected switches is
adapted to satisfy the switches capacities by repeatedly
improving on the most violated capacity constraint `a, as
follows.
end for
v
∗ ∗
λfa
In the Progress phase, consider the flows whose selected
_^
items correspond to switch `a (i.e. b |]
`ad ). For each item k
of these flows, the increase ∆ of multiplier λfa that results
from exchanging the selected item of flow j, is computed.
Eventually, the item k* of flow j* causing the least increase of
multiplier λfa is chosen for exchange. This choice minimizes
the gap between the optimal solution and the solution returned
by SDMM algorithm. The process is repeated until an item has
been selected for each user such that the capacity constraints
∗
_ =∗
m
∗
0∗
(sa
(0 ∗
end for
λfa
∆0 ∗
∗
b ∆0 d
_ ∗ ← ]∗
, i.e. ]
(0 ∗
End while
8
0
(sa − &ss_t
a
s_
s_
(rfa − r0 − λfa (&fa t − &00= ))/&fa t
for k=1 to S
&0 ∗
∗
III- Adjusting phase
While ∃ jϵ+ F- ∃ kϵ+ S-
~0 >0 and ~0 ≥ r0
for j=1 to F
for k=1 to S
r −
€ 0
~0
number of hops traversed by these messages and the size of
mobility signaling message. For the SDN based architecture,
the signaling cost is the number of packet exchanged with the
controller.
r0 −
•=
0
•=
0
>
(0
Packets tunneling cost: is the total traffic overhead caused
by the tunneling. It is calculated as the product of the hop
distance of the tunnels and the size of the tunneling.
&00= '
Total cost: is the sum of the packet delivery cost and the
packet tunneling cost
end for
end for
vh
h
(0•=ƒ
(0h
h
0h
A~0 C ,
0
(0•=ƒ − &0•h
(0h
&0•
h
=ƒ
=ƒ
Handover latency: is the delay introduced due to the
handover operation. It is the delay from the moment when MN
or the MAG starts the handover procedure to the moment
when the MN receives the first packet in its new network.
v
We also define the Session to Mobility Ratio (SMR) as the
ratio between the session length in packets and the MN
mobility which is the number of times the MN changes its
network.
h
• =ƒ
0
B. Simulation parameters
We consider the access router's coverage area as a circle
with radius R, and the MN is moving with a velocity V [27].
The session generation rate is λ, the session size is S, and the
average packet size is p. In Table II, we summarize the main
simulation parameters and their values. The unit cost is
calculated as the product of message length and hop distance,
and its unit is Kbytes * hops.
End While
V. PERFORMANCE EVALUATION
In this section, we present a comprehensive comparison
study of our mechanism for mobility management called
SDMM (SDN based Mobility Management). We compare the
performance of SDMM against two pioneering mobility
management mechanisms, namely PMIPv6 [4] and
HMIPv6 [24], as well as another SDN based mobility
management (SDN-PMIPv6) mechanism [21]. For evaluating
SDN based protocols, we use mininet tool [32] to emulate the
network connected to OpenDaylight controller [33] for the
implementation of V_MAG and V_LMA functions [23]. To
connect the OpenDaylight controller to the switches, we select
openFlow 1.0.
TABLE II
SYSTEM PARAMETERS AND VALUES
A. Comparison metrics
We consider the following metrics for evaluating and
comparing our proposed mechanism [26]:
Parameter
Value
Radius (R)
[400, 800] m
Velocity (V)
[0, 30] m/s
Session generation rate (λ)
[0.1, 1]
Session size (S)
10 packets
Average packet size (p)
1 Kbytes
Tunneling overhead (ω)
40 bytes
C. Results and discussions
In this section, we present the most important results
pertaining to our evaluation of SDMM through simulations.
Packets delivery cost: is the total traffic overhead caused by
the delivery of packets from the corresponding node (CN) to
the Mobile Node (MN). It is calculated as the product of the
overhead, in terms of hops between the CN and the MN, due
to the mobility, and the data packet size. This metric also
reflects the packet delays experienced by the consumer as the
packet delays are related to the hop distance.
1) Packet delivery cost
Figure 6 shows the comparison of packet delivery cost with
respect to different session arrival rates for the four mobility
management mechanisms. We note that the access routers
radius is set to 500m and the MN velocity is set to 20m/s. The
average distance between the MN and the CN is 10 hops.
Signaling cost: is the total mobility signaling overhead for
supporting MN mobility. It is calculated as the product of the
It can be remarked that in general the packet delivery cost
9
two nodes. While the packet delivery cost increase in the case
of SDMM is nearly linear, the packet delivery cost increases
exponentially with the number of hops between MN and CN
in the case of PMIPv6 and HMIPv6. We explain this by the
fact that in PMIPv6 all the packets pass by the central anchor
point, which consequently increases the distance between the
MN and the CN and also results in non-optimality of the route.
In the case of HMIPv6, when the distance is long between the
MN and CN, the tunneling function is assigned to higher level
anchor point in the hierarchy. Consequently, the route between
the MN and the CN becomes longer, which in turn increases
the delivery cost.
increases with the session arrival rate. However, we can see
that SDMM outperforms the three other mobility management
mechanisms. We explain this by the fact that for selecting the
mobility anchor point for each MN's flows, SDMM optimally
selects the nearest switch to each MN (utility function of the
assignment problem in 3.3). This minimizes the number of
hopes that the packets take to reach MN, which in turn reduces
the packet delivery cost.
In the case of intra-domain communications, such that the
SDN controller controls the whole domain containing both the
MN and the CN, a direct tunnel is created between the MN
and the CN in SDMM. This results in minimum number of
hops as the tunnel passes through the shortest path, between
the MN and the CN, determined by the already running
routing protocol. On the other hand, in PMIPv6 and SDNPMIPv6, a single, often non-optimal, anchor point is used and
all the packets pass through it. The non-optimal anchor point
may not lie in the shortest path and this leads to non-optimal
routing and consequently high packet delivery cost.
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2/..
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8
=
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8 1...
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9
8
7
6 0/..
5
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0...
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.
/
Now, we fix the session arrival rate to 0.2, and we also fix the
radius to R=500m. We vary the velocity of the mobile node
from 5 to 30 m/s, and we measure the signaling cost for each
velocity value. The obtained results of the four protocols are
shown in Figure 8.
)&*) +,
Firstly, we note that the signaling cost increases with the
increase in the velocity of the MNs. Indeed, faster moving
MNs, lead to more handovers and consequently to more
exchanged signaling messages.
1.
2) Signaling cost
-& *)+,
0/
Figure 7: Packet delivery cost Vs. average distance between
MN and CN
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0.
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We note also that HMIPv6 outperforms the PMIPv6 in terms
of packet delivery cost, and we explain this by the fact the
HMIPv6 allocates a set of local mobility anchor points close
to the MN, which results in shorter route from the MN to the
anchor point and from the anchor point to the CN, and vice
versa. Consequently the packet delivery cost is lower in
HMIPv6 than in PMIPv6 and SDN-PMIPv6. However, in
some case the disposition of anchor points in HMIPv6, in a
rigid form of a tree, leads to non-optimal routing. This is why
HMIPv6 has lower performance as compared to SDMM.
WXZ[\ Y]\^_
9
Secondly, we note that the SDN based protocols (SDMM and
SDN-PMIPv6) have lower signaling cost as compared to the
traditional protocols (PMIPv6 and HMIPv6). This can be
naturally explained by the virtualization of the mobility
management functions (MAG, LMA) in SDN-based protocols.
Thus, the mobility signaling messages in this case are
exchanged between the switches and the controller (one hop),
rather than between the MN and the MAP in the case of
HMIPv6 or between the MAG and the LMA, which may be
far from each other in the case of the PMIPv6 protocol.
!"
#
Figure 6: Packet delivery cost Vs. session arrival rate
We fix now the session delivery rate to 0.5 while varying the
average number of hops between the MN and the CN. By the
number of hops, we mean the hops existing in the shortest
path between the two nodes. The obtained results are shown in
Figure 7.
Moreover, we note that SDN-PMIPv6 has low signaling cost
than SDMM. We explain this by the fact that SDMM
dynamically selects the anchor points and in each case of
context modification (mobility of a node) all the optimal
anchor points are recomputed using algorithm 1, and the new
rules are pushed to all the concerned switches. However, in
We note in Figure 7 that the packet delivery cost increases
with the distance between the MN and the CN. This is
explained by the fact that the increase in the distance between
the MN and the CN results in the number of hops between the
10
the case of the SDN-PMIPv6, only one switch plays the role
of anchor point and in case of node mobility only the initial
MAG switch and the new MAG which are affected. They
receive new rules from the controller. However, this slight
signaling overhead in SDMM as compared to SDN-PMIPv6
can be justified by the better performance of SDMM in terms
of delay and packets delivery cost (see Figure 8)
!"##
!"$%&#'&()
&#'&()
*#'&()
This results in tunnels of small length in terms of number of
hops. We also note here that there is no difference between the
SDN-PMIPv6 and PMIPv6 since the same mobility anchor
point is adopted in both mechanisms. The packet tunneling
cost is also higher in HMIPv6, because the anchor point in this
mechanism is selected in order to reduce the frequency of MN
switches between anchors, regardless of the MN-Anchor
distance.
.2+
@8
./+
.++
;
;
;9
:
4+
@7
2+
?>
=7
-
JKLL
JKMNOLPOQR
OLPOQR
SLPOQR
.1+
@X
>W
<
V
1+
/+
+
+
+T.
+T/
+T0
+T1
+T,
+T2
YCIIGZ[ EDDG\E] DE^C
+T3
+T4
+TU
.
Figure 8: Signaling cost Vs. MN velocity
Figure 10: Packet tunneling cost Vs. Session arrival rate
In the following scenario we fix the velocity = 20 m/s and we
vary the access switch/router radius from 400 to 800m, and we
study the signaling cost for the four protocols. The obtained
results are represented in Figure 9. We note that the access
routers radius has the opposite impact of the signaling cost
than the velocity. Indeed, we note that the signaling cost is
inversely proportional to the radius. High access router radius
leads to less handovers and consequently low signaling cost.
1,
In order to measure the impact of average number of hops
between the MN and the CN, on the packet tunneling cost, we
fix the session arrival rate at 0.5 and we vary the distance
between the MN and the CN from 5 to 20 hops. The results
are shown in Figure 11. We note that similar to the delivery
cost (see Figure 7), the packet tunneling cost also increases
linearly with the increase in the distance between the MN and
the CN in the case of SDMM, and exponentially in the case of
the other protocols.
JKLL
JKMNOLPOQR
OLPOQR
SLPOQR
1+
@8 0,
>? 0+
:
/++
@8 .2+
=
< /,
;
9:8
7
65
JKLL
JKMNOLPOQR
OLPOQR
SLPOQR
.4+
;9
?>
: .1+
;9
=7 ./+
/+
;
.,
;
@X .++
@7
.+
>W
4+
<
,
V
+
1++
1,+
,++
,,+
2++
2,+
ABC DEFGHI
3++
3,+
2+
1+
4++
/+
+
Figure 9: Signaling cost Vs. radius
,
3) Packet tunneling cost
.+
.,
_\CDE`C [HabCD Zc BZdI bC^eCC[ fg E[F hg
/+
Figure 11: Packet tunneling cost Vs. distance between MN
and CN
In Figure 10, we plot the evolution of the packet tunneling
cost while increasing the session arrival rate from 0.1 to 1. We
can see clearly in the figure that the tunneling cost is
significantly low in the case of SDMM. We explain this by the
fact that in SDMM, the anchor points are selected such that
they lie topologically near to the foreign MAG (corresponding
to the new position of the MN), thus, the anchor point is
selected in such a way to reduce the packet transmission cost.
4)
Handover latency
We measured the handover latency experienced by the
mobile devices of the consumers in the case of four mobility
management mechanisms and we show the results in Figure
12. We note here that the latency is notably higher in PMIPv6.
This is due to the delay introduced by the signaling messages
11
exchanged between the MAG and the LMA in order to update
the binding between the MAG and MN, when the MN moves.
These messages are absent in the case of SDMM and SDN,
because the binding updates are done at the network
application level and no messages are exchanged between the
MAG and the anchor node. We also note that the handover
latency is low in HMIPv6 because the anchor point is selected
dynamically to reduce the association between the MN and the
anchor node.
#$%%
#$&'(%)(*+
(%)(*+
,%)(*+
Using SDN concepts our mobility management mechanism
dynamically selects the appropriate mobility anchors which
tunnel the packets towards the new locations of mobile
devices and assure the session continuity of consumers even
during mobility. Our solution selects the nearest anchor point
for each mobile node and ensures load balancing in the overall
network. We modeled this problem as an assignment problem
of a set of flows to a set of anchor points, and then we
proposed a solution to this problem. The obtained results
outperform the pioneering mobility management mechanisms
existing in the literature. Indeed, the proposed mechanism
ensures the session continuity with very low handover latency,
the key performance metric when a consumer moves from one
network to another.
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"
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1 !
Figure 12: Handover latency Vs. wireless link delay
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Total cost
In Figure 13, we study the impact of the session length over
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SDN-PMIPv6 because the anchor point selection method is
same in both the protocols. Nevertheless, the guain of SDNPMIPv6 approach can be measured in terms of gains in other
performance metrics such as latency thanks to the SDN
approach.
32-30-3/-3.-8<
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98
76
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EFGG
EFHIJGKJLM
JGKJLM
NGKJLM
/-.-4
3-
34
.-
.4
5=>? @ABCD
54
/-
/4
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In this paper, we proposed a new mobility management
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12
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Applications, 2014.
Abbas Bradai received his M.S in Computer
Science from National Institute of Computer
Science (ESI ex-INI), Algiers, Algeria, and from
university of Rennes1, France in 2009, and his
PhD at LaBRI/University of Bordeaux-1, France,
in 2012. He is actually assistant professor at
university of Grenoble and research fellow at LIG
lab, Grenoble. His main research interests are multimedia
communications over wired and wireless networks, cognitive radio,
software defined network and virtualization. Abbas Bradai is/was
involved in many French and European projects (FP7, H2020) such
as ENVISION, VITAL, Data-Tweet.
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operator control of selected IP traffic offload,” Communications (ICC),
2011 IEEE International Conference on. IEEE, 2011. p. 1-5.
Kamal D. Singh obtained his PhD degree in
computer science from University Rennes 1,
France in 2007. He then worked as a post doc in
the Dionysos group at INRIA, where he codeveloped many components of Quality of
Experience estimation tools and worked mainly on
the analysis of video-based applications. He is
currently an associate professor at University of Saint Etienne /
Telecom Saint Etienne, France. His research interests include Quality
of Experience, Video streaming, Software Defined Networking, Big
Data and Semantic web.
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Proceedings of the 8th International Conference on Ubiquitous
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Norm for Networks,” White Paper, 2012.
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Rexford, et al., “OpenFlow: enabling innovation in campus networks,”
ACM SIGCOMM Computer Communication Review, 69-74, 2008.
[24] S. FANG, “LTTMAP Fast Handoff Scheme of Advancing Hierarchical
Mobile IPv6,” Applied Mechanics and Materials. 2014. p. 6375-6378.
Abderrahim Benslimane is Full Professor of
Computer Science and Engineering at the
University of Avignon (France) since September
2001. He has been as Associate Professor at the
University of Technology of Belfort-Montbliard
since September 1994. He obtained the title to
supervise researches (HDR 2000) from the
University of Cergy-Pontoise, France. He received the PhD degree
(1993), DEA (MS 1989) from the Franche-Comte University of
Besanon, and BS (1987) from the University of Nancy, all in
Computer Science. His research and teaching interests are in wireless
ad-hoc and sensor networks. Particularly, he works on multicast
routing, inter-vehicular communications, Quality of service, energy
conservation, localization, intrusion detection and MAC layer
performance evaluation. He was also interested in specification and
verification of communication protocols, group communication
algorithms and multimedia synchronization. He has several refereed
international publications (book, journals and conferences) in all
those domains.
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[32] http://mininet.org/overview/
Toufik Ahmed is currently a professor at
ENSEIRB-MATMECA school of engineers in
Institut Polytechnique de Bordeaux (IPB) and
performing research activities in CNRS-LaBRI
Lab-UMR 5800 at University Bordeaux 1. T.
Ahmed’s main research activities concern Quality
of Service (QoS) management and provisioning
for multimedia wired and wireless networks, media streaming over
P2P network, cross-layer optimization, and endto-end QoS signaling
protocols. T. Ahmed has also worked on a number of national and
international projects. He is serving as TPC member for international
conferences including IEEE ICC, IEEE GlobeCom.
[33] http://www.opendaylight.org/
13