User-Adaptive Vertical Handover Scheme Based on MIH for Heterogeneous Wireless Networks Fu Jiadi , Ji Hong , Li Xi Key Lab of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications Beijing, P.R.China Emails:
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[email protected] Abstract—Mobile terminals have to accomplish vertical handovers among heterogeneous networks for the purpose of realizing seamless roaming and guaranteeing Quality of Service (QoS). Media Independent Handover (MIH) mechanism defined by IEEE 802.21 standard is a possible approach to this problem. In this paper, we propose a novel user-adaptive vertical handover scheme based on MIH in UMTS, Wi-Fi and WiMAX networks. It follows user-adaptive principles in which a user’s QoS demand is taken into consideration in both handover initiation and decision making procedures. We define two kinds of handover triggers caused by unfulfilled QoS requirements or deteriorating wireless channel conditions. Compared with classical Multiple Attribute Decision Making (MADM) methods, a more flexible selection criterion to choose the network providing proper QoS according to a user’s need is designed and discussed. The simulation results show that the proposed scheme provides smaller handover times and better QoS than the basic vertical handover scheme. Keywords-media independent handover handover; heterogeneous wireless networks
I.
(MIH);
vertical
INTRODUCTION
The rapid increase of mobile terminals and access technologies makes it possible to provide users with better applications and seamless mobility services. Interoperability and seamless roaming among heterogeneous networks are key points to achieve these goals. Integrated IP network architecture applies possibility for communications between different networks. The development of multi-mode terminal enables more flexible network accesses and works as the foundation for the realization of seamless roaming. Traditional horizontal handover decision is made on the base of received signal strength, which is not suitable in heterogeneous networks because of their unsymmetrical characteristics. Vertical handover schemes have become hot focus in the relative research fields. Existing research results suggest some modifications in the underlying network architectures to realize vertical handover. The most widely recognized method is to add a Media Independent Handover (MIH) entity above link layer, which is proposed by IEEE 802.21 working group [1].Many approaches have been proposed based on MIH handover process. In [2] authors design a handover decision algorithm using MIH services with QoS provision in Wi-Fi and WiMAX
networks. In [3], authors address the integration of IEEE802.11 WLANs and IEEE802.16 WMANs, focusing on the handover management aspects. However, the definition of trigger mechanism is not addressed in these approaches. Meanwhile, various Multiple Attribute Decision Making (MADM) methods have been applied in handover target network selection. A classical fuzzy MADM method is proposed in [4] to deal with the imprecise information of some criteria and user preference. In [5], authors propose an adaptive multi-criteria vertical handoff decision algorithm. However, most MADM algorithms choose the network providing best service without considering the users’ QoS demands and the balance between single user performance and network resource usage. In [6], authors propose selecting an appropriate network instead of the best one based on basic MADM method but the selection criterion is not efficient enough to select the most proper one. In this paper, a user-adaptive vertical handover scheme based on MIH function is introduced. The main advantages include: (1) Handover triggers are generated not only from link layer but also from application layer, which enables users to initiate handovers according to the link conditions and their QoS requests. (2) We propose an improved MADM method in which a network providing users with enough QoS guarantee according to their real needs is selected as target network. The proposed method can make better use of network resources. The rest of paper is organized as follows: the MIH architecture is introduced in section II. Section III describes the proposed MIH based handover decision scheme in details. The simulation model and simulation results are presented in section IV. Finally, section V concludes the work in this paper. II.
MEDIA INDEPENDENT HANDOVER FUNCTION
IEEE 802.21 (Media Independent Handover) [1] intends to provide link layer intelligence and other related network information to upper layers for optimizing handovers among heterogeneous networks. The central part of the 802.21 framework is MIH Function (MIHF) which is added between network layer and link layer. It gathers link layer related information and notifies upper layer of the link characteristics. Fig. 1 shows the location of MIHF within the protocol stack of a mobile node or a network entity.
This work is jointly supported by the National Natural Science Foundation of China under Grant 60832009 and the National Hi-Tech Research and Development Program (National 863 Program) under Grant 2007AA01Z221 and Grant 2009AA01Z211.
978-1-4244-3693-4/09/$25.00 ©2009 IEEE
link layers. However they don’t give specific ways of implementation. In our scheme, new decision factors and related trigger events are defined from link layer as well as application layer which is closer to users. •
The first trigger is generated from application layer when QoS is not fulfilled by current network. This trigger can be caused by the change of user preference, the lack of better choices when that application started or the loss of resources in the serving network. Users can initiate handovers actively according to their service demands and the actual performances. Users whose QoS are not satisfied can start a handover initialized stage to check if there are better networks to access, which can be done periodically in order to save mobile nodes’ battery. This operation can provide users with better services and take advantage of different network resources.
•
The second trigger is Link_Going_Down event which indicates that a link layer connection is predicted to go down within a certain time interval. When a user has received a Link_Going_Down event with a high confidence level, for example more than 80%, a handover is supposed to be triggered.
Figure 1. MIH services and their directions.
Since the MIHF provides services to the MIH users through a single media-independent interface, it prevents upper layer from knowing the details of access technology and facilities seamless handovers. The IEEE 802.21 standard defines three kinds of service that enhance handovers between heterogeneous access links. A. Media Independent Event Service (MIES) This service provides event definitions and event reporting according to dynamic changes in link quality. Some of the events that have been specified by IEEE 802.21 are "Link Up", "Link Down", "Link Detected"," "Link Parameter Reports" and "Link Going Down".
When MIH user has received handover triggers, it will start to collect relevant information including channel range and geographical location of candidate networks from MIIS server. After receiving response from MIIS server, the mobile node switches on its related interfaces and starts listening to broadcasting messages on specific channels that are presented in response and then records the signal strengths.
B. Media Independent Command Service (MICS) This service enables MIH users to manage and control link behavior relevant to handovers and mobility. The higher layers may control the reconfiguration or selection of an appropriate link through a set of handover commands.
In order to provide required QoS, many attributes should be taken into consideration. In this paper, we choose price, delay, jitter, SNR and available data rate as the typical QoS attributes and suppose price, average delay, jitter and available data rate can be attained using MIIS from serving access point while SNR is measured by mobile node itself. Price is related with different kinds of network, UMTS is the most expensive, WiMAX is the second one and WLAN is the cheapest. However, since the 802.11 mac layer adopts CSMA/CA protocol, the available bandwidth can be approximated using the time in which the channel status is busy and the NAV duration for a successful frame Transmission as described in [7].
C. Media Independent Information Service (MIIS) This service provides details on the quality of service provided by the serving and neighboring networks. Mobile nodes can get relevant information by communicating with MIIS server. Additionally or alternatively, the neighboring network information discovered and obtained by this framework and mechanisms. III.
USER-ADAPTIVE VERTICAL HANDOVER SCHEME BASED ON MIH
There are three stages during a handover process: handover initialized stage, network selection stage and handover execution stage. The proposed scheme mainly focuses on the first two stages. A. handover initialized stage In the handover initialized stage, MIH users obtain trigger events and relative information. IEEE 802.21 working group defines several events acting as triggers to facilitate handover,. For example, MIES provides measurements and triggers from
B. network selection stage Now the mobile node has enough information about the surrounding networks to take an evaluation on the target network, a decision matrix can be generated. Suppose there are four networks available, the decision matrix is shown as below.
d 4×5
⎛ d11 ⎜d 21 =⎜ ⎜ d 31 ⎜ ⎝ d 41
d12
d13
d14
d 22
d 23
d 24
d32
d 33
d 34
d 42
d 43
d 44
⎞ ⎟ d 25 ⎟. d 35 ⎟ ⎟ d 45 ⎠ d15
(1)
g = 0.7 * 0.8 + 0.3 * 0.1 = 0.59 .
d ij in (1) denotes the values of the QoS parameter j provided by the ith available networks. Matrix d '1×5 = ( d1 ' d 2 ' d 3 ' d 4 ' d 5 ' ) expected QoS parameter values of users.
The overall score of network 1 is describes
the
The normalized preferences, i.e. the weighting factors for
g1 = 0.7 * 0.5 + 0.3 * 0.85 = 0.605 .
j =1
are involved in decision matrixes or weighting factors, they should be transferred to crisp numbers first using the method described in [4].
⎛ d '1×5 ⎞ = ⎜ ⎟ ⎝ d 4× 5 ⎠
rij = xij /
x max ( i = 1, ..., 5, j = 1, ..., 5 ) . j
rij = x min / xij j 5
gi = ∑ w j rij j =1
5
X 5×5 .
(3)
( i = 1,..., 5, j = 1, ..., 5) .
(4)
( i = 1, ..., 5) .
(5)
zi = ∑ w j rij − r1 j j =1
(2)
( i = 2, ..., 5 ) .
(6)
Make a comparable scale for all elements in the decision matrix (2). If a criterion is benefit, the comparable scale is obtained by using (3); and (4) is used for cost criteria. g1 in (5) denotes the overall score of the user’s demand, while gi (i ≠ 1) denotes the overall score of network i . zi (i ≠ 1) in (6) denotes the additive weighing sum of distance between network i and the user’s need. If zi is closer to 0, it means that the quality of network i is closer to the request of user. In order to make efficient use of base station resources, it is proposed to pick up the most proper one instead of the best one. This selection criterion can make each user access appropriate network according to its demand. Suppose that a group of users move into a serving area, taking a WLAN cell for example, and they all discover that the new network can provide best service then decide to handover. As a result of that, the performance of this network will become worse than it was thought to be. Proposed selection methods can avoid this situation by considering the specific QoS demand of every user and assigning suitable resources to users according to their real needs. Many approaches propose a way to select the proper network by choosing the lowest one from those networks that give higher score than the user’s, however this manner is not accurate in some situations. For example, suppose we use data rate and delay as two attributes and a user with ftp application sets w1 = 0.7, w2 = 0.3 , its normalized expected QoS values are (0.8,0.1), there are two candidate networks whose normalized capability values are (0.5,0.85) and (0.8,0.2), so the user’s demand is
(8)
The overall score of network 2 is g 2 = 0.7 * 0.8 + 0.3* 0.2 = 0.62 .
5
user’s application is w j , in which ∑ w j = 1 . If imprecise terms
D=
(7)
(9)
Because g1 is higher than g and closer to it than g 2 , the user should choose network 1 according to the traditional method, however, it is obvious that network 1 could not provide enough data rate for the user who cares this parameter much more than delay. In order to solve this problem, we introduce the additive weighing sum of distance defined in (6). The concrete selection method is as follows. Choose the minimum zi (i ≠ 1) in set { g i g i > g1} first, if there exists a network that fulfills the request above, mobile node can select this one as the target network and send resource reservation require message to it according to the MIH function. If there is no proper choice, which means that all candidate networks are not capable of providing demanded QoS then mobile node should choose the best one and keep on looking for a better candidate network. C. handover execution stage If a mobile node decides to handover to a new target base station, it will make a handover execution, it will send resource preparation to target network and establish connection with the target access point then certain mobility management protocol procedures are carried out between mobile node and target network.
IV.
SIMULATION RESULTS AND ANALYSIS
A. Simulation Model We use NS2 network simulation tool to verify our scheme. The simulation scenario is the overlay wireless network environment composed of UMTS, WiMAX and WLAN. The mobile nodes follow Poisson distribution and the mobility model is random walk. The cell radius of UMTS, WiMAX cell and Wi-Fi network are 1000m, 3000m and 100m respectively. We assume that throughout the simulation time, mobile nodes are within the coverage area of at least one network. Meanwhile, all the mobile nodes and networks are MIH enabled.
To make the simulation scenarios closer to actual network environments, random-generated background data flows are added to each access network. In order to check whether proposed scheme is applicable to different QoS traffic classes, two mobile nodes with distinct applications move across three kinds of network in the overall simulation process, we choose ftp and VOIP as typical applications which care about different QoS parameters, the former one prefers higher throughput while the second one cares more about data delay. We compare the performances of basic handover scheme with the proposed scheme. The basic vertical handover is
triggered when a network with stronger RSS is detected, handover decision algorithm only compares the RSS’s values and chooses the network which provides the strongest RSS, no more criteria or decision algorithm is involved. B. Simulation Results Fig.2 shows the handover times in average with different mobile nodes speed. Form the comparison of the basic SNR based scheme and the proposed scheme, it can be seen that mobile node has less handover times using proposed scheme because it executes handover only when its QoS are not fulfilled or a Layer 2 connection is expected to go down within a certain time interval instead of making handovers as soon as it has entered a network with stronger signal strength. The decrease of handover times can make the system more stable.
Fig.3 is the throughput of the mobile node with ftp application in simulation. The simulation result shows that MIH based method achieves higher average throughput because it takes more factors into consideration to select better network for users and adopts QoS based handover triggers besides link based triggers. Fig.4 is the end to end delay of the mobile node with VOIP application in simulation. Results show that the proposed scheme provides lower end to end delay in average than that of basic RSS based scheme.
Figure 4. End-to-end delay based on different decision schemes.
V.
CONCLUSION AND FUTRUE WORK
In this paper, we proposed a user-adaptive vertical handover scheme based on MIH function in the integration of Wi-Fi, WiMAX and UMTS networks environment. Users’ QoS demands are given full consideration throughout the whole handover procedure. From the user’s respect, the proposed scheme adopts two kinds of handover triggers considering the user’s QoS demands as well as the link layer conditions, which can improve the provided service quality. From the whole network’s respect, the scheme uses a decision making method based on classical fuzzy MADM method and chooses the most suitable network for users, which can make full use of network resources. Simulation results show that the proposed scheme provides less handover times and better QoS than basic handover scheme. In future work, we will apply more comprehensive trigger events such as mobile node’s location and velocity. REFERENCES [1]
Figure 2. Handover times in average with different mobile node’s speed. [2]
[3]
[4]
[5]
[6] Figure 3. Instant throughput based on different decision schemes. [7]
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