This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2008 proceedings.
Vertical Handoff Decision Scheme Using MADM for Wireless Networks R.Tawil1 ,O. Salazar2 and G. Pujolle1
1 Pierre et Marie Curie University , 104 av. Pr´esident Kennedy 75016 Paris, France
Email : (rami.tawil, guy.pujolle)@lip6.fr
2 Ecole Nationale Superieure des Telecommunications (ENST), 46, rue Barrault, 75013 Paris, France
Email :
[email protected]
Abstract— Wireless enviromnent is expected to support heterogeneous wireless access technologies. The objective is the support of a diverse range of high-data rate multimedia services. The main issue in this enviromnent is to provide a seamless vertical handoff mechanisms, which allow mobile users to handoff transparently from access technology to another. In this paper we propose a distributed handoff decision scheme to enhance service mobility using the Simple Additive Weighting (SAW) method in a distributed manner, under heterogeneous environments. Our main goal is to reduce the overload and power consumption in the mobile terminal, by delegating the calculation of handoff metrics for network selection to the Visiting Networks
is selected using a Network Selection Function (NSF) defined on multiple attributes (bandwidth, dropping probability and cost in our work). The main contributions of our work are the following: 1) Incorporate the dropping probability metrics in the handoff decision. 2) Delegate the computing processing for the handoff decision making to the VNs, in order to decrease the terminal overload and the power consumption. The rest of this paper is organized as follows: we present in Section 2 the related work this subject matter. Section 3 describes our DVHD. Additionally, the simulation results and analysis are presented in section 4. Finally, Section 5 concludes this article. II. RELATED WORK
Keywords: Handover, Service Continuity, Handoff Decision, Mobile Terminal, Mobile Wireless Network.
I. INTRODUCTION Wireless network enviromnent is expected to support heterogeneous access technologies with the objective of exploiting the technical characteristics, i.e. high data-rates, of such networks. A typical scenario is the following: third-generation (3G), Universal Mobile Telecommunications System (UMTS) (large-coverage, slower, higher-cost) and 802.11x WLAN (faster, high-bandwidth, lower-cost, short distance access). These wireless access networks are combined to provide an ubiquitous environment of wireless access for mobile terminals equiped with multiple network interfaces. The provision of seamless vertical handoff and service continuity requires the design of a robust Vertical Handoff Decision (VHD) scheme. Moreover, the vertical handoff decision making depends on different parameters (for instance, bandwidth, cost, power consumption, network condition, user preference and security). relating to the current connected network to which the mobile terminal is connected and to the Visiting Network (VN) which are the handoff target networks, and the decision is made basing on a tradeoff between these parameters. In this article, we propose a Distributed Vertical Handoff Decision (DVHD) scheme, which uses the Multiple Attribute Decision Making (MADM) method the Simple Additive Weighting (SAW) [6] in a distributed manner, and the dropping probability, bandwidth and cost as handoff parameters in order to make the decision. In particular, the ”best” network
Certain handoff decision algorithms have been proposed in the literature. In [2], the authors propose a generic handoff decision function. A set of criteria is used in order to evaluate the quality of the available networks. In [6], the vertical handoff decision is formulated as a fuzzy multiple attribute decision making problem. Two ranking methods are proposed: Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In [5], a performance comparison among SAW, TOPSIS, Grey Relational Analysis (GRA), and the Multiplicative Exponent Weighting (MEW) for vertical handoff decision is presented. In [12], the authors formulate the handoff decision mechanism as an optimization problem. Each candidate network is associated with a cost function which depends on a number of criteria, including the bandwidth, delay, and power requirement. A smart handoff decision mechanism is proposed in [4], authors propose two phases to accomplish the handoff decision: priority phase and normal phase, in priority phase a list of available networks is created, while in the normal phase a score function is used, in order to choose the best available network from the list, the function consists of three criteria: link capacity, cost and power consumption. In [13], the vertical handoff decision is evaluated via a handoff cost function and a handoff threshold function which can be adapted to changes in the network environment dynamically. Nonetheless, all these approaches mainly focused on the handoff decision, assuming that the calculation of the handoff decision criteria is performed on the mobile terminal
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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2008 proceedings.
side. Such calculation requires a non negligible amount of resource that can impact the mobile terminal performance in terms of processing delay and power consumption. In the next section, we propose our novel distributed vertical handoff decision scheme using the SAW method with a distributed manner, in order to avoid the centralized scheme drawbacks. III. P ROPOSAL Our proposed handoff decision scheme, DVHD, delegates the handoff calculation to the VN rather than on the mobile terminal, as some approaches propose. DVHD takes into account : bandwidth, dropping probability, and cost (in money) as evaluation metrics to select a suitable VN. These metrics are gathered as a Multiple Attribute Decision Making (MADM) [6] access selection function. The DVHD scheme comprises the following steps: 1. First, it delegates the calculation of the handoff metric to the VN. 2. Second, it incorporates the dropping probability metric as a parameter to calculate the handoff metric. Thus, we assumed that any terminal should not handoff into a VN with high dropping probability. Additionally, we also assumed that the VN can provide us with this metric. In the remaining of this section, we present our proposal scenario under which our work was evaluated along with a simulation model to validate our proposed handoff decision scheme. A. Scenario Before describing the scenario we state the underlying assumptions. Hence, we consider that the mobile terminal is moving in an overlapping area covered by a set of various wireless networks and managed by the same network operator. The cellular network covers the entire mobility area and represents the user’s Home Network (HN), while wireless local area networks provide limited coverage and represent the Visited Network (VN), as illustrated in Fig. 1 (Nj , j =1,. . . ,N). The relation between the different networks is caused by handoff terminal events from PoA (e.g. Access Point or Base Station) to another. The cellular network provides relatively low data rates, while WLAN support higher data rates (e.g. N5 refers to a wireless cellular system, and Nj (j = 1, ..., 4) refers to a WLAN network such as WiFi). Mobile terminal runs a Voice over IP (VoIP) application that requires an appropriate QoS level. B. Network Selection Algorithm 1) Network Selection Function (NSF): We formulated the network selection decision process as a MADM problem which is an evaluation of a set of alternatives (networks) using a multiple criteria NSF. NSF is an amalgamation of a set of evaluation parameters as network condition, bandwidth, power consumption, cost, latency and security. As stated, for our work we used only three parameters:
Fig. 1.
System Model
bandwidth, dropping probability, and cost. This function provides a measure of the target handoff network (Nj (j = 1,.., N)) quality1 (Q). Thus, the decision maker can select the ”best”2 network that has the highest Q value. The function is defined as follow: Q=B+
1 1 + Dp C
(1)
where, B represents the bandwidth, DP the dropping probability and C the cost of the service. Table 1 shows the evaluation parameters; the user required parameters and the parameters offered by the network. User required parameters
Network offered parameters
Bandwidth (in Mbits/s)
Required bandwidth
offered bandwidth
Dropping probability
Accepted dropping probability
network condition (Dp)
Cost (in money)
Required cost
service cost
Table 1. Evaluation parameters The cellular network operator, based on the user’s service profile, assigns wheights to the handoff decision parameters in order to determine the parameters’ levels of importance. Thus, weighted function will be as follow : Q = (WB ∗ B) + (WDp ∗
1 1 ) + (WC ∗ ) Dp C
(2)
The total of these weigths must be equal to one , WB + WDP + WC = 1
(3)
parameters with high weight value are more important to the user than those with low weight value and vice versa. 1 Quality (Q) refers to the behaviour of each network, it gives an estimation of how the network will behave for a specified environment and conditions. 2 ”best” network refers to the level of network handoff suitability
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2008 proceedings.
2) Distributed Decision Scheme: Our decision scheme, Distributed Vertical Handoff Decision (DVHD) scheme, uses the ”SAW” method in a distributed manner. DVHD allows the terminal to choose the ”best” network toward which it will be connected. Vertical Handoff Decision Process DVHD scheme consists on the following set of steps: 1. The mobile terminal initiates the handoff process based on the frame retransmissions [17], then it discovers its neighboring networks, if there are potential VNs, the mobile terminal broadcasts its requirements requesting a handoff. The request message includes the terminal required metrics (see Table 1) with their respective weights already defined by the Home Network. 2. The handoff decision metric calculation is performed among VNs, in order to avoid measures at the mobile terminal side, each VN applies the MADM method (SAW) using the NSF on the required and offered parameters (see Table 1) in order to computes the network quality value, then this value (QV11 ) is sent to the mobile terminal.
QV = WBreq WDreq WCreq ∗ =
QV11 QV12
Bof f Dp1
of f
Breq Dp1
req
1 Cof f 1 Creq
of time. Matching metric reflects the service continuity level of a mobile terminal, i.e. as long as a mobile terminal chooses the best network as long as it continuous its service. 2) Non-matching rate: Non-matching occurs when a decision is not matched which means that the decision maker chooses an unappropriate VN. Unappropriate VNs are the networks providing higher (or lower) quality than the quality required by the mobile terminal. Therefore, non-matching rate represents the percentage of unmatched decision. (nonmatching rate = 1 - matching rate). Non-matching event results a blocking handoff or an excessive use of resources. 3) Mobile terminal throughput: Mobile terminal throughput refers to the data amount that are sent by the mobile terminal after a set of matching decisions during a defined period. It reflects the robustness of the decision scheme. B. Results and Analysis The simulation outputs of this paper present the average of 50 runs of terminating simulations in each of them we calculate the mean of matching, non-matching rate and throughput for 50000 handoff decisions.
(4) (5)
3. Finally, the mobile terminal chooses the highest QV11 value and recommends the wireless network with the highest metric as a potential VN, and all connections will be redirected to the chosen VN. IV. NUMERICAL RESULTS AND ANALYSIS In this section, we provide the evaluation metrics used to analyze the performance of the DVHD scheme as well as the numerical results and analysis. In our work we consider an overlay network with 5 networks (system model presented in section III). Bandwidth provided by the network N5 is in the range of (1, 5) bandwidth units (bu), while network N1 to N4 provide bandwidth in the range of (1, 20) bu. We assume, that one user is running a VoIP application, which needs a stable amount of bandwidth (2 bu in our simulation). i.e. a mobile terminal may handoff to target network if this network offers at least 2 bu. Mobile terminal avoids networks with high dropping probability. Finally, we assume that terminal is always covered by at least two networks, N5 and Ni (i = 1, ..,4). Three evaluation parameters are used, in order to evaluate DVHD scheme; matching rate, Non-matching rate and throughput. A. Evaluation parameters 1) Matching rate: A matching means that the decision maker have chosen the ”best” VN. (e.g. if a 802.11 interface provides the approriate user preference, it said to be matching if the handoff decision algorithm chooses this interface). Therefore, matching rate represents the percentage of the matching number taken by the mobile terminal over a period
Fig. 2.
Matching Rate
Fig.2 and Fig.3 illustrate the difference between DVHD and CVHD (Centralized Vertical Handoff Decision) schemes in term of matching rate and non-matching rate. In this perspective, we can clearly see that the level of matching rate while implementing the DVHD decision is higher than the one achieved by using the CVHD. While the non-matching rate level is less than the one provided by the implementation of the CVHD due to the high level of matching rate. In the other side, up to 75% of CVHD decision were matched, while up to 30% of the CVHD decisions are not matched. Thus, by applying the DVHD scheme in the manner described above the system is more efficient in term of service continuity and stability. Therefore, more mobile user can continue their connections without being disrupted by the handover decision event.
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2008 proceedings.
We will continue to look how to optimise our proposed scheme (DVHD) in the context of next generation wireless network environment. This environment does not provide unique network characteristics, which makes the evaluation of the quality of these networks hard to achieve. More performance evaluation (processing delay, power consumption and system utilisation) will be achieved in order to enhance the DVHD scheme. R EFERENCES
Fig. 3.
Fig. 4.
Non-Matching Rate
Mobile Terminal Throughput
Furthermore, Fig.4, displays that DVHD, due to the high level of matching rate and the low level of the handoff blocking rate, provides higher throughput level than the one provided by the CVHD. V. CONCLUSION AND FUTURE WORK This article introduced a novel Distributed Vertical Handoff Decision (DVHD) scheme. It considers bandwidth, dropping probability and cost parameters as metrics of the network selection function, and it places the calculation of the network quality at the VNs side instead of the mobile terminal side. Numerical results showed that DVHD scheme exhibited better performance in terms of matching rate and throughput, than the CVHD scheme. DVHD scheme has a higher level of matching rate and throughput, and a lower level of nonmatching rate.
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