IPASJ International Journal of Information Technology (IIJIT) Web Site: http://www.ipasj.org/IIJIT/IIJIT.htm Email:
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Volume 6, Issue 7, July 2018
Bandwidth Allocation Policy using the Game Theory Model in Heterogeneous Wireless Networks Farhat Anwar, Mosharrof H. Masud, Burhan Ul Islam Khan*, Rashidah F. Olanrewaju and Suhaimi A. Latif Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur, Malaysia *Corresponding author E-mail:
[email protected]
ABSTRACT In Heterogeneous Wireless Network (WHN), a Mobile Device (MD) can be connected with multiple access technologies available in a particular geographical area. Selection of appropriate access technology is a challenge for the MD where game theory policy can be applied. Shapley Value is one of the game-theoretic models that can be applied to allocate appropriate bandwidth for i number of users for k number of services from N access technologies. It proposes the fairest allocation of the collectively gained profits among the collaborative players in the game. The primary focus is to find the relative contribution of every player in a cooperative game. This paper has drawn a numerical analysis of Shapley Value for three wireless access technologies, namely WiFi, Cellular and WiMAX. It has been shown how much bandwidth can be allocated from an access technology for a required bandwidth for a specific service. It can be noted from the results that 225Kbps, 141.67Kbps and 233.33Kbps can be allocated from WiFi, Cellular and WiMAX respectively to transmit the 600Kbps data in an HWN network.
Keywords: heterogeneous wireless network, game theory, bandwidth allocation, shapley formula
1. INTRODUCTION Game theory is a mathematical tool used in designing and modeling of complex scenarios that involves the interaction of rational decision makers with mutual and possibly conflicting interests [1]. It was initially invented to solve the complex issue of economic behavior. It has been popular in other fields, including politics, philosophy, military, sociology and telecommunication due to the effectiveness of its studying complex dynamics among players. Recently, a large number of issues of wireless communications and networking, particularly security [2]-[4] have been addressed using game theory and its solution. Wireless resources are insufficient in terms of bandwidth, power and capacity. On the other hand, increasing number of wireless access terminals, resource scarcity makes competition among mobile users for required wireless resources very severe. In this context, game theory can significantly better understand and optimize allocations of resources among the players. In recent years, game theory has been investigated in order to address wireless communication issues, including power control, resource allocation, MIMO systems, medium access control, routing, load control, etc. [1]. A classification has been performed based on OSI layer (Physical, Data link, Network, and Transport) in the light of game theoretic approaches [5]. A detailed discussion has been covered in a recent book on the broad area of wireless communications and networking domains, including sensor networking, vehicular networking, power control system, and radio resource management [6]. Heterogeneous wireless communication networks are dynamic in nature in terms of network load, availability, energy conservation and monetary cost. Both operators and users seek to maximize their payoffs. In HWN environment, the MD has the options to select the best suitable access point (AP) for its needs based on its preferences. Considering the multiple scenarios in HWN including the type of users, technology, service provider and applications, require the development of the new dimension that offers dynamic automatic networks selection [1]. Many solutions have been proposed to address this multi-criteria decision-making algorithms in HWN. Game theory [7] also can be used to deal with the complex decision making between the mobile users and the networks for resource allocations in HWN [8] environment. The payoffs can be estimated using utility functions based on the several decision criteria from both sides where game theory can be well suited.
Volume 6, Issue 7, July 2018
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Volume 6, Issue 7, July 2018
2. HETEROGENEOUS WIRELESS NETWORK SCENARIO It has been considered a geographical area where a different N set of wireless technologies like WiFi, WiMAX and 3G are available, N = {1, 2, 3, 4……N}. Each network n, 𝑛 ∈ 𝑁 is operated independently and has a unique set of Base Stations (BSs) or Access Points (APs) 𝑆𝑛 , 𝑆𝑛 = {1, 2, 3, 4 … … 𝑆𝑛 }. The set of BSs/APs, 𝑆𝑛 has different coverage area in a particular geographical area and some places can also be overlapped as shown in Figure 1.
Figure 1 A typical scenario of Heterogeneous Wireless Networks (HWN) The geographical area of a Sn can be denoted as 𝐺𝑆𝑛 = {1, 2, 3, 4 … … 𝐺𝑆𝑛 }. Each BS/AP 𝑠 ∈ 𝑆𝑛 has a transmission capacity 𝐶𝑛 Mbps. There are M numbers of Multimode Devices (MDs) in that particular geographical area denoted as the set M, 𝑀 = {1, 2, 3, 4 … … 𝑀}. Each MD, 𝑚 ∈ 𝑀 can get services from its home network and also from other available networks using multi-homing services. An MD using multi-homing capability can receive its required bandwidth from all available wireless technologies in that particular geographical area. The bandwidth allocated to MD m from network n through BS/AP s can be denoted as 𝐵𝑚𝑛𝑠 where 𝑚 ∈ 𝑀, 𝑛 ∈ 𝑁, and 𝑠 ∈ 𝑆𝑛 . The network supports the Constant Bit Rate (CBR) and Variable Bit Rate (VBR) services. The CBR connection of MD m needs a constant bandwidth Bm from all available wireless BSs/APs in that particular geographical area. On the other 𝑚𝑎𝑥 𝑚𝑎𝑥 hand, a VBR call of MD m requires a bandwidth allocation within a maximum value 𝐵𝑚 and a minimum value 𝐵𝑚 . 𝑚𝑎𝑥 The maximum level of bandwidth 𝐵𝑚 can be allocated for VBR when sufficient resources are available in that particular area. However, if the other MDs reach their capacity limitations, the level of bandwidth can be reduced to minimum 𝑚𝑖𝑛 bandwidth 𝐵𝑚 to increase the efficient utilization of the networks N. For each network n BS/AP s in the geographical area, the allocated resources should be such that the total load in its coverage area is within the network BS/AP capacity limitation C n, that is given in (1). ∑ 𝐵𝑚𝑛𝑠 ≤ 𝐶𝑛 , ∀ 𝑠 ∈ 𝑆𝑛 , ∀𝑛
(1)
𝑚∈𝑀
For a CBR service, the allocated bandwidth from available BSs/APs should satisfy the application required bandwidth Bm, 𝑁
𝑆𝑛
∑ ∑ 𝐵𝑚𝑛𝑠 = 𝐵𝑚 , ∀ 𝑚 ∈ 𝑀1
(2)
𝑛=1 𝑠=1
For VBR service, the allocated bandwidth from the available BSs/APs to an MD should satisfy in between the minimum 𝑚𝑖𝑛 𝑚𝑎𝑥 𝐵𝑚 and maximum 𝐵𝑚 bandwidth allocation.
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Volume 6, Issue 7, July 2018 𝑁 𝑚𝑖𝑛 𝐵𝑚
𝑆𝑛
𝑚𝑎𝑥 ≤ ∑ ∑ 𝐵𝑚𝑛𝑠 ≥ 𝐵𝑚 , ∀ 𝑚 ∈ 𝑀2
(3)
𝑛=1 𝑠=1
It can be said that if the requirements do not meet the equations (1) to (3) for the respective circumstances, the bandwidth will not be allocated to any particular link.
3. RESOURCE ALLOCATION CONSTRAINTS In order to get the best bandwidth resource allocation, some constraints must be considered. Resource particularly bandwidth allocation in heterogeneous wireless networks is one of the challenging issues due to the several constraints. The general constraint is, the allocated bandwidth should not be more than available bandwidth in the particular area for certain types of services. Conditional constraints include that, the allocated bandwidth must be sufficient with respect to the required bandwidth and allocated bandwidth must be satisfied with the minimum requirement of the requested bandwidth. The details of the resource allocation constraints have been covered in the following section. 3.1 General constraints It has been assumed that there are i numbers of networks that support different types of services. 𝐵𝑖𝑎𝑣 can be denoted as total available bandwidth resources of the ith network. The sum of bandwidth resources allocated to different kinds of 𝑘 𝑎𝑣 services in the ith network ∑𝐾 𝑘=1 𝐵𝑖 should be no larger than 𝐵𝑖 . 𝐾
∑ 𝐵𝑖𝑘 ≤ 𝐵𝑖𝑎𝑣 , for 𝑖 = 1, 2, 3 … … 𝑀
(4)
𝑘=1
Moreover, it is also known that different types of services required different bandwidth requirement, denoting 𝐵𝑘,𝑚𝑎𝑥 and 𝐵𝑘,𝑚𝑖𝑛 as the maximum and minimal bandwidth requirements of the kth type of service. The bandwidth allocation needs to satisfy the following constraints. 𝐾
𝐵
𝑘,𝑚𝑖𝑛
≤ ∑ 𝐵𝑖𝑘 ≤ 𝐵𝑘,𝑚𝑎𝑥
(5)
𝑘=1
3.2 Conditional constraints Different conditional constraints need to be introduced as there is a difference between total user service requirements 𝑎𝑣 𝑘,𝑚𝑎𝑥 ∑𝐾 and total available bandwidth ∑𝑀 𝑘=1 𝐵 𝑖=1 𝐵𝑖 . 3.2.1 Sufficient Bandwidth Allocation In the case when the demand of total user service requirement is smaller than or equal to the total available bandwidth, then sufficient bandwidth can be allocated. 𝐾
𝑀
∑𝐵
𝑘,𝑚𝑎𝑥
𝑘=1
≤ ∑ 𝐵𝑖𝑎𝑣
(6)
𝑖=1
The optimum service is provided when user service requirement is precisely equal to the total available bandwidth in the particular area, i.e. 𝑀
∑ 𝐵𝑖𝑘 = 𝐵𝑘,𝑚𝑎𝑥
(7)
𝑖=1
From this optimization constraint, it can be guaranteed as the best service from the network to the particular user. This allocation also confirms the proper utilization of the wireless resources to the users. 3.2.2 Limited Bandwidth Allocation In the case that the network bandwidth resource is limited compared to the user requirements, i.e., the maximal bandwidth allocation for all the service types cannot be provided. 𝐾
∑𝐵 𝑘=1
𝑀 𝑘,𝑚𝑖𝑛
≤
∑ 𝐵𝑖𝑎𝑣 𝑖=1
𝐾
≤ ∑ 𝐵𝑘,𝑚𝑎𝑥
(8)
𝑘=1
3.2.3 Severely Insufficient Bandwidth Allocation In the case that the network bandwidth resource is severely insufficient comparing to user requirements, i.e.,
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Volume 6, Issue 7, July 2018 𝑀
∑ 𝐵𝑖𝑎𝑣 𝑖=1
𝐾
≤ ∑ 𝐵𝑘,𝑚𝑖𝑛
(9)
𝑘=1
Any aforementioned constraints must need to be fulfilled for the respective required allocation. The concern arises, how much bandwidth can be allocated from each network to allocate the required bandwidth for the specific services. Hence, a game theory model can be used for the allocation of bandwidth in a heterogeneous wireless network. The theoretic model of game theory and its numerical analysis have been discussed in the following sections.
4. GAME THEORETIC MODEL The game theoretic model is being used to solve the distribution problems to allocate the resources among the group of agents. It is well suited in a circumstance where the resources (bandwidth) are insufficient to satisfy all the agents (mobile users). To understand the concept of game theory, let us assume that a company with estate E becomes bankrupt and it owes money to the creditors with the amount of the money as d. Hence, the money E is needed to be divided among the N creditors. In the worst scenario, the sum of the claims of the creditors is larger than the money of bankrupt companies, E
