Cross Layered Approach for Network Selection

Cross Layered Approach for Network Selection A Cross Layered Approach for Network Selection in Heterogeneous Wireless Networks M. Deva Priya, Dr. M. L Valarmathi, D.Prithviraj Abstract: Service delivery in a heterogeneous wireless network environment requires the selection of an optimal access network. Selection of a non-optimal network can result in undesirable effects such as higher costs or poor service experience. Consequently, network selection techniques play a vital role in ensuring quality of service in heterogeneous networks. Network selection in such an environment is influenced by several factors, with different relative importance, the access network selection problem is usually looked at from the aspect of multi-criteria analysis. The proposed mechanism is based on a modified Multi-Criteria Decision Making (MCDM) steps to assist the Mobile Subscriber Stations (MSSs) in selecting the top candidate network dynamically. The performance analysis reveals that this network selection scheme yields a better results in selecting the better network. Keywords: MCDM, Analytic Hierarchy Process (AHP), WiMAX–Wi-Fi Scenario Introduction: The 4th Generation (4G) wireless networks aims at integrating various heterogeneous wireless access networks such as GPRS, 3G, Wi-Fi, WiMAX over an Internet Protocol (IP) backbone. With the integration of different access networks, wider ranges and higher Quality of Service (QoS) can be provided to the users. The next generation wireless networks have been designed to provide support for multimedia services with different traffic characteristics, different QoS guarantees and to satisfy different types of service level agreements (SLAs) for an increasing number of mobile users. The integration of different wireless network technologies is required to provide a â€Å"seamless† interoperability, integration and convergence among the heterogeneous technologies. Several heterogeneous wireless networks that consist of Worldwide Interoperability for Microwave Access (WiMAX) and Wireless Fidelity (Wi-Fi) networks have started to be operated. IEEE 802.16 WiMAX: WiMAX, a broadband wireless technology, developed by the WiMAX Forum [IEEE standard] is based on the 802.16 standard. The main objective is to provide high speed data transfers over the air. It has a frequency range of about 2-11 GHz for Non-Line-of- Sight and 10-66 GHz for Line of Sight. The signal range for Line of Sight and Non Line of Sight are 30 miles and 5 miles respectively. There are two types of WiMAX, say Fixed and Mobile WiMAX. WiMAX supports different types of traffics like Best Effort (BE), Unsolicited Grant Service (UGS), nrtPS (Non- Extended Real-Time Polling Service), rtPS (Extended Real-Time Polling Service) and ertPS (Extended Real-Time Polling Service). It is a technology for next generation with potential applications such as cellular backhaul, hotspot, VoIP mobiles and broadband connection etc. Itis a standard based wireless technology that provides internet access and multimedia services at very high speed to the end user. IEEE 802.11 Wi-Fi: WLAN (or WiFi) is an open-standard technology that enables wireless connectivity between equipments and local area networks. Public access WLAN services are designed to deliver LAN services over short distances. Coverage extends over a 50 to 150 meter radius of the access point. Connection speeds range from 1.6 Mbps, which is comparable to fixed DSL transmission speed, to 11 Mbps [Part 11 -1]. New standards promise to increase speeds to 54 Mbps. Today’s WLANs run in the unlicensed 2.4 GHz and 5 GHz radio spectrums [Part 11 2]. The 2.4 GHz frequency is already crowded—it has been allocated for several purposes besides WLAN service. The 5 GHz spectrum is a much larger bandwidth, providing higher speeds, greater reliability, and better throughput [Part 11 3]. Handover Process: When a Mobile Subscriber Station (MSS) moving in an overlapping area, continuous service must be need so the technique â€Å"HANDOVER† is done. The handover technique is mainly used to redirect the mobile user’s service network from current network to a new network or one base station (BS) to another BS or one access point (AP) to another AP with same technology or among different technologies to reduce the processing delay in the overlapping area. Handover technique has the two types, Horizontal Handover and Vertical Handover. The homogenous wireless network performs horizontal handover, if there are two BSs using the same access technology, in current system called horizontal handover. This type of mechanism use signal strength measurements for surrounding BSs to trigger and to perform the handover decision. In heterogeneous wireless networks, the MSS or BS will be equipped with multiple network interfaces to reach different wireless networks. When an emerging mix of overlapping heterogeneous wireless networks deployed, vertical handover is used among the networks using different access technologies. Handover technique has the four phases: Handover Initiation, System discovery, Handover decision, Handoff execution. Handoff Initiation phase: The handover process was modified by some criteria value like signal strength, link quality etc. System discovery phase: It is used to decide which mobile user discovers its neighbour network and exchanges information about Quality of Service (QOS) offered by these networks. Handover Decision phase: This phase compares the neighbour network QOS and the mobile users QOS with this QOS decision maker makes the decision to which network the mobile user has to direct the connection. Handoff Execution phase: This phase is responsible for establishing the connection and release the connections and as well as the invocation of security service. The scope of our work is mainly in handover decision phase, as mentioned in the decision phase; decision makers must choose the best network from available networks. Multi – Criteria Decision Making: Handover decision problem deals with making selection among limited number of candidate networks from various service providers and technologies with respect to different criteria. Network selection schemes can be categorized in to two kinds: Fuzzy Logic based schemes and multiple criteria decision making (MCDM) based schemes. Three different approaches for the decision of the optimal access network selection are as follows: the network centric, the user centric and the collaborative approaches [Hwang, C. L, Meriem, K]. In network centric approach, the decision for the access network selection is made at the network side with goal to optimize the network operator’s benefit. The majority of network centric approaches are using game theory in order to select the network that will optimize the network operator’s profit. In the user centric approach, the decision is taken at the user terminal based only on the minimization of the user’s cost without considering the n etwork load balancing or other users. The selection of the access network is determined by using utility or cost or profit functions or by applying MCDM methods. The selection of an access network depends on several parameters with different relative importance such as the network and application characteristics, user preferences, service and cost etc., the access network selection problem can be solved by applying different MCDM algorithms. In the collaborative approach, the decision for the access network selection is made at the profits of both users and network operator. Multiple criteria decision making deals with the problem of selecting an alternative from a set of alternatives which are categorized in terms of their attributes. Generally there are two processes in MCDM techniques: (1) Weighting and (2) Ranking. Most popular classical MADM algorithms are SAW, TOPSIS, AHP, and GRA. In Simple Additive Weighting (SAW), overall score of a candidate network is determined by weighting sum of all the attribute values. In Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the chosen candidate network is one which is closest to ideal solution and farthest from the worst case solution. Analytical hierarchical Process (AHP) decomposes the network selection problem in to several sub-problems and assigns a weight value for each sub-problem. Grey Relational Analysis (GRA) is then used to rank the candidate networks and selects the one with highest ranking. Related Work A novel optimization utility is presented [Pervaiz, Haris, Qiang Ni, and Charilaos C. Zarakovitis] to incorporate the quality-of-service (QoS) dynamics of the available networks along with heterogeneous attributes of each user. The joint network and user selection is modelled by an evolutionary game theoretical approach and replicator dynamics is solved to seek an optimal stable solution by combining both self-control of users’ preferences and self-adjustment of networks’ parameters, our study innovates over related efforts. This paper [Mehbodniya, Abolfazl, Faisal Kaleem, Kang K. Yen, and Fumiyuki Adachi] presents a novel approach for the design and implementation of a multi-criteria vertical handoff decision algorithm for heterogeneous wireless networks based on the fuzzy extension of the Techniques for Order Preference by Similarity to Ideal Solution (TOPSIS) which is used to prioritize all the available networks within the coverage of the mobile user and to achieve seamless mobility while maximizing end-users satisfaction. A network selection mechanism based on two multi attribute decision making (MADM) methods namely multiple analytic hierarchy process (M-AHP) and grey relational analysis (GRA) method is proposed [Lahby, Mohamed, and Abdellah Adib]. The M-AHP is used to weigh each criterion and GRA is used to rank the alternatives. This paper [Rao, K. R., Zoran S. Bojkovic, and Bojan M. Bakmaz] provides a survey on fundamental aspects of network selection process and deals with network selection concept as a perspective approach to the always best connected and served paradigm in heterogeneous wireless environment. A cross-layer architectural framework for network and channel selection in a Heterogeneous Cognitive Wireless Network (HCWN) [Haldar, Kuheli Louha, Chittabrata Ghosh, and Dharma P. Agrawal] is proposed. A novel probabilistic model for channel classification based on its adjacent channels’ occupancy within the spectrum of an operating network is also introduced. Further, a modified Hungarian algorithm is implemented for channel and network selection among secondary users. A two-step vertical handoff decision algorithm [Liu, Chao, Yong Sun, Peng Yang, Zhen Liu, Haijun Zhang, and Xiangming Wen] based on dynamic weight compensation is proposed. It also adopts the filtering mechanism to reduce the system cost and improves the conventional algorithm by dynamic weight compensation and consistency adjustment. A speed-adaptive system discovery scheme [Yang, Peng, Yong Sun, Chao Liu, Wei Li, and Xiangming Wen] before vertical handoff decision, which effectively improves the update rate of the candidate networks set is introduced. Then a vertical handoff decision algorithm based on fuzzy logic with a pre-handoff decision method which reduces unnecessary handoffs, balancing the whole network resources and decreasing the probability of call blocking and dropping. A context-aware service adaptation mechanism [Chang, Jie, and Junde Song] under ubiquitous network relying on user-to-object, space-time interaction patterns which helps perform service adaptation is presented. Similar Users-based Service Adaptation algorithm (SUSA) is proposed, by combining entropy theory and fuzzy Analytic Hierarchy Process algorithm (FAHP). This approach adopts a suitably defined utility function [Pervaiz, Haris, and Qiang Ni], which at the same time takes into account the users importance for the considered attributes and the quality offered for these attributes by the available networks. The dynamics of network selection in cooperative wireless networks is modeled using an evolutionary game theory where an evolutionary equilibrium is sought as a solution to this game. A bandwidth allocation algorithm is proposed [Fei, Wenchao, Hui Tian, and Rongrong Lian] for Constant Bit Rate (CBR) and Variable Bit Rate (VBR) services depending on utility fairness among different networks and the fairness between new arrival and ongoing services. A utility function is introduced whose parameters are determined by the modified multi-state Analytic Hierarchy Process (AHP) which adapts to different load levels according to dynamic thresholds. A novel load balancing algorithm based on analytic hierarchy process (AHP) is proposed [Song, Qingyang, Jianhua Zhuang, and Rui Wen], which helps the heterogeneous WLAN/UMTS network to provide better service to high-priority users without decreasing system revenue. A novel selection policy [Sasaki, Misato, Akira Yamaguchi, Yuichi Imagaki, Kosuke Yamazaki, and Toshinori Suzuki] for a communication system in heterogeneous wireless networks, which applies the Analytic Hierarchy Process (AHP) algorithm by taking into account the mobility of the user terminals is proposed. An intelligent context-aware solution based on advanced decision approaches like fuzzy logic and analytic hierarchy processes that considers both users and services requirements is proposed in [Zekri, Mariem, Badii Jouaber, and Djamal Zeghlache]. REFERENCES: IEEE Std 802.16-2009. IEEE standard for local and metropolitan area networks. Part 16: Air interface for broadband wireless access systems; 2009. 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