A Bio-Inspired QoS-Oriented Handover Model in Heterogeneous Wireless Networks

Abstract

We propose a bio-inspired model for making handover decision in heterogeneous wireless networks. It is based on an extended attractor selection model, which is biologically inspired by the self-adaptability and robustness of cellular response to the changes in dynamic environments. The goal of the proposed model is to guarantee multiple terminals’ satisfaction by meeting the QoS requirements of those terminals’ applications, and this model also attempts to ensure the fairness of network resources allocation, in the meanwhile, to enable the QoS-oriented handover decision adaptive to dynamic wireless environments. Some numerical simulations are preformed to validate our proposed bio-inspired model in terms of adaptive attractor selection in different noisy environments. And the results of some other simulations prove that the proposed handover scheme can adapt terminals’ network selection to the varying wireless environment and benefits the QoS of multiple terminal applications simultaneously and automatically. Furthermore, the comparative analysis also shows that the bio-inspired model outperforms the utility function based handover decision scheme in terms of ensuring a better QoS satisfaction and a better fairness of network resources allocation in dynamic heterogeneous wireless networks.

A Dynamic and Self-Adaptive Network Selection Method for Multimode Communications in Heterogeneous Vehicular Telematics

“…Furthermore, we evaluate the performance of the network selection solution by combining both terminalside and network-side interest, namely, in terms of the global mobile users' QoS satisfaction and the efficiency and fairness of network resource allocation among multiple users. An ASM based network selection method is proposed in [19], where the network selection solution only takes into account the QoS satisfaction perceived at individual terminals. In this paper, we develop a novel dynamic network selection method which not only can satisfy the QoS requirements of different terminal's applications, but also can ensuring the efficient utilization and fair allocation of heterogeneous network resources in a global sense.…”

“…It is worth pointing out that the (19) also adopts the form of the cumulative product function. From (19), it can be observed that GlobalSatisf action can be treated as a multivariable function which monotonously increases with each M T Satisf action i .…”

An adaptive vehicular epidemic routing method based on attractor selection model

“…As shown by the studies [26], the attractor selection mechanism could provide a novel bio-inspired paradigm for achieving a self-adaptive and robust solution in dynamic environments. For specified application contexts of mobile communication, some researchers have successfully applied this bio-inspired mechanism to design a multi-path routing protocol in overlay networks [27], improve the robustness of a AODV-like routing protocol in MANETs [28], and build handover model in heterogeneous wireless networks [29]. In this paper, we integrate the attractor selection into the proposed epidemic broadcasting for the enhancement of routing performance in VANETs in terms of robustness and adaptability.…”

“…Some existing work has already revealed the power of the attractor selection to induce some solution designs of more scalability, adaptability and robustness for specified computer networking problems [27,28,29]. Based on the high-dimensional attractor selection model defined in [29], we propose an adaptive and robust message dissemination method for VANETs. Firstly, we present the adopted attractor selection model as the following differential equations:…”

“…Based on the work of [29], we can adopt a mathematical polynomial to design s(α) since a polynomial-type form is well-known as a kind of function whose mathematical structure is simple and monotonicity could be easily tunable by setting its coefficients and degree. Hence, denoting a 1 and a 2 as two positive polynomial coefficients (a 1 , a 2 ∈ R + ) and…”