New Genetic Optimization Strategies In Efficient Off-Line Traffic Engineering For Simulating Multi-Service UMTS Cellular Networks

Abstract

This paper presents new strategies for offline traffic engineering, when designing multi-service UMTS networks, based on an efficient modification of basic genetic optimization techniques. More specifically, the problem setup includes Mobile Internet access as the most emergent trade in the telecommunications industry due to the advancement of cellular smartphones, tablets, notebooks and netbooks based computing and communicating technologies. In this real world set-up, the integration of deployed wireless networks with the Internet and the transparent interworking among different wireless technologies, namely EDGE/GPRS/CDMA2000 cellular and Wireless LAN (WLAN), appears to be a demanding objective for mobile communications service providers. The mixture and convergence of mobile and fixed infrastructures related services make it urgent to tackle quality of service and traffic engineering for mobile networks at the fundamental transport level with regards to OSI network analysis. A good solution to address such issues is the Multi-Protocol Label Switching (MPLS) technology providing a fused control instrument with connectionless multiprotocol capabilities, functioning over different communication media while supporting traffic engineering and quality of service (QoS) offering smooth traffic over the complex network of mobile and fixed communication infrastructures. Therefore, the MPLS architecture offers the required capacity to integrate different services over wired and wireless infrastructures in a unified convergent approach. Based on these concepts, this research proposal investigates traffic engineering solutions in MPLS involved wireless cellular networks. In this paper, two new methods for the solution of the off-line Traffic Engineering (TE) problem in multi-service wireless networks based on a certain efficient modification of basic genetic optimisation are presented. In the first method the off-line TE problem is formulated as an optimisation model with linear constraints and then solved using a new modified version of the Genetic Algorithm for Numerical Optimisation for Constraint Problems (GENOCOP). Besides, a hybrid method for the solution of the aforementioned problem involving modified GENOCOP and a heuristic TE algorithm is also provided. The performance of the above methods against a standard LP-based optimisation method is examined in terms of two different network topologies mixing both wireless and wired links and numerical test results are provided.