EVEREST IST - 2002 - 00185 : D23 : final report

Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Performance analysis of the intelligent mobility optimization CRRM approach using a markovian chain model

Due to the increasing demand of wireless services, mobile technology has rapidly progressed towards the fourth generation (4G) networking paradigm. This generation will be heterogeneous in nature and it can be achieved through the integration of different Radio Access Technologies (RATs) over a common platform. Common Radio Resource Management (CRRM) was proposed to manage radio resource utilization in heterogeneous wireless networks and to provide required Quality of Service (QoS) for allocated calls. RAT selection algorithms are an integral part of the CRRM algorithms. Their role is to decide, when a new or Vertical Handover (VHO) call is requested, which of the available RATs is most suitable to fit the need of the incoming call and when to admit them. This paper extends our earlier work on the proposed intelligent hybrid mobility optimization RAT selection approach which allocates users in high mobility to the most suitable RAT and proposes an analytical presentation of the proposed approach in a multidimensional Markov chain model. A comparison for the performance of centralized load-balancing, distributed and the proposed intelligent mobility optimization algorithms is presented in terms of new calls blocking probability, VHO calls dropping probability, users' satisfactions probability, average networks load and average system throughput. Simulation and analytical results show that the proposed algorithm performs better than the centralized loadbalancing and distributed algorithms. © 2014 ACADEMY PUBLISHER

Intelligent hybrid cheapest cost and mobility optimization RAT selection approaches for heterogeneous wireless networks

The evolution of wireless networks has led to the deployment of different Radio Access Technologies (RATs) such as UMTS Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE), Wireless Local Area Network (WLAN) and Mobile Worldwide Interoperability for Microwave Access (WiMAX) which are integrated through a common platform. Common Radio Resource Management (CRRM) was proposed to manage radio resource utilization in heterogeneous wireless networks and to provide the required Quality of Service (QoS) for allocated calls. RAT selection algorithms are an integral part of the CRRM algorithms. Their role is to decide, when a new or Vertical Handover (VHO) call is requested, which of the available RATs is most suitable to fit the need of the incoming call and when to admit them. This paper extends our earlier work on the proposed intelligent mobility optimization and proposes an intelligent hybrid cheapest cost RAT selection approach which aims to increase users' satisfaction by allocation users that are looking for cheapest cost connections to a RAT that offers the cheapest cost of service. A comparison for the performance of centralized load-balancing, proposed and distributed cheapest cost and mobility optimization algorithms is presented. Simulation results show that the proposed intelligent algorithms perform better than the centralized load-balancing and the distributed algorithms. © 2014 Academy Publisher

Quality of Service in bandwidth adapted hybrid UMTS/WLAN interworking network

Integration of Universal Mobile Telecommunications System (UMTS) and Wireless Local Area Network (WLAN) result in ubiquitous connection for end users. In the integrated network, ensuring the quality of service to users and enhancing capacity of network are prominent issues. Bandwidth adaptation technique is one of the solutions to overcome these issues. Bandwidth adaptation based on per flow and per class schemes were proposed for loosely coupled interworking network. In this paper, hybrid coupled UMTS and WLAN interworking network is analyzed with bandwidth adaptation based on per flow and per class schemes and the performances have been compared. Simulation result shows that the proposed hybrid coupled interworking network with bandwidth adaptation based on per class scheme performs better with enhanced quality of service and network capacity

Auction-based Bandwidth Allocation Mechanisms for Wireless Future Internet

An important aspect of the Future Internet is the efficient utilization of (wireless) network resources. In order for the - demanding in terms of QoS - Future Internet services to be provided, the current trend is evolving towards an "integrated" wireless network access model that enables users to enjoy mobility, seamless access and high quality of service in an all-IP network on an "Anytime, Anywhere" basis. The term "integrated" is used to denote that the Future Internet wireless "last mile" is expected to comprise multiple heterogeneous geographically coexisting wireless networks, each having different capacity and coverage radius. The efficient management of the wireless access network resources is crucial due to their scarcity that renders wireless access a potential bottleneck for the provision of high quality services. In this paper we propose an auction mechanism for allocating the bandwidth of such a network so that efficiency is attained, i.e. social welfare is maximized. In particular, we propose an incentive-compatible, efficient auction-based mechanism of low computational complexity. We define a repeated game to address user utilities and incentives issues. Subsequently, we extend this mechanism so that it can also accommodate multicast sessions. We also analyze the computational complexity and message overhead of the proposed mechanism. We then show how user bids can be replaced from weights generated by the network and transform the auction to a cooperative mechanism capable of prioritizing certain classes of services and emulating DiffServ and time-of-day pricing schemes. The theoretical analysis is complemented by simulations that assess the proposed mechanisms properties and performance. We finally provide some concluding remarks and directions for future research