SuperBS: A methodology for resource management in heterogeneous wireless networks

It is envisaged that next generation wireless networks (NGWN) will be heterogeneous, consisting of multiple radio access technologies (RATs) coexisting in the same geographical area. In these heterogeneous wireless networks, mobile terminals of different capabilities (heterogeneous terminals) will be used by subscribers to access network services. We investigate the effect of using heterogeneous mobile terminals (e.g. single-mode, dual-mode, triple-mode, etc.) on call blocking and call dropping probabilities in cooperative heterogeneous wireless networks. We develop analytical models for heterogeneous mobile terminals and joint radio resource management in heterogeneous wireless networks. Using a two-class three-RAT heterogeneous wireless network as an example, the effect of using heterogeneous terminals in the network is evaluated. Results show the overall call blocking/dropping probability experienced by subscribers in heterogeneous wireless networks depends on the capabilities of mobile terminals used by the subscribers. In the worst case scenario, when all subscribers use single-mode mobile terminals, each subscriber is confined to a single RAT and consequently, joint radio resource management in heterogeneous wireless network has no improvement on new call blocking and handoff call dropping probabilities. However, in the best case scenario, when all subscribers use three-mode terminals, new class-1 call blocking probability decreases from 0.37 (for 100% single-mode terminals) to 0.05, at the arrival rate of 6 calls per minute. New class-2 call blocking probability also decreases from 0.8 to 0.52. Similarly, handoff class-1 call dropping probability decreases from 0.14 to 0.003, and handoff class-2 call dropping probability decreases from 0.44 to 0.09.

Due to the heterogeneity and versatility of emerging services and applications in wireless networks, it has been a great challenge on improving the network utility by taking advantage of the spatial and temporal diversity of radio resource consumption. This paper is committed to solving this problem by introducing a service-aware spectrum sharing algorithm (SSA) in a joint radio resource management (JRRM) architecture, where a spectrum pool is adopted for leisure spectrum resource management in heterogeneous wireless networks. Based on an objective utility function, the JRRM unit could optimize the spectrum scheduling decisions for the composing networks with awareness of the related supporting services. Moreover, to facilitate a precise decision process, we illustrate an transmission rate requirement prediction model (TRPM) that is adaptive to the system condition variants to forecast service requests. Experiment results show that the proposed SSA can solidly enhance the system performance in terms of radio resource usage ratio, system throughput, user service access ratio, and eventually achieve better network utility.

As the rapid development of mobile broadband access network technologies in recent years, 802.11 Wi-Fi, GPRS and 3G access networks have been widely used. Users have the characteristic of mobility in these wireless heterogeneous networks. As users are roaming, How to report rapidly the current location of users to network management center, so that the pagers are able to obtain the right user location for establishing communication, has become an important issue. we focus on the architecture and policies of location management for wireless heterogeneous networks. we propose the Geographical Location Registration (GLR) mechanism for location updating and paging, where the location information in wireless heterogeneous networks is maintained to rapidly page other users and to reduce the overall cost. Compared to traditional mechanisms, the proposed GLR mechanism is capable of improving the paging cost by 79%. Besides, as the moving speed of users increases, the paging cost will not increase substantially.Keywordsheterogeneous access networknetwork managementlocation updatepaging

In order to enable the autonomic network resource management, we resort to game theory to facilitate the spectrum sharing between heterogeneous wireless networks. We set the spectrum sharing objective to improve spectrum efficiency and maximise network revenue. Based on this goal, we propose a revenue sharing bargain game to model the spectrum sharing behaviour of intra-operator radio access networks (RANs) and a price bargain game to model the spectrum trading behaviour between inter-operator RANs. Furthermore, we adopt multi-agent architecture to implement the spectrum sharing schemes autonomously. Both bargaining mechanisms are analysed using bargaining game theory, and consequently the implementations are refined and simplified based on the analysis. Simulation results show that the proposed mechanisms outperform the conventional fixed spectrum management method in network revenue, spectrum efficiency and call blocking rate.KeywordsAutonomic spectrum managementGame theoryMulti-Agent

Designing a good joint radio resource management (JRRM) is a major challenge in heterogeneous wireless networks. Many analytical as well as simulation models of heterogeneous wireless networks are not based on fairly realistic assumptions so that the research outputs may be less practical. We design a JRRM taking into consideration different features of component access technologies in a heterogeneous wireless environment. We also consider different important realistic features of access networks, such as asymmetry of their overlap and the variability of network resources according to traffic conditions. We use the network simulator (NS-2) to validate our design. The simulation results show that the blocking probability improves when different considerations are taken into account.

In this paper, we propose a novel approach to jointly address energy management and network throughput maximization problems for heterogeneous IoT low-power wireless communication networks. In particular, we consider a low-power communication network in which the IoT devices can harvest energy from a dedicated RF energy source to support their transmissions or backscatter the signals of the RF energy source to transmit information to the gateway. Different IoT devices may have dissimilar hardware configurations, and thus they may have various communications types and energy requirements. In addition, the RF energy source may have a limited energy supply source which needs to be minimized. Thus, to maximize the network throughput, we need to jointly optimize energy usage and operation time for the IoT devices under different energy demands and communication constraints. However, this optimization problem is non-convex due to the strong relation between energy supplied by the RF energy source and the IoT communication time, and thus obtaining the optimal solution is intractable. To address this problem, we study the relation between energy supply and communication time, and then transform the non-convex optimization problem to an equivalent convex-optimization problem which can achieve the optimal solution. Through simulation results, we show that our solution can achieve greater network throughputs (up to five times) than those of other conventional methods, e.g., TDMA. In addition, the simulation results also reveal some important information in controlling energy supply and managing low-power IoT devices in heterogeneous wireless communication networks.

Recently, there has been great interest in the community over heterogeneous wireless networks in order to support services with high quality. The integration of Wimax and Wi-Fi technologies in communication systems such as Voice ,FTP ,Video conducted heterogeneous system reveal that the proposed network selection technique can effectively decide the optimum network through making trade-offs among network condition, user preference while avoiding frequent handoffs. We identify vertical handover decision algorithm suitable for multimode mobile devices based on the Analytic Hierarchy Process (AHP) and evaluates its performance through simulation by Opnet. This paper gives a comparative analysis of two queuing systems FIFO and WFQ by showing the advantages of using suitable weight which was calculated by AHP. The simulation results show that WFQ technique has a superior quality than FIFO. It could be opportunity to network designers and suppliers are providing the resources to servers more efficient use.

This special issue is devoted to the new research addressing challenges in the areas of wireless computing and networking. Wireless computing and networking has enabled heterogeneous access technologies for providing services to ubiquitous users. The demanding networking environment of wireless communications imposes many challenges, such as channel estimation, network protocol design, resource management, and systematic design. Due to nonuniform spectrum allocation, various radio resource management policies, economic concerns, scarcity of radio resources, and user mobility, overcoming these issues becomes more demanding. This special issue includes ten research articles from five countries including the United States, China, South Korea, Norway, and India which covers various research issues in the areas of wireless computing and networking. These articles can be broadly classified into three categories: (1) data management and query processing in wireless networks; (2) backbone management in wireless networks; and (3) routing in wireless networks. A detailed description of the corresponding works in each category is given below.

On the optimal formulation of resource management in wireless networks by Jihui Zhang thesis 2005 xvi, 176 leaves : ill. ; 30 cm Resource management is of great importance in wireless networks, as it can improve the scarce wireless spectrum…Read more ›

The wide majority of existing trust-based systems in wireless networks are today bound to a single service. As such, they cannot use past experiences related to other services. Even those that support multiple services hide this heterogeneity by regrouping all past experiences and contexts into a single metric, which strongly degrades the quality of results. To go beyond these restrictions, we designed a novel context-aware and multi-service trust model for heterogeneous wireless networks that involve nodes with different resources capabilities. Simulation results prove the proper functioning of the proposed system and its effectiveness against common attacks hindering trust models.

Resource management in UAV-assisted wireless networks: An optimization perspective

The coexistence of multiple access technologies deployed by different operators is fundamental for future fourth-generation mobile networks. In spite of this heterogeneity, seamless interoperator/intersystem mobility is a mandatory requirement. In this article we present a seamless mobility management approach that does not require changes to existing network infrastructure. The novelty of the proposed approach is that mobility management is fully controlled by the terminal, and network selection is user-centric, power-saving, cost-aware, and performance-aware. Total mobility management, including interface management, handover decision, and execution, is also detailed

Location-aware computing is widely discussed to be one attractor of the future ubiquitous networks for intelligent home and telematics services. Apart from technical difficulties in providing accurate position information there is also a lack of a clearly defined framework how to create innovative and secure services using location information. In this paper, we identify QoS, interworking and security problems in location-aware computing. We propose a number of concepts and infrastructures for location-aware security services including micro and macro mobility management in ubiquitous home networks and heterogeneous wireless networks. We further explain how the proposed approach can be applied to seamless secure interworking among wireless LANs and 3G, 4G cellular systems. Our approach might be helpful in the discussion for the frameworks especially highlighting evolutionary steps for the next ubiquitous networks.KeywordsLocation-awarenessubiquitous computing4Gsecurityinterworkingagentshome network

Effective resource management plays a pivotal role in wireless networks, which, unfortunately, typically results in challenging mixed-integer nonlinear programming (MINLP) problems. Machine learning-based methods have recently emerged as a disruptive way to obtain near-optimal performance for MINLPs with affordable computational complexity. There have been some attempts in applying such methods to resource management in wireless networks, but these attempts require huge amounts of training samples and lack the capability to handle constrained problems. Furthermore, they suffer from severe performance deterioration when the network parameters change, which commonly happens and is referred to as the task mismatch problem. In this paper, to reduce the sample complexity and address the feasibility issue, we propose a framework of Learning to Optimize for Resource Management (LORM). In contrast to the end-to-end learning approach adopted in previous studies, LORM learns the optimal pruning policy in the branch-and-bound algorithm for MINLPs via a sample-efficient method, namely, imitation learning . To further address the task mismatch problem, we develop a transfer learning method via self-imitation in LORM, named LORM-TL , which can quickly adapt a pre-trained machine learning model to the new task with only a few additional unlabeled training samples. Numerical simulations demonstrate that LORM outperforms specialized state-of-the-art algorithms and achieves near-optimal performance, while providing significant speedup compared with the branch-and-bound algorithm. Moreover, LORM-TL, by relying on a few unlabeled samples, achieves comparable performance with the model trained from scratch with sufficient labeled samples.

The evolution of cellular networks from one generation to another has led to the deployment of multiple radio access technologies (such as 2G/2.5G/3G/4G) in the same geographical area. This scenario is termed heterogeneous cellular networks. In heterogeneous cellular networks, radio resources can be jointly or independently managed. When radio resources are jointly managed, joint call admission control algorithms are needed for making radio access technology selection decisions. This chapter gives an overview of joint call admission control in heterogeneous cellular networks. It then presents a model of load-based joint call admission control algorithm. Four different scenarios of call admission control in heterogeneous cellular networks are analyzed and compared. Simulations results are given to show the effectiveness of call admission control in the different scenarios. The coexistence of different cellular networks in the same geographical area necessitates joint radio resource management (JRRM) for enhanced QoS provisioning and efficient radio resource utilization. The concept of JRRM arises in order to efficiently manage the common pool of radio resources that are available in each of the existing radio access technologies (RATs) (Perez-Romero et al, 2005). In heterogeneous cellular networks, the radio resource pool consists of resources that are available in a set of cells, typically under the control of a radio network controller or a base station controller. There are a number of motivations for heterogeneous wireless networks. These motivations are (1) limitation of a single radio access technology (RAT), (2) users’ demand for advanced services and complementary features of different RATs, and (3) evolution of wireless technology. Every RAT is limited in one or more of the following: data rate, coverage, security-level, type of services, and quality of service it can provide, etc. (Vidales et al, 2005). A motivation for heterogeneous cellular networks arises from the fact that no single RAT can provide ubiquitous coverage and continuous high QoS levels across multiple smart spaces, e.g. home, office, public smart spaces, etc. Moreover, increasing users’ demand for advanced services that consume a lot of network resources has made network researchers developed more and more spectrally efficient multiple access and modulation schemes to support these services. Consequently, wireless networks have evolved from one generation to another. However, due to huge investment in existing RATs, operators do not readily discard their existing RATs when they acquire new ones. This situation has led to coexistence of multiple RATs in the same geographical area.