Petros Nicopolitidis

Using learning automata for adaptive push-based data broadcasting in asymmetric wireless environments

Push systems are not suitable for applications with a priori unknown, dynamic client demands. This paper proposes an adaptive push-based system. It suggests the use of a learning automaton at the broadcast server to provide adaptivity to an existing push system while maintaining its computational complexity. Using simple feedback from the clients, the automaton continuously adapts to the client population demands so as to reflect the overall popularity of each data item. Simulation results are presented that reveal the superior performance of the proposed approach in environments with a priori unknown, dynamic client demands.

Learning automata-based polling protocols for wireless LANs

A learning automata-based polling (LEAP) protocol for wireless LANs, capable of operating efficiently under bursty traffic conditions, is introduced. We consider an infrastructure wireless LAN, where the access point (AP) is located at the center of a cell which comprises a number of mobile stations. According to the proposed protocol, the mobile station that is granted permission to transmit is selected by the AP by means of a learning automaton. The learning automaton takes into account the network feedback information in order to update the choice probability of each mobile station. It is proved that the learning algorithm asymptotically tends to assign to each station a portion of the bandwidth proportional to the stations needs. LEAP is compared to the randomly addressed polling and group randomly addressed polling protocols and is shown to exhibit superior performance under bursty traffic.

Adaptive wireless networks using learning automata

Wireless networks operate in environments with unknown and time-varying characteristics. The changing nature of many of these characteristics will significantly affect network performance. This fact has a profound impact on the design of efficient protocols for wireless networks and as a result adaptivity arises as one of the most important properties of these protocols. Learning automata are artificial intelligence tools that have been used in many areas where adaptivity to the characteristics of the wireless environment can result in a significant increase in network performance. This article reviews state of the art approaches in using learning automata to provide adaptivity to wireless networking.

Distributed protocols for ad hoc wireless LANs: a learning-automata-based approach

Abstract An ad hoc learning-automata-based protocol for wireless LANs, capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the mobile station that is granted permission to transmit is selected by means of learning automata. At each station, the learning automaton takes into account the network feedback information in order to update the choice probability of each mobile station. The proposed protocol is compared via simulation to TDMA and IEEE 802.11 under bursty traffic conditions. Ad hoc learning-automata-based protocol (AHLAP) is shown to exhibit superior performance compared to TDMA in all cases. Compared to IEEE 802.11, the burstier the network traffic, the larger the performance increase of AHLAP. Furthermore, the implementation of AHLAP is more easier than that of IEEE 802.11.

Architectures and Bandwidth Allocation Schemes for Hybrid Wireless-Optical Networks

The combination of the most prestigious optical and wireless technologies for implementing a modern broadband integrated access network has been progressively gaining ground. By extending the network coverage in a cost-efficient way, hybrid wireless-optical networks are able to enclose a larger number of potential subscribers than standalone access architectures. Hence, they are capable of increasing revenue levels and facilitating commercial penetration to the telecom market. At the same time, hybrid wireless-optical networks pose an ambitious, alternative, and efficient solution to coping with new bandwidth-hungry user applications. Hybrid wireless-optical networks incorporate sophisticated modules, fabrics, and network entities to effectively provide adequate quality of service (QoS) provisioning. This survey endeavors to classify the main features of wireless-optical integration. We provide a comprehensive compilation of the latest architectures, integrated technologies, QoS features, and dynamic bandwidth allocation (DBA) schemes. In addition, new trends towards wireless-optical convergence are presented. Moreover, as the up-to-date hybrid network standards remain under development, since there is not yet an integrated standard for approving hybrid network access platforms, we accompany this survey with detailed challenges indicating potential avenues of future research.

Adaptive Data Broadcasting in Underwater Wireless Networks

Underwater acoustic networks have recently emerged as a new area of research in wireless networking. These networks can support a large number of applications such as environmental and underwater equipment monitoring. In recent years, there has been substantial work on protocol design for these networks with most efforts focusing on MAC and network layer protocols. Despite being a fundamental networking primitive, data broadcasting has so far received little attention in the context of underwater networks. This paper proposes an adaptive push system for dissemination of data in underwater acoustic wireless networks. Besides achieving adaptation of its broadcast schedule according to the a priori unknown needs of the clients, the proposed system also efficiently combats the problem of high latency of the underwater acoustic wireless environment. Simulation results show superior performance of the proposed system in the underwater environment compared to adaptations of existing terrestrial push systems.

Continuous Flow Wireless Data Broadcasting for High-Speed Environments

With the increasing popularity of wireless networks and mobile computing, data broadcasting has emerged as an efficient way of delivering data to mobile clients having a high degree of commonality in their demand patterns. This paper proposes an adaptive wireless push system that operates efficiently in environments characterized by high broadcasting speeds and a-priori unknown client demands for data items. The proposed system adapts to the demand pattern of the client population in order to reflect the overall popularity of each data item. We propose a method for feedback collection by the server so that the client population can enjoy a performance increase in proportion to the broadcasting speed used by the server. Simulation results are presented which reveal satisfactory performance in environments with a-priori unknown client demands and under various high broadcasting speeds.

Priority-Oriented Adaptive Control With QoS Guarantee for Wireless LANs

In todays wireless networks, there is a great need for quality of service (QoS), because of the time-bounded voice, audio, and video traffic. A new QoS enhanced standard is being standardized by the IEEE 802.11e workgroup. It uses a contention free access mechanism called hybrid control channel access (HCCA) to guarantee QoS. However, HCCA is not efficient for all types of time-bounded traffic. This paper proposes an alternative protocol which could be adapted in hybrid coordination function (HCF). The priority-oriented adaptive control with QoS guarantee (POAC-QG) is a complete centralized channel access mechanism, it is able to guarantee QoS for all types of multimedia network applications, it enhances the parameterized traffic with priorities, and it supports time division access using slots. Furthermore, it instantly negotiates the quality levels of the traffic streams (TSs) according to their priorities, supporting multiple streams to the best quality it can achieve. POAC-QG, compared to HCCA, provides higher channel utilization, adapts better to the characteristics of the different traffic types, differentiates the TSs more efficiently using priorities, and, generally, exhibits superior performance.

Multiple-Antenna Data Broadcasting for Environments With Locality of Demand

Data broadcasting is an efficient way of delivering data to mobile clients having a high degree of commonality in their demand patterns. This paper proposes the use of multiple directional antennas to increase the performance of an adaptive wireless push system in environments that are characterized by the locality of client demands. Simulation results reveal that using up to three antennas suffices for a significant performance increase over the single-antenna adaptive wireless push system.

Third generation and beyond wireless systems

Exploring the capabilities of increased data transmission rates.