A WiMAX technology is a very promising Broadband Wireless Access technology that is able to transmit different service types. This latter can have different constraints such as traffic rate, maximum latency, and tolerated jitter. The IEEE 802.16 Medium Access Control specifies five types of QoS classes: UGS, rtPS, ertPS, nrtPS, and BE. However, the IEEE 802.16 standard does not specify the scheduling algorithm to be used. Operators have the choice among many existing scheduling techniques. Also, they can propose their own scheduling algorithms. In this paper, we propose a scheduling strategy (Adaptive Weighted Round Robin, AWRR) for various Internet Protocol Television (IPTV) services traffic over 802.16j networks. Our scheme adapts dynamically the scheduler operation to according queue load and quality of service constraints. In particular, the proposed mechanism gives more priority to high definition television and standard definition television traffic by using two schedulers. The proposed scheduling algorithm has been simulated using the QualNet network simulator. The experimental results show that our scheduler schemes AWRR have a better performance than the traditional scheduling techniques for rtPS traffic, which allows ensuring QoS requirements for IPTV application.Unsolicited grant service (UGS): such as T1/E1 transport. It requires reserved traffic rate, maximum latency, and tolerated jitter. Extended real-time polling service (ertPS): such as voice of IP (VoIP). It is built on the efficiency of both UGS and rtPS, reduces overhead and access delay of rtPS, and improves uplink resource utilization of the UGS. As a subcategory of rtPS, ertPS has the same QoS parameters as rtPS in the scheduler design. Real-time polling service (rtPS): such as MPEG audio/video streaming and video conferencing. It supports variable bit rate traffic via minimum reserved and maximum sustained traffic rates and requires tolerable stringent latency constraints. Non-real-time polling service (nrtPS): delay tolerant streams with variable-sized packets, for which only minimum reserved and maximum sustained traffic rates are required, such as File Transfer Protocol (FTP). Best effort (BE) service: such as HTTP and email. BE services are handled on a space available basis and do not require tight latency/jitter constraints, with upper limited bandwidth consumption via maximum sustained traffic rate.
Internet protocol television (IPTV) service depends on the network quality of service (QoS) and bandwidth of the broadband service provider. IEEE 802.16j mobile multihop relay Worldwide Interoperability for Microwave Access networks have the opportunity to offer high bandwidth capacity by introducing relay stations. However, to actually satisfy QoS requirements for offering IPTV services (HDTV, SDTV, Web TV, and mobile TV) for heterogeneous users' requests, providers must use a video server for each IPTV service type, which increases the network load, especially bandwidth consumption and forwarding time. In this paper, we present a solution for forwarding IPTV video streaming to diverse subscribers via an 802.16j broadband wireless access network. In particular, we propose a new multicast tree construction and aggregation mechanism based on the unique property of prime numbers. Performance evaluation results show that the proposed scheme reduces both bandwidth consumption and forwarding time.
Recent advances in hardware and communication technologies have accelerated the deployment of billions of wireless sensors. This transformation has created a wide range of applications adapted to the evolving trends of our daily life requirements. Wireless sensor networks (WSNs) could be deployed in several target areas including buildings, forests, oceans, and smart cities. Nevertheless, finding the optimal location for each sensor node is a challenging task, typically when the environment involves heterogeneous obstacles. Many approaches and methods have been proposed to deal with the problem of WSN deployment, each addressing one or more objectives and constraints, such as network coverage, lifetime, connectivity, and energy consumption. The purpose of this survey paper is to provide the needed background to understand and study the WSNs deployment problem with a focus on its two key aspects: the optimization model and the solving methods based on artificial intelligence (AI). Additionally, it covers recent works on WSNs deployment and identifies their advantages and limitations. Furthermore, simulation experiments were carried out to compare the performance of widely used algorithms in the context of WSNs deployment problem, primarily genetic algorithm, particle swarm optimization, flower pollination, and ant colony optimization. Finally, this paper discusses and highlights several open challenges and research issues that must be explored in the future.
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