An adaptive bandwidth reservation scheme in multimedia wireless networks

The article presents a dynamic connection admission control (CAC) and bandwidth reservation (BR) scheme for IEEE 802.16e Broadband Wireless Access networks to simultaneously improve the utilization efficiency of network resources and guarantee QoS for admitted connections. The proposed CAC algorithm dynamically determines the admission criteria according to network loads and adopts an adaptive QoS strategy to improve the utilization efficiency of network resources. After new or handoff connections enter the networks based on current admission criteria, the proposed adaptive BR scheme adjusts the amount of reserved bandwidth for handoffs according to the arrival distributions of new and handoff connections in order to increase the admission opportunities of new connections and provide handoff QoS as well. We conduct simulations to compare the performance of our proposed CAC algorithm and BR scheme with that of other approaches. The results illustrate that our approach can effectively improve the network efficiency in terms of granting more connections by as large as about 22% in comparison with other schemes, and can also guarantee adaptive QoS for admitted new and handoff connections.

In wireless networks carrying multimedia traffic, it becomes necessary to provide a quality of service (QoS) guarantee for multimedia traffic connections. A novel timing-based bandwidth allocation protocol is proposed as a solution to support QoS guarantees in the multimedia wireless networks. Based on the existing network conditions, the proposed scheme makes an adaptive decision for bandwidth reservation and call admission by employing fuzzy inference mechanism, timing based reservation strategy, and round-borrowing strategy in each base station. The amount of reserved bandwidth for each base station is dynamically adjusted, according to the online traffic information of each base station. Simulation results show that our timing-based bandwidth reservation scheme outperforms the previous schemes in terms of connection-blocking probability, connection-dropping probability, and bandwidth utilization.

Next generation wireless communication systems target to provide guaranteed quality of service (QoS) for multimedia applications. In this paper, a multiple-threshold bandwidth reservation scheme combined with a call admission control algorithm is proposed and analyzed. The objective of our work is to be able to achieve better QoS provisioning for mobile users while achieving efficient utilization of the available limited bandwidth. The proposed scheme is modelled as M/M/C/C queueing system and the performance measures, call blocking probability and call dropping probability are computed. The performance of our scheme is compared to the complete sharing (CS) policy. Simulation results show that our scheme surpasses the CS policy in terms of call blocking probability, call dropping probability and bandwidth utilization.

Artificial Intelligence (AI) improves resource management and energy conservation through machine learning, improved forecasting, and quicker data processing. Artificial intelligence (AI) and machine learning (ML) have become essential enablers of this integration in this context. Machine learning and artificial intelligence are necessary for an organization’s survival and expansion, not just a choice. This research explores the growing significance of machine learning and artificial intelligence in resource management. The proposed method, deep reinforcement learning (DRL) based on machine learning is an essential tool for addressing the issues of resource management. Resource management can ensure that certain QoS criteria are met for various applications, such as information or real-time video transmission. Reducing total transmit power allows optimal resource management, while following Quality of Service (QoS) criteria permits a better relay choice. In this paper, the numerical results show that it performs competitively in terms of bandwidth of 97.5%, power consumption of 96%, spectrum efficiency of 91%, and network lifespan of 93 percent. Costs are decreased and environmental responsibility is enhanced through resource management. This research examines how AI might increase bandwidth, power consumption, spectrum efficiency, and resource management, with a particular emphasis on automation, efficiency, and prediction via quality of service.

An important quality-of-service (QoS) issue in wireless multimedia networks is how to control handoff drops. We propose admission-control algorithms that adaptively control the admission threshold in each cell in order to keep the handoff-dropping probability below a predefined level. The admission threshold is dynamically adjusted based on handoff-dropping events. We first present a simple admission-control scheme that brings out an important performance evaluation criterion - intercell fairness - and serves as a reference point. We then investigate the intercell unfairness problem and develop two enhanced schemes to overcome this problem. The performance of these protocols is benchmarked and compared with other competitive schemes. The results indicate that our schemes perform very well while, in addition, achieving significantly reduced complexity and signaling load.

In cellular networks, an important practical issue is how to limit the handoff dropping probability efficiently. One possible approach is to perform dynamic bandwidth reservation based on mobility predictions. With the rapid advances in mobile positioning technology, and the widespread availability of digital road maps previously designed for navigational devices, we propose a predictive bandwidth reservation scheme built upon these timely opportunities. In contrast to the common practice of utilizing only incoming handoff predictions at each cell to compute the reservations, our scheme is more efficient as it innovatively utilizes both incoming and outgoing handoff predictions; it can meet the same target handoff dropping probability by blocking fewer new calls. The individual base stations are responsible for the computations, which are shown to be simple enough to be performed in real-time. We evaluate the scheme via simulation, along with five other schemes for comparison. Simulation results show that those schemes that rely on positioning information are significantly more efficient than those that do not. Our scheme's additional use of the road topology information further improves upon this advantage, bringing the efficiency closer to the bound set by a benchmark scheme that assumes perfect knowledge about future handoffs

Adaptive call admission control for QoS provisioning in multimedia wireless networks

Cloud computing suffers from various challenging issues in Internet of Things (IoT) networks like real-time response, energy-efficient execution, and cost of computation. Fog is an emerging distributed computing paradigm which is useful for delay-sensitive tasks in IoT network. An offloading strategy decides where to offload the task and a task scheduling strategy chooses an appropriate fog node based on the requirements of the task while meeting the quality of services (QoS) criteria. Although the computational offloading and task scheduling problem has been widely studied, there is very limited research on delay-energy tradeoff. We propose a fog network that follows an M/M/c queue for computational offloading and a differential scale-based Best Worst Method (BWM) for computation of optimal weights in multi-objective task scheduling. The optimization problem minimizes the execution delay while meeting QoS criteria. The numerical experiments show the efficacy for the different QoS criteria.

A multi-path QoS multicast routing protocol with slot assignment for mobile ad hoc networks

Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To address this challenge, This paper proposes the Neural Control Exponential Weight of Priority Based Rate Control (NEWPBRC) algorithm for adjusting the node transmission rate and facilitate the problem of congestion occur in WMSNs. The proposed algorithm combines Neural Network Controller (NC) with the Exponential Weight of Priority Based Rate Control (EWPBRC) algorithms. The NC controller can calculate the appropriate weight parameter λ in the Exponential Weight (EW) algorithm for estimating the output transmission rate of the sink node, and then ,on the basis of the priority of each child node , an appropriate transmission rate is assigned . The proposed algorithm can support four different traffic classes namely, Real Time traffic class (RT class); High priority, Non Real-Time traffic class (NRT1 class); Medium priority, Non Real-Time traffic class (NRT2 class); and Low priority, Non Real-Time traffic class (NRT3 class). Simulation result shows that the proposed algorithm can effectively reduce congestion and enhance the transmission rate. Furthermore, the proposed algorithm can enhance Quality of Service (QoS) by achieve better throughput, and reduced the transmission delay and loss probability.

A dynamic bandwidth reservation (DBR) scheme for hybrid IEEE 802.16 wireless networks is investigated, in which 802.16 networks serve as the backhaul for client networks, such as WiFi hotspots and cellular networks. The DBR scheme implemented in the subscription stations (SSs) (co-locating with access pointers) consists of two components: connection admission controller (CAC), and bandwidth controller (BC). The CAC processes the received connection set-up requests from the client networks connected to the SSs. The BC manages the request and release of bandwidth from the base station (BS). It dynamically changes the reserved bandwidth between a small number of values. Hysteresis is incorporated in bandwidth release to reduce bandwidth request signalling load and connection blocking probability. An analytical model is proposed to evaluate the performances of reserved bandwidth, connection blocking probability and signalling load. The impacts of hysteresis mechanism and probability of reservation request blocking are taken into account. Simulation verifies the analytical model.

Distributed middleware technology is emerging as a flexible promising solution for network resource management and QoS (quality of service) control in a distributed environment. The concept of dynamic bandwidth reservation (DBR) algorithm additionally allocates the terminated bandwidth for an ongoing call is one of the promising methods to reduce the new call blocking and handoff call dropping probabilities. Dynamic resource management (DRM) framework concentrates on design and developing a framework for allocating shared resources to support multiple QoS and to provide probabilistic assurances of service in wireless networks. Existing methods and architecture do not guarantee on resource allocation and management in mobile, wireless and ad hoc networks. When a mobile node (MN) moves from its home network (HN) to foreign network (FN), the minimal required resources and services can be provided locally in the current network where it is connected presently. Dynamic resource management (DRM) framework provides an application level simulator for wireless network with new QoS management concept. DRM framework comprises of a set of programmable distributed objects and distributed middleware. DRM framework is constructed using distributed objects and distributed middleware. Distributed object carry applications across networks and allow them to connect to local server with FN in the same way as they had moved from the HN. The framework must dynamically accommodate multimedia calls with different bandwidth requirements in response to network traffic and it supports mobility management. The utility of DRM framework describes how the required resources are reserved based on the user priority option in an adaptive manner. The proposed DBR algorithm guarantees the required bandwidth during call setup and handoff without any flow rejection.

In this paper, we propose a distributed admission control scheme based on dynamic bandwidth reservation, with the aid of GPS to trade the position of the mobile terminal (MT) and predict its trajectory. We consider both wireless and wired links as potential bottlenecks and perform reservation in both types of links. By predicting a MT's target handoff cell and its remaining time to handoff, bandwidth reservation can be performed dynamically and efficiently. We perform simulations using an arbitrary hierarchical wireless ATM network with 256 cells, and show that the proposed scheme is able to prioritize handoff requests with moderate tradeoff of the blocking probability for new calls. We also show that the proposed scheme does not affect the amount of bandwidth utilization significantly, and the amount of prediction errors is approximately 1% of the total number of handoffs.

Problem statement: The demand for multimedia applications in WiMAX networks is growing at a rapid pace. A method for guaranteeing Quality of Service (QoS) for different classes of traffic is therefore gaining importance. Hence desi gning and analyzing multimedia traffic and QoS parameters has become central to this problem. In t his study, we propose a cross layer frame work in which a coordination between the Medium Access Control layer (MAC) and the Physical layer (PHY) is established for guaranteeing the QoS requirement in a multiclass traffic WiMAX environment. Two traffic classes' real time Polling Service (rtPS) a nd non real time Polling Service (nrtPS) are considered for analyzing the performance. Approach: The objective of study is to guarantee QoS for multiple service class traffic in a multiple connec tion environment in WiMAX network. A cross layer design approach is used for this purpose. A priorit y scheduler at the MAC layer schedules the traffic based on channel state information. The Adaptive modulation and coding scheme is used at the physical layer that adapts to the scheduled traffic to stabilize the QoS requirements of different tra ffic classes. Results: The Priority value is estimated using the Friis eq uation that calculates the received power and determines the SNR. The average throughput, average bytes received and the packet loss are plotted against time. This indicated that these QoS parameters are stable over a period of time. Conclusion: A cross layer frame work was developed based on a scheduler for QoS stability that uses CSI at the MAC layer and an AMC at the PHY layer in WiMax Networks. The scheduler enjoyed flexibility and scalability, whose performance was evaluated against existing systems through simulati on.

Many mechanisms based on bandwidth reservation have been proposed in the literature to decrease connection blocking probability and connection dropping probability in cellular communications. The handoff events occur at a much higher rate in sectored cellular networks than in traditional cellular systems. An efficient bandwidth reservation mechanism for the neighboring cells is therefore critical in the process of handoff during the connection of multimedia calls to avoid the unwillingly forced termination and waste of limited bandwidth in the sectored cellular communications, particularly when the handoff traffic is heavy. A self-adaptive bandwidth reservation scheme which employs a neural fuzzy bandwidth-reserving estimator, is proposed, and the simulation results show that our scheme can achieve superior performance than traditional fixed bandwidth-reserving scheme in sectored cellular networks when performance metrics are measured in terms of the new call blocking probability and the forced termination probability.