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A modern home could contain a large variety of devices and all of them should be able to work together so as to bring a rich experience to the users. Quality of service (QoS) is a critical factor for measuring user satisfaction. It represents the ability to provide different priorities based on the type of the data flows or to guarantee a certain q...
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... I NTRODUCTION I n variety today’s of media lifestyle, devices modern such as homes PCs, gateways, are furnished iPods, with DVD a recorders, HDTV sets, set-top boxes, wireless printers, etc. Many of these devices are traditionally isolated, lacking a strong inter-connectivity, and thus making it difficult to share data among different devices. Emerging home networking technologies aim at providing ways to connect and control home devices for the user to have a rich experience while offering tools and protocols for a convenient management of all the networked devices. The architecture of a home network is shown in Fig. 1. It demonstrates two major roles that modern home networks are going to play in the years to come. First, a home network acts as an extension to the access network. From the access network, data streams, which belong to different protocols, enter the home through a home gateway and are then forwarded to their destinations over the home network. The second role of the home network is inter-connecting the consumer electronics devices in the home environment. The devices within the home network should be able to communicate to each other through the home gateway despite of what protocols they use. A home gateway may also act as a temporary repository for the contents downloaded, for example, at night to be watched later. The underlying infrastructure is expected to use Internet Protocol (IP) based technologies for content delivery. Some of the devices in the home network may work as an extension of the access network, for example devices configured remotely to support an acceptable level of transmission quality in home network primary domains described in [12]. The home networks can thus be operating in a bigger operational environment where the access networks have direct influence on the home networking environments. The two domains, therefore, may overlap, which may have profound implications for the design and performance of the home networks. There may be, for example, a contention for networking resources among the devices in the two domains. In order to guarantee the required bit rate, delay, jitter, packet dropping probability, etc. for specified services, users, or data flows, an appropriate quality of service (QoS) mechanism must be used for this situation. Since the devices in the home network do not necessarily follow the same protocol, their QoS schemes are different as well. When several streams enter a home gateway at the same time, because of the inconsistency of QoS schemes, the home gateway has no way to decide on the relative priorities for data packets in these streams. As a result, the QoS mechanism of each device becomes useless. It is, therefore, important to harmonize all different protocols, currently competing for providing services to home users, for fair and optimal resource allocation in home networks. In [2], the authors proposed to add an Intelligent Control Center (ICC) in the home network, which is placed between home gateway and all the other home devices. ICC controls all the upstream and downstream traffic and is regarded as an aggregation point. While the ICC, which has a central control, might be able to harmonize the inconsistencies in different QoS schemes, no specific mechanism for QoS harmonization was offered. In addition, because the harmonization process would take place in the ICC, the problem of optimal and fair resource allocation at the home gateway might still be left ...
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... architecture of a home network is shown in Fig. 1. It demonstrates two major roles that modern home networks are going to play in the years to come. First, a home network acts as an extension to the access network. From the access network, data streams, which belong to different protocols, enter the home through a home gateway and are then forwarded to their destinations over the home ...
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Citations
... In [11] a home network QoS harmonization algorithm was used. This algorithm used a class-based communication protocol. ...
Internet of Things (IoT) has been seen playing a tremendous change in the Information Technology (IT) environments, and thus its importance has also been realized and played a vital role within Intelligent Home Networks (IHNs). This is because IoT establishes a connection between things and the Internet by utilizing different sensing devices to implement the intelligence to deal with the identification and management of the connected things. IHNs use intelligent systems to perform their daily operations. Meanwhile, these networks ensure comfort, safety, healthcare, automation, energy conservation, and remote management to devices and users. Apart from that, these networks provide assistance in self-healing for faults, power outages, reconfigurations, and more. However, we have realized that more and advanced devices and services continue to be introduced and used in these networks. This has led to competitions of the limited available network resources, services, and bandwidth. In this paper, therefore, we present the design and implementation of a Novel Dynamic Bandwidth Allocation (NoDBA) algorithm to solve the performance bottleneck incurred with IHNs. The proposed algorithm deals with the management of bandwidth and its allocation. In the proposed algorithm, this study integrates two algorithms, namely; Offline Cooperative Algorithm (OCA) and Particle Swarm Optimization (PSO) to improve the Quality of Service (QoS). PSO defines the priority limits for subnets and nodes in the network. Meanwhile, OCA facilitates dynamic bandwidth allocation in the network. The Network Simulator-2 (NS-2) was used to simulate and evaluate the NoDBA and it showed improved results compared to the traditional bandwidth allocation algorithms. The obtained results show an average throughput of 92%, an average delay of 0.8 seconds, and saves energy consumption of 95% compared to Dynamic QoS-aware Bandwidth Allocation (DQBA) and Data-Driven Allocation (DDA).
... In [9] a home network QoS harmonization algorithm was used. This algorithm used a class-based communication protocol. ...
Internet of Things (IoT) has played a tremendous change in the Information Technology (IT) environments, and thus its importance has also been realized within Intelligent Home Networks (IHNs). IHNs ensure comfort, safety, healthcare, automation, energy conservation, and remote management to devices and users. However, we have realized that more advanced devices and services continue to be introduced and used in IHNs. This has led to competitions of the limited available network resources, services, and bandwidth. In this paper, we propose a Novel Dynamic Bandwidth Allocation (NoDBA) algorithm to deal with bandwidth management and allocation. The algorithm integrates two algorithms, namely; Offline Cooperative Algorithm (OCA) and Particle Swarm Optimization (PSO). PSO defines the priority limits for subnets and nodes in the network. Meanwhile, OCA facilitates dynamic bandwidth allocation in the network. Network Simulator-2 (NS-2) was used to simulate and evaluate NoDBA and showed improved results compared to the traditional bandwidth allocation algorithm.
... In [5], a home network QoS harmonization model that used class based communication protocol was presented. The model differentiated priorities in third and second layers. ...
... Transmit max p = 7 End. We then compute throughput for each CoS as shown in equation (5). Throughput = ∑ number of packets ୲ ୲ భ (5) In which t ଵ is the start time of the first dispatched packet p ଵ and t ୬ is the end time of the last dispatched packet p ୬ in each CoS. ...
... We then compute throughput for each CoS as shown in equation (5). Throughput = ∑ number of packets ୲ ୲ భ (5) In which t ଵ is the start time of the first dispatched packet p ଵ and t ୬ is the end time of the last dispatched packet p ୬ in each CoS. Arrival and departure times for each CoS are represented by a ୨ ୡ and d ୨ ୡ respectively. ...
Devices and services used at homes continue to upsurge in numbers. This is associated to various evolutions happening in engineering and telecommunication industries. Consequently, technological changes in networking standards being experienced world over have not left intelligent home networks behind. Introduction of more devices and services into intelligent home network overloads network traffic and resources. In resultant, intelligent home networks experience poor Quality of Service (QoS) in their operations. This leads to unavailable, unreliable, and ineffective and poor performing intelligent home network both locally and remotely. Therefore, in this paper, we present a model that optimizes performance of intelligent home networks. In the model, we have used Virtual Local Area network (VLAN) protocol to segment and prioritize intelligent home network into six subnets. We have used weighing factor numbers in classifying and prioritizing devices. Further, we have used Differentiated Services Code Points (DSCP) in identifying, prioritizing and scheduling supported intelligent home network services into six classes. Finally, we have escalated number of transmitted packets per iteration in each Class of Service (CoS). We have simulated, tested and evaluated our proposed model in OMNET++. Average network throughputs of 99.735%, packet loss of 1.59% and delay of 1.82 seconds have been realised. This has presented an all-time available, reliable, efficient and optimized performing intelligent home network either locally or remotely to consumers.
... 11. As more and more new multimedia equipments are networked and managed in a plug and play fashion, the home network is thus becoming the "media hub" of the house [2], [3]. However, according to physical limitations, bandwidth is a relatively scarce resource in home networks. ...
An analytical model for streaming multiple heterogeneous multimedia services over home networks is established,in which the quality of service (QoS) provisioning problems are investigated. The goal is to simultaneously support as many service streams as possible, and to optimally guarantee all users' QoS within residential environments. A novel admission control algorithm, in conjunction with a quality adaptation scheme is proposed, which is capable of effectively guaranteeing and improving the service quality. Upon examination of the simulation results, we conclude that the proposed model and schemes provide valuable guidelines for the planning of future home networks and multimedia systems.
Home networks continue to experience an increase in the number of devices and services. This increase has come as a result of rapid technological revolutions in engineering and telecommunication industries. The advancement in technology has enabled access of intelligent home networks locally as well as remotely. This in turn has led to poor quality of service (QoS) to the consumers of such services and applications. Therefore, in this chapter, we present performance optimization of intelligent home network model that is scalable and adaptable to these increases and technological changes. We segmented and prioritized the intelligent home network into six subnets. Then we assigned weighing factor numbers to the devices, which aided in their classification and prioritization. We then grouped the supported home network services and applications into six classes and increased the number of transmitted packets per iteration in each Class of Service (CoS). We tested and evaluated proposed model using OMNET++ simulator against Priority Queuing (PQ) and Class-Based Weighted Fair Queuing (CBWFQ) models. The results show an average network packet throughput of 99.74 %, delay of 3.02 s, and loss of 1.59 %.
